System

Abstract

A system is provided.SOLUTION: A system comprising: means for collecting point program information from a user; means for storing the collected point program information in a database; means for analyzing the stored point program information and generating a notification when a point expiration date is approaching; means for transmitting the generated notification to the user; and means for obtaining campaign information from the outside and matching the campaign information with the point information of the user to propose an optimal campaign.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The technology of the present disclosure relates to a system. [Background technology]

[0002] Patent document 1 discloses a persona chatbot control method performed by at least one processor, the method including the steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to a description of the chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2022-180282 Summary of the Invention [Problem to be solved by the invention]

[0004] Today's consumers participate in a variety of point programs, but managing each one is complicated, resulting in frequent points expiring or forgetting to use them. It's also difficult to determine the optimal timing for using points. This makes it difficult to maximize users' economic benefits. Furthermore, it's difficult to keep track of the latest campaign information for efficient point usage. [Means for solving the problem]

[0005] In order to solve the above problems, the present invention provides the following means: A system is constructed that includes means for collecting point program information from users, means for saving the collected point program information in a database, means for analyzing the saved point program information and generating a notification when the expiration date of points is approaching, means for sending the generated notification to the user, and means for acquiring campaign information from an external source and comparing it with the user's point information to suggest the most suitable campaign.

[0006] In addition, by providing a means for users to receive notifications sent from the server via a point management app on their devices and check the status of their points, users can always be aware of the status of their points.Furthermore, by using an AI algorithm to analyze point usage history and expiration dates and providing a means to set usage priorities, users can use their points efficiently without waste.

[0007] "User" refers to an individual or corporation that uses this system to manage multiple point programs and receives notifications about point usage and campaign information.

[0008] "Points program" is a general term for customer loyalty programs that award points based on purchase amounts and service usage, which can then be exchanged for benefits or discounts.

[0009] A "database" is an information storage system for centrally storing and managing user point program information.

[0010] The "AI algorithm" is an artificial intelligence technology that analyzes point usage history and expiration dates to determine optimal usage methods and priorities.

[0011] "Notification" is a message sent to inform the user that the expiration date of points is approaching, campaign information, etc.

[0012] "Campaign Information" refers to information about benefits such as double points and limited offers, which are obtained to promote the efficient use of points.

[0013] A "terminal" is an electronic device such as a smartphone, tablet, or PC that a user uses to use the point management app. [Brief explanation of the drawings]

[0014] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13]FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0015] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0016] First, the terms used in the following description will be explained.

[0017] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0018] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0019] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0020] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0021] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0022] [First embodiment]

[0023] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0024] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0025] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0026] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0027] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0028] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0029] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0030] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0031] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0032] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0033] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0034] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0035] The system for implementing this invention includes three main components: a server, a terminal, and a user. The specific operation of each component will be described below.

[0036] Server Processing

[0037] User Data Collection and Storage

[0038] The server collects user data through the API of each point program, including the number of points a user has, the date they have earned them, their usage history, and their point expiration date. This data is stored in a database, and point program information is centrally managed using the user ID as a key.

[0039] Point status analysis

[0040] An AI algorithm installed on the server periodically analyzes the user's point usage history and expiration date. It checks whether the points are about to expire and generates a notification if so. It also prioritizes the use of points and suggests the best time to use them.

[0041] Sending notifications

[0042] The server notifies users when their points are about to expire and about the latest campaign information. Notifications are sent via email, SMS, app push notifications, etc. to encourage users to use their points.

[0043] Collection of campaign information and notification

[0044] Campaign information is obtained through an external API and compared with the user's point information. Based on the comparison results, the system notifies the user that points can be used more efficiently by taking advantage of a specific campaign. For example, if a specific store is running a double points campaign, the system notifies the user of this information.

[0045] Terminal handling

[0046] Check your points

[0047] A points management app is installed on the user's device. The app periodically synchronizes data with the server and displays the latest points status. Users can open the app to check the balance and expiration date of each points program.

[0048] Receive notifications

[0049] The device receives notifications sent from the server and displays them to the user. The notification content includes information about upcoming points expiration dates and campaign information. When the user taps the notification, detailed information is displayed within the app and an action such as using points is prompted.

[0050] User Behavior

[0051] Viewing and using points

[0052] The user receives a notification from the server and launches the app to check the status of their points. For example, if they receive a notification that "XX points will expire in 5 days," the user can check the points within the app and use them at affiliated stores or online sites.

[0053] Use of the campaign

[0054] Users can check campaign notifications from the server and use their points efficiently at specific stores or online sites. For example, if a user receives a notification that "There is a double points campaign this weekend at store X," the user can plan to shop at the store that weekend.

[0055] Specific examples

[0056] For example, suppose user C has 300 points in point program A. When the expiration date is approaching in three days, the server detects this information and sends C a notification saying, "Your 300 points in program A will expire in three days." A notification will appear on C's smartphone, and when C opens the app, a link saying "Use now" will appear. By tapping the link, C will be taken to an affiliated online shop where she can use her points to purchase products.

[0057] This system allows users to prevent points from expiring and use them efficiently. It also allows users to get the most out of their points by staying up to date with the latest campaign information.

[0058] The processing flow will be explained below.

[0059] Specific processing of the program

[0060] Server Processing

[0061] Step 1: Collect data

[0062] The server obtains user point information through the API of each point program, including the number of points, acquisition date, usage history, and expiration date.

[0063] Step 2: Save your data

[0064] The server stores the acquired data in a database. There is a separate table for each point program, and data is associated using the user ID as a key.

[0065] Step 3: Analyze the data

[0066] An AI algorithm installed on the server analyzes the points information in the database, in particular checking whether the points are about to expire and listing those points that are about to expire.

[0067] Step 4: Generate notifications

[0068] Based on the results of the AI ​​algorithm's analysis, the server generates a notification message, such as "Your points for Program A will expire in 3 days."

[0069] Step 5: Sending notifications

[0070] The server generates the notification and sends it to the user, either via email, SMS, or push notification, allowing the user to receive the notification.

[0071] Step 6: Gather campaign information

[0072] The server calls an external API to obtain the latest campaign information, such as information about a double points campaign being held at a specific store.

[0073] Step 7: Campaign information verification and notification

[0074] The server compares the acquired campaign information with the user's point information, generates a notification proposing the relevant campaign, and sends it to the user.

[0075] Terminal handling

[0076] Step 1: Synchronize your data

[0077] The point management app installed on the device periodically synchronizes with the server to obtain the latest point information.

[0078] Step 2: Viewing points

[0079] The acquired point information is displayed within the app, allowing users to check the balance and expiration date of each point program.

[0080] Step 3: Receive notifications

[0081] The device receives notifications sent from the server and displays them to the user in-app or as push notifications.

[0082] Step 4: View details

[0083] When users tap on the notification, more information will be displayed within the app, including where points can be used and details about the campaign.

[0084] User Behavior

[0085] Step 1: Check notifications

[0086] The user checks the notification received on the device, which notifies them of the approaching expiration date of specific points and campaign information.

[0087] Step 2: Use your points

[0088] Users can redeem their points by clicking a link within the app, for example by being redirected to a partner online shop where they can use their points to purchase products.

[0089] Step 3: Use the campaign

[0090] Users can use points efficiently at physical stores and online sites based on the campaign information received on their devices, and plan their shopping accordingly.

[0091] Through these steps, a system is realized in which the server, terminal, and user work together to efficiently manage and use points.

[0092] Example 1

[0093] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0094] With conventional point management systems, users were unable to properly grasp the expiration dates of points or available campaign information, making it difficult to prevent points from expiring or use them at the optimal time. In particular, when managing multiple point programs, it was time-consuming to check the point balance and expiration date of each program individually, which was a significant burden for users. In addition, the priority order for point usage was unclear, which also hindered users from using points efficiently.

[0095] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0096] In this invention, the server includes means for collecting point program information from users, means for saving the collected point program information in a database, means for analyzing the saved point program information and generating a notification when points are about to expire, means for sending the generated notification to the user, means for externally acquiring campaign information and comparing it with the user's point information to propose optimal campaigns, means having an algorithm for periodically analyzing the collected point data and campaign information, and means for notifying the collected campaign information based on the user's point usage priority. This allows users to efficiently understand and use point expiration dates, optimal usage times, and campaign information through the app.

[0097] "User information" refers to data related to the points program, such as user identification information, number of points, acquisition date, usage history, and expiration date.

[0098] A "database" is an electronic storage system that centrally manages collected point program information and allows for easy storage, searching, and updating.

[0099] "Notifications" are messages that inform users when their points are about to expire or about the best campaign information. Notification formats include email, SMS, and app push notifications.

[0100] An "external API" is an interface that a server uses to obtain information from external services or databases. It is used to obtain campaign information, etc.

[0101] "Campaign information" refers to information about benefits for using points efficiently, such as a campaign to double points at a specific store.

[0102] "Algorithm" refers to a series of computational procedures that run on the server and analyze the point usage history and expiration date. Specifically, it includes pattern recognition and machine learning models.

[0103] A "point management app" is application software that users install on their smartphones or tablets to check their point balance, expiration date, and campaign information.

[0104] A "user device" is an electronic device used by a user, such as a smartphone, tablet, or computer, on which the point management app is installed and used.

[0105] "Verification" is a process in which the server compares the user's point data with the acquired campaign information to identify available point campaigns.

[0106] The "usage priority" is a standard for setting the priority when using points. For example, points that are close to their expiration date are set to be used first.

[0107] The system for implementing this invention includes three main components: a server, a terminal, and a user. The specific operation of each component and how they work together will be described in detail below.

[0108] Server Processing

[0109] The server first has a means of collecting point program information from users. This collection is done through the API of each point program, and data such as the number of points a user has, the date they acquired them, their usage history, and their expiration date is obtained. This information is then saved in a database. The saved point program information is managed centrally and registered using the user ID as a key.

[0110] The server then periodically analyzes the stored loyalty program information. Using AI algorithms, the server generates notifications when points are about to expire. These notifications include information about the points that are about to expire and recommended times to use them. These notifications are then sent to users via email, SMS, app push notifications, and more.

[0111] In addition, the server obtains campaign information through an external API. This campaign information is matched with the user's point data and used to suggest the most suitable campaign. If the campaign is an effective way to use points, the server notifies the user of this information. For example, if a specific store is running a double points campaign, the server notifies the user of this information.

[0112] Terminal handling

[0113] A points management app is installed on the device. This app periodically synchronizes data with the server and displays the latest points status. Users can open the app to check the balance and expiration date of each points program.

[0114] The device also receives notifications sent from the server. These notifications include information about upcoming point expiration dates and campaign information, and are displayed to the user. When the user taps the notification, more information is displayed in the app and an action is prompted, such as using points.

[0115] User Behavior

[0116] The user receives a notification from the server and launches the app to check the status of their points. For example, if they receive a notification saying, "X points will expire in 5 days," the user can check the status of their points within the app and use them at affiliated stores or online sites. Also, if they receive a notification about campaign information, for example, "There's a double points campaign at X store this weekend," they can check the notification and plan their shopping at the store that weekend.

[0117] Specific examples

[0118] For example, suppose user A has 300 points in point program A. When the expiration date is approaching in three days, the server detects this information and sends user A a notification saying, "Your 300 points in program A will expire in three days." A notification will appear on user A's smartphone, and when user A opens the app, a link saying "Use now" will appear. By tapping the link, user A will be taken to an affiliated online shop where they can use their points to purchase products.

[0119] Example prompts for generative AI models

[0120] "Please explain the specific behavior of a feature in a user's point management system that notifies users when their points are about to expire. As a specific scenario, please explain the case where a user has 300 points in point program A and the points are about to expire in three days."

[0121] This system allows users to prevent points from expiring, allowing them to use their points efficiently. It also allows users to get the most out of their points by staying up to date with the latest campaign information.

[0122] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0123] Step 1:

[0124] User Data Collection

[0125] The server calls the API of each point program to collect user data, including the number of points a user has, the date they acquired them, their usage history, and their expiration date.

[0126] Input: API endpoint of each point program

[0127] What happens: The server sends an HTTP request to the API endpoint and parses the returned JSON data.

[0128] Data processing: Parse the acquired JSON data and extract the user ID, number of points, acquisition date, usage history, and expiration date.

[0129] Output: Parsed user data

[0130] Step 2:

[0131] Saving to a database

[0132] The server stores the collected user data in a database. Point program information is centrally managed using the user ID as a key.

[0133] Input: Parsed user data

[0134] What happens: The server opens a database connection, executes an SQL query, and saves the user data.

[0135] Data processing: Convert user data into a database table format.

[0136] Output: User data stored in the database

[0137] Step 3:

[0138] Point status analysis

[0139] The AI ​​algorithm installed on the server analyzes point usage history and expiration dates, and generates a notification when a user's points are about to expire.

[0140] Input: User data stored in the database

[0141] How it works: The server runs an AI algorithm, taking user data as input and outputting a data set showing when points are about to expire.

[0142] Data calculation: Using a machine learning model, points usage history and expiration dates are analyzed to extract points that are close to expiring.

[0143] Output: List of points that are about to expire

[0144] Step 4:

[0145] Generate and send notifications

[0146] The server generates notifications based on the analysis results and sends them to the user in the form of email, SMS, app push notifications, etc.

[0147] Input: List of points that are about to expire

[0148] Specific operation: The server uses the notification template to generate notification content for each user, and then sends the notification using the SMTP protocol or SMS API.

[0149] Data processing: Embed user point information in the notification template.

[0150] Output: Notification sent to the user

[0151] Step 5:

[0152] Collection of campaign information and notification

[0153] The server obtains the latest campaign information through an external API, compares it with the user's point data, and generates notifications to suggest the most suitable campaigns.

[0154] Input: Campaign information from external API

[0155] What it does: The server sends an HTTP request to an external API to retrieve campaign information, which it then stores in a database and matches with the user's point data.

[0156] Data calculation: Compare the acquired campaign information with user point data to select the most suitable campaign.

[0157] Output: Campaign notification sent to users

[0158] Step 6:

[0159] Check your points

[0160] A points management app is installed on the device. This app periodically synchronizes data with the server and displays the latest points status. Users can open the app to check their points balance and expiration date.

[0161] Input: Latest point data synchronized from the server

[0162] Specific operation: The app calls the API in the background to get the latest point data from the server, which is then saved in local storage and displayed in the user interface.

[0163] Data processing: Convert the data obtained from the server into the display format of the app.

[0164] Output: Points balance and expiry date displayed in the app

[0165] Step 7:

[0166] Receive notifications

[0167] The device receives notifications sent from the server and displays them to the user, who can tap on them to view more information within the app.

[0168] Input: Notification sent from the server

[0169] Specific behavior: The device's notification service receives the push notification from the server and displays it in the notification center. When the user taps the notification, the relevant app screen is opened.

[0170] Data processing: Converts the notification content into a format suitable for the user interface.

[0171] Output: Notification displayed in the notification center and detailed information in the app

[0172] Step 8:

[0173] Viewing and using points

[0174] When users receive a notification, they can launch the app to check their points status and use them at affiliated stores or online sites.

[0175] Input: Point information and notification content displayed in the app

[0176] Specific operation: The user taps a link in the app to access a partner store or online shop, where they can use their points to purchase a product.

[0177] Data processing: Transaction data for point usage is generated and sent to the server.

[0178] Output: Transaction record of items purchased using points

[0179] Step 9:

[0180] Use of the campaign

[0181] The user checks the campaign notification from the server and uses the points to effectively take advantage of the campaign.

[0182] Input: In-app campaign notifications and details

[0183] Specific actions: The user taps on the campaign notification, checks the details, and redeems the campaign in a physical store or online shop.

[0184] Data processing: Campaign transaction data is generated and sent to the server.

[0185] Output: Transaction record of points redemption using campaign

[0186] (Application example 1)

[0187] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0188] Conventional point program management systems notify users when their points are about to expire, but this can sometimes prevent users from using their points at the appropriate time. Furthermore, they do not provide sufficient functionality for efficiently utilizing campaign information and optimizing point usage, resulting in point expiration and inefficient point usage. Therefore, there is a need for a way for users to use points efficiently and prevent them from expiring.

[0189] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0190] In this invention, the server includes means for collecting point program information from users, means for saving the collected point program information in a database, means for analyzing the saved point program information and generating a notification when the point expiration date is approaching, means for sending the generated notification to the user, means for acquiring campaign information from an external source and comparing it with the user's point information to propose the most suitable campaign, and means for sending point expiration date notifications and campaign information notifications to the user via a mail server. This allows users to check the point expiration date as needed and use their points efficiently. Furthermore, by utilizing the campaign information, the utility value of points can be maximized and users can manage their points effectively.

[0191] "User" refers to a person who uses the points program.

[0192] A "points program" is a system in which users are given points each time they use a specific service or product, and can use these points to receive discounts or benefits.

[0193] "Collecting information" refers to the process of obtaining data related to the loyalty program.

[0194] A "database" is an information system for systematically storing and efficiently managing collected data.

[0195] "Expiration date approaching" indicates that the points are about to expire.

[0196] "Generating a notification" is the act of creating a message to inform a user of information.

[0197] "Campaign Information" refers to information about promotions such as special offers and discounts that are held during a specific period of time.

[0198] "Matching" is the act of comparing specific data with other data to identify similarities and differences.

[0199] "Sending" refers to the act of delivering the generated notification to the user via electronic means.

[0200] A "mail server" is a server that manages the sending and receiving of email.

[0201] An "AI algorithm" is a computational process that analyzes user behavior patterns and data to derive efficient methods.

[0202] A "generative AI model" is a model that uses machine learning to generate new information and patterns from data.

[0203] The system for implementing this invention includes three main components: a server, a terminal, and a user. The main functions of this system are to collect, store, analyze, and notify users of point program information, and to suggest campaign information.

[0204] Server Processing

[0205] The server collects user data through the point program's API. Specifically, it obtains data such as the number of points a user has, the date they acquired them, their usage history, and their point expiration date, and stores this data in a database. The point program information is centrally managed using the user ID in the database as a key.

[0206] Next, an AI algorithm installed on the server periodically analyzes the user's point usage history and expiration date. This checks whether the points are about to expire and generates a notification if so. It also prioritizes the use of points and suggests the best time to use them.

[0207] Furthermore, campaign information is obtained through an external API and compared with the user's point information. Based on the comparison results, the system notifies the user that points can be used more efficiently by taking advantage of a specific campaign. For example, if a specific store is running a double points campaign, the system notifies the user of this information. Notifications are sent to the user via a mail server.

[0208] Terminal handling

[0209] A points management app is installed on the user's device. This app periodically synchronizes data with the server and displays the latest points status. Users can open the app to check the balance and expiration date of each points program. The app also includes a function to receive notifications sent from the server and display them to the user. By tapping the notification, users can check detailed information within the app and be prompted to take action, such as using points.

[0210] User Behavior

[0211] The user receives a notification from the server and launches the app to check the status of their points. For example, if they receive a notification that "XX points will expire in 5 days," they can check the points within the app and use them at affiliated stores or online sites. Furthermore, if they receive a notification that "XX store is having a double points campaign this weekend," they can plan to shop at the store that weekend.

[0212] This system allows users to prevent points from expiring and use them efficiently. Also, by staying up-to-date on the latest campaign information, users can make the most of their points. This increases user satisfaction and makes the point program more useful.

[0213] Specific examples

[0214] For example, suppose user C has 300 points in point program A. When the expiration date is approaching in three days, the server detects this information and sends C a notification saying, "Your 300 points in program A will expire in three days." A notification will appear on C's smartphone, and when C opens the app, a link saying "Use now" will appear. By tapping the link, C will be taken to an affiliated online shop where he can use his points to purchase products.

[0215] Prompt Sentence Examples

[0216] We want to build an app that centrally manages users' point information and campaign information, and suggests optimal point usage. The goal is to efficiently receive point expiration dates and campaign information from users, and to help them with the process of actually using their points. Specifically, the app includes the following features:

[0217] 1. Point expiration notification

[0218] 2. Notification of campaign information

[0219] 3. Suggestions for using points

[0220] How do you collect and analyze user data and send appropriate notifications? What technologies do you use to do so?

[0221] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0222] Step 1: Collect user data

[0223] The server obtains user data from the API of each point program. The input is an API request, and the output is data such as the number of points, acquisition date, usage history, and point expiration date. Specifically, it sends a request to the API endpoint, parses the results, and collects them as structured data. By doing this periodically, the latest information is maintained.

[0224] Step 2: Save your data

[0225] The server saves the point program information collected in step 1 in a database. The input here is the collected point information, and the output is structured data saved in the database. Specifically, it executes an INSERT or UPDATE query on the database and centrally manages the data using the user ID as a key.

[0226] Step 3: Analyze points expiration dates

[0227] The server periodically analyzes the stored point program information to check whether any points are about to expire. The input to this step is the point information in the database, and the output is a list of points that are about to expire. The specific operation is to perform an operation that compares the expiration date of each point with the current date, and extracts points that are about to expire within three days.

[0228] Step 4: Generate and send notifications

[0229] Based on the results of step 3, the server generates a notification when points are about to expire and sends the notification to the user. The input here is a list of points that are about to expire, and the output is the generated notification message and the sending result. The specific operation is to embed the point information in a message template, obtain the user's email address, and send the notification through the email server.

[0230] Step 5: Obtain and verify campaign information

[0231] The server retrieves campaign information through an external API and compares it with the user's point information. The input of this step is the campaign data from the external API and the user's point information, and the output is a list of points recommended for campaign use. The specific operation is to retrieve campaign information and match it with the user's point data to identify points that can be used effectively in a specific campaign.

[0232] Step 6: Generate and send campaign notifications

[0233] The server notifies the user of specific campaign information based on the results of step 5. The input here is a list of points where campaign use is recommended, and the output is the generated campaign notification and sending result. The specific operation is to generate a notification message containing the campaign information and send it to the user via the mail server.

[0234] Step 7: Check your points status

[0235] The device receives the notification sent from the server and displays it so that the user can check the status of point usage. The input here is the notification data from the server, and the output is the point information display screen on the device. The specific operation is that the device app receives the notification from the server and displays the information to the user in an appropriate format.

[0236] Step 8: Promote points usage

[0237] Users can use their points efficiently based on the notifications displayed on their devices. The input here is the displayed notification information, and the output is the actual act of using points. Specifically, users tap the notification to check detailed information, and then access affiliated online shops or stores via the link to use their points.

[0238] Step 9: Collect feedback data

[0239] The server collects data on how users use points and campaigns. The input here is user behavior data, and the output is updated point usage history data. The specific operation is to track user behavior and update the database to analyze campaign effectiveness and point usage trends.

[0240] Prompt Sentence Examples

[0241] We want to build an app that centrally manages users' point information and campaign information, and suggests optimal point usage. The goal is to efficiently receive point expiration dates and campaign information from users, and to help them with the process of actually using their points. Specifically, the app includes the following features:

[0242] 1. Point expiration notification

[0243] 2. Notification of campaign information

[0244] 3. Suggestions for using points

[0245] How do you collect and analyze user data and send appropriate notifications? What technologies do you use to do so?

[0246] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0247] The system for implementing this invention includes four main components: a server, a terminal, a user, and an emotion engine. The specific operation of each component will be described below.

[0248] Server Processing

[0249] User Data Collection and Storage

[0250] The server collects user data through the API of each point program. The data includes the number of points, acquisition date, usage history, and expiration date. This data is stored in a database, and point program information is centrally managed using the user ID as a key.

[0251] Point status analysis

[0252] An AI algorithm installed on the server analyzes the points information in the database, in particular checking whether the points are about to expire and listing those points that are about to expire.

[0253] Generate notifications

[0254] Based on the results of the AI ​​algorithm's analysis, the server generates a notification message, such as "Your points for Program A will expire in 3 days."

[0255] Sending notifications

[0256] The server generates the notification and sends it to the user, either via email, SMS, or push notification, allowing the user to receive the notification.

[0257] Collection of campaign information and notification

[0258] The server calls an external API to obtain the latest campaign information. For example, it obtains information about a double points campaign being held at a specific store. It compares the obtained campaign information with the user's point information and generates a notification suggesting a relevant campaign. It then sends this to the user.

[0259] Terminal handling

[0260] Check your points

[0261] A points management app is installed on the user's device. The app periodically synchronizes data with the server and displays the latest points information. Users can check the balance and expiration date of each points program.

[0262] Receive notifications

[0263] The device receives the notification sent from the server and displays it to the user in the app or as a push notification. When the user taps the notification, more information is displayed in the app and an action such as using points is prompted.

[0264] User Behavior

[0265] Viewing and using points

[0266] The user receives a notification from the server and launches the app to check the status of their points. For example, if they receive a notification that "XX points will expire in 5 days," the user can check the points within the app and use them at affiliated stores or online sites.

[0267] Use of the campaign

[0268] Users can check campaign notifications from the server and use their points efficiently at specific stores or online sites. For example, if a user receives a notification that "There is a double points campaign this weekend at store X," the user can plan to shop at the store that weekend.

[0269] Emotion Engine Operation

[0270] Emotion recognition

[0271] The emotion engine analyzes the text and voice input by the user, as well as facial expression data captured by a high-sensitivity camera, to recognize the user's emotions. For example, if a user inputs "I'm tired today" into the chatbot, it will classify that emotion as "fatigue."

[0272] Collecting and storing emotional information

[0273] The emotion recognition results are sent to the server and stored in a database along with point information. The emotion information is linked using the user ID as a key and used for future analysis.

[0274] Creating emotional notifications

[0275] The AI ​​algorithm generates notification messages based on emotional information. For example, if it detects that the user is feeling stressed, it will generate a notification such as "Double points campaign at store XX, perfect for refreshing yourself."

[0276] Adjusting the timing and content of notifications

[0277] The emotion engine analyzes the user's emotional state and adjusts the timing and content of notifications, for example, by sending notifications when the user is relaxed, which increases the user's response rate.

[0278] Specific examples

[0279] For example, suppose user D has 200 points in point program B, and the expiration date is approaching in five days. If D says, "I'm feeling a little stressed today," the emotion engine recognizes that emotion and passes it on to the server. Based on the points expiration information and emotion information, the server generates a notification saying, "D, if you use 200 points at ◎◎ Cafe to refresh yourself by the end of this week, you'll receive double points," and sends it to the device. A notification will appear on D's smartphone, and when he opens the app, a link saying "Use now" will appear. By tapping the link, he will be taken to the coupon page of the affiliated cafe, where he can use his points to refresh himself.

[0280] This allows users to prevent points from expiring and receive suggestions that match their emotions, resulting in a better user experience.

[0281] The processing flow will be explained below.

[0282] Server Processing

[0283] Step 1: Collect user data

[0284] The server collects user point information through the API of each point program, including the number of points, acquisition date, usage history, and expiration date.

[0285] Step 2: Save your data

[0286] The server saves the collected data in a database. The data for each point program is stored in a table and linked using the user ID as a key.

[0287] Step 3: Analyze your points situation

[0288] An AI algorithm on the server analyzes the points information in the database, specifically checking whether the points are nearing their expiration date and, if so, adding them to an alert list.

[0289] Step 4: Collecting emotional information

[0290] The server receives the user's emotional data from the emotion engine and stores it in a database. The emotional data is classified based on text analysis, voice analysis, image analysis, etc.

[0291] Step 5: Generate notifications

[0292] The AI ​​algorithm creates a notification message based on point data and emotion data, such as "Your points for Program A will expire in three days. Please visit XX Cafe to relieve stress."

[0293] Step 6: Sending notifications

[0294] The server generates the notification and sends it to the user, either via email, SMS, or app push notification, depending on how the user receives it.

[0295] Step 7: Collect and collate campaign information

[0296] The server calls an external API to get the latest campaign information, matches it with the user's point data, and adds applicable campaigns to a list.

[0297] Terminal handling

[0298] Step 1: Synchronize your data

[0299] The point management app installed on the device periodically synchronizes with the server to obtain the latest point information.

[0300] Step 2: Viewing points

[0301] The acquired point information is displayed within the app, allowing users to check the balance and expiration date of each point program.

[0302] Step 3: Receive notifications

[0303] The device receives notifications sent from the server and displays them to the user in the app or as a push notification.

[0304] Step 4: View details

[0305] When users tap on the notification, more information will be displayed within the app, including which points to use and details about the campaign.

[0306] User Behavior

[0307] Step 1: Check notifications

[0308] The user checks the notifications received on the device, which include information about upcoming point expiration dates and sentiment-based campaigns.

[0309] Step 2: Use your points

[0310] Users can tap on a link in the app to redeem their points, for example, by being redirected to a page of a partner online shop or physical store where they can make a purchase using their points.

[0311] Step 3: Use the campaign

[0312] Users can use their points efficiently at physical stores and online sites based on the campaign information they receive. For example, if they receive a notification that "There is a double points campaign this weekend at XX store," they can plan to shop at that store.

[0313] Emotion engine processing

[0314] Step 1: Recognize emotions

[0315] The emotion engine analyzes text, voice, and facial expression data entered by the user to recognize emotions. For example, it recognizes the input "I'm tired today" as "fatigue."

[0316] Step 2: Sending emotional information

[0317] The emotion engine sends the recognized emotion information to the server, where the emotion data is stored in a database using the user ID as a key.

[0318] Step 3: Reflection in notifications

[0319] The AI ​​algorithm tailors notifications based on emotional information, for example, if a user is feeling stressed, it will generate notifications suggesting relaxing offers or campaigns.

[0320] Specific examples

[0321] For example, suppose user E has 150 points in point program C, which are set to expire in seven days, and he or she voice-inputs, "I'm feeling stressed today." The emotion engine recognizes the emotion as "stress" and sends it to the server. Based on the point data and emotion data, the server generates a notification saying, "Your 150 points in program C will expire in seven days. We're running a campaign where you can refresh yourself with a free drink at ◎◎ Cafe," and sends it to E's device. E checks the notification, views the details of the campaign in the app, and takes action to use his or her points efficiently at the cafe during the campaign period, thereby relieving stress and not wasting points.

[0322] Example 2

[0323] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0324] With conventional point management systems, users often missed the expiration date of their points, which resulted in point expiry. Furthermore, the content and timing of notifications were not optimized to reflect the user's situation or emotions, which tended to result in low user response rates. Furthermore, campaign information that allowed users to use their points efficiently was often not provided, making improving the user experience a challenge.

[0325] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for collecting point program information from users, means for saving the collected point program information in a database, means for analyzing the saved point program information using an AI algorithm and generating a notification when the points are about to expire, means for sending the generated notification to the user, means for acquiring campaign information from an external source and comparing it with the user's point information to suggest an optimal campaign, and means for recognizing the user's emotions and adjusting the notification content based on the emotion information. This makes it possible to prevent the user's points from expiring and to suggest campaign information at the optimal timing according to the user's emotions.

[0326] A "user" is an individual or corporation that uses the points program, checks point balances, expiration dates, campaign information, etc., and takes appropriate action.

[0327] The "server" is a central control device that stores point program information collected from users, analyzes it using an AI algorithm, and sends notifications and campaign suggestions based on the results.

[0328] A "points program" is a system in which users accumulate points awarded for specific services or product purchases and can use them for various benefits and discounts.

[0329] A "database" is a data storage system that stores and centrally manages point program information, emotional information, and other data collected by the server.

[0330] "AI algorithms" are machine learning and statistical analysis techniques used to analyze collected data and determine expiration dates and the user's emotional state.

[0331] A "notification" is a message that the server generates based on the analysis results and sends to the user, and includes information such as the approaching expiration date of points and campaign information.

[0332] "Campaign information" refers to promotional information such as double points campaigns and discounts offered at specific stores or online sites.

[0333] An "emotion engine" is a software or hardware system that analyzes a user's text input, voice input, and facial expression data to recognize their emotional state at that time.

[0334] A "point management app" is application software that is installed on a user's device and allows the user to check point balances, expiration dates, and notifications.

[0335] An "external API" is a program interface for obtaining campaign information and point information from external services and databases.

[0336] The system for implementing this invention includes four main components: a server, a terminal, a user, and an emotion engine. The specific operation of each component will be described below.

[0337] Server Processing

[0338] User Data Collection and Storage

[0339] The server collects user data through the API of each point program. The data includes the number of points, acquisition date, usage history, and expiration date. This data is stored in a database, and point program information is centrally managed using the user ID as a key.

[0340] Point status analysis

[0341] The AI ​​algorithms installed on the server analyze the stored data, specifically checking whether points are about to expire, using libraries like Python's scikit-learn.

[0342] Generate notifications

[0343] Based on the analysis results of the AI ​​algorithm, the server generates a notification message, such as "Your points for Program A will expire in 3 days." A template engine such as Jinja2 is used to generate the message.

[0344] Sending notifications

[0345] The server generates notifications and sends them to users via email, SMS, push notifications, etc. These notifications are sent using an SMTP server, the Twilio API, or Firebase Cloud Messaging (FCM).

[0346] Collection of campaign information and notification

[0347] The server calls an external API to obtain the latest campaign information. It then compares the obtained campaign information with the user's point information and generates a notification suggesting a relevant campaign. For example, a notification such as "There is a double points campaign at store XX this weekend."

[0348] Terminal handling

[0349] Check your points

[0350] A points management app is installed on the user's device. The app periodically synchronizes data with the server and displays the latest points information. Users can check the balance and expiration date of each points program.

[0351] Receive notifications

[0352] The device receives the notification sent from the server and displays it to the user in the app or as a push notification. When the user taps the notification, more information is displayed in the app and an action such as using points is prompted.

[0353] User Behavior

[0354] Viewing and using points

[0355] The user receives a notification from the server and launches the app to check the status of their points. For example, if they receive a notification that "XX points will expire in 5 days," the user can check the points within the app and use them at affiliated stores or online sites.

[0356] Use of the campaign

[0357] Users can check campaign notifications from the server and use their points efficiently at specific stores or online sites. For example, if a user receives a notification that "There is a double points campaign this weekend at store X," the user can plan to shop at the store that weekend.

[0358] Emotion Engine Operation

[0359] Emotion recognition

[0360] The emotion engine analyzes the text and voice input by the user, as well as facial expression data captured by a high-sensitivity camera, to recognize the user's emotions. For example, if a user inputs "I'm tired today" into the chatbot, it will classify that emotion as "fatigue." This analysis is performed using IBM Watson's speech recognition engine, among other technologies.

[0361] Collecting and storing emotional information

[0362] The emotion recognition results are sent to the server and stored in a database along with point information. The emotion information is linked using the user ID as a key and used for future analysis.

[0363] Creating emotional notifications

[0364] The AI ​​algorithm generates notification messages based on emotional information. For example, if it detects that the user is feeling stressed, it will generate a notification such as "Double points campaign at store XX, perfect for refreshing yourself."

[0365] Adjusting the timing and content of notifications

[0366] The emotion engine analyzes the user's emotional state and adjusts the timing and content of notifications, for example, by sending notifications when the user is relaxed, which increases the user's response rate.

[0367] Specific examples

[0368] For example, suppose user A has 200 points in point program B, and the expiration date is approaching in five days. If user A says, "I'm feeling a little stressed today," the emotion engine recognizes that emotion and passes it on to the server. Based on the points expiration information and emotion information, the server generates a notification saying, "User A, if you use 200 points at store ◎◎ to refresh yourself by the end of this week, there's a double points campaign," and sends it to the device. A notification appears on user A's smartphone, and when A opens the app, a link saying "Use now" appears. By tapping the link, they can access the coupon page of the affiliated store and use their points to refresh themselves.

[0369] Prompt Sentence Examples

[0370] An example of a prompt sentence to input to the generative AI model is as follows:

[0371] Person A has 200 points in point program B, and the points are about to expire in 5 days. Person A voice-inputs, "I'm feeling a little stressed today." In this situation, explain how the emotion engine and server work together to send an appropriate notification to Person A.

[0372] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0373] Step 1:

[0374] User Data Collection and Storage

[0375] The server sends a request to the API of each point program and obtains user data (number of points, acquisition date, usage history, expiration date). The input is the response data from each point program API, and the output is user data in JSON format. This data is saved in a database. Specifically, the server uses Python's Requests library to send the API request, parses the received JSON-formatted response data, and saves it in a database (for example, MySQL).

[0376] Step 2:

[0377] Point status analysis

[0378] The server retrieves point information from the database and analyzes it using an AI algorithm. The input is the point information retrieved from the database, and the output is a list of points that are about to expire. The server runs an AI script written in Python, for example using the scikit-learn library, to analyze the point information. The AI ​​algorithm lists points that are about to expire.

[0379] Step 3:

[0380] Generate notifications

[0381] The server generates a notification message based on the analysis results of the AI ​​algorithm. The input is a list of points that are about to expire, and the output is the notification message to be sent to the user. The server uses a template engine (e.g., Jinja2) to generate the message. For example, it creates a message such as "Your points for Program A will expire in 3 days."

[0382] Step 4:

[0383] Sending notifications

[0384] The server generates and sends notification messages to users. The input is the generated notification message, and the output is the notification sent to the user. The sending method can be email, SMS, or push notification. Specifically, the server sends email using an SMTP server, SMS using the Twilio API, or push notification using Firebase Cloud Messaging (FCM).

[0385] Step 5:

[0386] Collection of campaign information and notification

[0387] The server obtains the latest campaign information through an external API, compares it with the user's point information, and generates a notification proposing the most suitable campaign. The input is the campaign information obtained from the external API and the user's point information, and the output is the generated campaign notification message. The server sends an API request, analyzes the obtained JSON data, compares it with the user's point information, and generates a message such as "There is a double points campaign this weekend at store XX."

[0388] Step 6:

[0389] Check your points

[0390] A points management app installed on the user's device periodically synchronizes with the server and displays the latest points information. The input is point data obtained from the server, and the output is the latest points information displayed on the app's UI. The user checks the balance and expiration date of each points program through the app. The device communicates with the server using HTTP requests, and displays the obtained data on the UI.

[0391] Step 7:

[0392] Receive notifications

[0393] The user's device receives notifications sent from the server and displays them in the app or as push notifications. The input is the notification data sent from the server, and the output is the notification message displayed on the user's device. The device uses Firebase Cloud Messaging (FCM) or similar to receive push notifications, and when the user taps the notification, detailed information is displayed in the app.

[0394] Step 8:

[0395] Viewing and using points

[0396] The user receives a notification from the server, launches the app, and checks the status of their points. The input is the notification content displayed on the device and the point data in the app, and the output is the user's action (using the points). The specific steps a user takes to check the notification and use their points at affiliated stores or online sites are to tap the link in the notification and access the coupon page or related site.

[0397] Step 9:

[0398] Use of the campaign

[0399] The user checks the campaign notification from the server and efficiently uses points at specific stores or online sites. The input is the campaign notification message, and the output is the user's point usage action. The user checks the notification and plans to shop at stores participating in the campaign. The specific steps to display in-app coupons and promote in-store usage include presenting the coupon at the store and using the points.

[0400] Step 10:

[0401] Emotion recognition

[0402] The emotion engine analyzes user input (text, voice, and facial expression data) and recognizes emotions. The input is text, voice, and facial expression data provided by the user through a chatbot or app, and the output is analyzed emotional information. For example, using IBM Watson's speech recognition engine, it can classify emotions such as "fatigue" from the voice input "I'm tired today."

[0403] Step 11:

[0404] Collecting and storing emotional information

[0405] The emotion recognition results are sent to the server and stored in a database. The input is the emotion information analyzed by the emotion engine, and the output is the emotion data stored in the database. This process involves sending the emotion information to the server through an HTTPS request and storing it in the database.

[0406] Step 12:

[0407] Creating emotional notifications

[0408] The AI ​​algorithm generates a notification message based on emotional information. The input is emotional information and point information, and the output is a notification message that takes emotion into consideration. The server uses a template engine to generate a message such as "Double points campaign at store XX, perfect for refreshing yourself."

[0409] Step 13:

[0410] Adjusting the timing and content of notifications

[0411] The emotion engine analyzes the user's emotional state and determines the optimal notification timing. The input is emotional information and the user's behavioral history, and the output is the timing and content of the notification. Specific steps are included to improve the user's response rate by sending notifications during times when the emotion engine is relaxed based on the analysis results.

[0412] (Application example 2)

[0413] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0414] Conventional point program management systems make it difficult for users to effectively utilize their points, as it is cumbersome to keep track of point expiration dates and the latest campaign information. Furthermore, because they do not take into account the user's emotional state, notifications and suggestions are not provided at the most effective times, which makes it difficult to increase user satisfaction. Furthermore, the lack of real-time information provided via smart devices reduces opportunities for users to efficiently use their points when shopping in physical stores.

[0415] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0416] In this invention, the server includes means for collecting point program information from users, means for saving the collected point program information in a database, means for analyzing the saved point program information and generating a notification when points are about to expire, means for sending the generated notification to the user, means for externally acquiring campaign information and comparing it with the user's point information to suggest an optimal campaign, means for recognizing the user's emotions using an emotion engine and reflecting the emotion information in a notification message, and means for displaying notifications via a smart device (including smart glasses, smartphones, and head-mounted displays) so that the user can check point information and campaign information in real time. This allows users to know point expiration dates and the latest campaign information in a timely manner and receive effective suggestions based on their emotion information, which promotes point usage in physical stores and improves user satisfaction.

[0417] A "points program" is a system in which users can earn points by performing certain activities or making purchases and then exchange those points for rewards or services.

[0418] A "database" is an information system for storing and managing point program information collected from users.

[0419] "Notification" is a message that notifies the user when the expiration date of points is approaching or when campaign information is available.

[0420] "Campaign information" is information about discounts and benefits that allow users to use points more advantageously under certain conditions.

[0421] The "emotion engine" is a system that analyzes the user's emotional state and reflects the results in notification messages.

[0422] A "smart device" is an electronic device that can display and input information using advanced technology, such as smart glasses, smartphones, and head-mounted displays.

[0423] A "point management app" is application software that is installed on a user's device and allows the user to check points and receive notifications.

[0424] An "AI algorithm" is a computational method for analyzing data and making predictions using artificial intelligence technology.

[0425] "User data" refers to various information about the user, such as point acquisition history, point usage history, and emotional information.

[0426] "Real-time" refers to a state in which information is collected, analyzed, and notified immediately without delay.

[0427] MODE FOR CARRYING OUT THE INVENTION

[0428] 1. System Program

[0429] The system that realizes this invention consists of four main components: a server, a terminal, a user, and an emotion engine. Each component cooperates to smoothly manage user points and notify users of campaigns.

[0430] 2. Server processing explanation

[0431] The server first collects point program information from users. The target point program data includes the number of points, acquisition date, usage history, expiration date, etc. This information is stored in a database and used as the basis for later analysis.

[0432] The AI ​​algorithm installed on the server analyzes the stored point program information and lists the information when points are about to expire. The AI ​​algorithm then generates a notification message based on the analysis results. For example, it creates a notification saying, "Program A's points will expire in 3 days." The server also calls an external API to obtain the latest campaign information, compares it with the user's point information, and generates a notification suggesting the most suitable campaign.

[0433] 3. Terminal processing explanation

[0434] A points management app is installed on the user's device. This app periodically synchronizes data with the server and displays the latest points information. Through the app, users can check their points balance and expiration date and receive notifications sent from the server. The received notifications are displayed within the app, providing detailed information and instructions on how to use points. In addition, points information and campaign information are displayed in real time through smart devices (smart glasses, smartphones, head-mounted displays, etc.).

[0435] 4. User behavior description

[0436] The user receives a notification from the server and launches the point management app to check the status of their points. For example, if they receive a notification that "XX points will expire in 5 days," the user can check the points in the app and use them at affiliated stores or online sites. They can also check campaign notifications from the server to use their points efficiently at specific stores or online sites. For example, if they receive a notification that "XX store is having a double points campaign this weekend," they can plan to shop at the store that weekend.

[0437] 5. Explanation of Emotion Engine Operation

[0438] The emotion engine analyzes the text and voice input by the user, as well as facial expression data captured by a high-sensitivity camera, to recognize the user's emotions. For example, if the user inputs, "I'm feeling a little stressed today," the emotion engine recognizes this emotion as "stress" and conveys it to the server. The server then generates a notification message based on the points expiration information and emotion information. For example, it might generate a notification with the content, "Double points campaign at store XX, perfect for refreshing yourself," and send it to the user. The timing and content of the notification are also adjusted based on the user's emotional state. For example, sending notifications during times when the user is relaxed can improve the response rate after receiving the notification.

[0439] 6. Explanation of specific examples

[0440] For example, suppose a user has 200 points and their expiration date is approaching in five days. If the user says, "I'm feeling a little stressed today," the emotion engine recognizes that emotion and communicates it to the server. Based on the points' expiration date and emotion information, the server generates a notification with the message, "Double points campaign at a cafe perfect for refreshing yourself," and sends it to the user's smart device. The notification is displayed on the user's smart glasses, and when the user opens the app, a link that says, "Use now." Tapping the link takes them to the coupon page of a partner cafe, where they can use their points to refresh themselves.

[0441] 7. Examples of prompts

[0442] Below is an example of a prompt sentence.

[0443] "The points for user ID 'user123' will expire in 4 days. A double points campaign is running until the end of this week at a cafe perfect for refreshing yourself. The coupon will be automatically applied when you use your smart glasses."

[0444] In this way, users can prevent points from expiring and receive more emotionally relevant suggestions, resulting in a better user experience.

[0445] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0446] Step 1:

[0447] User Data Collection and Storage

[0448] The server collects user data through the API of the point program. As input, it acquires point program information such as the number of points, acquisition date, usage history, and expiration date, and stores it in a database. Specifically, it links the point program information to the user ID and manages it centrally.

[0449] Step 2:

[0450] Point status analysis

[0451] The server uses the point program information stored in the database to list points that are about to expire. As input, it reads the stored point data and uses an AI algorithm to extract points that are about to expire. As output, it generates a list of points that are about to expire. Specifically, it calculates the number of days until the expiration date and lists points that will expire within a certain period of time.

[0452] Step 3:

[0453] Generate notifications

[0454] The server generates a notification message based on the results of point status analysis. The input is the list of points that are about to expire, which is the output of step 2. As an output, a specific notification message is generated. As a specific example, a message is created stating, "The points for user ID 'user123' will expire in 3 days."

[0455] Step 4:

[0456] Sending notifications

[0457] The server sends the generated notification message to the user. The input is the notification message generated in step 3, and the output is to send the notification to the user via email, SMS, or push notification. Specifically, the message is sent based on the notification method set by the user.

[0458] Step 5:

[0459] Collection and proposal of campaign information

[0460] The server retrieves the latest campaign information from an external API and compares it with the user's point information. The input is the campaign information retrieved from the external API, and the output is a message proposing the most suitable campaign for the user. Specifically, the server compares the user's point information and campaign information against the conditions to propose the most suitable campaign.

[0461] Step 6:

[0462] Recognizing and reflecting emotions

[0463] The emotion engine analyzes the user's text input, voice data, and facial expression data to recognize the user's emotions. The input is the emotional data provided by the user, and the output is emotional information sent to the server. Specifically, the emotion engine recognizes emotions such as "stress" and "relaxation" and passes that information to the server.

[0464] Step 7:

[0465] Generate emotional notifications

[0466] The server generates a notification that reflects emotional information based on the output from the emotion engine. The input is the emotional information from step 6, and the output is a notification message that takes emotion into consideration. As a specific example, it generates a notification that reads, "There is a double points campaign at a cafe that is perfect for refreshing yourself."

[0467] Step 8:

[0468] Displaying notifications on smart devices

[0469] The terminal receives the notification sent from the server and displays it to the user through the smart device. The input is the notification message generated in step 4 and step 7, and the output is the display on the smart glasses, smartphone, or head-mounted display. Specifically, the notification is displayed on the display of the smart device in real time.

[0470] Through these steps, users can understand point expiration dates and campaign information in real time, and receive emotionally tailored suggestions, allowing them to enjoy a better user experience.

[0471] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0472] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0473] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0474] [Second embodiment]

[0475] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0476] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0477] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0478] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0479] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0480] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0481] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0482] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0483] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0484] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0485] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0486] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0487] The system for implementing this invention includes three main components: a server, a terminal, and a user. The specific operation of each component will be described below.

[0488] Server Processing

[0489] User Data Collection and Storage

[0490] The server collects user data through the API of each point program, including the number of points a user has, the date they have earned them, their usage history, and their point expiration date. This data is stored in a database, and point program information is centrally managed using the user ID as a key.

[0491] Point status analysis

[0492] An AI algorithm installed on the server periodically analyzes the user's point usage history and expiration date. It checks whether the points are about to expire and generates a notification if so. It also prioritizes the use of points and suggests the best time to use them.

[0493] Sending notifications

[0494] The server notifies users when their points are about to expire and about the latest campaign information. Notifications are sent via email, SMS, app push notifications, etc. to encourage users to use their points.

[0495] Collection of campaign information and notification

[0496] Campaign information is obtained through an external API and compared with the user's point information. Based on the comparison results, the system notifies the user that points can be used more efficiently by taking advantage of a specific campaign. For example, if a specific store is running a double points campaign, the system notifies the user of this information.

[0497] Terminal handling

[0498] Check your points

[0499] A points management app is installed on the user's device. The app periodically synchronizes data with the server and displays the latest points status. Users can open the app to check the balance and expiration date of each points program.

[0500] Receive notifications

[0501] The device receives notifications sent from the server and displays them to the user. The notification content includes information about upcoming points expiration dates and campaign information. When the user taps the notification, detailed information is displayed within the app and an action such as using points is prompted.

[0502] User Behavior

[0503] Viewing and using points

[0504] The user receives a notification from the server and launches the app to check the status of their points. For example, if they receive a notification that "XX points will expire in 5 days," the user can check the points within the app and use them at affiliated stores or online sites.

[0505] Use of the campaign

[0506] Users can check campaign notifications from the server and use their points efficiently at specific stores or online sites. For example, if a user receives a notification that "There is a double points campaign this weekend at store X," the user can plan to shop at the store that weekend.

[0507] Specific examples

[0508] For example, suppose user C has 300 points in point program A. When the expiration date is approaching in three days, the server detects this information and sends C a notification saying, "Your 300 points in program A will expire in three days." A notification will appear on C's smartphone, and when C opens the app, a link saying "Use now" will appear. By tapping the link, C will be taken to an affiliated online shop where she can use her points to purchase products.

[0509] This system allows users to prevent points from expiring and use them efficiently. It also allows users to get the most out of their points by staying up to date with the latest campaign information.

[0510] The processing flow will be explained below.

[0511] Specific processing of the program

[0512] Server Processing

[0513] Step 1: Collect data

[0514] The server obtains user point information through the API of each point program, including the number of points, acquisition date, usage history, and expiration date.

[0515] Step 2: Save your data

[0516] The server stores the acquired data in a database. There is a separate table for each point program, and data is associated using the user ID as a key.

[0517] Step 3: Analyze the data

[0518] An AI algorithm installed on the server analyzes the points information in the database, in particular checking whether the points are about to expire and listing those points that are about to expire.

[0519] Step 4: Generate notifications

[0520] Based on the results of the AI ​​algorithm's analysis, the server generates a notification message, such as "Your points for Program A will expire in 3 days."

[0521] Step 5: Sending notifications

[0522] The server generates the notification and sends it to the user, either via email, SMS, or push notification, allowing the user to receive the notification.

[0523] Step 6: Gather campaign information

[0524] The server calls an external API to obtain the latest campaign information, such as information about a double points campaign being held at a specific store.

[0525] Step 7: Campaign information verification and notification

[0526] The server compares the acquired campaign information with the user's point information, generates a notification proposing the relevant campaign, and sends it to the user.

[0527] Terminal handling

[0528] Step 1: Synchronize your data

[0529] The point management app installed on the device periodically synchronizes with the server to obtain the latest point information.

[0530] Step 2: Viewing points

[0531] The acquired point information is displayed within the app, allowing users to check the balance and expiration date of each point program.

[0532] Step 3: Receive notifications

[0533] The device receives notifications sent from the server and displays them to the user in-app or as push notifications.

[0534] Step 4: View details

[0535] When users tap on the notification, more information will be displayed within the app, including where points can be used and details about the campaign.

[0536] User Behavior

[0537] Step 1: Check notifications

[0538] The user checks the notification received on the device, which notifies them of the approaching expiration date of specific points and campaign information.

[0539] Step 2: Use your points

[0540] Users can redeem their points by clicking a link within the app, for example by being redirected to a partner online shop where they can use their points to purchase products.

[0541] Step 3: Use the campaign

[0542] Users can use points efficiently at physical stores and online sites based on the campaign information received on their devices, and plan their shopping accordingly.

[0543] Through these steps, a system is realized in which the server, terminal, and user work together to efficiently manage and use points.

[0544] Example 1

[0545] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0546] With conventional point management systems, users were unable to properly grasp the expiration dates of points or available campaign information, making it difficult to prevent points from expiring or use them at the optimal time. In particular, when managing multiple point programs, it was time-consuming to check the point balance and expiration date of each program individually, which was a significant burden for users. In addition, the priority order for point usage was unclear, which also hindered users from using points efficiently.

[0547] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0548] In this invention, the server includes means for collecting point program information from users, means for saving the collected point program information in a database, means for analyzing the saved point program information and generating a notification when points are about to expire, means for sending the generated notification to the user, means for externally acquiring campaign information and comparing it with the user's point information to propose optimal campaigns, means having an algorithm for periodically analyzing the collected point data and campaign information, and means for notifying the collected campaign information based on the user's point usage priority. This allows users to efficiently understand and use point expiration dates, optimal usage times, and campaign information through the app.

[0549] "User information" refers to data related to the points program, such as user identification information, number of points, acquisition date, usage history, and expiration date.

[0550] A "database" is an electronic storage system that centrally manages collected point program information and allows for easy storage, searching, and updating.

[0551] "Notifications" are messages that inform users when their points are about to expire or about the best campaign information. Notification formats include email, SMS, and app push notifications.

[0552] An "external API" is an interface that a server uses to obtain information from external services or databases. It is used to obtain campaign information, etc.

[0553] "Campaign information" refers to information about benefits for using points efficiently, such as a campaign to double points at a specific store.

[0554] "Algorithm" refers to a series of computational procedures that run on the server and analyze the point usage history and expiration date. Specifically, it includes pattern recognition and machine learning models.

[0555] A "point management app" is application software that users install on their smartphones or tablets to check their point balance, expiration date, and campaign information.

[0556] A "user device" is an electronic device used by a user, such as a smartphone, tablet, or computer, on which the point management app is installed and used.

[0557] "Verification" is a process in which the server compares the user's point data with the acquired campaign information to identify available point campaigns.

[0558] The "usage priority" is a standard for setting the priority when using points. For example, points that are close to their expiration date are set to be used first.

[0559] The system for implementing this invention includes three main components: a server, a terminal, and a user. The specific operation of each component and how they work together will be described in detail below.

[0560] Server Processing

[0561] The server first has a means of collecting point program information from users. This collection is done through the API of each point program, and data such as the number of points a user has, the date they acquired them, their usage history, and their expiration date is obtained. This information is then saved in a database. The saved point program information is managed centrally and registered using the user ID as a key.

[0562] The server then periodically analyzes the stored loyalty program information. Using AI algorithms, the server generates notifications when points are about to expire. These notifications include information about the points that are about to expire and recommended times to use them. These notifications are then sent to users via email, SMS, app push notifications, and more.

[0563] In addition, the server obtains campaign information through an external API. This campaign information is matched with the user's point data and used to suggest the most suitable campaign. If the campaign is an effective way to use points, the server notifies the user of this information. For example, if a specific store is running a double points campaign, the server notifies the user of this information.

[0564] Terminal handling

[0565] A points management app is installed on the device. This app periodically synchronizes data with the server and displays the latest points status. Users can open the app to check the balance and expiration date of each points program.

[0566] The device also receives notifications sent from the server. These notifications include information about upcoming point expiration dates and campaign information, and are displayed to the user. When the user taps the notification, more information is displayed in the app and an action is prompted, such as using points.

[0567] User Behavior

[0568] The user receives a notification from the server and launches the app to check the status of their points. For example, if they receive a notification saying, "X points will expire in 5 days," the user can check the status of their points within the app and use them at affiliated stores or online sites. Also, if they receive a notification about campaign information, for example, "There's a double points campaign at X store this weekend," they can check the notification and plan their shopping at the store that weekend.

[0569] Specific examples

[0570] For example, suppose user A has 300 points in point program A. When the expiration date is approaching in three days, the server detects this information and sends user A a notification saying, "Your 300 points in program A will expire in three days." A notification will appear on user A's smartphone, and when user A opens the app, a link saying "Use now" will appear. By tapping the link, user A will be taken to an affiliated online shop where they can use their points to purchase products.

[0571] Example prompts for generative AI models

[0572] "Please explain the specific behavior of a feature in a user's point management system that notifies users when their points are about to expire. As a specific scenario, please explain the case where a user has 300 points in point program A and the points are about to expire in three days."

[0573] This system allows users to prevent points from expiring, allowing them to use their points efficiently. It also allows users to get the most out of their points by staying up to date with the latest campaign information.

[0574] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0575] Step 1:

[0576] User Data Collection

[0577] The server calls the API of each point program to collect user data, including the number of points a user has, the date they acquired them, their usage history, and their expiration date.

[0578] Input: API endpoint of each point program

[0579] What happens: The server sends an HTTP request to the API endpoint and parses the returned JSON data.

[0580] Data processing: Parse the acquired JSON data and extract the user ID, number of points, acquisition date, usage history, and expiration date.

[0581] Output: Parsed user data

[0582] Step 2:

[0583] Saving to a database

[0584] The server stores the collected user data in a database. Point program information is centrally managed using the user ID as a key.

[0585] Input: Parsed user data

[0586] What happens: The server opens a database connection, executes an SQL query, and saves the user data.

[0587] Data processing: Convert user data into a database table format.

[0588] Output: User data stored in the database

[0589] Step 3:

[0590] Point status analysis

[0591] The AI ​​algorithm installed on the server analyzes point usage history and expiration dates, and generates a notification when a user's points are about to expire.

[0592] Input: User data stored in the database

[0593] How it works: The server runs an AI algorithm, taking user data as input and outputting a data set showing when points are about to expire.

[0594] Data calculation: Using a machine learning model, points usage history and expiration dates are analyzed to extract points that are close to expiring.

[0595] Output: List of points that are about to expire

[0596] Step 4:

[0597] Generate and send notifications

[0598] The server generates notifications based on the analysis results and sends them to the user in the form of email, SMS, app push notifications, etc.

[0599] Input: List of points that are about to expire

[0600] Specific operation: The server uses the notification template to generate notification content for each user, and then sends the notification using the SMTP protocol or SMS API.

[0601] Data processing: Embed user point information in the notification template.

[0602] Output: Notification sent to the user

[0603] Step 5:

[0604] Collection of campaign information and notification

[0605] The server obtains the latest campaign information through an external API, compares it with the user's point data, and generates notifications to suggest the most suitable campaigns.

[0606] Input: Campaign information from external API

[0607] What it does: The server sends an HTTP request to an external API to retrieve campaign information, which it then stores in a database and matches with the user's point data.

[0608] Data calculation: Compare the acquired campaign information with user point data to select the most suitable campaign.

[0609] Output: Campaign notification sent to users

[0610] Step 6:

[0611] Check your points

[0612] A points management app is installed on the device. This app periodically synchronizes data with the server and displays the latest points status. Users can open the app to check their points balance and expiration date.

[0613] Input: Latest point data synchronized from the server

[0614] Specific operation: The app calls the API in the background to get the latest point data from the server, which is then saved in local storage and displayed in the user interface.

[0615] Data processing: Convert the data obtained from the server into the display format of the app.

[0616] Output: Points balance and expiry date displayed in the app

[0617] Step 7:

[0618] Receive notifications

[0619] The device receives notifications sent from the server and displays them to the user, who can tap on them to view more information within the app.

[0620] Input: Notification sent from the server

[0621] Specific behavior: The device's notification service receives the push notification from the server and displays it in the notification center. When the user taps the notification, the relevant app screen is opened.

[0622] Data processing: Converts the notification content into a format suitable for the user interface.

[0623] Output: Notification displayed in the notification center and detailed information in the app

[0624] Step 8:

[0625] Viewing and using points

[0626] When users receive a notification, they can launch the app to check their points status and use them at affiliated stores or online sites.

[0627] Input: Point information and notification content displayed in the app

[0628] Specific operation: The user taps a link in the app to access a partner store or online shop, where they can use their points to purchase a product.

[0629] Data processing: Transaction data for point usage is generated and sent to the server.

[0630] Output: Transaction record of items purchased using points

[0631] Step 9:

[0632] Use of the campaign

[0633] The user checks the campaign notification from the server and uses the points to effectively take advantage of the campaign.

[0634] Input: In-app campaign notifications and details

[0635] Specific actions: The user taps on the campaign notification, checks the details, and redeems the campaign in a physical store or online shop.

[0636] Data processing: Campaign transaction data is generated and sent to the server.

[0637] Output: Transaction record of points redemption using campaign

[0638] (Application example 1)

[0639] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0640] Conventional point program management systems notify users when their points are about to expire, but this can sometimes prevent users from using their points at the appropriate time. Furthermore, they do not provide sufficient functionality for efficiently utilizing campaign information and optimizing point usage, resulting in point expiration and inefficient point usage. Therefore, there is a need for a way for users to use points efficiently and prevent them from expiring.

[0641] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0642] In this invention, the server includes means for collecting point program information from users, means for saving the collected point program information in a database, means for analyzing the saved point program information and generating a notification when the point expiration date is approaching, means for sending the generated notification to the user, means for acquiring campaign information from an external source and comparing it with the user's point information to propose the most suitable campaign, and means for sending point expiration date notifications and campaign information notifications to the user via a mail server. This allows users to check the point expiration date as needed and use their points efficiently. Furthermore, by utilizing the campaign information, the utility value of points can be maximized and users can manage their points effectively.

[0643] "User" refers to a person who uses the points program.

[0644] A "points program" is a system in which users are given points each time they use a specific service or product, and can use these points to receive discounts or benefits.

[0645] "Collecting information" refers to the process of obtaining data related to the loyalty program.

[0646] A "database" is an information system for systematically storing and efficiently managing collected data.

[0647] "Expiration date approaching" indicates that the points are about to expire.

[0648] "Generating a notification" is the act of creating a message to inform a user of information.

[0649] "Campaign Information" refers to information about promotions such as special offers and discounts that are held during a specific period of time.

[0650] "Matching" is the act of comparing specific data with other data to identify similarities and differences.

[0651] "Sending" refers to the act of delivering the generated notification to the user via electronic means.

[0652] A "mail server" is a server that manages the sending and receiving of email.

[0653] An "AI algorithm" is a computational process that analyzes user behavior patterns and data to derive efficient methods.

[0654] A "generative AI model" is a model that uses machine learning to generate new information and patterns from data.

[0655] The system for implementing this invention includes three main components: a server, a terminal, and a user. The main functions of this system are to collect, store, analyze, and notify users of point program information, and to suggest campaign information.

[0656] Server Processing

[0657] The server collects user data through the point program's API. Specifically, it obtains data such as the number of points a user has, the date they acquired them, their usage history, and their point expiration date, and stores this data in a database. The point program information is centrally managed using the user ID in the database as a key.

[0658] Next, an AI algorithm installed on the server periodically analyzes the user's point usage history and expiration date. This checks whether the points are about to expire and generates a notification if so. It also prioritizes the use of points and suggests the best time to use them.

[0659] Furthermore, campaign information is obtained through an external API and compared with the user's point information. Based on the comparison results, the system notifies the user that points can be used more efficiently by taking advantage of a specific campaign. For example, if a specific store is running a double points campaign, the system notifies the user of this information. Notifications are sent to the user via a mail server.

[0660] Terminal handling

[0661] A points management app is installed on the user's device. This app periodically synchronizes data with the server and displays the latest points status. Users can open the app to check the balance and expiration date of each points program. The app also includes a function to receive notifications sent from the server and display them to the user. By tapping the notification, users can check detailed information within the app and be prompted to take action, such as using points.

[0662] User Behavior

[0663] The user receives a notification from the server and launches the app to check the status of their points. For example, if they receive a notification that "XX points will expire in 5 days," they can check the points within the app and use them at affiliated stores or online sites. Furthermore, if they receive a notification that "XX store is having a double points campaign this weekend," they can plan to shop at the store that weekend.

[0664] This system allows users to prevent points from expiring and use them efficiently. Also, by staying up-to-date on the latest campaign information, users can make the most of their points. This increases user satisfaction and makes the point program more useful.

[0665] Specific examples

[0666] For example, suppose user C has 300 points in point program A. When the expiration date is approaching in three days, the server detects this information and sends C a notification saying, "Your 300 points in program A will expire in three days." A notification will appear on C's smartphone, and when C opens the app, a link saying "Use now" will appear. By tapping the link, C will be taken to an affiliated online shop where he can use his points to purchase products.

[0667] Prompt Sentence Examples

[0668] We want to build an app that centrally manages users' point information and campaign information, and suggests optimal point usage. The goal is to efficiently receive point expiration dates and campaign information from users, and to help them with the process of actually using their points. Specifically, the app includes the following features:

[0669] 1. Point expiration notification

[0670] 2. Notification of campaign information

[0671] 3. Suggestions for using points

[0672] How do you collect and analyze user data and send appropriate notifications? What technologies do you use to do so?

[0673] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0674] Step 1: Collect user data

[0675] The server obtains user data from the API of each point program. The input is an API request, and the output is data such as the number of points, acquisition date, usage history, and point expiration date. Specifically, it sends a request to the API endpoint, parses the results, and collects them as structured data. By doing this periodically, the latest information is maintained.

[0676] Step 2: Save your data

[0677] The server saves the point program information collected in step 1 in a database. The input here is the collected point information, and the output is structured data saved in the database. Specifically, it executes an INSERT or UPDATE query on the database and centrally manages the data using the user ID as a key.

[0678] Step 3: Analyze points expiration dates

[0679] The server periodically analyzes the stored point program information to check whether any points are about to expire. The input to this step is the point information in the database, and the output is a list of points that are about to expire. The specific operation is to perform an operation that compares the expiration date of each point with the current date, and extracts points that are about to expire within three days.

[0680] Step 4: Generate and send notifications

[0681] Based on the results of step 3, the server generates a notification when points are about to expire and sends the notification to the user. The input here is a list of points that are about to expire, and the output is the generated notification message and the sending result. The specific operation is to embed the point information in a message template, obtain the user's email address, and send the notification through the email server.

[0682] Step 5: Obtain and verify campaign information

[0683] The server retrieves campaign information through an external API and compares it with the user's point information. The input of this step is the campaign data from the external API and the user's point information, and the output is a list of points recommended for campaign use. The specific operation is to retrieve campaign information and match it with the user's point data to identify points that can be used effectively in a specific campaign.

[0684] Step 6: Generate and send campaign notifications

[0685] The server notifies the user of specific campaign information based on the results of step 5. The input here is a list of points where campaign use is recommended, and the output is the generated campaign notification and sending result. The specific operation is to generate a notification message containing the campaign information and send it to the user via the mail server.

[0686] Step 7: Check your points status

[0687] The device receives the notification sent from the server and displays it so that the user can check the status of point usage. The input here is the notification data from the server, and the output is the point information display screen on the device. The specific operation is that the device app receives the notification from the server and displays the information to the user in an appropriate format.

[0688] Step 8: Promote points usage

[0689] Users can use their points efficiently based on the notifications displayed on their devices. The input here is the displayed notification information, and the output is the actual act of using points. Specifically, users tap the notification to check detailed information, and then access affiliated online shops or stores via the link to use their points.

[0690] Step 9: Collect feedback data

[0691] The server collects data on how users use points and campaigns. The input here is user behavior data, and the output is updated point usage history data. The specific operation is to track user behavior and update the database to analyze campaign effectiveness and point usage trends.

[0692] Prompt Sentence Examples

[0693] We want to build an app that centrally manages users' point information and campaign information, and suggests optimal point usage. The goal is to efficiently receive point expiration dates and campaign information from users, and to help them with the process of actually using their points. Specifically, the app includes the following features:

[0694] 1. Point expiration notification

[0695] 2. Notification of campaign information

[0696] 3. Suggestions for using points

[0697] How do you collect and analyze user data and send appropriate notifications? What technologies do you use to do so?

[0698] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0699] The system for implementing this invention includes four main components: a server, a terminal, a user, and an emotion engine. The specific operation of each component will be described below.

[0700] Server Processing

[0701] User Data Collection and Storage

[0702] The server collects user data through the API of each point program. The data includes the number of points, acquisition date, usage history, and expiration date. This data is stored in a database, and point program information is centrally managed using the user ID as a key.

[0703] Point status analysis

[0704] An AI algorithm installed on the server analyzes the points information in the database, in particular checking whether the points are about to expire and listing those points that are about to expire.

[0705] Generate notifications

[0706] Based on the results of the AI ​​algorithm's analysis, the server generates a notification message, such as "Your points for Program A will expire in 3 days."

[0707] Sending notifications

[0708] The server generates the notification and sends it to the user, either via email, SMS, or push notification, allowing the user to receive the notification.

[0709] Collection of campaign information and notification

[0710] The server calls an external API to obtain the latest campaign information. For example, it obtains information about a double points campaign being held at a specific store. It compares the obtained campaign information with the user's point information and generates a notification suggesting a relevant campaign. It then sends this to the user.

[0711] Terminal handling

[0712] Check your points

[0713] A points management app is installed on the user's device. The app periodically synchronizes data with the server and displays the latest points information. Users can check the balance and expiration date of each points program.

[0714] Receive notifications

[0715] The device receives the notification sent from the server and displays it to the user in the app or as a push notification. When the user taps the notification, more information is displayed in the app and an action such as using points is prompted.

[0716] User Behavior

[0717] Viewing and using points

[0718] The user receives a notification from the server and launches the app to check the status of their points. For example, if they receive a notification that "XX points will expire in 5 days," the user can check the points within the app and use them at affiliated stores or online sites.

[0719] Use of the campaign

[0720] Users can check campaign notifications from the server and use their points efficiently at specific stores or online sites. For example, if a user receives a notification that "There is a double points campaign this weekend at store X," the user can plan to shop at the store that weekend.

[0721] Emotion Engine Operation

[0722] Emotion recognition

[0723] The emotion engine analyzes the text and voice input by the user, as well as facial expression data captured by a high-sensitivity camera, to recognize the user's emotions. For example, if a user inputs "I'm tired today" into the chatbot, it will classify that emotion as "fatigue."

[0724] Collecting and storing emotional information

[0725] The emotion recognition results are sent to the server and stored in a database along with point information. The emotion information is linked using the user ID as a key and used for future analysis.

[0726] Creating emotional notifications

[0727] The AI ​​algorithm generates notification messages based on emotional information. For example, if it detects that the user is feeling stressed, it will generate a notification such as "Double points campaign at store XX, perfect for refreshing yourself."

[0728] Adjusting the timing and content of notifications

[0729] The emotion engine analyzes the user's emotional state and adjusts the timing and content of notifications, for example, by sending notifications when the user is relaxed, which increases the user's response rate.

[0730] Specific examples

[0731] For example, suppose user D has 200 points in point program B, and the expiration date is approaching in five days. If D says, "I'm feeling a little stressed today," the emotion engine recognizes that emotion and passes it on to the server. Based on the points expiration information and emotion information, the server generates a notification saying, "D, if you use 200 points at ◎◎ Cafe to refresh yourself by the end of this week, you'll receive double points," and sends it to the device. A notification will appear on D's smartphone, and when he opens the app, a link saying "Use now" will appear. By tapping the link, he will be taken to the coupon page of the affiliated cafe, where he can use his points to refresh himself.

[0732] This allows users to prevent points from expiring and receive suggestions that match their emotions, resulting in a better user experience.

[0733] The processing flow will be explained below.

[0734] Server Processing

[0735] Step 1: Collect user data

[0736] The server collects user point information through the API of each point program, including the number of points, acquisition date, usage history, and expiration date.

[0737] Step 2: Save your data

[0738] The server saves the collected data in a database. The data for each point program is stored in a table and linked using the user ID as a key.

[0739] Step 3: Analyze your points situation

[0740] An AI algorithm on the server analyzes the points information in the database, specifically checking whether the points are nearing their expiration date and, if so, adding them to an alert list.

[0741] Step 4: Collecting emotional information

[0742] The server receives the user's emotional data from the emotion engine and stores it in a database. The emotional data is classified based on text analysis, voice analysis, image analysis, etc.

[0743] Step 5: Generate notifications

[0744] The AI ​​algorithm creates a notification message based on point data and emotion data, such as "Your points for Program A will expire in three days. Please visit XX Cafe to relieve stress."

[0745] Step 6: Sending notifications

[0746] The server generates the notification and sends it to the user, either via email, SMS, or app push notification, depending on how the user receives it.

[0747] Step 7: Collect and collate campaign information

[0748] The server calls an external API to get the latest campaign information, matches it with the user's point data, and adds applicable campaigns to a list.

[0749] Terminal handling

[0750] Step 1: Synchronize your data

[0751] The point management app installed on the device periodically synchronizes with the server to obtain the latest point information.

[0752] Step 2: Viewing points

[0753] The acquired point information is displayed within the app, allowing users to check the balance and expiration date of each point program.

[0754] Step 3: Receive notifications

[0755] The device receives notifications sent from the server and displays them to the user in the app or as a push notification.

[0756] Step 4: View details

[0757] When users tap on the notification, more information will be displayed within the app, including which points to use and details about the campaign.

[0758] User Behavior

[0759] Step 1: Check notifications

[0760] The user checks the notifications received on the device, which include information about upcoming point expiration dates and sentiment-based campaigns.

[0761] Step 2: Use your points

[0762] Users can tap on a link in the app to redeem their points, for example, by being redirected to a page of a partner online shop or physical store where they can make a purchase using their points.

[0763] Step 3: Use the campaign

[0764] Users can use their points efficiently at physical stores and online sites based on the campaign information they receive. For example, if they receive a notification that "There is a double points campaign this weekend at XX store," they can plan to shop at that store.

[0765] Emotion engine processing

[0766] Step 1: Recognize emotions

[0767] The emotion engine analyzes text, voice, and facial expression data entered by the user to recognize emotions. For example, it recognizes the input "I'm tired today" as "fatigue."

[0768] Step 2: Sending emotional information

[0769] The emotion engine sends the recognized emotion information to the server, where the emotion data is stored in a database using the user ID as a key.

[0770] Step 3: Reflection in notifications

[0771] The AI ​​algorithm tailors notifications based on emotional information, for example, if a user is feeling stressed, it will generate notifications suggesting relaxing offers or campaigns.

[0772] Specific examples

[0773] For example, suppose user E has 150 points in point program C, which are set to expire in seven days, and he or she voice-inputs, "I'm feeling stressed today." The emotion engine recognizes the emotion as "stress" and sends it to the server. Based on the point data and emotion data, the server generates a notification saying, "Your 150 points in program C will expire in seven days. We're running a campaign where you can refresh yourself with a free drink at ◎◎ Cafe," and sends it to E's device. E checks the notification, views the details of the campaign in the app, and takes action to use his or her points efficiently at the cafe during the campaign period, thereby relieving stress and not wasting points.

[0774] Example 2

[0775] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0776] With conventional point management systems, users often missed the expiration date of their points, which resulted in point expiry. Furthermore, the content and timing of notifications were not optimized to reflect the user's situation or emotions, which tended to result in low user response rates. Furthermore, campaign information that allowed users to use their points efficiently was often not provided, making improving the user experience a challenge.

[0777] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for collecting point program information from users, means for saving the collected point program information in a database, means for analyzing the saved point program information using an AI algorithm and generating a notification when the points are about to expire, means for sending the generated notification to the user, means for acquiring campaign information from an external source and comparing it with the user's point information to suggest an optimal campaign, and means for recognizing the user's emotions and adjusting the notification content based on the emotion information. This makes it possible to prevent the user's points from expiring and to suggest campaign information at the optimal timing according to the user's emotions.

[0778] A "user" is an individual or corporation that uses the points program, checks point balances, expiration dates, campaign information, etc., and takes appropriate action.

[0779] The "server" is a central control device that stores point program information collected from users, analyzes it using an AI algorithm, and sends notifications and campaign suggestions based on the results.

[0780] A "points program" is a system in which users accumulate points awarded for specific services or product purchases and can use them for various benefits and discounts.

[0781] A "database" is a data storage system that stores and centrally manages point program information, emotional information, and other data collected by the server.

[0782] "AI algorithms" are machine learning and statistical analysis techniques used to analyze collected data and determine expiration dates and the user's emotional state.

[0783] A "notification" is a message that the server generates based on the analysis results and sends to the user, and includes information such as the approaching expiration date of points and campaign information.

[0784] "Campaign information" refers to promotional information such as double points campaigns and discounts offered at specific stores or online sites.

[0785] An "emotion engine" is a software or hardware system that analyzes a user's text input, voice input, and facial expression data to recognize their emotional state at that time.

[0786] A "point management app" is application software that is installed on a user's device and allows the user to check point balances, expiration dates, and notifications.

[0787] An "external API" is a program interface for obtaining campaign information and point information from external services and databases.

[0788] The system for implementing this invention includes four main components: a server, a terminal, a user, and an emotion engine. The specific operation of each component will be described below.

[0789] Server Processing

[0790] User Data Collection and Storage

[0791] The server collects user data through the API of each point program. The data includes the number of points, acquisition date, usage history, and expiration date. This data is stored in a database, and point program information is centrally managed using the user ID as a key.

[0792] Point status analysis

[0793] The AI ​​algorithms installed on the server analyze the stored data, specifically checking whether points are about to expire, using libraries like Python's scikit-learn.

[0794] Generate notifications

[0795] Based on the analysis results of the AI ​​algorithm, the server generates a notification message, such as "Your points for Program A will expire in 3 days." A template engine such as Jinja2 is used to generate the message.

[0796] Sending notifications

[0797] The server generates notifications and sends them to users via email, SMS, push notifications, etc. These notifications are sent using an SMTP server, the Twilio API, or Firebase Cloud Messaging (FCM).

[0798] Collection of campaign information and notification

[0799] The server calls an external API to obtain the latest campaign information. It then compares the obtained campaign information with the user's point information and generates a notification suggesting a relevant campaign. For example, a notification such as "There is a double points campaign at store XX this weekend."

[0800] Terminal handling

[0801] Check your points

[0802] A points management app is installed on the user's device. The app periodically synchronizes data with the server and displays the latest points information. Users can check the balance and expiration date of each points program.

[0803] Receive notifications

[0804] The device receives the notification sent from the server and displays it to the user in the app or as a push notification. When the user taps the notification, more information is displayed in the app and an action such as using points is prompted.

[0805] User Behavior

[0806] Viewing and using points

[0807] The user receives a notification from the server and launches the app to check the status of their points. For example, if they receive a notification that "XX points will expire in 5 days," the user can check the points within the app and use them at affiliated stores or online sites.

[0808] Use of the campaign

[0809] Users can check campaign notifications from the server and use their points efficiently at specific stores or online sites. For example, if a user receives a notification that "There is a double points campaign this weekend at store X," the user can plan to shop at the store that weekend.

[0810] Emotion Engine Operation

[0811] Emotion recognition

[0812] The emotion engine analyzes the text and voice input by the user, as well as facial expression data captured by a high-sensitivity camera, to recognize the user's emotions. For example, if a user inputs "I'm tired today" into the chatbot, it will classify that emotion as "fatigue." This analysis is performed using IBM Watson's speech recognition engine, among other technologies.

[0813] Collecting and storing emotional information

[0814] The emotion recognition results are sent to the server and stored in a database along with point information. The emotion information is linked using the user ID as a key and used for future analysis.

[0815] Creating emotional notifications

[0816] The AI ​​algorithm generates notification messages based on emotional information. For example, if it detects that the user is feeling stressed, it will generate a notification such as "Double points campaign at store XX, perfect for refreshing yourself."

[0817] Adjusting the timing and content of notifications

[0818] The emotion engine analyzes the user's emotional state and adjusts the timing and content of notifications, for example, by sending notifications when the user is relaxed, which increases the user's response rate.

[0819] Specific examples

[0820] For example, suppose user A has 200 points in point program B, and the expiration date is approaching in five days. If user A says, "I'm feeling a little stressed today," the emotion engine recognizes that emotion and passes it on to the server. Based on the points expiration information and emotion information, the server generates a notification saying, "User A, if you use 200 points at store ◎◎ to refresh yourself by the end of this week, there's a double points campaign," and sends it to the device. A notification appears on user A's smartphone, and when A opens the app, a link saying "Use now" appears. By tapping the link, they can access the coupon page of the affiliated store and use their points to refresh themselves.

[0821] Prompt Sentence Examples

[0822] An example of a prompt sentence to input to the generative AI model is as follows:

[0823] Person A has 200 points in point program B, and the points are about to expire in 5 days. Person A voice-inputs, "I'm feeling a little stressed today." In this situation, explain how the emotion engine and server work together to send an appropriate notification to Person A.

[0824] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0825] Step 1:

[0826] User Data Collection and Storage

[0827] The server sends a request to the API of each point program and obtains user data (number of points, acquisition date, usage history, expiration date). The input is the response data from each point program API, and the output is user data in JSON format. This data is saved in a database. Specifically, the server uses Python's Requests library to send the API request, parses the received JSON-formatted response data, and saves it in a database (for example, MySQL).

[0828] Step 2:

[0829] Point status analysis

[0830] The server retrieves point information from the database and analyzes it using an AI algorithm. The input is the point information retrieved from the database, and the output is a list of points that are about to expire. The server runs an AI script written in Python, for example using the scikit-learn library, to analyze the point information. The AI ​​algorithm lists points that are about to expire.

[0831] Step 3:

[0832] Generate notifications

[0833] The server generates a notification message based on the analysis results of the AI ​​algorithm. The input is a list of points that are about to expire, and the output is the notification message to be sent to the user. The server uses a template engine (e.g., Jinja2) to generate the message. For example, it creates a message such as "Your points for Program A will expire in 3 days."

[0834] Step 4:

[0835] Sending notifications

[0836] The server generates and sends notification messages to users. The input is the generated notification message, and the output is the notification sent to the user. The sending method can be email, SMS, or push notification. Specifically, the server sends email using an SMTP server, SMS using the Twilio API, or push notification using Firebase Cloud Messaging (FCM).

[0837] Step 5:

[0838] Collection of campaign information and notification

[0839] The server obtains the latest campaign information through an external API, compares it with the user's point information, and generates a notification proposing the most suitable campaign. The input is the campaign information obtained from the external API and the user's point information, and the output is the generated campaign notification message. The server sends an API request, analyzes the obtained JSON data, compares it with the user's point information, and generates a message such as "There is a double points campaign this weekend at store XX."

[0840] Step 6:

[0841] Check your points

[0842] A points management app installed on the user's device periodically synchronizes with the server and displays the latest points information. The input is point data obtained from the server, and the output is the latest points information displayed on the app's UI. The user checks the balance and expiration date of each points program through the app. The device communicates with the server using HTTP requests, and displays the obtained data on the UI.

[0843] Step 7:

[0844] Receive notifications

[0845] The user's device receives notifications sent from the server and displays them in the app or as push notifications. The input is the notification data sent from the server, and the output is the notification message displayed on the user's device. The device uses Firebase Cloud Messaging (FCM) or similar to receive push notifications, and when the user taps the notification, detailed information is displayed in the app.

[0846] Step 8:

[0847] Viewing and using points

[0848] The user receives a notification from the server, launches the app, and checks the status of their points. The input is the notification content displayed on the device and the point data in the app, and the output is the user's action (using the points). The specific steps a user takes to check the notification and use their points at affiliated stores or online sites are to tap the link in the notification and access the coupon page or related site.

[0849] Step 9:

[0850] Use of the campaign

[0851] The user checks the campaign notification from the server and efficiently uses points at specific stores or online sites. The input is the campaign notification message, and the output is the user's point usage action. The user checks the notification and plans to shop at stores participating in the campaign. The specific steps to display in-app coupons and promote in-store usage include presenting the coupon at the store and using the points.

[0852] Step 10:

[0853] Emotion recognition

[0854] The emotion engine analyzes user input (text, voice, and facial expression data) and recognizes emotions. The input is text, voice, and facial expression data provided by the user through a chatbot or app, and the output is analyzed emotional information. For example, using IBM Watson's speech recognition engine, it can classify emotions such as "fatigue" from the voice input "I'm tired today."

[0855] Step 11:

[0856] Collecting and storing emotional information

[0857] The emotion recognition results are sent to the server and stored in a database. The input is the emotion information analyzed by the emotion engine, and the output is the emotion data stored in the database. This process involves sending the emotion information to the server through an HTTPS request and storing it in the database.

[0858] Step 12:

[0859] Creating emotional notifications

[0860] The AI ​​algorithm generates a notification message based on emotional information. The input is emotional information and point information, and the output is a notification message that takes emotion into consideration. The server uses a template engine to generate a message such as "Double points campaign at store XX, perfect for refreshing yourself."

[0861] Step 13:

[0862] Adjusting the timing and content of notifications

[0863] The emotion engine analyzes the user's emotional state and determines the optimal notification timing. The input is emotional information and the user's behavioral history, and the output is the timing and content of the notification. Specific steps are included to improve the user's response rate by sending notifications during times when the emotion engine is relaxed based on the analysis results.

[0864] (Application example 2)

[0865] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0866] Conventional point program management systems make it difficult for users to effectively utilize their points, as it is cumbersome to keep track of point expiration dates and the latest campaign information. Furthermore, because they do not take into account the user's emotional state, notifications and suggestions are not provided at the most effective times, which makes it difficult to increase user satisfaction. Furthermore, the lack of real-time information provided via smart devices reduces opportunities for users to efficiently use their points when shopping in physical stores.

[0867] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0868] In this invention, the server includes means for collecting point program information from users, means for saving the collected point program information in a database, means for analyzing the saved point program information and generating a notification when points are about to expire, means for sending the generated notification to the user, means for externally acquiring campaign information and comparing it with the user's point information to suggest an optimal campaign, means for recognizing the user's emotions using an emotion engine and reflecting the emotion information in a notification message, and means for displaying notifications via a smart device (including smart glasses, smartphones, and head-mounted displays) so that the user can check point information and campaign information in real time. This allows users to know point expiration dates and the latest campaign information in a timely manner and receive effective suggestions based on their emotion information, which promotes point usage in physical stores and improves user satisfaction.

[0869] A "points program" is a system in which users can earn points by performing certain activities or making purchases and then exchange those points for rewards or services.

[0870] A "database" is an information system for storing and managing point program information collected from users.

[0871] "Notification" is a message that notifies the user when the expiration date of points is approaching or when campaign information is available.

[0872] "Campaign information" is information about discounts and benefits that allow users to use points more advantageously under certain conditions.

[0873] The "emotion engine" is a system that analyzes the user's emotional state and reflects the results in notification messages.

[0874] A "smart device" is an electronic device that can display and input information using advanced technology, such as smart glasses, smartphones, and head-mounted displays.

[0875] A "point management app" is application software that is installed on a user's device and allows the user to check points and receive notifications.

[0876] An "AI algorithm" is a computational method for analyzing data and making predictions using artificial intelligence technology.

[0877] "User data" refers to various information about the user, such as point acquisition history, point usage history, and emotional information.

[0878] "Real-time" refers to a state in which information is collected, analyzed, and notified immediately without delay.

[0879] MODE FOR CARRYING OUT THE INVENTION

[0880] 1. System Program

[0881] The system that realizes this invention consists of four main components: a server, a terminal, a user, and an emotion engine. Each component cooperates to smoothly manage user points and notify users of campaigns.

[0882] 2. Server processing explanation

[0883] The server first collects point program information from users. The target point program data includes the number of points, acquisition date, usage history, expiration date, etc. This information is stored in a database and used as the basis for later analysis.

[0884] The AI ​​algorithm installed on the server analyzes the stored point program information and lists the information when points are about to expire. The AI ​​algorithm then generates a notification message based on the analysis results. For example, it creates a notification saying, "Program A's points will expire in 3 days." The server also calls an external API to obtain the latest campaign information, compares it with the user's point information, and generates a notification suggesting the most suitable campaign.

[0885] 3. Terminal processing explanation

[0886] A points management app is installed on the user's device. This app periodically synchronizes data with the server and displays the latest points information. Through the app, users can check their points balance and expiration date and receive notifications sent from the server. The received notifications are displayed within the app, providing detailed information and instructions on how to use points. In addition, points information and campaign information are displayed in real time through smart devices (smart glasses, smartphones, head-mounted displays, etc.).

[0887] 4. User behavior description

[0888] The user receives a notification from the server and launches the point management app to check the status of their points. For example, if they receive a notification that "XX points will expire in 5 days," the user can check the points in the app and use them at affiliated stores or online sites. They can also check campaign notifications from the server to use their points efficiently at specific stores or online sites. For example, if they receive a notification that "XX store is having a double points campaign this weekend," they can plan to shop at the store that weekend.

[0889] 5. Explanation of Emotion Engine Operation

[0890] The emotion engine analyzes the text and voice input by the user, as well as facial expression data captured by a high-sensitivity camera, to recognize the user's emotions. For example, if the user inputs, "I'm feeling a little stressed today," the emotion engine recognizes this emotion as "stress" and conveys it to the server. The server then generates a notification message based on the points expiration information and emotion information. For example, it might generate a notification with the content, "Double points campaign at store XX, perfect for refreshing yourself," and send it to the user. The timing and content of the notification are also adjusted based on the user's emotional state. For example, sending notifications during times when the user is relaxed can improve the response rate after receiving the notification.

[0891] 6. Explanation of specific examples

[0892] For example, suppose a user has 200 points and their expiration date is approaching in five days. If the user says, "I'm feeling a little stressed today," the emotion engine recognizes that emotion and communicates it to the server. Based on the points' expiration date and emotion information, the server generates a notification with the message, "Double points campaign at a cafe perfect for refreshing yourself," and sends it to the user's smart device. The notification is displayed on the user's smart glasses, and when the user opens the app, a link that says, "Use now." Tapping the link takes them to the coupon page of a partner cafe, where they can use their points to refresh themselves.

[0893] 7. Examples of prompts

[0894] Below is an example of a prompt sentence.

[0895] "The points for user ID 'user123' will expire in 4 days. A double points campaign is running until the end of this week at a cafe perfect for refreshing yourself. The coupon will be automatically applied when you use your smart glasses."

[0896] In this way, users can prevent points from expiring and receive more emotionally relevant suggestions, resulting in a better user experience.

[0897] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0898] Step 1:

[0899] User Data Collection and Storage

[0900] The server collects user data through the API of the point program. As input, it acquires point program information such as the number of points, acquisition date, usage history, and expiration date, and stores it in a database. Specifically, it links the point program information to the user ID and manages it centrally.

[0901] Step 2:

[0902] Point status analysis

[0903] The server uses the point program information stored in the database to list points that are about to expire. As input, it reads the stored point data and uses an AI algorithm to extract points that are about to expire. As output, it generates a list of points that are about to expire. Specifically, it calculates the number of days until the expiration date and lists points that will expire within a certain period of time.

[0904] Step 3:

[0905] Generate notifications

[0906] The server generates a notification message based on the results of point status analysis. The input is the list of points that are about to expire, which is the output of step 2. As an output, a specific notification message is generated. As a specific example, a message is created stating, "The points for user ID 'user123' will expire in 3 days."

[0907] Step 4:

[0908] Sending notifications

[0909] The server sends the generated notification message to the user. The input is the notification message generated in step 3, and the output is to send the notification to the user via email, SMS, or push notification. Specifically, the message is sent based on the notification method set by the user.

[0910] Step 5:

[0911] Collection and proposal of campaign information

[0912] The server retrieves the latest campaign information from an external API and compares it with the user's point information. The input is the campaign information retrieved from the external API, and the output is a message proposing the most suitable campaign for the user. Specifically, the server compares the user's point information and campaign information against the conditions to propose the most suitable campaign.

[0913] Step 6:

[0914] Recognizing and reflecting emotions

[0915] The emotion engine analyzes the user's text input, voice data, and facial expression data to recognize the user's emotions. The input is the emotional data provided by the user, and the output is emotional information sent to the server. Specifically, the emotion engine recognizes emotions such as "stress" and "relaxation" and passes that information to the server.

[0916] Step 7:

[0917] Generate emotional notifications

[0918] The server generates a notification that reflects emotional information based on the output from the emotion engine. The input is the emotional information from step 6, and the output is a notification message that takes emotion into consideration. As a specific example, it generates a notification that reads, "There is a double points campaign at a cafe that is perfect for refreshing yourself."

[0919] Step 8:

[0920] Displaying notifications on smart devices

[0921] The terminal receives the notification sent from the server and displays it to the user through the smart device. The input is the notification message generated in step 4 and step 7, and the output is the display on the smart glasses, smartphone, or head-mounted display. Specifically, the notification is displayed on the display of the smart device in real time.

[0922] Through these steps, users can understand point expiration dates and campaign information in real time, and receive emotionally tailored suggestions, allowing them to enjoy a better user experience.

[0923] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0924] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0925] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0926] [Third embodiment]

[0927] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0928] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0929] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0930] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0931] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0932] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0933] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0934] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0935] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0936] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0937] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0938] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0939] The system for implementing this invention includes three main components: a server, a terminal, and a user. The specific operation of each component will be described below.

[0940] Server Processing

[0941] User Data Collection and Storage

[0942] The server collects user data through the API of each point program, including the number of points a user has, the date they have earned them, their usage history, and their point expiration date. This data is stored in a database, and point program information is centrally managed using the user ID as a key.

[0943] Point status analysis

[0944] An AI algorithm installed on the server periodically analyzes the user's point usage history and expiration date. It checks whether the points are about to expire and generates a notification if so. It also prioritizes the use of points and suggests the best time to use them.

[0945] Sending notifications

[0946] The server notifies users when their points are about to expire and about the latest campaign information. Notifications are sent via email, SMS, app push notifications, etc. to encourage users to use their points.

[0947] Collection of campaign information and notification

[0948] Campaign information is obtained through an external API and compared with the user's point information. Based on the comparison results, the system notifies the user that points can be used more efficiently by taking advantage of a specific campaign. For example, if a specific store is running a double points campaign, the system notifies the user of this information.

[0949] Terminal handling

[0950] Check your points

[0951] A points management app is installed on the user's device. The app periodically synchronizes data with the server and displays the latest points status. Users can open the app to check the balance and expiration date of each points program.

[0952] Receive notifications

[0953] The device receives notifications sent from the server and displays them to the user. The notification content includes information about upcoming points expiration dates and campaign information. When the user taps the notification, detailed information is displayed within the app and an action such as using points is prompted.

[0954] User Behavior

[0955] Viewing and using points

[0956] The user receives a notification from the server and launches the app to check the status of their points. For example, if they receive a notification that "XX points will expire in 5 days," the user can check the points within the app and use them at affiliated stores or online sites.

[0957] Use of the campaign

[0958] Users can check campaign notifications from the server and use their points efficiently at specific stores or online sites. For example, if a user receives a notification that "There is a double points campaign this weekend at store X," the user can plan to shop at the store that weekend.

[0959] Specific examples

[0960] For example, suppose user C has 300 points in point program A. When the expiration date is approaching in three days, the server detects this information and sends C a notification saying, "Your 300 points in program A will expire in three days." A notification will appear on C's smartphone, and when C opens the app, a link saying "Use now" will appear. By tapping the link, C will be taken to an affiliated online shop where she can use her points to purchase products.

[0961] This system allows users to prevent points from expiring and use them efficiently. It also allows users to get the most out of their points by staying up to date with the latest campaign information.

[0962] The processing flow will be explained below.

[0963] Specific processing of the program

[0964] Server Processing

[0965] Step 1: Collect data

[0966] The server obtains user point information through the API of each point program, including the number of points, acquisition date, usage history, and expiration date.

[0967] Step 2: Save your data

[0968] The server stores the acquired data in a database. There is a separate table for each point program, and data is associated using the user ID as a key.

[0969] Step 3: Analyze the data

[0970] An AI algorithm installed on the server analyzes the points information in the database, in particular checking whether the points are about to expire and listing those points that are about to expire.

[0971] Step 4: Generate notifications

[0972] Based on the results of the AI ​​algorithm's analysis, the server generates a notification message, such as "Your points for Program A will expire in 3 days."

[0973] Step 5: Sending notifications

[0974] The server generates the notification and sends it to the user, either via email, SMS, or push notification, allowing the user to receive the notification.

[0975] Step 6: Gather campaign information

[0976] The server calls an external API to obtain the latest campaign information, such as information about a double points campaign being held at a specific store.

[0977] Step 7: Campaign information verification and notification

[0978] The server compares the acquired campaign information with the user's point information, generates a notification proposing the relevant campaign, and sends it to the user.

[0979] Terminal handling

[0980] Step 1: Synchronize your data

[0981] The point management app installed on the device periodically synchronizes with the server to obtain the latest point information.

[0982] Step 2: Viewing points

[0983] The acquired point information is displayed within the app, allowing users to check the balance and expiration date of each point program.

[0984] Step 3: Receive notifications

[0985] The device receives notifications sent from the server and displays them to the user in-app or as push notifications.

[0986] Step 4: View details

[0987] When users tap on the notification, more information will be displayed within the app, including where points can be used and details about the campaign.

[0988] User Behavior

[0989] Step 1: Check notifications

[0990] The user checks the notification received on the device, which notifies them of the approaching expiration date of specific points and campaign information.

[0991] Step 2: Use your points

[0992] Users can redeem their points by clicking a link within the app, for example by being redirected to a partner online shop where they can use their points to purchase products.

[0993] Step 3: Use the campaign

[0994] Users can use points efficiently at physical stores and online sites based on the campaign information received on their devices, and plan their shopping accordingly.

[0995] Through these steps, a system is realized in which the server, terminal, and user work together to efficiently manage and use points.

[0996] Example 1

[0997] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0998] With conventional point management systems, users were unable to properly grasp the expiration dates of points or available campaign information, making it difficult to prevent points from expiring or use them at the optimal time. In particular, when managing multiple point programs, it was time-consuming to check the point balance and expiration date of each program individually, which was a significant burden for users. In addition, the priority order for point usage was unclear, which also hindered users from using points efficiently.

[0999] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1000] In this invention, the server includes means for collecting point program information from users, means for saving the collected point program information in a database, means for analyzing the saved point program information and generating a notification when points are about to expire, means for sending the generated notification to the user, means for externally acquiring campaign information and comparing it with the user's point information to propose optimal campaigns, means having an algorithm for periodically analyzing the collected point data and campaign information, and means for notifying the collected campaign information based on the user's point usage priority. This allows users to efficiently understand and use point expiration dates, optimal usage times, and campaign information through the app.

[1001] "User information" refers to data related to the points program, such as user identification information, number of points, acquisition date, usage history, and expiration date.

[1002] A "database" is an electronic storage system that centrally manages collected point program information and allows for easy storage, searching, and updating.

[1003] "Notifications" are messages that inform users when their points are about to expire or about the best campaign information. Notification formats include email, SMS, and app push notifications.

[1004] An "external API" is an interface that a server uses to obtain information from external services or databases. It is used to obtain campaign information, etc.

[1005] "Campaign information" refers to information about benefits for using points efficiently, such as a campaign to double points at a specific store.

[1006] "Algorithm" refers to a series of computational procedures that run on the server and analyze the point usage history and expiration date. Specifically, it includes pattern recognition and machine learning models.

[1007] A "point management app" is application software that users install on their smartphones or tablets to check their point balance, expiration date, and campaign information.

[1008] A "user device" is an electronic device used by a user, such as a smartphone, tablet, or computer, on which the point management app is installed and used.

[1009] "Verification" is a process in which the server compares the user's point data with the acquired campaign information to identify available point campaigns.

[1010] The "usage priority" is a standard for setting the priority when using points. For example, points that are close to their expiration date are set to be used first.

[1011] The system for implementing this invention includes three main components: a server, a terminal, and a user. The specific operation of each component and how they work together will be described in detail below.

[1012] Server Processing

[1013] The server first has a means of collecting point program information from users. This collection is done through the API of each point program, and data such as the number of points a user has, the date they acquired them, their usage history, and their expiration date is obtained. This information is then saved in a database. The saved point program information is managed centrally and registered using the user ID as a key.

[1014] The server then periodically analyzes the stored loyalty program information. Using AI algorithms, the server generates notifications when points are about to expire. These notifications include information about the points that are about to expire and recommended times to use them. These notifications are then sent to users via email, SMS, app push notifications, and more.

[1015] In addition, the server obtains campaign information through an external API. This campaign information is matched with the user's point data and used to suggest the most suitable campaign. If the campaign is an effective way to use points, the server notifies the user of this information. For example, if a specific store is running a double points campaign, the server notifies the user of this information.

[1016] Terminal handling

[1017] A points management app is installed on the device. This app periodically synchronizes data with the server and displays the latest points status. Users can open the app to check the balance and expiration date of each points program.

[1018] The device also receives notifications sent from the server. These notifications include information about upcoming point expiration dates and campaign information, and are displayed to the user. When the user taps the notification, more information is displayed in the app and an action is prompted, such as using points.

[1019] User Behavior

[1020] The user receives a notification from the server and launches the app to check the status of their points. For example, if they receive a notification saying, "X points will expire in 5 days," the user can check the status of their points within the app and use them at affiliated stores or online sites. Also, if they receive a notification about campaign information, for example, "There's a double points campaign at X store this weekend," they can check the notification and plan their shopping at the store that weekend.

[1021] Specific examples

[1022] For example, suppose user A has 300 points in point program A. When the expiration date is approaching in three days, the server detects this information and sends user A a notification saying, "Your 300 points in program A will expire in three days." A notification will appear on user A's smartphone, and when user A opens the app, a link saying "Use now" will appear. By tapping the link, user A will be taken to an affiliated online shop where they can use their points to purchase products.

[1023] Example prompts for generative AI models

[1024] "Please explain the specific behavior of a feature in a user's point management system that notifies users when their points are about to expire. As a specific scenario, please explain the case where a user has 300 points in point program A and the points are about to expire in three days."

[1025] This system allows users to prevent points from expiring, allowing them to use their points efficiently. It also allows users to get the most out of their points by staying up to date with the latest campaign information.

[1026] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1027] Step 1:

[1028] User Data Collection

[1029] The server calls the API of each point program to collect user data, including the number of points a user has, the date they acquired them, their usage history, and their expiration date.

[1030] Input: API endpoint of each point program

[1031] What happens: The server sends an HTTP request to the API endpoint and parses the returned JSON data.

[1032] Data processing: Parse the acquired JSON data and extract the user ID, number of points, acquisition date, usage history, and expiration date.

[1033] Output: Parsed user data

[1034] Step 2:

[1035] Saving to a database

[1036] The server stores the collected user data in a database. Point program information is centrally managed using the user ID as a key.

[1037] Input: Parsed user data

[1038] What happens: The server opens a database connection, executes an SQL query, and saves the user data.

[1039] Data processing: Convert user data into a database table format.

[1040] Output: User data stored in the database

[1041] Step 3:

[1042] Point status analysis

[1043] The AI ​​algorithm installed on the server analyzes point usage history and expiration dates, and generates a notification when a user's points are about to expire.

[1044] Input: User data stored in the database

[1045] How it works: The server runs an AI algorithm, taking user data as input and outputting a data set showing when points are about to expire.

[1046] Data calculation: Using a machine learning model, points usage history and expiration dates are analyzed to extract points that are close to expiring.

[1047] Output: List of points that are about to expire

[1048] Step 4:

[1049] Generate and send notifications

[1050] The server generates notifications based on the analysis results and sends them to the user in the form of email, SMS, app push notifications, etc.

[1051] Input: List of points that are about to expire

[1052] Specific operation: The server uses the notification template to generate notification content for each user, and then sends the notification using the SMTP protocol or SMS API.

[1053] Data processing: Embed user point information in the notification template.

[1054] Output: Notification sent to the user

[1055] Step 5:

[1056] Collection of campaign information and notification

[1057] The server obtains the latest campaign information through an external API, compares it with the user's point data, and generates notifications to suggest the most suitable campaigns.

[1058] Input: Campaign information from external API

[1059] What it does: The server sends an HTTP request to an external API to retrieve campaign information, which it then stores in a database and matches with the user's point data.

[1060] Data calculation: Compare the acquired campaign information with user point data to select the most suitable campaign.

[1061] Output: Campaign notification sent to users

[1062] Step 6:

[1063] Check your points

[1064] A points management app is installed on the device. This app periodically synchronizes data with the server and displays the latest points status. Users can open the app to check their points balance and expiration date.

[1065] Input: Latest point data synchronized from the server

[1066] Specific operation: The app calls the API in the background to get the latest point data from the server, which is then saved in local storage and displayed in the user interface.

[1067] Data processing: Convert the data obtained from the server into the display format of the app.

[1068] Output: Points balance and expiry date displayed in the app

[1069] Step 7:

[1070] Receive notifications

[1071] The device receives notifications sent from the server and displays them to the user, who can tap on them to view more information within the app.

[1072] Input: Notification sent from the server

[1073] Specific behavior: The device's notification service receives the push notification from the server and displays it in the notification center. When the user taps the notification, the relevant app screen is opened.

[1074] Data processing: Converts the notification content into a format suitable for the user interface.

[1075] Output: Notification displayed in the notification center and detailed information in the app

[1076] Step 8:

[1077] Viewing and using points

[1078] When users receive a notification, they can launch the app to check their points status and use them at affiliated stores or online sites.

[1079] Input: Point information and notification content displayed in the app

[1080] Specific operation: The user taps a link in the app to access a partner store or online shop, where they can use their points to purchase a product.

[1081] Data processing: Transaction data for point usage is generated and sent to the server.

[1082] Output: Transaction record of items purchased using points

[1083] Step 9:

[1084] Use of the campaign

[1085] The user checks the campaign notification from the server and uses the points to effectively take advantage of the campaign.

[1086] Input: In-app campaign notifications and details

[1087] Specific actions: The user taps on the campaign notification, checks the details, and redeems the campaign in a physical store or online shop.

[1088] Data processing: Campaign transaction data is generated and sent to the server.

[1089] Output: Transaction record of points redemption using campaign

[1090] (Application example 1)

[1091] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1092] Conventional point program management systems notify users when their points are about to expire, but this can sometimes prevent users from using their points at the appropriate time. Furthermore, they do not provide sufficient functionality for efficiently utilizing campaign information and optimizing point usage, resulting in point expiration and inefficient point usage. Therefore, there is a need for a way for users to use points efficiently and prevent them from expiring.

[1093] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1094] In this invention, the server includes means for collecting point program information from users, means for saving the collected point program information in a database, means for analyzing the saved point program information and generating a notification when the point expiration date is approaching, means for sending the generated notification to the user, means for acquiring campaign information from an external source and comparing it with the user's point information to propose the most suitable campaign, and means for sending point expiration date notifications and campaign information notifications to the user via a mail server. This allows users to check the point expiration date as needed and use their points efficiently. Furthermore, by utilizing the campaign information, the utility value of points can be maximized and users can manage their points effectively.

[1095] "User" refers to a person who uses the points program.

[1096] A "points program" is a system in which users are given points each time they use a specific service or product, and can use these points to receive discounts or benefits.

[1097] "Collecting information" refers to the process of obtaining data related to the loyalty program.

[1098] A "database" is an information system for systematically storing and efficiently managing collected data.

[1099] "Expiration date approaching" indicates that the points are about to expire.

[1100] "Generating a notification" is the act of creating a message to inform a user of information.

[1101] "Campaign Information" refers to information about promotions such as special offers and discounts that are held during a specific period of time.

[1102] "Matching" is the act of comparing specific data with other data to identify similarities and differences.

[1103] "Sending" refers to the act of delivering the generated notification to the user via electronic means.

[1104] A "mail server" is a server that manages the sending and receiving of email.

[1105] An "AI algorithm" is a computational process that analyzes user behavior patterns and data to derive efficient methods.

[1106] A "generative AI model" is a model that uses machine learning to generate new information and patterns from data.

[1107] The system for implementing this invention includes three main components: a server, a terminal, and a user. The main functions of this system are to collect, store, analyze, and notify users of point program information, and to suggest campaign information.

[1108] Server Processing

[1109] The server collects user data through the point program's API. Specifically, it obtains data such as the number of points a user has, the date they acquired them, their usage history, and their point expiration date, and stores this data in a database. The point program information is centrally managed using the user ID in the database as a key.

[1110] Next, an AI algorithm installed on the server periodically analyzes the user's point usage history and expiration date. This checks whether the points are about to expire and generates a notification if so. It also prioritizes the use of points and suggests the best time to use them.

[1111] Furthermore, campaign information is obtained through an external API and compared with the user's point information. Based on the comparison results, the system notifies the user that points can be used more efficiently by taking advantage of a specific campaign. For example, if a specific store is running a double points campaign, the system notifies the user of this information. Notifications are sent to the user via a mail server.

[1112] Terminal handling

[1113] A points management app is installed on the user's device. This app periodically synchronizes data with the server and displays the latest points status. Users can open the app to check the balance and expiration date of each points program. The app also includes a function to receive notifications sent from the server and display them to the user. By tapping the notification, users can check detailed information within the app and be prompted to take action, such as using points.

[1114] User Behavior

[1115] The user receives a notification from the server and launches the app to check the status of their points. For example, if they receive a notification that "XX points will expire in 5 days," they can check the points within the app and use them at affiliated stores or online sites. Furthermore, if they receive a notification that "XX store is having a double points campaign this weekend," they can plan to shop at the store that weekend.

[1116] This system allows users to prevent points from expiring and use them efficiently. Also, by staying up-to-date on the latest campaign information, users can make the most of their points. This increases user satisfaction and makes the point program more useful.

[1117] Specific examples

[1118] For example, suppose user C has 300 points in point program A. When the expiration date is approaching in three days, the server detects this information and sends C a notification saying, "Your 300 points in program A will expire in three days." A notification will appear on C's smartphone, and when C opens the app, a link saying "Use now" will appear. By tapping the link, C will be taken to an affiliated online shop where he can use his points to purchase products.

[1119] Prompt Sentence Examples

[1120] We want to build an app that centrally manages users' point information and campaign information, and suggests optimal point usage. The goal is to efficiently receive point expiration dates and campaign information from users, and to help them with the process of actually using their points. Specifically, the app includes the following features:

[1121] 1. Point expiration notification

[1122] 2. Notification of campaign information

[1123] 3. Suggestions for using points

[1124] How do you collect and analyze user data and send appropriate notifications? What technologies do you use to do so?

[1125] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1126] Step 1: Collect user data

[1127] The server obtains user data from the API of each point program. The input is an API request, and the output is data such as the number of points, acquisition date, usage history, and point expiration date. Specifically, it sends a request to the API endpoint, parses the results, and collects them as structured data. By doing this periodically, the latest information is maintained.

[1128] Step 2: Save your data

[1129] The server saves the point program information collected in step 1 in a database. The input here is the collected point information, and the output is structured data saved in the database. Specifically, it executes an INSERT or UPDATE query on the database and centrally manages the data using the user ID as a key.

[1130] Step 3: Analyze points expiration dates

[1131] The server periodically analyzes the stored point program information to check whether any points are about to expire. The input to this step is the point information in the database, and the output is a list of points that are about to expire. The specific operation is to perform an operation that compares the expiration date of each point with the current date, and extracts points that are about to expire within three days.

[1132] Step 4: Generate and send notifications

[1133] Based on the results of step 3, the server generates a notification when points are about to expire and sends the notification to the user. The input here is a list of points that are about to expire, and the output is the generated notification message and the sending result. The specific operation is to embed the point information in a message template, obtain the user's email address, and send the notification through the email server.

[1134] Step 5: Obtain and verify campaign information

[1135] The server retrieves campaign information through an external API and compares it with the user's point information. The input of this step is the campaign data from the external API and the user's point information, and the output is a list of points recommended for campaign use. The specific operation is to retrieve campaign information and match it with the user's point data to identify points that can be used effectively in a specific campaign.

[1136] Step 6: Generate and send campaign notifications

[1137] The server notifies the user of specific campaign information based on the results of step 5. The input here is a list of points where campaign use is recommended, and the output is the generated campaign notification and sending result. The specific operation is to generate a notification message containing the campaign information and send it to the user via the mail server.

[1138] Step 7: Check your points status

[1139] The device receives the notification sent from the server and displays it so that the user can check the status of point usage. The input here is the notification data from the server, and the output is the point information display screen on the device. The specific operation is that the device app receives the notification from the server and displays the information to the user in an appropriate format.

[1140] Step 8: Promote points usage

[1141] Users can use their points efficiently based on the notifications displayed on their devices. The input here is the displayed notification information, and the output is the actual act of using points. Specifically, users tap the notification to check detailed information, and then access affiliated online shops or stores via the link to use their points.

[1142] Step 9: Collect feedback data

[1143] The server collects data on how users use points and campaigns. The input here is user behavior data, and the output is updated point usage history data. The specific operation is to track user behavior and update the database to analyze campaign effectiveness and point usage trends.

[1144] Prompt Sentence Examples

[1145] We want to build an app that centrally manages users' point information and campaign information, and suggests optimal point usage. The goal is to efficiently receive point expiration dates and campaign information from users, and to help them with the process of actually using their points. Specifically, the app includes the following features:

[1146] 1. Point expiration notification

[1147] 2. Notification of campaign information

[1148] 3. Suggestions for using points

[1149] How do you collect and analyze user data and send appropriate notifications? What technologies do you use to do so?

[1150] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1151] The system for implementing this invention includes four main components: a server, a terminal, a user, and an emotion engine. The specific operation of each component will be described below.

[1152] Server Processing

[1153] User Data Collection and Storage

[1154] The server collects user data through the API of each point program. The data includes the number of points, acquisition date, usage history, and expiration date. This data is stored in a database, and point program information is centrally managed using the user ID as a key.

[1155] Point status analysis

[1156] An AI algorithm installed on the server analyzes the points information in the database, in particular checking whether the points are about to expire and listing those points that are about to expire.

[1157] Generate notifications

[1158] Based on the results of the AI ​​algorithm's analysis, the server generates a notification message, such as "Your points for Program A will expire in 3 days."

[1159] Sending notifications

[1160] The server generates the notification and sends it to the user, either via email, SMS, or push notification, allowing the user to receive the notification.

[1161] Collection of campaign information and notification

[1162] The server calls an external API to obtain the latest campaign information. For example, it obtains information about a double points campaign being held at a specific store. It compares the obtained campaign information with the user's point information and generates a notification suggesting a relevant campaign. It then sends this to the user.

[1163] Terminal handling

[1164] Check your points

[1165] A points management app is installed on the user's device. The app periodically synchronizes data with the server and displays the latest points information. Users can check the balance and expiration date of each points program.

[1166] Receive notifications

[1167] The device receives the notification sent from the server and displays it to the user in the app or as a push notification. When the user taps the notification, more information is displayed in the app and an action such as using points is prompted.

[1168] User Behavior

[1169] Viewing and using points

[1170] The user receives a notification from the server and launches the app to check the status of their points. For example, if they receive a notification that "XX points will expire in 5 days," the user can check the points within the app and use them at affiliated stores or online sites.

[1171] Use of the campaign

[1172] Users can check campaign notifications from the server and use their points efficiently at specific stores or online sites. For example, if a user receives a notification that "There is a double points campaign this weekend at store X," the user can plan to shop at the store that weekend.

[1173] Emotion Engine Operation

[1174] Emotion recognition

[1175] The emotion engine analyzes the text and voice input by the user, as well as facial expression data captured by a high-sensitivity camera, to recognize the user's emotions. For example, if a user inputs "I'm tired today" into the chatbot, it will classify that emotion as "fatigue."

[1176] Collecting and storing emotional information

[1177] The emotion recognition results are sent to the server and stored in a database along with point information. The emotion information is linked using the user ID as a key and used for future analysis.

[1178] Creating emotional notifications

[1179] The AI ​​algorithm generates notification messages based on emotional information. For example, if it detects that the user is feeling stressed, it will generate a notification such as "Double points campaign at store XX, perfect for refreshing yourself."

[1180] Adjusting the timing and content of notifications

[1181] The emotion engine analyzes the user's emotional state and adjusts the timing and content of notifications, for example, by sending notifications when the user is relaxed, which increases the user's response rate.

[1182] Specific examples

[1183] For example, suppose user D has 200 points in point program B, and the expiration date is approaching in five days. If D says, "I'm feeling a little stressed today," the emotion engine recognizes that emotion and passes it on to the server. Based on the points expiration information and emotion information, the server generates a notification saying, "D, if you use 200 points at ◎◎ Cafe to refresh yourself by the end of this week, you'll receive double points," and sends it to the device. A notification will appear on D's smartphone, and when he opens the app, a link saying "Use now" will appear. By tapping the link, he will be taken to the coupon page of the affiliated cafe, where he can use his points to refresh himself.

[1184] This allows users to prevent points from expiring and receive suggestions that match their emotions, resulting in a better user experience.

[1185] The processing flow will be explained below.

[1186] Server Processing

[1187] Step 1: Collect user data

[1188] The server collects user point information through the API of each point program, including the number of points, acquisition date, usage history, and expiration date.

[1189] Step 2: Save your data

[1190] The server saves the collected data in a database. The data for each point program is stored in a table and linked using the user ID as a key.

[1191] Step 3: Analyze your points situation

[1192] An AI algorithm on the server analyzes the points information in the database, specifically checking whether the points are nearing their expiration date and, if so, adding them to an alert list.

[1193] Step 4: Collecting emotional information

[1194] The server receives the user's emotional data from the emotion engine and stores it in a database. The emotional data is classified based on text analysis, voice analysis, image analysis, etc.

[1195] Step 5: Generate notifications

[1196] The AI ​​algorithm creates a notification message based on point data and emotion data, such as "Your points for Program A will expire in three days. Please visit XX Cafe to relieve stress."

[1197] Step 6: Sending notifications

[1198] The server generates the notification and sends it to the user, either via email, SMS, or app push notification, depending on how the user receives it.

[1199] Step 7: Collect and collate campaign information

[1200] The server calls an external API to get the latest campaign information, matches it with the user's point data, and adds applicable campaigns to a list.

[1201] Terminal handling

[1202] Step 1: Synchronize your data

[1203] The point management app installed on the device periodically synchronizes with the server to obtain the latest point information.

[1204] Step 2: Viewing points

[1205] The acquired point information is displayed within the app, allowing users to check the balance and expiration date of each point program.

[1206] Step 3: Receive notifications

[1207] The device receives notifications sent from the server and displays them to the user in the app or as a push notification.

[1208] Step 4: View details

[1209] When users tap on the notification, more information will be displayed within the app, including which points to use and details about the campaign.

[1210] User Behavior

[1211] Step 1: Check notifications

[1212] The user checks the notifications received on the device, which include information about upcoming point expiration dates and sentiment-based campaigns.

[1213] Step 2: Use your points

[1214] Users can tap on a link in the app to redeem their points, for example, by being redirected to a page of a partner online shop or physical store where they can make a purchase using their points.

[1215] Step 3: Use the campaign

[1216] Users can use their points efficiently at physical stores and online sites based on the campaign information they receive. For example, if they receive a notification that "There is a double points campaign this weekend at XX store," they can plan to shop at that store.

[1217] Emotion engine processing

[1218] Step 1: Recognize emotions

[1219] The emotion engine analyzes text, voice, and facial expression data entered by the user to recognize emotions. For example, it recognizes the input "I'm tired today" as "fatigue."

[1220] Step 2: Sending emotional information

[1221] The emotion engine sends the recognized emotion information to the server, where the emotion data is stored in a database using the user ID as a key.

[1222] Step 3: Reflection in notifications

[1223] The AI ​​algorithm tailors notifications based on emotional information, for example, if a user is feeling stressed, it will generate notifications suggesting relaxing offers or campaigns.

[1224] Specific examples

[1225] For example, suppose user E has 150 points in point program C, which are set to expire in seven days, and he or she voice-inputs, "I'm feeling stressed today." The emotion engine recognizes the emotion as "stress" and sends it to the server. Based on the point data and emotion data, the server generates a notification saying, "Your 150 points in program C will expire in seven days. We're running a campaign where you can refresh yourself with a free drink at ◎◎ Cafe," and sends it to E's device. E checks the notification, views the details of the campaign in the app, and takes action to use his or her points efficiently at the cafe during the campaign period, thereby relieving stress and not wasting points.

[1226] Example 2

[1227] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1228] With conventional point management systems, users often missed the expiration date of their points, which resulted in point expiry. Furthermore, the content and timing of notifications were not optimized to reflect the user's situation or emotions, which tended to result in low user response rates. Furthermore, campaign information that allowed users to use their points efficiently was often not provided, making improving the user experience a challenge.

[1229] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for collecting point program information from users, means for saving the collected point program information in a database, means for analyzing the saved point program information using an AI algorithm and generating a notification when the points are about to expire, means for sending the generated notification to the user, means for acquiring campaign information from an external source and comparing it with the user's point information to suggest an optimal campaign, and means for recognizing the user's emotions and adjusting the notification content based on the emotion information. This makes it possible to prevent the user's points from expiring and to suggest campaign information at the optimal timing according to the user's emotions.

[1230] A "user" is an individual or corporation that uses the points program, checks point balances, expiration dates, campaign information, etc., and takes appropriate action.

[1231] The "server" is a central control device that stores point program information collected from users, analyzes it using an AI algorithm, and sends notifications and campaign suggestions based on the results.

[1232] A "points program" is a system in which users accumulate points awarded for specific services or product purchases and can use them for various benefits and discounts.

[1233] A "database" is a data storage system that stores and centrally manages point program information, emotional information, and other data collected by the server.

[1234] "AI algorithms" are machine learning and statistical analysis techniques used to analyze collected data and determine expiration dates and the user's emotional state.

[1235] A "notification" is a message that the server generates based on the analysis results and sends to the user, and includes information such as the approaching expiration date of points and campaign information.

[1236] "Campaign information" refers to promotional information such as double points campaigns and discounts offered at specific stores or online sites.

[1237] An "emotion engine" is a software or hardware system that analyzes a user's text input, voice input, and facial expression data to recognize their emotional state at that time.

[1238] A "point management app" is application software that is installed on a user's device and allows the user to check point balances, expiration dates, and notifications.

[1239] An "external API" is a program interface for obtaining campaign information and point information from external services and databases.

[1240] The system for implementing this invention includes four main components: a server, a terminal, a user, and an emotion engine. The specific operation of each component will be described below.

[1241] Server Processing

[1242] User Data Collection and Storage

[1243] The server collects user data through the API of each point program. The data includes the number of points, acquisition date, usage history, and expiration date. This data is stored in a database, and point program information is centrally managed using the user ID as a key.

[1244] Point status analysis

[1245] The AI ​​algorithms installed on the server analyze the stored data, specifically checking whether points are about to expire, using libraries like Python's scikit-learn.

[1246] Generate notifications

[1247] Based on the analysis results of the AI ​​algorithm, the server generates a notification message, such as "Your points for Program A will expire in 3 days." A template engine such as Jinja2 is used to generate the message.

[1248] Sending notifications

[1249] The server generates notifications and sends them to users via email, SMS, push notifications, etc. These notifications are sent using an SMTP server, the Twilio API, or Firebase Cloud Messaging (FCM).

[1250] Collection of campaign information and notification

[1251] The server calls an external API to obtain the latest campaign information. It then compares the obtained campaign information with the user's point information and generates a notification suggesting a relevant campaign. For example, a notification such as "There is a double points campaign at store XX this weekend."

[1252] Terminal handling

[1253] Check your points

[1254] A points management app is installed on the user's device. The app periodically synchronizes data with the server and displays the latest points information. Users can check the balance and expiration date of each points program.

[1255] Receive notifications

[1256] The device receives the notification sent from the server and displays it to the user in the app or as a push notification. When the user taps the notification, more information is displayed in the app and an action such as using points is prompted.

[1257] User Behavior

[1258] Viewing and using points

[1259] The user receives a notification from the server and launches the app to check the status of their points. For example, if they receive a notification that "XX points will expire in 5 days," the user can check the points within the app and use them at affiliated stores or online sites.

[1260] Use of the campaign

[1261] Users can check campaign notifications from the server and use their points efficiently at specific stores or online sites. For example, if a user receives a notification that "There is a double points campaign this weekend at store X," the user can plan to shop at the store that weekend.

[1262] Emotion Engine Operation

[1263] Emotion recognition

[1264] The emotion engine analyzes the text and voice input by the user, as well as facial expression data captured by a high-sensitivity camera, to recognize the user's emotions. For example, if a user inputs "I'm tired today" into the chatbot, it will classify that emotion as "fatigue." This analysis is performed using IBM Watson's speech recognition engine, among other technologies.

[1265] Collecting and storing emotional information

[1266] The emotion recognition results are sent to the server and stored in a database along with point information. The emotion information is linked using the user ID as a key and used for future analysis.

[1267] Creating emotional notifications

[1268] The AI ​​algorithm generates notification messages based on emotional information. For example, if it detects that the user is feeling stressed, it will generate a notification such as "Double points campaign at store XX, perfect for refreshing yourself."

[1269] Adjusting the timing and content of notifications

[1270] The emotion engine analyzes the user's emotional state and adjusts the timing and content of notifications, for example, by sending notifications when the user is relaxed, which increases the user's response rate.

[1271] Specific examples

[1272] For example, suppose user A has 200 points in point program B, and the expiration date is approaching in five days. If user A says, "I'm feeling a little stressed today," the emotion engine recognizes that emotion and passes it on to the server. Based on the points expiration information and emotion information, the server generates a notification saying, "User A, if you use 200 points at store ◎◎ to refresh yourself by the end of this week, there's a double points campaign," and sends it to the device. A notification appears on user A's smartphone, and when A opens the app, a link saying "Use now" appears. By tapping the link, they can access the coupon page of the affiliated store and use their points to refresh themselves.

[1273] Prompt Sentence Examples

[1274] An example of a prompt sentence to input to the generative AI model is as follows:

[1275] Person A has 200 points in point program B, and the points are about to expire in 5 days. Person A voice-inputs, "I'm feeling a little stressed today." In this situation, explain how the emotion engine and server work together to send an appropriate notification to Person A.

[1276] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1277] Step 1:

[1278] User Data Collection and Storage

[1279] The server sends a request to the API of each point program and obtains user data (number of points, acquisition date, usage history, expiration date). The input is the response data from each point program API, and the output is user data in JSON format. This data is saved in a database. Specifically, the server uses Python's Requests library to send the API request, parses the received JSON-formatted response data, and saves it in a database (for example, MySQL).

[1280] Step 2:

[1281] Point status analysis

[1282] The server retrieves point information from the database and analyzes it using an AI algorithm. The input is the point information retrieved from the database, and the output is a list of points that are about to expire. The server runs an AI script written in Python, for example using the scikit-learn library, to analyze the point information. The AI ​​algorithm lists points that are about to expire.

[1283] Step 3:

[1284] Generate notifications

[1285] The server generates a notification message based on the analysis results of the AI ​​algorithm. The input is a list of points that are about to expire, and the output is the notification message to be sent to the user. The server uses a template engine (e.g., Jinja2) to generate the message. For example, it creates a message such as "Your points for Program A will expire in 3 days."

[1286] Step 4:

[1287] Sending notifications

[1288] The server generates and sends notification messages to users. The input is the generated notification message, and the output is the notification sent to the user. The sending method can be email, SMS, or push notification. Specifically, the server sends email using an SMTP server, SMS using the Twilio API, or push notification using Firebase Cloud Messaging (FCM).

[1289] Step 5:

[1290] Collection of campaign information and notification

[1291] The server obtains the latest campaign information through an external API, compares it with the user's point information, and generates a notification proposing the most suitable campaign. The input is the campaign information obtained from the external API and the user's point information, and the output is the generated campaign notification message. The server sends an API request, analyzes the obtained JSON data, compares it with the user's point information, and generates a message such as "There is a double points campaign this weekend at store XX."

[1292] Step 6:

[1293] Check your points

[1294] A points management app installed on the user's device periodically synchronizes with the server and displays the latest points information. The input is point data obtained from the server, and the output is the latest points information displayed on the app's UI. The user checks the balance and expiration date of each points program through the app. The device communicates with the server using HTTP requests, and displays the obtained data on the UI.

[1295] Step 7:

[1296] Receive notifications

[1297] The user's device receives notifications sent from the server and displays them in the app or as push notifications. The input is the notification data sent from the server, and the output is the notification message displayed on the user's device. The device uses Firebase Cloud Messaging (FCM) or similar to receive push notifications, and when the user taps the notification, detailed information is displayed in the app.

[1298] Step 8:

[1299] Viewing and using points

[1300] The user receives a notification from the server, launches the app, and checks the status of their points. The input is the notification content displayed on the device and the point data in the app, and the output is the user's action (using the points). The specific steps a user takes to check the notification and use their points at affiliated stores or online sites are to tap the link in the notification and access the coupon page or related site.

[1301] Step 9:

[1302] Use of the campaign

[1303] The user checks the campaign notification from the server and efficiently uses points at specific stores or online sites. The input is the campaign notification message, and the output is the user's point usage action. The user checks the notification and plans to shop at stores participating in the campaign. The specific steps to display in-app coupons and promote in-store usage include presenting the coupon at the store and using the points.

[1304] Step 10:

[1305] Emotion recognition

[1306] The emotion engine analyzes user input (text, voice, and facial expression data) and recognizes emotions. The input is text, voice, and facial expression data provided by the user through a chatbot or app, and the output is analyzed emotional information. For example, using IBM Watson's speech recognition engine, it can classify emotions such as "fatigue" from the voice input "I'm tired today."

[1307] Step 11:

[1308] Collecting and storing emotional information

[1309] The emotion recognition results are sent to the server and stored in a database. The input is the emotion information analyzed by the emotion engine, and the output is the emotion data stored in the database. This process involves sending the emotion information to the server through an HTTPS request and storing it in the database.

[1310] Step 12:

[1311] Creating emotional notifications

[1312] The AI ​​algorithm generates a notification message based on emotional information. The input is emotional information and point information, and the output is a notification message that takes emotion into consideration. The server uses a template engine to generate a message such as "Double points campaign at store XX, perfect for refreshing yourself."

[1313] Step 13:

[1314] Adjusting the timing and content of notifications

[1315] The emotion engine analyzes the user's emotional state and determines the optimal notification timing. The input is emotional information and the user's behavioral history, and the output is the timing and content of the notification. Specific steps are included to improve the user's response rate by sending notifications during times when the emotion engine is relaxed based on the analysis results.

[1316] (Application example 2)

[1317] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1318] Conventional point program management systems make it difficult for users to effectively utilize their points, as it is cumbersome to keep track of point expiration dates and the latest campaign information. Furthermore, because they do not take into account the user's emotional state, notifications and suggestions are not provided at the most effective times, which makes it difficult to increase user satisfaction. Furthermore, the lack of real-time information provided via smart devices reduces opportunities for users to efficiently use their points when shopping in physical stores.

[1319] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1320] In this invention, the server includes means for collecting point program information from users, means for saving the collected point program information in a database, means for analyzing the saved point program information and generating a notification when points are about to expire, means for sending the generated notification to the user, means for externally acquiring campaign information and comparing it with the user's point information to suggest an optimal campaign, means for recognizing the user's emotions using an emotion engine and reflecting the emotion information in a notification message, and means for displaying notifications via a smart device (including smart glasses, smartphones, and head-mounted displays) so that the user can check point information and campaign information in real time. This allows users to know point expiration dates and the latest campaign information in a timely manner and receive effective suggestions based on their emotion information, which promotes point usage in physical stores and improves user satisfaction.

[1321] A "points program" is a system in which users can earn points by performing certain activities or making purchases and then exchange those points for rewards or services.

[1322] A "database" is an information system for storing and managing point program information collected from users.

[1323] "Notification" is a message that notifies the user when the expiration date of points is approaching or when campaign information is available.

[1324] "Campaign information" is information about discounts and benefits that allow users to use points more advantageously under certain conditions.

[1325] The "emotion engine" is a system that analyzes the user's emotional state and reflects the results in notification messages.

[1326] A "smart device" is an electronic device that can display and input information using advanced technology, such as smart glasses, smartphones, and head-mounted displays.

[1327] A "point management app" is application software that is installed on a user's device and allows the user to check points and receive notifications.

[1328] An "AI algorithm" is a computational method for analyzing data and making predictions using artificial intelligence technology.

[1329] "User data" refers to various information about the user, such as point acquisition history, point usage history, and emotional information.

[1330] "Real-time" refers to a state in which information is collected, analyzed, and notified immediately without delay.

[1331] MODE FOR CARRYING OUT THE INVENTION

[1332] 1. System Program

[1333] The system that realizes this invention consists of four main components: a server, a terminal, a user, and an emotion engine. Each component cooperates to smoothly manage user points and notify users of campaigns.

[1334] 2. Server processing explanation

[1335] The server first collects point program information from users. The target point program data includes the number of points, acquisition date, usage history, expiration date, etc. This information is stored in a database and used as the basis for later analysis.

[1336] The AI ​​algorithm installed on the server analyzes the stored point program information and lists the information when points are about to expire. The AI ​​algorithm then generates a notification message based on the analysis results. For example, it creates a notification saying, "Program A's points will expire in 3 days." The server also calls an external API to obtain the latest campaign information, compares it with the user's point information, and generates a notification suggesting the most suitable campaign.

[1337] 3. Terminal processing explanation

[1338] A points management app is installed on the user's device. This app periodically synchronizes data with the server and displays the latest points information. Through the app, users can check their points balance and expiration date and receive notifications sent from the server. The received notifications are displayed within the app, providing detailed information and instructions on how to use points. In addition, points information and campaign information are displayed in real time through smart devices (smart glasses, smartphones, head-mounted displays, etc.).

[1339] 4. User behavior description

[1340] The user receives a notification from the server and launches the point management app to check the status of their points. For example, if they receive a notification that "XX points will expire in 5 days," the user can check the points in the app and use them at affiliated stores or online sites. They can also check campaign notifications from the server to use their points efficiently at specific stores or online sites. For example, if they receive a notification that "XX store is having a double points campaign this weekend," they can plan to shop at the store that weekend.

[1341] 5. Explanation of Emotion Engine Operation

[1342] The emotion engine analyzes the text and voice input by the user, as well as facial expression data captured by a high-sensitivity camera, to recognize the user's emotions. For example, if the user inputs, "I'm feeling a little stressed today," the emotion engine recognizes this emotion as "stress" and conveys it to the server. The server then generates a notification message based on the points expiration information and emotion information. For example, it might generate a notification with the content, "Double points campaign at store XX, perfect for refreshing yourself," and send it to the user. The timing and content of the notification are also adjusted based on the user's emotional state. For example, sending notifications during times when the user is relaxed can improve the response rate after receiving the notification.

[1343] 6. Explanation of specific examples

[1344] For example, suppose a user has 200 points and their expiration date is approaching in five days. If the user says, "I'm feeling a little stressed today," the emotion engine recognizes that emotion and communicates it to the server. Based on the points' expiration date and emotion information, the server generates a notification with the message, "Double points campaign at a cafe perfect for refreshing yourself," and sends it to the user's smart device. The notification is displayed on the user's smart glasses, and when the user opens the app, a link that says, "Use now." Tapping the link takes them to the coupon page of a partner cafe, where they can use their points to refresh themselves.

[1345] 7. Examples of prompts

[1346] Below is an example of a prompt sentence.

[1347] "The points for user ID 'user123' will expire in 4 days. A double points campaign is running until the end of this week at a cafe perfect for refreshing yourself. The coupon will be automatically applied when you use your smart glasses."

[1348] In this way, users can prevent points from expiring and receive more emotionally relevant suggestions, resulting in a better user experience.

[1349] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1350] Step 1:

[1351] User Data Collection and Storage

[1352] The server collects user data through the API of the point program. As input, it acquires point program information such as the number of points, acquisition date, usage history, and expiration date, and stores it in a database. Specifically, it links the point program information to the user ID and manages it centrally.

[1353] Step 2:

[1354] Point status analysis

[1355] The server uses the point program information stored in the database to list points that are about to expire. As input, it reads the stored point data and uses an AI algorithm to extract points that are about to expire. As output, it generates a list of points that are about to expire. Specifically, it calculates the number of days until the expiration date and lists points that will expire within a certain period of time.

[1356] Step 3:

[1357] Generate notifications

[1358] The server generates a notification message based on the results of point status analysis. The input is the list of points that are about to expire, which is the output of step 2. As an output, a specific notification message is generated. As a specific example, a message is created stating, "The points for user ID 'user123' will expire in 3 days."

[1359] Step 4:

[1360] Sending notifications

[1361] The server sends the generated notification message to the user. The input is the notification message generated in step 3, and the output is to send the notification to the user via email, SMS, or push notification. Specifically, the message is sent based on the notification method set by the user.

[1362] Step 5:

[1363] Collection and proposal of campaign information

[1364] The server retrieves the latest campaign information from an external API and compares it with the user's point information. The input is the campaign information retrieved from the external API, and the output is a message proposing the most suitable campaign for the user. Specifically, the server compares the user's point information and campaign information against the conditions to propose the most suitable campaign.

[1365] Step 6:

[1366] Recognizing and reflecting emotions

[1367] The emotion engine analyzes the user's text input, voice data, and facial expression data to recognize the user's emotions. The input is the emotional data provided by the user, and the output is emotional information sent to the server. Specifically, the emotion engine recognizes emotions such as "stress" and "relaxation" and passes that information to the server.

[1368] Step 7:

[1369] Generate emotional notifications

[1370] The server generates a notification that reflects emotional information based on the output from the emotion engine. The input is the emotional information from step 6, and the output is a notification message that takes emotion into consideration. As a specific example, it generates a notification that reads, "There is a double points campaign at a cafe that is perfect for refreshing yourself."

[1371] Step 8:

[1372] Displaying notifications on smart devices

[1373] The terminal receives the notification sent from the server and displays it to the user through the smart device. The input is the notification message generated in step 4 and step 7, and the output is the display on the smart glasses, smartphone, or head-mounted display. Specifically, the notification is displayed on the display of the smart device in real time.

[1374] Through these steps, users can understand point expiration dates and campaign information in real time, and receive emotionally tailored suggestions, allowing them to enjoy a better user experience.

[1375] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1376] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1377] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1378] [Fourth embodiment]

[1379] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1380] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1381] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1382] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1383] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1384] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1385] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1386] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1387] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1388] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1389] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1390] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1391] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1392] The system for implementing this invention includes three main components: a server, a terminal, and a user. The specific operation of each component will be described below.

[1393] Server Processing

[1394] User Data Collection and Storage

[1395] The server collects user data through the API of each point program, including the number of points a user has, the date they have earned them, their usage history, and their point expiration date. This data is stored in a database, and point program information is centrally managed using the user ID as a key.

[1396] Point status analysis

[1397] An AI algorithm installed on the server periodically analyzes the user's point usage history and expiration date. It checks whether the points are about to expire and generates a notification if so. It also prioritizes the use of points and suggests the best time to use them.

[1398] Sending notifications

[1399] The server notifies users when their points are about to expire and about the latest campaign information. Notifications are sent via email, SMS, app push notifications, etc. to encourage users to use their points.

[1400] Collection of campaign information and notification

[1401] Campaign information is obtained through an external API and compared with the user's point information. Based on the comparison results, the system notifies the user that points can be used more efficiently by taking advantage of a specific campaign. For example, if a specific store is running a double points campaign, the system notifies the user of this information.

[1402] Terminal handling

[1403] Check your points

[1404] A points management app is installed on the user's device. The app periodically synchronizes data with the server and displays the latest points status. Users can open the app to check the balance and expiration date of each points program.

[1405] Receive notifications

[1406] The device receives notifications sent from the server and displays them to the user. The notification content includes information about upcoming points expiration dates and campaign information. When the user taps the notification, detailed information is displayed within the app and an action such as using points is prompted.

[1407] User Behavior

[1408] Viewing and using points

[1409] The user receives a notification from the server and launches the app to check the status of their points. For example, if they receive a notification that "XX points will expire in 5 days," the user can check the points within the app and use them at affiliated stores or online sites.

[1410] Use of the campaign

[1411] Users can check campaign notifications from the server and use their points efficiently at specific stores or online sites. For example, if a user receives a notification that "There is a double points campaign this weekend at store X," the user can plan to shop at the store that weekend.

[1412] Specific examples

[1413] For example, suppose user C has 300 points in point program A. When the expiration date is approaching in three days, the server detects this information and sends C a notification saying, "Your 300 points in program A will expire in three days." A notification will appear on C's smartphone, and when C opens the app, a link saying "Use now" will appear. By tapping the link, C will be taken to an affiliated online shop where she can use her points to purchase products.

[1414] This system allows users to prevent points from expiring and use them efficiently. It also allows users to get the most out of their points by staying up to date with the latest campaign information.

[1415] The processing flow will be explained below.

[1416] Specific processing of the program

[1417] Server Processing

[1418] Step 1: Collect data

[1419] The server obtains user point information through the API of each point program, including the number of points, acquisition date, usage history, and expiration date.

[1420] Step 2: Save your data

[1421] The server stores the acquired data in a database. There is a separate table for each point program, and data is associated using the user ID as a key.

[1422] Step 3: Analyze the data

[1423] An AI algorithm installed on the server analyzes the points information in the database, in particular checking whether the points are about to expire and listing those points that are about to expire.

[1424] Step 4: Generate notifications

[1425] Based on the results of the AI ​​algorithm's analysis, the server generates a notification message, such as "Your points for Program A will expire in 3 days."

[1426] Step 5: Sending notifications

[1427] The server generates the notification and sends it to the user, either via email, SMS, or push notification, allowing the user to receive the notification.

[1428] Step 6: Gather campaign information

[1429] The server calls an external API to obtain the latest campaign information, such as information about a double points campaign being held at a specific store.

[1430] Step 7: Campaign information verification and notification

[1431] The server compares the acquired campaign information with the user's point information, generates a notification proposing the relevant campaign, and sends it to the user.

[1432] Terminal handling

[1433] Step 1: Synchronize your data

[1434] The point management app installed on the device periodically synchronizes with the server to obtain the latest point information.

[1435] Step 2: Viewing points

[1436] The acquired point information is displayed within the app, allowing users to check the balance and expiration date of each point program.

[1437] Step 3: Receive notifications

[1438] The device receives notifications sent from the server and displays them to the user in-app or as push notifications.

[1439] Step 4: View details

[1440] When users tap on the notification, more information will be displayed within the app, including where points can be used and details about the campaign.

[1441] User Behavior

[1442] Step 1: Check notifications

[1443] The user checks the notification received on the device, which notifies them of the approaching expiration date of specific points and campaign information.

[1444] Step 2: Use your points

[1445] Users can redeem their points by clicking a link within the app, for example by being redirected to a partner online shop where they can use their points to purchase products.

[1446] Step 3: Use the campaign

[1447] Users can use points efficiently at physical stores and online sites based on the campaign information received on their devices, and plan their shopping accordingly.

[1448] Through these steps, a system is realized in which the server, terminal, and user work together to efficiently manage and use points.

[1449] Example 1

[1450] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1451] With conventional point management systems, users were unable to properly grasp the expiration dates of points or available campaign information, making it difficult to prevent points from expiring or use them at the optimal time. In particular, when managing multiple point programs, it was time-consuming to check the point balance and expiration date of each program individually, which was a significant burden for users. In addition, the priority order for point usage was unclear, which also hindered users from using points efficiently.

[1452] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1453] In this invention, the server includes means for collecting point program information from users, means for saving the collected point program information in a database, means for analyzing the saved point program information and generating a notification when points are about to expire, means for sending the generated notification to the user, means for externally acquiring campaign information and comparing it with the user's point information to propose optimal campaigns, means having an algorithm for periodically analyzing the collected point data and campaign information, and means for notifying the collected campaign information based on the user's point usage priority. This allows users to efficiently understand and use point expiration dates, optimal usage times, and campaign information through the app.

[1454] "User information" refers to data related to the points program, such as user identification information, number of points, acquisition date, usage history, and expiration date.

[1455] A "database" is an electronic storage system that centrally manages collected point program information and allows for easy storage, searching, and updating.

[1456] "Notifications" are messages that inform users when their points are about to expire or about the best campaign information. Notification formats include email, SMS, and app push notifications.

[1457] An "external API" is an interface that a server uses to obtain information from external services or databases. It is used to obtain campaign information, etc.

[1458] "Campaign information" refers to information about benefits for using points efficiently, such as a campaign to double points at a specific store.

[1459] "Algorithm" refers to a series of computational procedures that run on the server and analyze the point usage history and expiration date. Specifically, it includes pattern recognition and machine learning models.

[1460] A "point management app" is application software that users install on their smartphones or tablets to check their point balance, expiration date, and campaign information.

[1461] A "user device" is an electronic device used by a user, such as a smartphone, tablet, or computer, on which the point management app is installed and used.

[1462] "Verification" is a process in which the server compares the user's point data with the acquired campaign information to identify available point campaigns.

[1463] The "usage priority" is a standard for setting the priority when using points. For example, points that are close to their expiration date are set to be used first.

[1464] The system for implementing this invention includes three main components: a server, a terminal, and a user. The specific operation of each component and how they work together will be described in detail below.

[1465] Server Processing

[1466] The server first has a means of collecting point program information from users. This collection is done through the API of each point program, and data such as the number of points a user has, the date they acquired them, their usage history, and their expiration date is obtained. This information is then saved in a database. The saved point program information is managed centrally and registered using the user ID as a key.

[1467] The server then periodically analyzes the stored loyalty program information. Using AI algorithms, the server generates notifications when points are about to expire. These notifications include information about the points that are about to expire and recommended times to use them. These notifications are then sent to users via email, SMS, app push notifications, and more.

[1468] In addition, the server obtains campaign information through an external API. This campaign information is matched with the user's point data and used to suggest the most suitable campaign. If the campaign is an effective way to use points, the server notifies the user of this information. For example, if a specific store is running a double points campaign, the server notifies the user of this information.

[1469] Terminal handling

[1470] A points management app is installed on the device. This app periodically synchronizes data with the server and displays the latest points status. Users can open the app to check the balance and expiration date of each points program.

[1471] The device also receives notifications sent from the server. These notifications include information about upcoming point expiration dates and campaign information, and are displayed to the user. When the user taps the notification, more information is displayed in the app and an action is prompted, such as using points.

[1472] User Behavior

[1473] The user receives a notification from the server and launches the app to check the status of their points. For example, if they receive a notification saying, "X points will expire in 5 days," the user can check the status of their points within the app and use them at affiliated stores or online sites. Also, if they receive a notification about campaign information, for example, "There's a double points campaign at X store this weekend," they can check the notification and plan their shopping at the store that weekend.

[1474] Specific examples

[1475] For example, suppose user A has 300 points in point program A. When the expiration date is approaching in three days, the server detects this information and sends user A a notification saying, "Your 300 points in program A will expire in three days." A notification will appear on user A's smartphone, and when user A opens the app, a link saying "Use now" will appear. By tapping the link, user A will be taken to an affiliated online shop where they can use their points to purchase products.

[1476] Example prompts for generative AI models

[1477] "Please explain the specific behavior of a feature in a user's point management system that notifies users when their points are about to expire. As a specific scenario, please explain the case where a user has 300 points in point program A and the points are about to expire in three days."

[1478] This system allows users to prevent points from expiring, allowing them to use their points efficiently. It also allows users to get the most out of their points by staying up to date with the latest campaign information.

[1479] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1480] Step 1:

[1481] User Data Collection

[1482] The server calls the API of each point program to collect user data, including the number of points a user has, the date they acquired them, their usage history, and their expiration date.

[1483] Input: API endpoint of each point program

[1484] What happens: The server sends an HTTP request to the API endpoint and parses the returned JSON data.

[1485] Data processing: Parse the acquired JSON data and extract the user ID, number of points, acquisition date, usage history, and expiration date.

[1486] Output: Parsed user data

[1487] Step 2:

[1488] Saving to a database

[1489] The server stores the collected user data in a database. Point program information is centrally managed using the user ID as a key.

[1490] Input: Parsed user data

[1491] What happens: The server opens a database connection, executes an SQL query, and saves the user data.

[1492] Data processing: Convert user data into a database table format.

[1493] Output: User data stored in the database

[1494] Step 3:

[1495] Point status analysis

[1496] The AI ​​algorithm installed on the server analyzes point usage history and expiration dates, and generates a notification when a user's points are about to expire.

[1497] Input: User data stored in the database

[1498] How it works: The server runs an AI algorithm, taking user data as input and outputting a data set showing when points are about to expire.

[1499] Data calculation: Using a machine learning model, points usage history and expiration dates are analyzed to extract points that are close to expiring.

[1500] Output: List of points that are about to expire

[1501] Step 4:

[1502] Generate and send notifications

[1503] The server generates notifications based on the analysis results and sends them to the user in the form of email, SMS, app push notifications, etc.

[1504] Input: List of points that are about to expire

[1505] Specific operation: The server uses the notification template to generate notification content for each user, and then sends the notification using the SMTP protocol or SMS API.

[1506] Data processing: Embed user point information in the notification template.

[1507] Output: Notification sent to the user

[1508] Step 5:

[1509] Collection of campaign information and notification

[1510] The server obtains the latest campaign information through an external API, compares it with the user's point data, and generates notifications to suggest the most suitable campaigns.

[1511] Input: Campaign information from external API

[1512] What it does: The server sends an HTTP request to an external API to retrieve campaign information, which it then stores in a database and matches with the user's point data.

[1513] Data calculation: Compare the acquired campaign information with user point data to select the most suitable campaign.

[1514] Output: Campaign notification sent to users

[1515] Step 6:

[1516] Check your points

[1517] A points management app is installed on the device. This app periodically synchronizes data with the server and displays the latest points status. Users can open the app to check their points balance and expiration date.

[1518] Input: Latest point data synchronized from the server

[1519] Specific operation: The app calls the API in the background to get the latest point data from the server, which is then saved in local storage and displayed in the user interface.

[1520] Data processing: Convert the data obtained from the server into the display format of the app.

[1521] Output: Points balance and expiry date displayed in the app

[1522] Step 7:

[1523] Receive notifications

[1524] The device receives notifications sent from the server and displays them to the user, who can tap on them to view more information within the app.

[1525] Input: Notification sent from the server

[1526] Specific behavior: The device's notification service receives the push notification from the server and displays it in the notification center. When the user taps the notification, the relevant app screen is opened.

[1527] Data processing: Converts the notification content into a format suitable for the user interface.

[1528] Output: Notification displayed in the notification center and detailed information in the app

[1529] Step 8:

[1530] Viewing and using points

[1531] When users receive a notification, they can launch the app to check their points status and use them at affiliated stores or online sites.

[1532] Input: Point information and notification content displayed in the app

[1533] Specific operation: The user taps a link in the app to access a partner store or online shop, where they can use their points to purchase a product.

[1534] Data processing: Transaction data for point usage is generated and sent to the server.

[1535] Output: Transaction record of items purchased using points

[1536] Step 9:

[1537] Use of the campaign

[1538] The user checks the campaign notification from the server and uses the points to effectively take advantage of the campaign.

[1539] Input: In-app campaign notifications and details

[1540] Specific actions: The user taps on the campaign notification, checks the details, and redeems the campaign in a physical store or online shop.

[1541] Data processing: Campaign transaction data is generated and sent to the server.

[1542] Output: Transaction record of points redemption using campaign

[1543] (Application example 1)

[1544] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1545] Conventional point program management systems notify users when their points are about to expire, but this can sometimes prevent users from using their points at the appropriate time. Furthermore, they do not provide sufficient functionality for efficiently utilizing campaign information and optimizing point usage, resulting in point expiration and inefficient point usage. Therefore, there is a need for a way for users to use points efficiently and prevent them from expiring.

[1546] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1547] In this invention, the server includes means for collecting point program information from users, means for saving the collected point program information in a database, means for analyzing the saved point program information and generating a notification when the point expiration date is approaching, means for sending the generated notification to the user, means for acquiring campaign information from an external source and comparing it with the user's point information to propose the most suitable campaign, and means for sending point expiration date notifications and campaign information notifications to the user via a mail server. This allows users to check the point expiration date as needed and use their points efficiently. Furthermore, by utilizing the campaign information, the utility value of points can be maximized and users can manage their points effectively.

[1548] "User" refers to a person who uses the points program.

[1549] A "points program" is a system in which users are given points each time they use a specific service or product, and can use these points to receive discounts or benefits.

[1550] "Collecting information" refers to the process of obtaining data related to the loyalty program.

[1551] A "database" is an information system for systematically storing and efficiently managing collected data.

[1552] "Expiration date approaching" indicates that the points are about to expire.

[1553] "Generating a notification" is the act of creating a message to inform a user of information.

[1554] "Campaign Information" refers to information about promotions such as special offers and discounts that are held during a specific period of time.

[1555] "Matching" is the act of comparing specific data with other data to identify similarities and differences.

[1556] "Sending" refers to the act of delivering the generated notification to the user via electronic means.

[1557] A "mail server" is a server that manages the sending and receiving of email.

[1558] An "AI algorithm" is a computational process that analyzes user behavior patterns and data to derive efficient methods.

[1559] A "generative AI model" is a model that uses machine learning to generate new information and patterns from data.

[1560] The system for implementing this invention includes three main components: a server, a terminal, and a user. The main functions of this system are to collect, store, analyze, and notify users of point program information, and to suggest campaign information.

[1561] Server Processing

[1562] The server collects user data through the point program's API. Specifically, it obtains data such as the number of points a user has, the date they acquired them, their usage history, and their point expiration date, and stores this data in a database. The point program information is centrally managed using the user ID in the database as a key.

[1563] Next, an AI algorithm installed on the server periodically analyzes the user's point usage history and expiration date. This checks whether the points are about to expire and generates a notification if so. It also prioritizes the use of points and suggests the best time to use them.

[1564] Furthermore, campaign information is obtained through an external API and compared with the user's point information. Based on the comparison results, the system notifies the user that points can be used more efficiently by taking advantage of a specific campaign. For example, if a specific store is running a double points campaign, the system notifies the user of this information. Notifications are sent to the user via a mail server.

[1565] Terminal handling

[1566] A points management app is installed on the user's device. This app periodically synchronizes data with the server and displays the latest points status. Users can open the app to check the balance and expiration date of each points program. The app also includes a function to receive notifications sent from the server and display them to the user. By tapping the notification, users can check detailed information within the app and be prompted to take action, such as using points.

[1567] User Behavior

[1568] The user receives a notification from the server and launches the app to check the status of their points. For example, if they receive a notification that "XX points will expire in 5 days," they can check the points within the app and use them at affiliated stores or online sites. Furthermore, if they receive a notification that "XX store is having a double points campaign this weekend," they can plan to shop at the store that weekend.

[1569] This system allows users to prevent points from expiring and use them efficiently. Also, by staying up-to-date on the latest campaign information, users can make the most of their points. This increases user satisfaction and makes the point program more useful.

[1570] Specific examples

[1571] For example, suppose user C has 300 points in point program A. When the expiration date is approaching in three days, the server detects this information and sends C a notification saying, "Your 300 points in program A will expire in three days." A notification will appear on C's smartphone, and when C opens the app, a link saying "Use now" will appear. By tapping the link, C will be taken to an affiliated online shop where he can use his points to purchase products.

[1572] Prompt Sentence Examples

[1573] We want to build an app that centrally manages users' point information and campaign information, and suggests optimal point usage. The goal is to efficiently receive point expiration dates and campaign information from users, and to help them with the process of actually using their points. Specifically, the app includes the following features:

[1574] 1. Point expiration notification

[1575] 2. Notification of campaign information

[1576] 3. Suggestions for using points

[1577] How do you collect and analyze user data and send appropriate notifications? What technologies do you use to do so?

[1578] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1579] Step 1: Collect user data

[1580] The server obtains user data from the API of each point program. The input is an API request, and the output is data such as the number of points, acquisition date, usage history, and point expiration date. Specifically, it sends a request to the API endpoint, parses the results, and collects them as structured data. By doing this periodically, the latest information is maintained.

[1581] Step 2: Save your data

[1582] The server saves the point program information collected in step 1 in a database. The input here is the collected point information, and the output is structured data saved in the database. Specifically, it executes an INSERT or UPDATE query on the database and centrally manages the data using the user ID as a key.

[1583] Step 3: Analyze points expiration dates

[1584] The server periodically analyzes the stored point program information to check whether any points are about to expire. The input to this step is the point information in the database, and the output is a list of points that are about to expire. The specific operation is to perform an operation that compares the expiration date of each point with the current date, and extracts points that are about to expire within three days.

[1585] Step 4: Generate and send notifications

[1586] Based on the results of step 3, the server generates a notification when points are about to expire and sends the notification to the user. The input here is a list of points that are about to expire, and the output is the generated notification message and the sending result. The specific operation is to embed the point information in a message template, obtain the user's email address, and send the notification through the email server.

[1587] Step 5: Obtain and verify campaign information

[1588] The server retrieves campaign information through an external API and compares it with the user's point information. The input of this step is the campaign data from the external API and the user's point information, and the output is a list of points recommended for campaign use. The specific operation is to retrieve campaign information and match it with the user's point data to identify points that can be used effectively in a specific campaign.

[1589] Step 6: Generate and send campaign notifications

[1590] The server notifies the user of specific campaign information based on the results of step 5. The input here is a list of points where campaign use is recommended, and the output is the generated campaign notification and sending result. The specific operation is to generate a notification message containing the campaign information and send it to the user via the mail server.

[1591] Step 7: Check your points status

[1592] The device receives the notification sent from the server and displays it so that the user can check the status of point usage. The input here is the notification data from the server, and the output is the point information display screen on the device. The specific operation is that the device app receives the notification from the server and displays the information to the user in an appropriate format.

[1593] Step 8: Promote points usage

[1594] Users can use their points efficiently based on the notifications displayed on their devices. The input here is the displayed notification information, and the output is the actual act of using points. Specifically, users tap the notification to check detailed information, and then access affiliated online shops or stores via the link to use their points.

[1595] Step 9: Collect feedback data

[1596] The server collects data on how users use points and campaigns. The input here is user behavior data, and the output is updated point usage history data. The specific operation is to track user behavior and update the database to analyze campaign effectiveness and point usage trends.

[1597] Prompt Sentence Examples

[1598] We want to build an app that centrally manages users' point information and campaign information, and suggests optimal point usage. The goal is to efficiently receive point expiration dates and campaign information from users, and to help them with the process of actually using their points. Specifically, the app includes the following features:

[1599] 1. Point expiration notification

[1600] 2. Notification of campaign information

[1601] 3. Suggestions for using points

[1602] How do you collect and analyze user data and send appropriate notifications? What technologies do you use to do so?

[1603] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1604] The system for implementing this invention includes four main components: a server, a terminal, a user, and an emotion engine. The specific operation of each component will be described below.

[1605] Server Processing

[1606] User Data Collection and Storage

[1607] The server collects user data through the API of each point program. The data includes the number of points, acquisition date, usage history, and expiration date. This data is stored in a database, and point program information is centrally managed using the user ID as a key.

[1608] Point status analysis

[1609] An AI algorithm installed on the server analyzes the points information in the database, in particular checking whether the points are about to expire and listing those points that are about to expire.

[1610] Generate notifications

[1611] Based on the results of the AI ​​algorithm's analysis, the server generates a notification message, such as "Your points for Program A will expire in 3 days."

[1612] Sending notifications

[1613] The server generates the notification and sends it to the user, either via email, SMS, or push notification, allowing the user to receive the notification.

[1614] Collection of campaign information and notification

[1615] The server calls an external API to obtain the latest campaign information. For example, it obtains information about a double points campaign being held at a specific store. It compares the obtained campaign information with the user's point information and generates a notification suggesting a relevant campaign. It then sends this to the user.

[1616] Terminal handling

[1617] Check your points

[1618] A points management app is installed on the user's device. The app periodically synchronizes data with the server and displays the latest points information. Users can check the balance and expiration date of each points program.

[1619] Receive notifications

[1620] The device receives the notification sent from the server and displays it to the user in the app or as a push notification. When the user taps the notification, more information is displayed in the app and an action such as using points is prompted.

[1621] User Behavior

[1622] Viewing and using points

[1623] The user receives a notification from the server and launches the app to check the status of their points. For example, if they receive a notification that "XX points will expire in 5 days," the user can check the points within the app and use them at affiliated stores or online sites.

[1624] Use of the campaign

[1625] Users can check campaign notifications from the server and use their points efficiently at specific stores or online sites. For example, if a user receives a notification that "There is a double points campaign this weekend at store X," the user can plan to shop at the store that weekend.

[1626] Emotion Engine Operation

[1627] Emotion recognition

[1628] The emotion engine analyzes the text and voice input by the user, as well as facial expression data captured by a high-sensitivity camera, to recognize the user's emotions. For example, if a user inputs "I'm tired today" into the chatbot, it will classify that emotion as "fatigue."

[1629] Collecting and storing emotional information

[1630] The emotion recognition results are sent to the server and stored in a database along with point information. The emotion information is linked using the user ID as a key and used for future analysis.

[1631] Creating emotional notifications

[1632] The AI ​​algorithm generates notification messages based on emotional information. For example, if it detects that the user is feeling stressed, it will generate a notification such as "Double points campaign at store XX, perfect for refreshing yourself."

[1633] Adjusting the timing and content of notifications

[1634] The emotion engine analyzes the user's emotional state and adjusts the timing and content of notifications, for example, by sending notifications when the user is relaxed, which increases the user's response rate.

[1635] Specific examples

[1636] For example, suppose user D has 200 points in point program B, and the expiration date is approaching in five days. If D says, "I'm feeling a little stressed today," the emotion engine recognizes that emotion and passes it on to the server. Based on the points expiration information and emotion information, the server generates a notification saying, "D, if you use 200 points at ◎◎ Cafe to refresh yourself by the end of this week, you'll receive double points," and sends it to the device. A notification will appear on D's smartphone, and when he opens the app, a link saying "Use now" will appear. By tapping the link, he will be taken to the coupon page of the affiliated cafe, where he can use his points to refresh himself.

[1637] This allows users to prevent points from expiring and receive suggestions that match their emotions, resulting in a better user experience.

[1638] The processing flow will be explained below.

[1639] Server Processing

[1640] Step 1: Collect user data

[1641] The server collects user point information through the API of each point program, including the number of points, acquisition date, usage history, and expiration date.

[1642] Step 2: Save your data

[1643] The server saves the collected data in a database. The data for each point program is stored in a table and linked using the user ID as a key.

[1644] Step 3: Analyze your points situation

[1645] An AI algorithm on the server analyzes the points information in the database, specifically checking whether the points are nearing their expiration date and, if so, adding them to an alert list.

[1646] Step 4: Collecting emotional information

[1647] The server receives the user's emotional data from the emotion engine and stores it in a database. The emotional data is classified based on text analysis, voice analysis, image analysis, etc.

[1648] Step 5: Generate notifications

[1649] The AI ​​algorithm creates a notification message based on point data and emotion data, such as "Your points for Program A will expire in three days. Please visit XX Cafe to relieve stress."

[1650] Step 6: Sending notifications

[1651] The server generates the notification and sends it to the user, either via email, SMS, or app push notification, depending on how the user receives it.

[1652] Step 7: Collect and collate campaign information

[1653] The server calls an external API to get the latest campaign information, matches it with the user's point data, and adds applicable campaigns to a list.

[1654] Terminal handling

[1655] Step 1: Synchronize your data

[1656] The point management app installed on the device periodically synchronizes with the server to obtain the latest point information.

[1657] Step 2: Viewing points

[1658] The acquired point information is displayed within the app, allowing users to check the balance and expiration date of each point program.

[1659] Step 3: Receive notifications

[1660] The device receives notifications sent from the server and displays them to the user in the app or as a push notification.

[1661] Step 4: View details

[1662] When users tap on the notification, more information will be displayed within the app, including which points to use and details about the campaign.

[1663] User Behavior

[1664] Step 1: Check notifications

[1665] The user checks the notifications received on the device, which include information about upcoming point expiration dates and sentiment-based campaigns.

[1666] Step 2: Use your points

[1667] Users can tap on a link in the app to redeem their points, for example, by being redirected to a page of a partner online shop or physical store where they can make a purchase using their points.

[1668] Step 3: Use the campaign

[1669] Users can use their points efficiently at physical stores and online sites based on the campaign information they receive. For example, if they receive a notification that "There is a double points campaign this weekend at XX store," they can plan to shop at that store.

[1670] Emotion engine processing

[1671] Step 1: Recognize emotions

[1672] The emotion engine analyzes text, voice, and facial expression data entered by the user to recognize emotions. For example, it recognizes the input "I'm tired today" as "fatigue."

[1673] Step 2: Sending emotional information

[1674] The emotion engine sends the recognized emotion information to the server, where the emotion data is stored in a database using the user ID as a key.

[1675] Step 3: Reflection in notifications

[1676] The AI ​​algorithm tailors notifications based on emotional information, for example, if a user is feeling stressed, it will generate notifications suggesting relaxing offers or campaigns.

[1677] Specific examples

[1678] For example, suppose user E has 150 points in point program C, which are set to expire in seven days, and he or she voice-inputs, "I'm feeling stressed today." The emotion engine recognizes the emotion as "stress" and sends it to the server. Based on the point data and emotion data, the server generates a notification saying, "Your 150 points in program C will expire in seven days. We're running a campaign where you can refresh yourself with a free drink at ◎◎ Cafe," and sends it to E's device. E checks the notification, views the details of the campaign in the app, and takes action to use his or her points efficiently at the cafe during the campaign period, thereby relieving stress and not wasting points.

[1679] Example 2

[1680] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1681] With conventional point management systems, users often missed the expiration date of their points, which resulted in point expiry. Furthermore, the content and timing of notifications were not optimized to reflect the user's situation or emotions, which tended to result in low user response rates. Furthermore, campaign information that allowed users to use their points efficiently was often not provided, making improving the user experience a challenge.

[1682] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for collecting point program information from users, means for saving the collected point program information in a database, means for analyzing the saved point program information using an AI algorithm and generating a notification when the points are about to expire, means for sending the generated notification to the user, means for acquiring campaign information from an external source and comparing it with the user's point information to suggest an optimal campaign, and means for recognizing the user's emotions and adjusting the notification content based on the emotion information. This makes it possible to prevent the user's points from expiring and to suggest campaign information at the optimal timing according to the user's emotions.

[1683] A "user" is an individual or corporation that uses the points program, checks point balances, expiration dates, campaign information, etc., and takes appropriate action.

[1684] The "server" is a central control device that stores point program information collected from users, analyzes it using an AI algorithm, and sends notifications and campaign suggestions based on the results.

[1685] A "points program" is a system in which users accumulate points awarded for specific services or product purchases and can use them for various benefits and discounts.

[1686] A "database" is a data storage system that stores and centrally manages point program information, emotional information, and other data collected by the server.

[1687] "AI algorithms" are machine learning and statistical analysis techniques used to analyze collected data and determine expiration dates and the user's emotional state.

[1688] A "notification" is a message that the server generates based on the analysis results and sends to the user, and includes information such as the approaching expiration date of points and campaign information.

[1689] "Campaign information" refers to promotional information such as double points campaigns and discounts offered at specific stores or online sites.

[1690] An "emotion engine" is a software or hardware system that analyzes a user's text input, voice input, and facial expression data to recognize their emotional state at that time.

[1691] A "point management app" is application software that is installed on a user's device and allows the user to check point balances, expiration dates, and notifications.

[1692] An "external API" is a program interface for obtaining campaign information and point information from external services and databases.

[1693] The system for implementing this invention includes four main components: a server, a terminal, a user, and an emotion engine. The specific operation of each component will be described below.

[1694] Server Processing

[1695] User Data Collection and Storage

[1696] The server collects user data through the API of each point program. The data includes the number of points, acquisition date, usage history, and expiration date. This data is stored in a database, and point program information is centrally managed using the user ID as a key.

[1697] Point status analysis

[1698] The AI ​​algorithms installed on the server analyze the stored data, specifically checking whether points are about to expire, using libraries like Python's scikit-learn.

[1699] Generate notifications

[1700] Based on the analysis results of the AI ​​algorithm, the server generates a notification message, such as "Your points for Program A will expire in 3 days." A template engine such as Jinja2 is used to generate the message.

[1701] Sending notifications

[1702] The server generates notifications and sends them to users via email, SMS, push notifications, etc. These notifications are sent using an SMTP server, the Twilio API, or Firebase Cloud Messaging (FCM).

[1703] Collection of campaign information and notification

[1704] The server calls an external API to obtain the latest campaign information. It then compares the obtained campaign information with the user's point information and generates a notification suggesting a relevant campaign. For example, a notification such as "There is a double points campaign at store XX this weekend."

[1705] Terminal handling

[1706] Check your points

[1707] A points management app is installed on the user's device. The app periodically synchronizes data with the server and displays the latest points information. Users can check the balance and expiration date of each points program.

[1708] Receive notifications

[1709] The device receives the notification sent from the server and displays it to the user in the app or as a push notification. When the user taps the notification, more information is displayed in the app and an action such as using points is prompted.

[1710] User Behavior

[1711] Viewing and using points

[1712] The user receives a notification from the server and launches the app to check the status of their points. For example, if they receive a notification that "XX points will expire in 5 days," the user can check the points within the app and use them at affiliated stores or online sites.

[1713] Use of the campaign

[1714] Users can check campaign notifications from the server and use their points efficiently at specific stores or online sites. For example, if a user receives a notification that "There is a double points campaign this weekend at store X," the user can plan to shop at the store that weekend.

[1715] Emotion Engine Operation

[1716] Emotion recognition

[1717] The emotion engine analyzes the text and voice input by the user, as well as facial expression data captured by a high-sensitivity camera, to recognize the user's emotions. For example, if a user inputs "I'm tired today" into the chatbot, it will classify that emotion as "fatigue." This analysis is performed using IBM Watson's speech recognition engine, among other technologies.

[1718] Collecting and storing emotional information

[1719] The emotion recognition results are sent to the server and stored in a database along with point information. The emotion information is linked using the user ID as a key and used for future analysis.

[1720] Creating emotional notifications

[1721] The AI ​​algorithm generates notification messages based on emotional information. For example, if it detects that the user is feeling stressed, it will generate a notification such as "Double points campaign at store XX, perfect for refreshing yourself."

[1722] Adjusting the timing and content of notifications

[1723] The emotion engine analyzes the user's emotional state and adjusts the timing and content of notifications, for example, by sending notifications when the user is relaxed, which increases the user's response rate.

[1724] Specific examples

[1725] For example, suppose user A has 200 points in point program B, and the expiration date is approaching in five days. If user A says, "I'm feeling a little stressed today," the emotion engine recognizes that emotion and passes it on to the server. Based on the points expiration information and emotion information, the server generates a notification saying, "User A, if you use 200 points at store ◎◎ to refresh yourself by the end of this week, there's a double points campaign," and sends it to the device. A notification appears on user A's smartphone, and when A opens the app, a link saying "Use now" appears. By tapping the link, they can access the coupon page of the affiliated store and use their points to refresh themselves.

[1726] Prompt Sentence Examples

[1727] An example of a prompt sentence to input to the generative AI model is as follows:

[1728] Person A has 200 points in point program B, and the points are about to expire in 5 days. Person A voice-inputs, "I'm feeling a little stressed today." In this situation, explain how the emotion engine and server work together to send an appropriate notification to Person A.

[1729] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1730] Step 1:

[1731] User Data Collection and Storage

[1732] The server sends a request to the API of each point program and obtains user data (number of points, acquisition date, usage history, expiration date). The input is the response data from each point program API, and the output is user data in JSON format. This data is saved in a database. Specifically, the server uses Python's Requests library to send the API request, parses the received JSON-formatted response data, and saves it in a database (for example, MySQL).

[1733] Step 2:

[1734] Point status analysis

[1735] The server retrieves point information from the database and analyzes it using an AI algorithm. The input is the point information retrieved from the database, and the output is a list of points that are about to expire. The server runs an AI script written in Python, for example using the scikit-learn library, to analyze the point information. The AI ​​algorithm lists points that are about to expire.

[1736] Step 3:

[1737] Generate notifications

[1738] The server generates a notification message based on the analysis results of the AI ​​algorithm. The input is a list of points that are about to expire, and the output is the notification message to be sent to the user. The server uses a template engine (e.g., Jinja2) to generate the message. For example, it creates a message such as "Your points for Program A will expire in 3 days."

[1739] Step 4:

[1740] Sending notifications

[1741] The server generates and sends notification messages to users. The input is the generated notification message, and the output is the notification sent to the user. The sending method can be email, SMS, or push notification. Specifically, the server sends email using an SMTP server, SMS using the Twilio API, or push notification using Firebase Cloud Messaging (FCM).

[1742] Step 5:

[1743] Collection of campaign information and notification

[1744] The server obtains the latest campaign information through an external API, compares it with the user's point information, and generates a notification proposing the most suitable campaign. The input is the campaign information obtained from the external API and the user's point information, and the output is the generated campaign notification message. The server sends an API request, analyzes the obtained JSON data, compares it with the user's point information, and generates a message such as "There is a double points campaign this weekend at store XX."

[1745] Step 6:

[1746] Check your points

[1747] A points management app installed on the user's device periodically synchronizes with the server and displays the latest points information. The input is point data obtained from the server, and the output is the latest points information displayed on the app's UI. The user checks the balance and expiration date of each points program through the app. The device communicates with the server using HTTP requests, and displays the obtained data on the UI.

[1748] Step 7:

[1749] Receive notifications

[1750] The user's device receives notifications sent from the server and displays them in the app or as push notifications. The input is the notification data sent from the server, and the output is the notification message displayed on the user's device. The device uses Firebase Cloud Messaging (FCM) or similar to receive push notifications, and when the user taps the notification, detailed information is displayed in the app.

[1751] Step 8:

[1752] Viewing and using points

[1753] The user receives a notification from the server, launches the app, and checks the status of their points. The input is the notification content displayed on the device and the point data in the app, and the output is the user's action (using the points). The specific steps a user takes to check the notification and use their points at affiliated stores or online sites are to tap the link in the notification and access the coupon page or related site.

[1754] Step 9:

[1755] Use of the campaign

[1756] The user che...

Claims

1. A means for collecting point program information from users; a means for storing the collected points program information in a database; means for analyzing stored loyalty program information and generating notifications when loyalty points are about to expire; means for sending the generated notification to a user; A means for acquiring campaign information from an external source and comparing it with the user's point information to suggest the most suitable campaign; A system including:

2. The system according to claim 1, further comprising means for receiving a notification sent from the server via a point management application from a user terminal and checking the status of point usage.

3. The system according to claim 1, further comprising means for analyzing the usage history and expiration date of points using an AI algorithm and setting usage priorities.

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