System

Abstract

A system is provided.SOLUTION: A system comprising: means for a representative of an enterprise to register a proposed promotion; means for operating a generative AI model to optimize the registered proposed promotion; means for delivering the optimized proposed promotion to a user; means for receiving and verifying questionnaire responses from the user; and means for awarding reward points to the user.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] Traditional advertising methods have had issues with making it difficult to effectively promote specific users and delivering ads to premium members. This creates the risk that new products and services may be overlooked by users. As a result, advertisers experience low advertising effectiveness, while users have limited access to attractive offers and information. Another problem is that users often find ads annoying and have a strong resistance to them. [Means for solving the problem]

[0005] The present invention provides a system including a means for a company representative to register a promotion proposal, a means for running a generative AI model to optimize the registered promotion proposal, a means for delivering the optimized promotion proposal to users, a means for receiving and verifying survey responses from users, and a means for awarding reward points to users.

[0006] This allows businesses to effectively deliver promotions optimized for their target users, and users can earn points as rewards while reducing their resistance to advertising. Utilizing user profile data allows advertisers to develop more effective marketing campaigns. Furthermore, by adding a LINE account as a friend, users' profile data can be analyzed to generate individually optimized promotion ideas and surveys.

[0007] "Company representative" refers to the person in charge of promotion and marketing activities within the company, who creates and registers promotion proposals.

[0008] "Promotion proposal" refers to the content and details of an advertising campaign proposed by an advertiser for the purpose of increasing awareness of and promoting sales of a new product or service.

[0009] A "generative AI model" is an artificial intelligence program that analyzes input data and generates promotional ideas and surveys optimized for users.

[0010] "User" means an individual or business targeted by an advertising campaign who uses the System to receive promotional offers and surveys.

[0011] "Profile data" refers to information such as a user's age, gender, and interests that is collected by the system and used by the generative AI model for analysis.

[0012] A "survey" is data in the form of questions sent to users, and is used to collect users' opinions and evaluations.

[0013] "Reward points" are digital points that users can use as an incentive for answering surveys.

[0014] A "LINE Official Account" is an account operated by a company or organization on the LINE platform for communicating with users and distributing information. [Brief explanation of the drawings]

[0015] [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 illustrating 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

[0016] 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.

[0017] First, the terms used in the following description will be explained.

[0018] 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).

[0019] 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.

[0020] 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.

[0021] 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.

[0022] 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."

[0023] [First embodiment]

[0024] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0025] 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.

[0026] 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).

[0027] 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.

[0028] 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.

[0029] 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.

[0030] 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.

[0031] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0032] 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.

[0033] 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.

[0034] 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.

[0035] 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."

[0036] The present invention is a system that delivers optimized corporate promotional ideas to users and allows users to earn points by answering questionnaires. This system is highly convenient for both advertisers and users, and realizes effective advertising delivery.

[0037] System Overview

[0038] This system consists of an advertiser terminal, a user terminal, and a server. Advertisers register promotion proposals, and the server generates optimized promotions. Users register as friends on the LINE official account and receive individually optimized promotions and surveys. When users answer the survey, the server receives the answers and, after verification, awards reward points.

[0039] Program processing flow

[0040] 1. Advertiser terminal: Advertisers log in to a dedicated management screen and register new promotion proposals. The registered information includes product information, target demographic, distribution start date, etc. Once the promotion proposal is submitted, the data is sent to the server.

[0041] 2. Server: The server sends the promotion ideas it receives to the generative AI model, which analyzes and optimizes the content. The generative AI model then generates the most effective promotion for the target demographic and returns the information to the server.

[0042] 3. Server: Saves the optimized promotion proposal and sends a confirmation to the advertiser. The advertiser reviews the optimized proposal and makes any necessary adjustments. After final confirmation, the advertiser schedules the launch of distribution.

[0043] 4. User device: The user adds the LINE Official Account as a friend. Once the friend addition is complete, the user profile data is sent to the server.

[0044] 5. Generative AI model: Analyzes user profile data and generates individually optimized promotional ideas and surveys, taking into account the user's age, gender, past behavioral data, etc.

[0045] 6. Server: Sends the optimized promotion proposal and the corresponding survey to the user, who receives the notification and answers the survey.

[0046] 7. User terminal: When the user answers and submits the questionnaire, the data is sent to the server.

[0047] 8. Server: Validates the received survey responses and stores them in the database. After validation, reward points are awarded to the user.

[0048] 9. User device: Users can check their points in LINE Wallet and use them as needed. Points can be used for purchases within LINE.

[0049] Specific examples

[0050] Example 1: New Product Campaign

[0051] Advertisers plan a free sample campaign for a new product and register the promotion proposal on a dedicated management screen. The server sends the received promotion proposal to a generative AI model, which optimizes it for the target demographic. The optimized campaign proposal is generated, and the advertiser can review it and set the distribution schedule.

[0052] When a user adds a LINE official account as a friend, their profile data is sent to the server and analyzed by the generative AI model. A new product campaign information and a survey are sent to the user, who then answers the survey. The server receives and verifies the responses and awards the user 50 points. The user can view the reward points in their LINE Wallet and use them for purchases.

[0053] In this way, the system of the present invention provides benefits to both advertisers and users while realizing efficient advertisement distribution.

[0054] The processing flow will be explained below.

[0055] Step 1:

[0056] Advertiser terminal: The advertiser logs in to the dedicated management screen, enters login credentials, and accesses the system.

[0057] Step 2:

[0058] Advertiser terminal: Click the Create New Promotion Proposal button. Enter promotion information (product information, target demographic, campaign start date, etc.).

[0059] Step 3:

[0060] Advertiser terminal: After completing the input, click the send button to send the promotion proposal data to the server.

[0061] Step 4:

[0062] Server: Sends the received promotion proposal data to the generation AI model. The data is analyzed by AI and an optimized promotion proposal is generated.

[0063] Step 5:

[0064] Server: Stores the optimized promotion proposal in a database and sends a confirmation to the advertiser.

[0065] Step 6:

[0066] Advertiser terminal: The advertiser checks the notification and reviews the optimized promotion plan on a dedicated management screen, making fine adjustments as necessary and finalizing the plan.

[0067] Step 7:

[0068] Advertiser terminal: After final confirmation, schedule the start of distribution and click the approval button to send the final data to the server.

[0069] Step 8:

[0070] User device: The user adds the LINE Official Account as a friend. A notification is sent to the user confirming the friend addition.

[0071] Step 9:

[0072] Server: Once the friend registration is confirmed, generate user profile data and send it to the generative AI model.

[0073] Step 10:

[0074] Generative AI model: Analyzes user profile data and generates individually optimized promotional ideas and surveys.

[0075] Step 11:

[0076] Server: Stores the generated promotion ideas and questionnaires in a database and distributes them to users.

[0077] Step 12:

[0078] User device: The user receives the notification and answers the questionnaire. After completing the questionnaire, the user clicks the send button to send the answers to the server.

[0079] Step 13:

[0080] Server: Receives the survey responses sent by users, stores them in a database, and verifies the responses.

[0081] Step 14:

[0082] Server: Once verification is complete, it will credit the reward points to the user's account and send a notification to the user's device.

[0083] Step 15:

[0084] User device: The user opens the LINE Wallet function, checks the points awarded, and uses them to purchase goods and services.

[0085] Step 16:

[0086] Server: Records point usage history and updates user data.

[0087] Through the above processing steps, this system realizes effective and efficient ad delivery and reward provision for both advertisers and users.

[0088] Example 1

[0089] 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."

[0090] Conventional ad delivery systems do not optimize based on detailed user profile data, resulting in poor advertising effectiveness. Furthermore, the lack of an incentive system to encourage users to respond positively to ads presents a challenge, resulting in low ad acceptance. As a result, efficient and effective ad delivery has not been achieved for both advertisers and users.

[0091] 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.

[0092] In this invention, the server includes a means for a company representative to register promotion plans, a means for operating a generation AI model to optimize the registered promotion plans, a means for sending user profile data to the generation AI model and generating individual promotion plans and questionnaires optimized for the target demographic, a means for delivering the optimized promotion plans and questionnaires to users, a means for receiving and verifying questionnaire responses from users, and a means for awarding reward points to users. This enables optimization of promotion plans and individual responses to each user, resulting in high advertising effectiveness and improved user incentives.

[0093] "Company Representative" means a person within a company who is responsible for managing and registering promotion proposals.

[0094] "Promotion Ideas" refers to information about plans and strategies for promoting products and services.

[0095] "Generative AI models" are algorithms and systems that use artificial intelligence to analyze data and generate optimized promotional ideas based on specified criteria.

[0096] "User profile data" refers to information relating to an individual, such as the user's age, gender, location, and past behavioral history.

[0097] A "survey" is a method of asking specific questions to users and collecting their responses.

[0098] "Reward points" are points that users receive as an incentive for certain actions in the system.

[0099] A "communications application" is a software application that a user uses to exchange information with a server.

[0100] "Target demographic" refers to a specific group of users targeted for promotion.

[0101] "Delivery means" refers to the methods and techniques used to deliver promotional ideas and surveys to users.

[0102] "Verification measures" are methods or techniques for verifying the accuracy of survey responses from users.

[0103] This invention is a system that delivers optimized corporate promotional ideas to users and allows users to earn reward points by answering questionnaires. This system is composed of a server, a user terminal, and an advertiser terminal. The roles and detailed operations of each are explained below.

[0104] server

[0105] The server sends the received promotion proposals to the generative AI model and generates optimized promotion proposals. Specifically, it analyzes the promotion proposals sent from the advertiser's device and generates promotion proposals optimized for the target demographic using a prompt for the generative AI model. The generative AI model uses the prompt, "Please optimize this promotion proposal for the target demographic." After receiving the optimized promotion proposal, the server stores it in a database and notifies the advertiser. The server also analyzes the received user profile data and generates individually optimized promotion proposals and questionnaires, taking into account the user's age, gender, past behavioral data, etc.

[0106] Advertiser terminal

[0107] The advertiser terminal provides a dedicated management screen and a means for advertisers to register new promotion proposals. The advertiser enters information such as product information, target demographic, and distribution start date, and sends the promotion proposal to the server. After the optimized promotion proposal is notified by the server, the advertiser can review it, make adjustments as necessary, and set the final distribution schedule.

[0108] User Device

[0109] The user's device is primarily used by the user to add the LINE Official Account as a friend. Once friend addition is complete, the user's profile data is sent to the server. Optimized promotion ideas and surveys are then sent to the user, who receives a notification and answers the survey. Once the answers are sent to the server and verified, the user receives reward points, which can be viewed and used in the LINE Wallet.

[0110] Specific examples

[0111] Example 1: New Product Campaign

[0112] The advertiser plans a free sample campaign for a new product and registers the promotion plan on a dedicated management screen. The server sends the received promotion plan to the generation AI model, which optimizes it for the target demographic. The optimized campaign plan is generated, and the advertiser confirms it and sets the distribution schedule. When a user adds the LINE official account as a friend, their profile data is sent to the server and analyzed by the generation AI model. Information about the new product campaign and a survey are sent to the user, who then answers the survey. The server receives and verifies the responses and awards the user 50 points. The user can check the reward points in their LINE Wallet and use them for purchases.

[0113] Prompt Sentence Examples

[0114] "Please optimize this promotional idea for the target demographic."

[0115] "Optimize a new product campaign aimed at women in their 20s"

[0116] "Generate promotion ideas for male users in their 30s."

[0117] This system will enable effective and efficient ad delivery for both advertisers and users.

[0118] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0119] Step 1:

[0120] Advertiser registration of promotion proposals

[0121] Input: Receive promotional proposal data such as product information, target demographic, and distribution start date from the advertiser's terminal.

[0122] How it works: Advertisers log in to the dedicated management screen, enter each item, and press the "Submit" button to register their promotion proposal.

[0123] Output: The registered promotion proposal data is sent to the server.

[0124] Step 2:

[0125] Optimizing promotion ideas

[0126] Input: Promotion proposal data sent to the server.

[0127] Operation: The server sends the received promotion proposal to the generative AI model and instructs the generative AI model to analyze it using the prompt "Please optimize this promotion proposal for the target demographic."

[0128] Output: The optimized promotion proposal data is sent back to the server from the generative AI model.

[0129] Step 3:

[0130] Checking optimization recommendations and setting delivery schedules

[0131] Input: Optimized promotion proposal data.

[0132] Operation: The server sends the optimized promotion proposal to the advertiser's terminal and sends a confirmation notice to the advertiser. The advertiser checks the optimization proposal, makes any necessary adjustments, and presses the "Final Confirm" button to schedule the distribution.

[0133] Output: The finalized promotion plan and distribution schedule data are saved on the server.

[0134] Step 4:

[0135] Users adding LINE Official Accounts as friends

[0136] Input: A user adds a LINE Official Account as a friend.

[0137] How it works: A user opens the LINE application and adds the official account as a friend. Once the friend registration is complete, the information is sent to the server.

[0138] Output: User profile data (age, gender, region, etc.) is sent to the server.

[0139] Step 5:

[0140] Generate personalized promotion ideas and surveys

[0141] Input: User profile data.

[0142] How it works: The server sends user profile data to the generative AI model and directs its analysis using the prompt "Generate promotion ideas and surveys optimized for each target demographic."

[0143] Output: The generative AI model sends individually optimized promotion ideas and survey data back to the server.

[0144] Step 6:

[0145] Promotion ideas and survey distribution

[0146] Input: Individually optimized promotion ideas and survey data.

[0147] How it works: The server sends the optimized promotion proposal and survey to the user's device. The user receives a notification and answers the survey.

[0148] Output: The user's survey response data is sent to the server.

[0149] Step 7:

[0150] Receiving and verifying survey responses

[0151] Input: User survey response data.

[0152] Operation: The server validates the received survey response data to ensure accuracy.

[0153] Output: The verified survey response data is stored in a database.

[0154] Step 8:

[0155] Awarding reward points

[0156] Input: Validated survey response data.

[0157] Operation: The server processes the reward points to the user based on the survey responses.

[0158] Output: Reward points are reflected in the user's LINE Wallet.

[0159] Step 9:

[0160] Checking and using points

[0161] Input: Reward points awarded.

[0162] How it works: Users can view reward points in LINE Wallet and use them for purchases within LINE as needed.

[0163] Output: A record of the user's reward points usage is kept.

[0164] In this way, the system realizes effective and personalized promotions for both advertisers and users.

[0165] (Application example 1)

[0166] 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."

[0167] In today's advertising market, companies want to run effective promotions, but they face the challenge of delivering advertisements in an optimal way to target users. Furthermore, users often receive promotions and surveys that they are not interested in, which can lead to a decline in engagement. The objective of this invention is to provide a promotion delivery system that efficiently optimizes companies' promotion proposals and is both attractive and convenient for users.

[0168] 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.

[0169] In this invention, the server includes: means for a company representative to register promotion proposals; means for operating a generative AI model to optimize the registered promotion proposals; means for delivering the optimized promotion proposals to users; means including a smartphone application to be installed on the user's device; means for receiving and verifying survey responses from users; means for awarding reward points to users; and means for users to receive and answer promotion proposals and surveys via the application installed on their smartphones. This enables companies to efficiently deliver optimal promotions to target users, and enables users to actively participate in promotional content that interests them and earn rewards.

[0170] A "promotion proposal" refers to the plan and content for effectively communicating information about the products and services offered by a company to users.

[0171] "Generative AI model" refers to an artificial intelligence algorithm or system used to optimize promotional ideas.

[0172] "Optimization" means adjusting and improving the content of a promotional proposal to achieve the most effective results for a specific purpose.

[0173] "User" refers to the consumer or user who receives and responds to the promotion proposal and survey.

[0174] "Survey" refers to a survey in the form of questions to collect opinions and information from users.

[0175] "Reward points" are points that users can earn by answering surveys and can later be exchanged for specific services or products.

[0176] "Server" means the computer system that receives, analyzes, optimizes, and delivers Promotional Ideas.

[0177] "Smartphone Application" refers to software installed on a User's smartphone to receive promotional offers and surveys.

[0178] An "official account for a communication application" refers to an official communication channel operated by a company or organization that allows direct interaction with users.

[0179] The present invention is a system that allows advertisers to register promotion proposals, optimize those proposals, and deliver them to users. Users can earn reward points by answering surveys, and operate the system through a smartphone application.

[0180] System Overview

[0181] The server provides a management screen for company personnel to register promotion proposals. This management screen includes an interface for advertisers to enter details such as product information, target demographics, and distribution start date. The data entered by the advertiser is sent to the server, where the promotion proposal is analyzed and optimized by the generative AI model.

[0182] The server uses the generative AI model to optimize promotion ideas and send them to target users. Users receive promotion ideas and surveys through a dedicated application installed on their smartphones. This application works by users adding the official account of the communication application as a friend.

[0183] Overview of program processing

[0184] The server does the following:

[0185] 1. The advertiser registers a promotion proposal via the management screen.

[0186] 2. The registered promotion proposals are sent to the generation AI model to generate optimized promotion proposals.

[0187] 3. Deliver optimized promotional ideas to the user's smartphone application.

[0188] The smartphone application installed on the user's device performs the following operations:

[0189] 1. Add the official account of the communication application as a friend.

[0190] 2. Display promotion proposals and surveys received from the server.

[0191] 3. The user answers the survey and sends the answers to the server.

[0192] The server receives the survey responses from the user and performs the following actions:

[0193] 1. Verify the contents of the survey responses.

[0194] 2. Give reward points to users after verification.

[0195] 3. Save as a user report.

[0196] Hardware and software used

[0197] The hardware required includes a server, the user's smartphone, and the official account of the communication application. The software required includes an administration screen, a generative AI model, and a smartphone application. Specific examples include an application developed in Python, the LINE API, and a generative AI model.

[0198] Specific examples

[0199] For example, if Company A wants to run a free sample campaign for a new product, it enters a promotion idea into the admin screen. The server optimizes this information using a generative AI model and distributes it to target users. Users receive the promotion idea and a survey through a smartphone application, and by answering the survey, they can earn reward points. These points can be viewed and used in the user's LINE Wallet.

[0200] Prompt Sentence Examples

[0201] "Use a generative AI model to optimize promotional ideas for cosmetics for women in their 30s. Generate optimal promotional ideas and questionnaires based on behavioral data of the target demographic."

[0202] As described above, the present invention is a system that realizes efficient advertisement distribution while providing benefits to both advertisers and users.

[0203] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0204] Step 1:

[0205] The advertiser enters the promotion proposal into the management screen. The management screen provides an interface for entering details such as product information, target demographic, and distribution start date. After input, the promotion proposal is sent to the server. Input: Detailed data of the promotion proposal. Output: Promotion proposal data sent to the server.

[0206] Step 2:

[0207] The server sends the received promotion proposal to the generative AI model, which analyzes the promotion proposal and generates a promotion optimized for the target demographic. Input: Promotion proposal data. Output: Optimized promotion proposal.

[0208] Step 3:

[0209] The server receives the optimized promotion offer and delivers it to the user's smartphone application. Input: Optimized promotion offer. Output: Promotion offer sent to the user's smartphone application.

[0210] Step 4:

[0211] The user opens the application installed on their smartphone. The application adds the official account of the communication application as a friend and displays the promotion proposals and surveys received from the server. Input: Promotion proposals and surveys received from the server. Output: Displayed promotion proposals and surveys.

[0212] Step 5:

[0213] Users answer the survey and send their answers to the server via a smartphone application. Input: User's survey response data. Output: Survey response data sent to the server.

[0214] Step 6:

[0215] The server receives the survey responses from the user and verifies the responses. Once the verification is complete, reward points are awarded to the user. Input: User's survey response data. Output: Verified data and reward points.

[0216] Step 7:

[0217] The server stores the survey results as a user report. Input: Survey data after validation. Output: Stored survey result report.

[0218] 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.

[0219] This invention is a system that optimizes corporate promotional ideas for users and delivers them to them, allows users to earn points by answering questionnaires, and improves the effectiveness of promotions by using an emotion engine that recognizes users' emotions. This system is highly convenient for both advertisers and users, and realizes effective advertising delivery.

[0220] System Overview

[0221] The system consists of an advertiser terminal, a user terminal, a server, and an emotion engine. Advertisers register promotion proposals, and the server generates optimized promotions. Users add the LINE official account as a friend and receive individually optimized promotions and surveys. When users answer the survey, the server receives the answers and awards reward points after verification. The emotion engine then analyzes the user's emotions and optimizes the promotion proposals based on this information.

[0222] Program processing flow

[0223] 1. Advertiser terminal: Advertisers log in to a dedicated management screen and register new promotion proposals. The registered information includes product information, target demographics, campaign start date, etc. Once the promotion proposal is submitted, the data is sent to the server.

[0224] 2. Server: The server sends the received promotion proposal data to the generation AI model and emotion engine for content analysis and optimization. The generation AI model generates the most effective promotion for the target demographic, and the emotion engine analyzes user emotion data and feeds that information back to the generation AI model.

[0225] 3. Server: Generates an optimized promotion proposal and stores it in the database. Sends a confirmation to the advertiser, who can review the proposal and make any necessary adjustments. After final confirmation, schedules the launch of distribution.

[0226] 4. User device: The user adds the LINE Official Account as a friend. Once the friend addition is complete, the user profile data is sent to the server.

[0227] 5. Generative AI model: Analyzes user profile data and generates individually optimized promotional ideas and surveys, taking into account the user's age, gender, past behavioral data, etc.

[0228] 6. Emotion Engine: Analyzes user facial expressions, voice, and text data to recognize emotions and send the results to the generative AI model, which then uses this information to further optimize promotion ideas and surveys.

[0229] 7. Server: The optimized promotion proposals and corresponding questionnaires are stored in the database and sent to users, who then receive notifications and answer the questionnaires.

[0230] 8. User terminal: When the user answers and submits the questionnaire, the data is sent to the server.

[0231] 9. Server: Validates the received survey responses and stores them in the database. After validation, reward points are awarded to the user.

[0232] 10. User device: Users can check their points in LINE Wallet and use them as needed. Points can be used for purchases within LINE.

[0233] Specific examples

[0234] Example 1: New Product Campaign

[0235] Advertisers plan a free sample campaign for a new product and register the promotion proposal on a dedicated management screen. The server sends the received promotion proposal to a generative AI model, which optimizes it for the target demographic. An optimized campaign proposal is generated, and the emotion engine also takes user emotional data into account. The advertiser confirms the proposal and sets the distribution schedule.

[0236] When a user adds a LINE official account as a friend, their profile data and emotion data are sent to the server and analyzed by the generative AI model. A new product campaign information and a survey are sent to the user, who then answers the survey. The server receives and verifies the responses and awards the user 50 points. The user can check the reward points in their LINE Wallet and use them for purchases.

[0237] In this way, the system of the present invention provides benefits to both advertisers and users while realizing efficient advertisement distribution. By combining it with an emotion engine, even more effective promotions become possible.

[0238] The processing flow will be explained below.

[0239] Step 1:

[0240] Advertiser terminal: The advertiser logs in to the dedicated management screen, enters their login ID and password, and is authenticated.

[0241] Step 2:

[0242] Advertiser's terminal: After logging in, click the Create New Promotion Proposal button. Enter promotion information (product details, target demographic, campaign period, etc.).

[0243] Step 3:

[0244] Advertiser terminal: After all input is completed, click the send button to send the promotion proposal data to the server.

[0245] Step 4:

[0246] Server: Analyzes the received promotion proposal data and sends it to the generative AI model and emotion engine.

[0247] Step 5:

[0248] Generative AI model: Analyzes promotional proposal data and generates segment-optimized promotional proposals, taking into account the interests and preferences of target users.

[0249] Step 6:

[0250] Emotion engine: Analyzes input data about promotion ideas and extracts background emotional information (e.g., past reactions and reviews). Based on this, it creates emotional data and feeds it back to the generative AI model.

[0251] Step 7:

[0252] Generative AI model: Taking into account the received emotional data, it re-optimizes promotional suggestions, reflecting what advertising content will be most effective when the user is in a particular emotional state.

[0253] Step 8:

[0254] Server: Stores the optimized promotion proposal in a database and sends a confirmation to the advertiser.

[0255] Step 9:

[0256] Advertiser terminal: The advertiser checks the notification and reviews the optimized promotion plan on a dedicated management screen. They make any necessary adjustments and, after final confirmation, schedule the launch of the promotion.

[0257] Step 10:

[0258] User device: The user adds the LINE Official Account as a friend. Once the friend addition is complete, the user receives a notification that the friend addition is complete.

[0259] Step 11:

[0260] Server: Once the friend registration is confirmed, user profile data is generated and sent to the generative AI model.

[0261] Step 12:

[0262] Generative AI model: Analyzes user profile data to generate individually optimized promotion ideas and surveys. It also takes into account real-time emotional data from the emotion engine to generate surveys with optimal timing and content.

[0263] Step 13:

[0264] Server: Stores the generated optimized promotion proposals and surveys in a database and delivers them to users.

[0265] Step 14:

[0266] User device: The user receives a notification and answers the survey. Once the answers are complete, the user clicks the submit button to send the answers to the server.

[0267] Step 15:

[0268] Server: Receives the survey responses sent by users, stores them in a database, and verifies the responses.

[0269] Step 16:

[0270] Server: After the answer is verified, the server grants reward points to the user's account and sends a notification of the grant to the user's device.

[0271] Step 17:

[0272] User device: The user opens the LINE Wallet function and checks the points they have received. Points can be used for purchases and services within LINE.

[0273] Step 18:

[0274] Server: Records point usage history and updates user data.

[0275] Through the above processing steps, this system not only realizes effective and efficient ad delivery and reward allocation for both advertisers and users, but also enables even more personalized promotions by combining it with an emotion engine.

[0276] Example 2

[0277] 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."

[0278] In modern advertising, it is important for advertisers to efficiently deliver promotions that are optimized for specific target demographics. However, conventional systems have difficulty achieving detailed optimization based on individual user profiles, and are unable to deliver promotions that take user emotions into account. As a result, promotions are not as effective as they could be, making it difficult to achieve satisfactory results for both advertisers and users.

[0279] 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 a means for a company representative to register a promotion plan, a means for running a generative AI model to optimize the registered promotion plan, and a means for analyzing user emotion data using an emotion analysis engine and using the results to optimize the promotion. This enables more effective distribution of promotions to the target demographic.

[0280] "Company Representative" means the advertiser or marketing representative who is responsible for registering and managing promotion proposals.

[0281] A "promotion proposal" is a plan or proposal for promoting a product or service to consumers, and includes the content of the advertisement and a distribution schedule.

[0282] A "generative AI model" is a system that uses artificial intelligence to optimize promotional ideas, such as a text generation model or a machine learning algorithm.

[0283] An "emotion analysis engine" is software or algorithms for analyzing a user's emotions, and uses techniques such as facial expression analysis, voice analysis, and text analysis to understand the user's emotional state.

[0284] "User" refers to the consumer or customer who receives the promotion and responds to the survey.

[0285] A "survey" is a list of questions to gather user feedback, and is composed of multiple choice answers and free-form responses.

[0286] "Reward points" are incentives that users can receive by answering surveys, and can be used as electronic money or coupons, for example.

[0287] A "communication application account" is an account for a communication tool used on a smartphone or computer, which allows you to send and receive messages and add friends.

[0288] The present invention is a system that allows advertisers to register promotion proposals, delivers promotions optimized by a generative AI model and a sentiment analysis engine to users, and allows users to earn points by answering surveys. A specific embodiment of this system will be described.

[0289] System configuration

[0290] This system consists of an advertiser terminal, a user terminal, a server, a generative AI model, a sentiment analysis engine, and a database. The advertiser terminal and user terminal are general-purpose PCs or smartphones, and the server is located in a cloud environment.

[0291] Program processing explanation

[0292] Advertiser promotion proposal registration

[0293] Advertiser Device:

[0294] Advertisers log in to a dedicated management screen and register new promotion ideas, including product information, target demographics, and campaign start date.

[0295] For example, if you are registering a promotional proposal for a new shampoo product, you would enter "new shampoo" as the product information, "women in their 20s" as the target demographic, and "May 1, 2023" as the campaign start date.

[0296] Once registration is complete, the data is sent to the server.

[0297] Optimizing promotion ideas

[0298] server:

[0299] The server sends the received promotion proposal data to the generation AI model and sentiment analysis engine.

[0300] The generative AI model (e.g., GPT-3) generates an optimized promotion based on the received promotion proposal. The generative AI model is given a prompt like this:

[0301] Please optimize a shampoo campaign proposal aimed at women in their 20s.

[0302] The sentiment analysis engine analyzes user emotional data and feeds the results back into the generative AI model.

[0303] Sentiment analysis and promotion optimization

[0304] Sentiment Analysis Engine:

[0305] The sentiment analysis engine analyzes users' facial expressions, voice, and text data to recognize their emotions. For example, if a user responded positively to a previous promotion, it will provide positive feedback to the generative AI model.

[0306] The server receives the emotion data and sends it to the generative AI model.

[0307] Advertiser validation and delivery schedule setting

[0308] server:

[0309] An optimized promotion plan is generated and stored in a database.

[0310] Send the advertiser a confirmation of the optimized proposal.

[0311] Advertisers can check the optimization suggestions on the management screen, make any necessary adjustments, and then press the "Confirm" button to set the delivery schedule.

[0312] Promotion ideas and survey distribution

[0313] User device:

[0314] A user adds an official account of a communication application as a friend. Once the friend registration is complete, the user profile data (e.g., LINE ID, age, gender) is sent to the server.

[0315] The server sends user profile data to a generative AI model to generate individually optimized promotional ideas and surveys.

[0316] The server stores the optimized promotion proposals and corresponding questionnaires in a database and delivers them to users.

[0317] Answer surveys and receive reward points

[0318] User device:

[0319] The user answers the questionnaire and presses the send button, and the questionnaire response data is sent to the server.

[0320] server:

[0321] The server verifies the received survey responses and stores them in a database.

[0322] After verification, reward points will be awarded to the user and a notification will be sent.

[0323] User device:

[0324] Users can check their points in the wallet within the communication application and use them as electronic money, for example.

[0325] This embodiment allows advertisers to distribute effective promotions, and users can answer corresponding surveys and receive rewards. Furthermore, by using a sentiment analysis engine, optimization can be performed taking into account user sentiment data, further improving the effectiveness of promotions.

[0326] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0327] Step 1:

[0328] Advertiser promotion proposal registration

[0329] Advertiser Device:

[0330] Advertisers log in to a dedicated management screen and register new promotion proposals.

[0331] Input: Product information, target demographic, campaign start date, etc.

[0332] Data processing: These input data are organized into a single data package.

[0333] Output: Promotion proposal data sent to the server.

[0334] Specific actions: The advertiser enters product information for the "new shampoo," the target demographic of "women in their 20s," and "May 1, 2023" as the campaign start date, and clicks the submit button.

[0335] Step 2:

[0336] Optimizing promotion ideas

[0337] server:

[0338] The server sends the received promotion proposal data to the generation AI model and sentiment analysis engine.

[0339] Input: Promotion proposal data.

[0340] Data processing: Generate prompts to be passed to the generative AI model. For example, "Please optimize the shampoo campaign proposal for women in their 20s."

[0341] Output: Optimized promotion ideas returned by the generative AI model. Sentiment data feedback from the sentiment analysis engine.

[0342] Specific operation: The generative AI model optimizes promotional proposals, and the sentiment analysis engine analyzes user sentiment data and feeds the results back to the generative AI model.

[0343] Step 3:

[0344] Sentiment analysis and promotion optimization

[0345] Sentiment Analysis Engine:

[0346] The server uses an emotion analysis engine to analyze the user's facial expressions, voice, and text data.

[0347] Input: User facial expression, voice, and text data.

[0348] Data processing: Apply sentiment analysis algorithms to classify emotional states, e.g., "positive," "negative," etc.

[0349] Output: Send the analysis results to the generative AI model.

[0350] Specific behavior: For example, if a user shows a positive facial expression in response to a previous promotion, the reaction is classified as positive and fed back to the generative AI model.

[0351] Step 4:

[0352] Advertiser validation and delivery schedule setting

[0353] server:

[0354] Generate optimized promotion proposals, store them in the database, and send a confirmation to the advertiser.

[0355] Input: Optimized promotion ideas, sentiment data.

[0356] Data processing: Convert data into a format to be saved in the database. Generate a notification message to the advertiser.

[0357] Output: Database storage, advertiser notification.

[0358] Specific operation: The server stores the optimized promotion proposal in the database and sends a notification message to the advertiser requesting confirmation of the optimization proposal.

[0359] Step 5:

[0360] User's official account registration

[0361] User device:

[0362] A user adds the official account of a communication application as a friend.

[0363] Input: User's account information (e.g. LINE ID), age, gender.

[0364] Data processing: Assemble user profile data into a single data package.

[0365] Output: Sends user profile data to the server.

[0366] Specific operation: A user adds an official account of a communication application as a friend, and upon completion of the registration, the profile data is automatically sent to the server.

[0367] Step 6:

[0368] Analyzing user profile data

[0369] server:

[0370] The server sends the received user profile data to the generative AI model for analysis.

[0371] Input: User profile data.

[0372] Data processing: Generative AI models analyze profile data to generate individually optimized promotional ideas and surveys.

[0373] Output: Individually optimized promotion ideas, surveys.

[0374] Specific operation: Based on user profile data, the generative AI model automatically generates individually optimized promotion ideas and surveys.

[0375] Step 7:

[0376] Promotion ideas and survey distribution

[0377] server:

[0378] Optimized promotion ideas and surveys are stored in a database and distributed to users.

[0379] Input: individually optimized promotion ideas, surveys.

[0380] Data processing: storing data in a database and generating messages for delivery to users.

[0381] Output: User notification, database save.

[0382] Specific operation: The server stores the optimized promotion proposals and surveys in a database and delivers them to the user as messages.

[0383] Step 8:

[0384] User survey responses

[0385] User device:

[0386] The user answers the survey and presses the submit button.

[0387] Input: User's survey responses.

[0388] Data processing: Survey response data is sent to the server.

[0389] Output: Survey response data sent to the server.

[0390] Specific operation: The user answers the questionnaire and presses the send button to send the response data to the server.

[0391] Step 9:

[0392] Survey response verification and point awarding

[0393] server:

[0394] The server verifies the received survey responses and stores them in a database.

[0395] Input: User survey response data.

[0396] Data processing: Validating response data and storing it in a database.

[0397] Output: Reward points awarded to user and notification.

[0398] Specific operation: The server verifies the survey response data, stores it in the database, and then awards reward points to the user and sends a notification.

[0399] Step 10:

[0400] Check and use reward points

[0401] User device:

[0402] Users can check their points in the wallet within the communication application and use them as needed.

[0403] Input: Reward point award notification from the server.

[0404] Data processing: Update the points balance in the wallet.

[0405] Output: Point balance confirmation screen.

[0406] Specific operation: The user checks the reward points in the wallet and uses them as electronic money.

[0407] (Application example 2)

[0408] 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."

[0409] In conventional advertising systems, ad optimization was limited to the user's basic profile and behavioral data, and promotions did not reflect the user's emotional state. This limited the effectiveness of promotions. Also, while there were reward systems based on survey responses, these did not provide effective feedback to improve the user experience.

[0410] The specification processing by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes a means for a company representative to register promotion proposals, a means for operating a generative AI model to optimize the registered promotion proposals, a means for delivering the optimized promotion proposals to users, a means for receiving and verifying questionnaire responses from users, a means for awarding reward points to users, a means for operating an emotion engine that recognizes user emotions, and a means for feeding back emotion data to the generative AI model. This enables optimal promotions that reflect the user's emotional state and improves advertising effectiveness.

[0411] "Company Representative" means a member of an organization responsible for registering a Promotion Proposal.

[0412] "Promotion Proposal" means a plan that describes the implementation and content of an advertisement or campaign.

[0413] "Generative AI model" refers to an artificial intelligence algorithm that generates optimized promotional ideas based on input data.

[0414] "Optimized Promotion Ideas" means advertising or campaign content that is tailored based on user characteristics and emotional data using generative AI models.

[0415] "User" refers to a consumer who receives a company's promotion and completes a survey.

[0416] A "survey" is a form of survey that asks users questions related to a promotion proposal.

[0417] "Emotion Engine" refers to a software or hardware system that provides technology for analyzing a user's emotional state.

[0418] "Emotional data" refers to information about a user's emotional state analyzed based on facial expressions, voice, text, etc.

[0419] A "communication app" is an application that allows users to register friends and receive promotions and surveys.

[0420] This invention provides a mechanism for realizing a system that delivers optimized corporate promotional ideas to users and allows them to earn points by answering questionnaires. It also uses an emotion engine to recognize users' emotions and improve the effectiveness of promotions.

[0421] The system consists of an administration screen where company representatives can register promotion ideas, a generative AI model, an emotion engine, a server, and a user terminal.

[0422] Company personnel use the management screen to register promotion proposals. The management screen runs on a web browser and allows users to enter product information, target demographics, campaign start date, etc. This promotion proposal data is then sent to the server.

[0423] The server sends the received promotion proposal data to the generative AI model to generate optimized promotion proposals. The generative AI model generates promotions that are most effective for the target demographic and further optimizes them using feedback from the emotion engine.

[0424] The emotion engine recognizes emotions by analyzing the user's facial expressions, voice, and text data. This is done using the smartphone's camera and microphone, as well as generic services from Microsoft and Google. For example, by using the "Microsoft Azure Emotion API" or "Google Cloud Vision API," it is possible to analyze the user's emotional state in real time.

[0425] The optimized promotion ideas are managed by the server and sent to the communication app accounts of users who have registered them as friends. Users receive the promotion ideas and surveys through the app and then answer the surveys.

[0426] When a user answers a survey, the data is sent to the server. After the server verifies the received data, it grants reward points to the user. The user can view and use the reward points within the communication app.

[0427] As a concrete example, consider a situation where a new product campaign is being conducted. A company representative plans a sample campaign for the new product and registers the promotion proposal in a dedicated management screen. The following example can be considered.

[0428] Example prompt: (New product campaign) A free sample of our new shampoo is now available! Try this shampoo and answer a simple questionnaire to receive 500 points! These points can be used in the in-app store. Answer the questions and get points!

[0429] When a user receives this promotional information, their emotions are recognized from their facial expressions and voice, and a survey optimized for them is delivered. By answering the survey, they can earn reward points. In this way, promotions that reflect the user's emotional state can be optimally delivered.

[0430] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0431] Step 1:

[0432] Company personnel use the management screen to register promotion proposals, including product information, target demographics, and campaign start date. This data is then sent to the server.

[0433] Step 2:

[0434] The server analyzes the received promotion proposal data and sends it to the generative AI model, which processes the data to generate the most effective promotion proposal for the target demographic and outputs the optimized promotion proposal.

[0435] Step 3:

[0436] The emotion engine uses the smartphone's camera and microphone to analyze the user's facial expressions and voice, generating emotion data using, for example, the Microsoft Azure Emotion API or Google Cloud Vision API, and then sends the resulting emotion data to a server.

[0437] Step 4:

[0438] The server feeds back the emotion data received from the emotion engine to the generative AI model, which then further optimizes the promotion proposals.

[0439] Step 5:

[0440] The optimized promotion ideas are stored in a database by the server, which then distributes them to the communication app accounts that the user has registered as friends.

[0441] Step 6:

[0442] Users receive optimized promotional offers and surveys through the app, including promotional text (e.g., new shampoo samples are now available!) and survey questions.

[0443] Step 7:

[0444] When a user answers a questionnaire, the answer data is sent from the app to the server, which validates the input data and stores the validation results in a database.

[0445] Step 8:

[0446] The server will award reward points to the user based on the verified survey responses, which will be added to the user's reward account.

[0447] Step 9:

[0448] Users can check the points they have earned in their rewards account within the communication app and use them in in-app stores, etc.

[0449] 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.

[0450] 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.

[0451] 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.

[0452] [Second embodiment]

[0453] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0454] 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.

[0455] 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).

[0456] 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.

[0457] 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.

[0458] 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).

[0459] 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.

[0460] 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.

[0461] 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.

[0462] 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.

[0463] 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.

[0464] 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."

[0465] The present invention is a system that delivers optimized corporate promotional ideas to users and allows users to earn points by answering questionnaires. This system is highly convenient for both advertisers and users, and realizes effective advertising delivery.

[0466] System Overview

[0467] This system consists of an advertiser terminal, a user terminal, and a server. Advertisers register promotion proposals, and the server generates optimized promotions. Users register as friends on the LINE official account and receive individually optimized promotions and surveys. When users answer the survey, the server receives the answers and, after verification, awards reward points.

[0468] Program processing flow

[0469] 1. Advertiser terminal: Advertisers log in to a dedicated management screen and register new promotion proposals. The registered information includes product information, target demographic, distribution start date, etc. Once the promotion proposal is submitted, the data is sent to the server.

[0470] 2. Server: The server sends the promotion ideas it receives to the generative AI model, which analyzes and optimizes the content. The generative AI model then generates the most effective promotion for the target demographic and returns the information to the server.

[0471] 3. Server: Saves the optimized promotion proposal and sends a confirmation to the advertiser. The advertiser reviews the optimized proposal and makes any necessary adjustments. After final confirmation, the advertiser schedules the launch of distribution.

[0472] 4. User device: The user adds the LINE Official Account as a friend. Once the friend addition is complete, the user profile data is sent to the server.

[0473] 5. Generative AI model: Analyzes user profile data and generates individually optimized promotional ideas and surveys, taking into account the user's age, gender, past behavioral data, etc.

[0474] 6. Server: Sends the optimized promotion proposal and the corresponding survey to the user, who receives the notification and answers the survey.

[0475] 7. User terminal: When the user answers and submits the questionnaire, the data is sent to the server.

[0476] 8. Server: Validates the received survey responses and stores them in the database. After validation, reward points are awarded to the user.

[0477] 9. User device: Users can check their points in LINE Wallet and use them as needed. Points can be used for purchases within LINE.

[0478] Specific examples

[0479] Example 1: New Product Campaign

[0480] Advertisers plan a free sample campaign for a new product and register the promotion proposal on a dedicated management screen. The server sends the received promotion proposal to a generative AI model, which optimizes it for the target demographic. The optimized campaign proposal is generated, and the advertiser can review it and set the distribution schedule.

[0481] When a user adds a LINE official account as a friend, their profile data is sent to the server and analyzed by the generative AI model. A new product campaign information and a survey are sent to the user, who then answers the survey. The server receives and verifies the responses and awards the user 50 points. The user can view the reward points in their LINE Wallet and use them for purchases.

[0482] In this way, the system of the present invention provides benefits to both advertisers and users while realizing efficient advertisement distribution.

[0483] The processing flow will be explained below.

[0484] Step 1:

[0485] Advertiser terminal: The advertiser logs in to the dedicated management screen, enters login credentials, and accesses the system.

[0486] Step 2:

[0487] Advertiser terminal: Click the Create New Promotion Proposal button. Enter promotion information (product information, target demographic, campaign start date, etc.).

[0488] Step 3:

[0489] Advertiser terminal: After completing the input, click the send button to send the promotion proposal data to the server.

[0490] Step 4:

[0491] Server: Sends the received promotion proposal data to the generation AI model. The data is analyzed by AI and an optimized promotion proposal is generated.

[0492] Step 5:

[0493] Server: Stores the optimized promotion proposal in a database and sends a confirmation to the advertiser.

[0494] Step 6:

[0495] Advertiser terminal: The advertiser checks the notification and reviews the optimized promotion plan on a dedicated management screen, making fine adjustments as necessary and finalizing the plan.

[0496] Step 7:

[0497] Advertiser terminal: After final confirmation, schedule the start of distribution and click the approval button to send the final data to the server.

[0498] Step 8:

[0499] User device: The user adds the LINE Official Account as a friend. A notification is sent to the user confirming the friend addition.

[0500] Step 9:

[0501] Server: Once the friend registration is confirmed, generate user profile data and send it to the generative AI model.

[0502] Step 10:

[0503] Generative AI model: Analyzes user profile data and generates individually optimized promotional ideas and surveys.

[0504] Step 11:

[0505] Server: Stores the generated promotion ideas and questionnaires in a database and distributes them to users.

[0506] Step 12:

[0507] User device: The user receives the notification and answers the questionnaire. After completing the questionnaire, the user clicks the send button to send the answers to the server.

[0508] Step 13:

[0509] Server: Receives the survey responses sent by users, stores them in a database, and verifies the responses.

[0510] Step 14:

[0511] Server: Once verification is complete, it will credit the reward points to the user's account and send a notification to the user's device.

[0512] Step 15:

[0513] User device: The user opens the LINE Wallet function, checks the points awarded, and uses them to purchase goods and services.

[0514] Step 16:

[0515] Server: Records point usage history and updates user data.

[0516] Through the above processing steps, this system realizes effective and efficient ad delivery and reward provision for both advertisers and users.

[0517] Example 1

[0518] 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."

[0519] Conventional ad delivery systems do not optimize based on detailed user profile data, resulting in poor advertising effectiveness. Furthermore, the lack of an incentive system to encourage users to respond positively to ads presents a challenge, resulting in low ad acceptance. As a result, efficient and effective ad delivery has not been achieved for both advertisers and users.

[0520] 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.

[0521] In this invention, the server includes a means for a company representative to register promotion plans, a means for operating a generation AI model to optimize the registered promotion plans, a means for sending user profile data to the generation AI model and generating individual promotion plans and questionnaires optimized for the target demographic, a means for delivering the optimized promotion plans and questionnaires to users, a means for receiving and verifying questionnaire responses from users, and a means for awarding reward points to users. This enables optimization of promotion plans and individual responses to each user, resulting in high advertising effectiveness and improved user incentives.

[0522] "Company Representative" means a person within a company who is responsible for managing and registering promotion proposals.

[0523] "Promotion Ideas" refers to information about plans and strategies for promoting products and services.

[0524] "Generative AI models" are algorithms and systems that use artificial intelligence to analyze data and generate optimized promotional ideas based on specified criteria.

[0525] "User profile data" refers to information relating to an individual, such as the user's age, gender, location, and past behavioral history.

[0526] A "survey" is a method of asking specific questions to users and collecting their responses.

[0527] "Reward points" are points that users receive as an incentive for certain actions in the system.

[0528] A "communications application" is a software application that a user uses to exchange information with a server.

[0529] "Target demographic" refers to a specific group of users targeted for promotion.

[0530] "Delivery means" refers to the methods and techniques used to deliver promotional ideas and surveys to users.

[0531] "Verification measures" are methods or techniques for verifying the accuracy of survey responses from users.

[0532] This invention is a system that delivers optimized corporate promotional ideas to users and allows users to earn reward points by answering questionnaires. This system is composed of a server, a user terminal, and an advertiser terminal. The roles and detailed operations of each are explained below.

[0533] server

[0534] The server sends the received promotion proposals to the generative AI model and generates optimized promotion proposals. Specifically, it analyzes the promotion proposals sent from the advertiser's device and generates promotion proposals optimized for the target demographic using a prompt for the generative AI model. The generative AI model uses the prompt, "Please optimize this promotion proposal for the target demographic." After receiving the optimized promotion proposal, the server stores it in a database and notifies the advertiser. The server also analyzes the received user profile data and generates individually optimized promotion proposals and questionnaires, taking into account the user's age, gender, past behavioral data, etc.

[0535] Advertiser terminal

[0536] The advertiser terminal provides a dedicated management screen and a means for advertisers to register new promotion proposals. The advertiser enters information such as product information, target demographic, and distribution start date, and sends the promotion proposal to the server. After the optimized promotion proposal is notified by the server, the advertiser can review it, make adjustments as necessary, and set the final distribution schedule.

[0537] User Device

[0538] The user's device is primarily used by the user to add the LINE Official Account as a friend. Once friend addition is complete, the user's profile data is sent to the server. Optimized promotion ideas and surveys are then sent to the user, who receives a notification and answers the survey. Once the answers are sent to the server and verified, the user receives reward points, which can be viewed and used in the LINE Wallet.

[0539] Specific examples

[0540] Example 1: New Product Campaign

[0541] The advertiser plans a free sample campaign for a new product and registers the promotion plan on a dedicated management screen. The server sends the received promotion plan to the generation AI model, which optimizes it for the target demographic. The optimized campaign plan is generated, and the advertiser confirms it and sets the distribution schedule. When a user adds the LINE official account as a friend, their profile data is sent to the server and analyzed by the generation AI model. Information about the new product campaign and a survey are sent to the user, who then answers the survey. The server receives and verifies the responses and awards the user 50 points. The user can check the reward points in their LINE Wallet and use them for purchases.

[0542] Prompt Sentence Examples

[0543] "Please optimize this promotional idea for the target demographic."

[0544] "Optimize a new product campaign aimed at women in their 20s"

[0545] "Generate promotion ideas for male users in their 30s."

[0546] This system will enable effective and efficient ad delivery for both advertisers and users.

[0547] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0548] Step 1:

[0549] Advertiser registration of promotion proposals

[0550] Input: Receive promotional proposal data such as product information, target demographic, and distribution start date from the advertiser's terminal.

[0551] How it works: Advertisers log in to the dedicated management screen, enter each item, and press the "Submit" button to register their promotion proposal.

[0552] Output: The registered promotion proposal data is sent to the server.

[0553] Step 2:

[0554] Optimizing promotion ideas

[0555] Input: Promotion proposal data sent to the server.

[0556] Operation: The server sends the received promotion proposal to the generative AI model and instructs the generative AI model to analyze it using the prompt "Please optimize this promotion proposal for the target demographic."

[0557] Output: The optimized promotion proposal data is sent back to the server from the generative AI model.

[0558] Step 3:

[0559] Checking optimization recommendations and setting delivery schedules

[0560] Input: Optimized promotion proposal data.

[0561] Operation: The server sends the optimized promotion proposal to the advertiser's terminal and sends a confirmation notice to the advertiser. The advertiser checks the optimization proposal, makes any necessary adjustments, and presses the "Final Confirm" button to schedule the distribution.

[0562] Output: The finalized promotion plan and distribution schedule data are saved on the server.

[0563] Step 4:

[0564] Users adding LINE Official Accounts as friends

[0565] Input: A user adds a LINE Official Account as a friend.

[0566] How it works: A user opens the LINE application and adds the official account as a friend. Once the friend registration is complete, the information is sent to the server.

[0567] Output: User profile data (age, gender, region, etc.) is sent to the server.

[0568] Step 5:

[0569] Generate personalized promotion ideas and surveys

[0570] Input: User profile data.

[0571] How it works: The server sends user profile data to the generative AI model and directs its analysis using the prompt "Generate promotion ideas and surveys optimized for each target demographic."

[0572] Output: The generative AI model sends individually optimized promotion ideas and survey data back to the server.

[0573] Step 6:

[0574] Promotion ideas and survey distribution

[0575] Input: Individually optimized promotion ideas and survey data.

[0576] How it works: The server sends the optimized promotion proposal and survey to the user's device. The user receives a notification and answers the survey.

[0577] Output: The user's survey response data is sent to the server.

[0578] Step 7:

[0579] Receiving and verifying survey responses

[0580] Input: User survey response data.

[0581] Operation: The server validates the received survey response data to ensure accuracy.

[0582] Output: The verified survey response data is stored in a database.

[0583] Step 8:

[0584] Awarding reward points

[0585] Input: Validated survey response data.

[0586] Operation: The server processes the reward points to the user based on the survey responses.

[0587] Output: Reward points are reflected in the user's LINE Wallet.

[0588] Step 9:

[0589] Checking and using points

[0590] Input: Reward points awarded.

[0591] How it works: Users can view reward points in LINE Wallet and use them for purchases within LINE as needed.

[0592] Output: A record of the user's reward points usage is kept.

[0593] In this way, the system realizes effective and personalized promotions for both advertisers and users.

[0594] (Application example 1)

[0595] 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."

[0596] In today's advertising market, companies want to run effective promotions, but they face the challenge of delivering advertisements in an optimal way to target users. Furthermore, users often receive promotions and surveys that they are not interested in, which can lead to a decline in engagement. The objective of this invention is to provide a promotion delivery system that efficiently optimizes companies' promotion proposals and is both attractive and convenient for users.

[0597] 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.

[0598] In this invention, the server includes: means for a company representative to register promotion proposals; means for operating a generative AI model to optimize the registered promotion proposals; means for delivering the optimized promotion proposals to users; means including a smartphone application to be installed on the user's device; means for receiving and verifying survey responses from users; means for awarding reward points to users; and means for users to receive and answer promotion proposals and surveys via the application installed on their smartphones. This enables companies to efficiently deliver optimal promotions to target users, and enables users to actively participate in promotional content that interests them and earn rewards.

[0599] A "promotion proposal" refers to the plan and content for effectively communicating information about the products and services offered by a company to users.

[0600] "Generative AI model" refers to an artificial intelligence algorithm or system used to optimize promotional ideas.

[0601] "Optimization" means adjusting and improving the content of a promotional proposal to achieve the most effective results for a specific purpose.

[0602] "User" refers to the consumer or user who receives and responds to the promotion proposal and survey.

[0603] "Survey" refers to a survey in the form of questions to collect opinions and information from users.

[0604] "Reward points" are points that users can earn by answering surveys and can later be exchanged for specific services or products.

[0605] "Server" means the computer system that receives, analyzes, optimizes, and delivers Promotional Ideas.

[0606] "Smartphone Application" refers to software installed on a User's smartphone to receive promotional offers and surveys.

[0607] An "official account for a communication application" refers to an official communication channel operated by a company or organization that allows direct interaction with users.

[0608] The present invention is a system that allows advertisers to register promotion proposals, optimize those proposals, and deliver them to users. Users can earn reward points by answering surveys, and operate the system through a smartphone application.

[0609] System Overview

[0610] The server provides a management screen for company personnel to register promotion proposals. This management screen includes an interface for advertisers to enter details such as product information, target demographics, and distribution start date. The data entered by the advertiser is sent to the server, where the promotion proposal is analyzed and optimized by the generative AI model.

[0611] The server uses the generative AI model to optimize promotion ideas and send them to target users. Users receive promotion ideas and surveys through a dedicated application installed on their smartphones. This application works by users adding the official account of the communication application as a friend.

[0612] Overview of program processing

[0613] The server does the following:

[0614] 1. The advertiser registers a promotion proposal via the management screen.

[0615] 2. The registered promotion proposals are sent to the generation AI model to generate optimized promotion proposals.

[0616] 3. Deliver optimized promotional ideas to the user's smartphone application.

[0617] The smartphone application installed on the user's device performs the following operations:

[0618] 1. Add the official account of the communication application as a friend.

[0619] 2. Display promotion proposals and surveys received from the server.

[0620] 3. The user answers the survey and sends the answers to the server.

[0621] The server receives the survey responses from the user and performs the following actions:

[0622] 1. Verify the contents of the survey responses.

[0623] 2. Give reward points to users after verification.

[0624] 3. Save as a user report.

[0625] Hardware and software used

[0626] The hardware required includes a server, the user's smartphone, and the official account of the communication application. The software required includes an administration screen, a generative AI model, and a smartphone application. Specific examples include an application developed in Python, the LINE API, and a generative AI model.

[0627] Specific examples

[0628] For example, if Company A wants to run a free sample campaign for a new product, it enters a promotion idea into the admin screen. The server optimizes this information using a generative AI model and distributes it to target users. Users receive the promotion idea and a survey through a smartphone application, and by answering the survey, they can earn reward points. These points can be viewed and used in the user's LINE Wallet.

[0629] Prompt Sentence Examples

[0630] "Use a generative AI model to optimize promotional ideas for cosmetics for women in their 30s. Generate optimal promotional ideas and questionnaires based on behavioral data of the target demographic."

[0631] As described above, the present invention is a system that realizes efficient advertisement distribution while providing benefits to both advertisers and users.

[0632] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0633] Step 1:

[0634] The advertiser enters the promotion proposal into the management screen. The management screen provides an interface for entering details such as product information, target demographic, and distribution start date. After input, the promotion proposal is sent to the server. Input: Detailed data of the promotion proposal. Output: Promotion proposal data sent to the server.

[0635] Step 2:

[0636] The server sends the received promotion proposal to the generative AI model, which analyzes the promotion proposal and generates a promotion optimized for the target demographic. Input: Promotion proposal data. Output: Optimized promotion proposal.

[0637] Step 3:

[0638] The server receives the optimized promotion offer and delivers it to the user's smartphone application. Input: Optimized promotion offer. Output: Promotion offer sent to the user's smartphone application.

[0639] Step 4:

[0640] The user opens the application installed on their smartphone. The application adds the official account of the communication application as a friend and displays the promotion proposals and surveys received from the server. Input: Promotion proposals and surveys received from the server. Output: Displayed promotion proposals and surveys.

[0641] Step 5:

[0642] Users answer the survey and send their answers to the server via a smartphone application. Input: User's survey response data. Output: Survey response data sent to the server.

[0643] Step 6:

[0644] The server receives the survey responses from the user and verifies the responses. Once the verification is complete, reward points are awarded to the user. Input: User's survey response data. Output: Verified data and reward points.

[0645] Step 7:

[0646] The server stores the survey results as a user report. Input: Survey data after validation. Output: Stored survey result report.

[0647] 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.

[0648] This invention is a system that optimizes corporate promotional ideas for users and delivers them to them, allows users to earn points by answering questionnaires, and improves the effectiveness of promotions by using an emotion engine that recognizes users' emotions. This system is highly convenient for both advertisers and users, and realizes effective advertising delivery.

[0649] System Overview

[0650] The system consists of an advertiser terminal, a user terminal, a server, and an emotion engine. Advertisers register promotion proposals, and the server generates optimized promotions. Users add the LINE official account as a friend and receive individually optimized promotions and surveys. When users answer the survey, the server receives the answers and awards reward points after verification. The emotion engine then analyzes the user's emotions and optimizes the promotion proposals based on this information.

[0651] Program processing flow

[0652] 1. Advertiser terminal: Advertisers log in to a dedicated management screen and register new promotion proposals. The registered information includes product information, target demographics, campaign start date, etc. Once the promotion proposal is submitted, the data is sent to the server.

[0653] 2. Server: The server sends the received promotion proposal data to the generation AI model and emotion engine for content analysis and optimization. The generation AI model generates the most effective promotion for the target demographic, and the emotion engine analyzes user emotion data and feeds that information back to the generation AI model.

[0654] 3. Server: Generates an optimized promotion proposal and stores it in the database. Sends a confirmation to the advertiser, who can review the proposal and make any necessary adjustments. After final confirmation, schedules the launch of distribution.

[0655] 4. User device: The user adds the LINE Official Account as a friend. Once the friend addition is complete, the user profile data is sent to the server.

[0656] 5. Generative AI model: Analyzes user profile data and generates individually optimized promotional ideas and surveys, taking into account the user's age, gender, past behavioral data, etc.

[0657] 6. Emotion Engine: Analyzes user facial expressions, voice, and text data to recognize emotions and send the results to the generative AI model, which then uses this information to further optimize promotion ideas and surveys.

[0658] 7. Server: The optimized promotion proposals and corresponding questionnaires are stored in the database and sent to users, who then receive notifications and answer the questionnaires.

[0659] 8. User terminal: When the user answers and submits the questionnaire, the data is sent to the server.

[0660] 9. Server: Validates the received survey responses and stores them in the database. After validation, reward points are awarded to the user.

[0661] 10. User device: Users can check their points in LINE Wallet and use them as needed. Points can be used for purchases within LINE.

[0662] Specific examples

[0663] Example 1: New Product Campaign

[0664] Advertisers plan a free sample campaign for a new product and register the promotion proposal on a dedicated management screen. The server sends the received promotion proposal to a generative AI model, which optimizes it for the target demographic. An optimized campaign proposal is generated, and the emotion engine also takes user emotional data into account. The advertiser confirms the proposal and sets the distribution schedule.

[0665] When a user adds a LINE official account as a friend, their profile data and emotion data are sent to the server and analyzed by the generative AI model. A new product campaign information and a survey are sent to the user, who then answers the survey. The server receives and verifies the responses and awards the user 50 points. The user can check the reward points in their LINE Wallet and use them for purchases.

[0666] In this way, the system of the present invention provides benefits to both advertisers and users while realizing efficient advertisement distribution. By combining it with an emotion engine, even more effective promotions become possible.

[0667] The processing flow will be explained below.

[0668] Step 1:

[0669] Advertiser terminal: The advertiser logs in to the dedicated management screen, enters their login ID and password, and is authenticated.

[0670] Step 2:

[0671] Advertiser's terminal: After logging in, click the Create New Promotion Proposal button. Enter promotion information (product details, target demographic, campaign period, etc.).

[0672] Step 3:

[0673] Advertiser terminal: After all input is completed, click the send button to send the promotion proposal data to the server.

[0674] Step 4:

[0675] Server: Analyzes the received promotion proposal data and sends it to the generative AI model and emotion engine.

[0676] Step 5:

[0677] Generative AI model: Analyzes promotional proposal data and generates segment-optimized promotional proposals, taking into account the interests and preferences of target users.

[0678] Step 6:

[0679] Emotion engine: Analyzes input data about promotion ideas and extracts background emotional information (e.g., past reactions and reviews). Based on this, it creates emotional data and feeds it back to the generative AI model.

[0680] Step 7:

[0681] Generative AI model: Taking into account the received emotional data, it re-optimizes promotional suggestions, reflecting what advertising content will be most effective when the user is in a particular emotional state.

[0682] Step 8:

[0683] Server: Stores the optimized promotion proposal in a database and sends a confirmation to the advertiser.

[0684] Step 9:

[0685] Advertiser terminal: The advertiser checks the notification and reviews the optimized promotion plan on a dedicated management screen. They make any necessary adjustments and, after final confirmation, schedule the launch of the promotion.

[0686] Step 10:

[0687] User device: The user adds the LINE Official Account as a friend. Once the friend addition is complete, the user receives a notification that the friend addition is complete.

[0688] Step 11:

[0689] Server: Once the friend registration is confirmed, user profile data is generated and sent to the generative AI model.

[0690] Step 12:

[0691] Generative AI model: Analyzes user profile data to generate individually optimized promotion ideas and surveys. It also takes into account real-time emotional data from the emotion engine to generate surveys with optimal timing and content.

[0692] Step 13:

[0693] Server: Stores the generated optimized promotion proposals and surveys in a database and delivers them to users.

[0694] Step 14:

[0695] User device: The user receives a notification and answers the survey. Once the answers are complete, the user clicks the submit button to send the answers to the server.

[0696] Step 15:

[0697] Server: Receives the survey responses sent by users, stores them in a database, and verifies the responses.

[0698] Step 16:

[0699] Server: After the answer is verified, the server grants reward points to the user's account and sends a notification of the grant to the user's device.

[0700] Step 17:

[0701] User device: The user opens the LINE Wallet function and checks the points they have received. Points can be used for purchases and services within LINE.

[0702] Step 18:

[0703] Server: Records point usage history and updates user data.

[0704] Through the above processing steps, this system not only realizes effective and efficient ad delivery and reward allocation for both advertisers and users, but also enables even more personalized promotions by combining it with an emotion engine.

[0705] Example 2

[0706] 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."

[0707] In modern advertising, it is important for advertisers to efficiently deliver promotions that are optimized for specific target demographics. However, conventional systems have difficulty achieving detailed optimization based on individual user profiles, and are unable to deliver promotions that take user emotions into account. As a result, promotions are not as effective as they could be, making it difficult to achieve satisfactory results for both advertisers and users.

[0708] 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 a means for a company representative to register a promotion plan, a means for running a generative AI model to optimize the registered promotion plan, and a means for analyzing user emotion data using an emotion analysis engine and using the results to optimize the promotion. This enables more effective distribution of promotions to the target demographic.

[0709] "Company Representative" means the advertiser or marketing representative who is responsible for registering and managing promotion proposals.

[0710] A "promotion proposal" is a plan or proposal for promoting a product or service to consumers, and includes the content of the advertisement and a distribution schedule.

[0711] A "generative AI model" is a system that uses artificial intelligence to optimize promotional ideas, such as a text generation model or a machine learning algorithm.

[0712] An "emotion analysis engine" is software or algorithms for analyzing a user's emotions, and uses techniques such as facial expression analysis, voice analysis, and text analysis to understand the user's emotional state.

[0713] "User" refers to the consumer or customer who receives the promotion and responds to the survey.

[0714] A "survey" is a list of questions to gather user feedback, and is composed of multiple choice answers and free-form responses.

[0715] "Reward points" are incentives that users can receive by answering surveys, and can be used as electronic money or coupons, for example.

[0716] A "communication application account" is an account for a communication tool used on a smartphone or computer, which allows you to send and receive messages and add friends.

[0717] The present invention is a system that allows advertisers to register promotion proposals, delivers promotions optimized by a generative AI model and a sentiment analysis engine to users, and allows users to earn points by answering surveys. A specific embodiment of this system will be described.

[0718] System configuration

[0719] This system consists of an advertiser terminal, a user terminal, a server, a generative AI model, a sentiment analysis engine, and a database. The advertiser terminal and user terminal are general-purpose PCs or smartphones, and the server is located in a cloud environment.

[0720] Program processing explanation

[0721] Advertiser promotion proposal registration

[0722] Advertiser Device:

[0723] Advertisers log in to a dedicated management screen and register new promotion ideas, including product information, target demographics, and campaign start date.

[0724] For example, if you are registering a promotional proposal for a new shampoo product, you would enter "new shampoo" as the product information, "women in their 20s" as the target demographic, and "May 1, 2023" as the campaign start date.

[0725] Once registration is complete, the data is sent to the server.

[0726] Optimizing promotion ideas

[0727] server:

[0728] The server sends the received promotion proposal data to the generation AI model and sentiment analysis engine.

[0729] The generative AI model (e.g., GPT-3) generates an optimized promotion based on the received promotion proposal. The generative AI model is given a prompt like this:

[0730] Please optimize a shampoo campaign proposal aimed at women in their 20s.

[0731] The sentiment analysis engine analyzes user emotional data and feeds the results back into the generative AI model.

[0732] Sentiment analysis and promotion optimization

[0733] Sentiment Analysis Engine:

[0734] The sentiment analysis engine analyzes users' facial expressions, voice, and text data to recognize their emotions. For example, if a user responded positively to a previous promotion, it will provide positive feedback to the generative AI model.

[0735] The server receives the emotion data and sends it to the generative AI model.

[0736] Advertiser validation and delivery schedule setting

[0737] server:

[0738] An optimized promotion plan is generated and stored in a database.

[0739] Send the advertiser a confirmation of the optimized proposal.

[0740] Advertisers can check the optimization suggestions on the management screen, make any necessary adjustments, and then press the "Confirm" button to set the delivery schedule.

[0741] Promotion ideas and survey distribution

[0742] User device:

[0743] A user adds an official account of a communication application as a friend. Once the friend registration is complete, the user profile data (e.g., LINE ID, age, gender) is sent to the server.

[0744] The server sends user profile data to a generative AI model to generate individually optimized promotional ideas and surveys.

[0745] The server stores the optimized promotion proposals and corresponding questionnaires in a database and delivers them to users.

[0746] Answer surveys and receive reward points

[0747] User device:

[0748] The user answers the questionnaire and presses the send button, and the questionnaire response data is sent to the server.

[0749] server:

[0750] The server verifies the received survey responses and stores them in a database.

[0751] After verification, reward points will be awarded to the user and a notification will be sent.

[0752] User device:

[0753] Users can check their points in the wallet within the communication application and use them as electronic money, for example.

[0754] This embodiment allows advertisers to distribute effective promotions, and users can answer corresponding surveys and receive rewards. Furthermore, by using a sentiment analysis engine, optimization can be performed taking into account user sentiment data, further improving the effectiveness of promotions.

[0755] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0756] Step 1:

[0757] Advertiser promotion proposal registration

[0758] Advertiser Device:

[0759] Advertisers log in to a dedicated management screen and register new promotion proposals.

[0760] Input: Product information, target demographic, campaign start date, etc.

[0761] Data processing: These input data are organized into a single data package.

[0762] Output: Promotion proposal data sent to the server.

[0763] Specific actions: The advertiser enters product information for the "new shampoo," the target demographic of "women in their 20s," and "May 1, 2023" as the campaign start date, and clicks the submit button.

[0764] Step 2:

[0765] Optimizing promotion ideas

[0766] server:

[0767] The server sends the received promotion proposal data to the generation AI model and sentiment analysis engine.

[0768] Input: Promotion proposal data.

[0769] Data processing: Generate prompts to be passed to the generative AI model. For example, "Please optimize the shampoo campaign proposal for women in their 20s."

[0770] Output: Optimized promotion ideas returned by the generative AI model. Sentiment data feedback from the sentiment analysis engine.

[0771] Specific operation: The generative AI model optimizes promotional proposals, and the sentiment analysis engine analyzes user sentiment data and feeds the results back to the generative AI model.

[0772] Step 3:

[0773] Sentiment analysis and promotion optimization

[0774] Sentiment Analysis Engine:

[0775] The server uses an emotion analysis engine to analyze the user's facial expressions, voice, and text data.

[0776] Input: User facial expression, voice, and text data.

[0777] Data processing: Apply sentiment analysis algorithms to classify emotional states, e.g., "positive," "negative," etc.

[0778] Output: Send the analysis results to the generative AI model.

[0779] Specific behavior: For example, if a user shows a positive facial expression in response to a previous promotion, the reaction is classified as positive and fed back to the generative AI model.

[0780] Step 4:

[0781] Advertiser validation and delivery schedule setting

[0782] server:

[0783] Generate optimized promotion proposals, store them in the database, and send a confirmation to the advertiser.

[0784] Input: Optimized promotion ideas, sentiment data.

[0785] Data processing: Convert data into a format to be saved in the database. Generate a notification message to the advertiser.

[0786] Output: Database storage, advertiser notification.

[0787] Specific operation: The server stores the optimized promotion proposal in the database and sends a notification message to the advertiser requesting confirmation of the optimization proposal.

[0788] Step 5:

[0789] User's official account registration

[0790] User device:

[0791] A user adds the official account of a communication application as a friend.

[0792] Input: User's account information (e.g. LINE ID), age, gender.

[0793] Data processing: Assemble user profile data into a single data package.

[0794] Output: Sends user profile data to the server.

[0795] Specific operation: A user adds an official account of a communication application as a friend, and upon completion of the registration, the profile data is automatically sent to the server.

[0796] Step 6:

[0797] Analyzing user profile data

[0798] server:

[0799] The server sends the received user profile data to the generative AI model for analysis.

[0800] Input: User profile data.

[0801] Data processing: Generative AI models analyze profile data to generate individually optimized promotional ideas and surveys.

[0802] Output: Individually optimized promotion ideas, surveys.

[0803] Specific operation: Based on user profile data, the generative AI model automatically generates individually optimized promotion ideas and surveys.

[0804] Step 7:

[0805] Promotion ideas and survey distribution

[0806] server:

[0807] Optimized promotion ideas and surveys are stored in a database and distributed to users.

[0808] Input: individually optimized promotion ideas, surveys.

[0809] Data processing: storing data in a database and generating messages for delivery to users.

[0810] Output: User notification, database save.

[0811] Specific operation: The server stores the optimized promotion proposals and surveys in a database and delivers them to the user as messages.

[0812] Step 8:

[0813] User survey responses

[0814] User device:

[0815] The user answers the survey and presses the submit button.

[0816] Input: User's survey responses.

[0817] Data processing: Survey response data is sent to the server.

[0818] Output: Survey response data sent to the server.

[0819] Specific operation: The user answers the questionnaire and presses the send button to send the response data to the server.

[0820] Step 9:

[0821] Survey response verification and point awarding

[0822] server:

[0823] The server verifies the received survey responses and stores them in a database.

[0824] Input: User survey response data.

[0825] Data processing: Validating response data and storing it in a database.

[0826] Output: Reward points awarded to user and notification.

[0827] Specific operation: The server verifies the survey response data, stores it in the database, and then awards reward points to the user and sends a notification.

[0828] Step 10:

[0829] Check and use reward points

[0830] User device:

[0831] Users can check their points in the wallet within the communication application and use them as needed.

[0832] Input: Reward point award notification from the server.

[0833] Data processing: Update the points balance in the wallet.

[0834] Output: Point balance confirmation screen.

[0835] Specific operation: The user checks the reward points in the wallet and uses them as electronic money.

[0836] (Application example 2)

[0837] 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."

[0838] In conventional advertising systems, ad optimization was limited to the user's basic profile and behavioral data, and promotions did not reflect the user's emotional state. This limited the effectiveness of promotions. Also, while there were reward systems based on survey responses, these did not provide effective feedback to improve the user experience.

[0839] The specification processing by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes a means for a company representative to register promotion proposals, a means for operating a generative AI model to optimize the registered promotion proposals, a means for delivering the optimized promotion proposals to users, a means for receiving and verifying questionnaire responses from users, a means for awarding reward points to users, a means for operating an emotion engine that recognizes user emotions, and a means for feeding back emotion data to the generative AI model. This enables optimal promotions that reflect the user's emotional state and improves advertising effectiveness.

[0840] "Company Representative" means a member of an organization responsible for registering a Promotion Proposal.

[0841] "Promotion Proposal" means a plan that describes the implementation and content of an advertisement or campaign.

[0842] "Generative AI model" refers to an artificial intelligence algorithm that generates optimized promotional ideas based on input data.

[0843] "Optimized Promotion Ideas" means advertising or campaign content that is tailored based on user characteristics and emotional data using generative AI models.

[0844] "User" refers to a consumer who receives a company's promotion and completes a survey.

[0845] A "survey" is a form of survey that asks users questions related to a promotion proposal.

[0846] "Emotion Engine" refers to a software or hardware system that provides technology for analyzing a user's emotional state.

[0847] "Emotional data" refers to information about a user's emotional state analyzed based on facial expressions, voice, text, etc.

[0848] A "communication app" is an application that allows users to register friends and receive promotions and surveys.

[0849] This invention provides a mechanism for realizing a system that delivers optimized corporate promotional ideas to users and allows them to earn points by answering questionnaires. It also uses an emotion engine to recognize users' emotions and improve the effectiveness of promotions.

[0850] The system consists of an administration screen where company representatives can register promotion ideas, a generative AI model, an emotion engine, a server, and a user terminal.

[0851] Company personnel use the management screen to register promotion proposals. The management screen runs on a web browser and allows users to enter product information, target demographics, campaign start date, etc. This promotion proposal data is then sent to the server.

[0852] The server sends the received promotion proposal data to the generative AI model to generate optimized promotion proposals. The generative AI model generates promotions that are most effective for the target demographic and further optimizes them using feedback from the emotion engine.

[0853] The emotion engine recognizes emotions by analyzing the user's facial expressions, voice, and text data. This is done using the smartphone's camera and microphone, as well as generic services from Microsoft and Google. For example, by using the "Microsoft Azure Emotion API" or "Google Cloud Vision API," it is possible to analyze the user's emotional state in real time.

[0854] The optimized promotion ideas are managed by the server and sent to the communication app accounts of users who have registered them as friends. Users receive the promotion ideas and surveys through the app and then answer the surveys.

[0855] When a user answers a survey, the data is sent to the server. After the server verifies the received data, it grants reward points to the user. The user can view and use the reward points within the communication app.

[0856] As a concrete example, consider a situation where a new product campaign is being conducted. A company representative plans a sample campaign for the new product and registers the promotion proposal in a dedicated management screen. The following example can be considered.

[0857] Example prompt: (New product campaign) A free sample of our new shampoo is now available! Try this shampoo and answer a simple questionnaire to receive 500 points! These points can be used in the in-app store. Answer the questions and get points!

[0858] When a user receives this promotional information, their emotions are recognized from their facial expressions and voice, and a survey optimized for them is delivered. By answering the survey, they can earn reward points. In this way, promotions that reflect the user's emotional state can be optimally delivered.

[0859] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0860] Step 1:

[0861] Company personnel use the management screen to register promotion proposals, including product information, target demographics, and campaign start date. This data is then sent to the server.

[0862] Step 2:

[0863] The server analyzes the received promotion proposal data and sends it to the generative AI model, which processes the data to generate the most effective promotion proposal for the target demographic and outputs the optimized promotion proposal.

[0864] Step 3:

[0865] The emotion engine uses the smartphone's camera and microphone to analyze the user's facial expressions and voice, generating emotion data using, for example, the Microsoft Azure Emotion API or Google Cloud Vision API, and then sends the resulting emotion data to a server.

[0866] Step 4:

[0867] The server feeds back the emotion data received from the emotion engine to the generative AI model, which then further optimizes the promotion proposals.

[0868] Step 5:

[0869] The optimized promotion ideas are stored in a database by the server, which then distributes them to the communication app accounts that the user has registered as friends.

[0870] Step 6:

[0871] Users receive optimized promotional offers and surveys through the app, including promotional text (e.g., new shampoo samples are now available!) and survey questions.

[0872] Step 7:

[0873] When a user answers a questionnaire, the answer data is sent from the app to the server, which validates the input data and stores the validation results in a database.

[0874] Step 8:

[0875] The server will award reward points to the user based on the verified survey responses, which will be added to the user's reward account.

[0876] Step 9:

[0877] Users can check the points they have earned in their rewards account within the communication app and use them in in-app stores, etc.

[0878] 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.

[0879] 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.

[0880] 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.

[0881] [Third embodiment]

[0882] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0883] 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.

[0884] 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).

[0885] 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.

[0886] 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.

[0887] 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).

[0888] 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.

[0889] 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.

[0890] 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.

[0891] 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.

[0892] 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.

[0893] 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."

[0894] The present invention is a system that delivers optimized corporate promotional ideas to users and allows users to earn points by answering questionnaires. This system is highly convenient for both advertisers and users, and realizes effective advertising delivery.

[0895] System Overview

[0896] This system consists of an advertiser terminal, a user terminal, and a server. Advertisers register promotion proposals, and the server generates optimized promotions. Users register as friends on the LINE official account and receive individually optimized promotions and surveys. When users answer the survey, the server receives the answers and, after verification, awards reward points.

[0897] Program processing flow

[0898] 1. Advertiser terminal: Advertisers log in to a dedicated management screen and register new promotion proposals. The registered information includes product information, target demographic, distribution start date, etc. Once the promotion proposal is submitted, the data is sent to the server.

[0899] 2. Server: The server sends the promotion ideas it receives to the generative AI model, which analyzes and optimizes the content. The generative AI model then generates the most effective promotion for the target demographic and returns the information to the server.

[0900] 3. Server: Saves the optimized promotion proposal and sends a confirmation to the advertiser. The advertiser reviews the optimized proposal and makes any necessary adjustments. After final confirmation, the advertiser schedules the launch of distribution.

[0901] 4. User device: The user adds the LINE Official Account as a friend. Once the friend addition is complete, the user profile data is sent to the server.

[0902] 5. Generative AI model: Analyzes user profile data and generates individually optimized promotional ideas and surveys, taking into account the user's age, gender, past behavioral data, etc.

[0903] 6. Server: Sends the optimized promotion proposal and the corresponding survey to the user, who receives the notification and answers the survey.

[0904] 7. User terminal: When the user answers and submits the questionnaire, the data is sent to the server.

[0905] 8. Server: Validates the received survey responses and stores them in the database. After validation, reward points are awarded to the user.

[0906] 9. User device: Users can check their points in LINE Wallet and use them as needed. Points can be used for purchases within LINE.

[0907] Specific examples

[0908] Example 1: New Product Campaign

[0909] Advertisers plan a free sample campaign for a new product and register the promotion proposal on a dedicated management screen. The server sends the received promotion proposal to a generative AI model, which optimizes it for the target demographic. The optimized campaign proposal is generated, and the advertiser can review it and set the distribution schedule.

[0910] When a user adds a LINE official account as a friend, their profile data is sent to the server and analyzed by the generative AI model. A new product campaign information and a survey are sent to the user, who then answers the survey. The server receives and verifies the responses and awards the user 50 points. The user can view the reward points in their LINE Wallet and use them for purchases.

[0911] In this way, the system of the present invention provides benefits to both advertisers and users while realizing efficient advertisement distribution.

[0912] The processing flow will be explained below.

[0913] Step 1:

[0914] Advertiser terminal: The advertiser logs in to the dedicated management screen, enters login credentials, and accesses the system.

[0915] Step 2:

[0916] Advertiser terminal: Click the Create New Promotion Proposal button. Enter promotion information (product information, target demographic, campaign start date, etc.).

[0917] Step 3:

[0918] Advertiser terminal: After completing the input, click the send button to send the promotion proposal data to the server.

[0919] Step 4:

[0920] Server: Sends the received promotion proposal data to the generation AI model. The data is analyzed by AI and an optimized promotion proposal is generated.

[0921] Step 5:

[0922] Server: Stores the optimized promotion proposal in a database and sends a confirmation to the advertiser.

[0923] Step 6:

[0924] Advertiser terminal: The advertiser checks the notification and reviews the optimized promotion plan on a dedicated management screen, making fine adjustments as necessary and finalizing the plan.

[0925] Step 7:

[0926] Advertiser terminal: After final confirmation, schedule the start of distribution and click the approval button to send the final data to the server.

[0927] Step 8:

[0928] User device: The user adds the LINE Official Account as a friend. A notification is sent to the user confirming the friend addition.

[0929] Step 9:

[0930] Server: Once the friend registration is confirmed, generate user profile data and send it to the generative AI model.

[0931] Step 10:

[0932] Generative AI model: Analyzes user profile data and generates individually optimized promotional ideas and surveys.

[0933] Step 11:

[0934] Server: Stores the generated promotion ideas and questionnaires in a database and distributes them to users.

[0935] Step 12:

[0936] User device: The user receives the notification and answers the questionnaire. After completing the questionnaire, the user clicks the send button to send the answers to the server.

[0937] Step 13:

[0938] Server: Receives the survey responses sent by users, stores them in a database, and verifies the responses.

[0939] Step 14:

[0940] Server: Once verification is complete, it will credit the reward points to the user's account and send a notification to the user's device.

[0941] Step 15:

[0942] User device: The user opens the LINE Wallet function, checks the points awarded, and uses them to purchase goods and services.

[0943] Step 16:

[0944] Server: Records point usage history and updates user data.

[0945] Through the above processing steps, this system realizes effective and efficient ad delivery and reward provision for both advertisers and users.

[0946] Example 1

[0947] 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."

[0948] Conventional ad delivery systems do not optimize based on detailed user profile data, resulting in poor advertising effectiveness. Furthermore, the lack of an incentive system to encourage users to respond positively to ads presents a challenge, resulting in low ad acceptance. As a result, efficient and effective ad delivery has not been achieved for both advertisers and users.

[0949] 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.

[0950] In this invention, the server includes a means for a company representative to register promotion plans, a means for operating a generation AI model to optimize the registered promotion plans, a means for sending user profile data to the generation AI model and generating individual promotion plans and questionnaires optimized for the target demographic, a means for delivering the optimized promotion plans and questionnaires to users, a means for receiving and verifying questionnaire responses from users, and a means for awarding reward points to users. This enables optimization of promotion plans and individual responses to each user, resulting in high advertising effectiveness and improved user incentives.

[0951] "Company Representative" means a person within a company who is responsible for managing and registering promotion proposals.

[0952] "Promotion Ideas" refers to information about plans and strategies for promoting products and services.

[0953] "Generative AI models" are algorithms and systems that use artificial intelligence to analyze data and generate optimized promotional ideas based on specified criteria.

[0954] "User profile data" refers to information relating to an individual, such as the user's age, gender, location, and past behavioral history.

[0955] A "survey" is a method of asking specific questions to users and collecting their responses.

[0956] "Reward points" are points that users receive as an incentive for certain actions in the system.

[0957] A "communications application" is a software application that a user uses to exchange information with a server.

[0958] "Target demographic" refers to a specific group of users targeted for promotion.

[0959] "Delivery means" refers to the methods and techniques used to deliver promotional ideas and surveys to users.

[0960] "Verification measures" are methods or techniques for verifying the accuracy of survey responses from users.

[0961] This invention is a system that delivers optimized corporate promotional ideas to users and allows users to earn reward points by answering questionnaires. This system is composed of a server, a user terminal, and an advertiser terminal. The roles and detailed operations of each are explained below.

[0962] server

[0963] The server sends the received promotion proposals to the generative AI model and generates optimized promotion proposals. Specifically, it analyzes the promotion proposals sent from the advertiser's device and generates promotion proposals optimized for the target demographic using a prompt for the generative AI model. The generative AI model uses the prompt, "Please optimize this promotion proposal for the target demographic." After receiving the optimized promotion proposal, the server stores it in a database and notifies the advertiser. The server also analyzes the received user profile data and generates individually optimized promotion proposals and questionnaires, taking into account the user's age, gender, past behavioral data, etc.

[0964] Advertiser terminal

[0965] The advertiser terminal provides a dedicated management screen and a means for advertisers to register new promotion proposals. The advertiser enters information such as product information, target demographic, and distribution start date, and sends the promotion proposal to the server. After the optimized promotion proposal is notified by the server, the advertiser can review it, make adjustments as necessary, and set the final distribution schedule.

[0966] User Device

[0967] The user's device is primarily used by the user to add the LINE Official Account as a friend. Once friend addition is complete, the user's profile data is sent to the server. Optimized promotion ideas and surveys are then sent to the user, who receives a notification and answers the survey. Once the answers are sent to the server and verified, the user receives reward points, which can be viewed and used in the LINE Wallet.

[0968] Specific examples

[0969] Example 1: New Product Campaign

[0970] The advertiser plans a free sample campaign for a new product and registers the promotion plan on a dedicated management screen. The server sends the received promotion plan to the generation AI model, which optimizes it for the target demographic. The optimized campaign plan is generated, and the advertiser confirms it and sets the distribution schedule. When a user adds the LINE official account as a friend, their profile data is sent to the server and analyzed by the generation AI model. Information about the new product campaign and a survey are sent to the user, who then answers the survey. The server receives and verifies the responses and awards the user 50 points. The user can check the reward points in their LINE Wallet and use them for purchases.

[0971] Prompt Sentence Examples

[0972] "Please optimize this promotional idea for the target demographic."

[0973] "Optimize a new product campaign aimed at women in their 20s"

[0974] "Generate promotion ideas for male users in their 30s."

[0975] This system will enable effective and efficient ad delivery for both advertisers and users.

[0976] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0977] Step 1:

[0978] Advertiser registration of promotion proposals

[0979] Input: Receive promotional proposal data such as product information, target demographic, and distribution start date from the advertiser's terminal.

[0980] How it works: Advertisers log in to the dedicated management screen, enter each item, and press the "Submit" button to register their promotion proposal.

[0981] Output: The registered promotion proposal data is sent to the server.

[0982] Step 2:

[0983] Optimizing promotion ideas

[0984] Input: Promotion proposal data sent to the server.

[0985] Operation: The server sends the received promotion proposal to the generative AI model and instructs the generative AI model to analyze it using the prompt "Please optimize this promotion proposal for the target demographic."

[0986] Output: The optimized promotion proposal data is sent back to the server from the generative AI model.

[0987] Step 3:

[0988] Checking optimization recommendations and setting delivery schedules

[0989] Input: Optimized promotion proposal data.

[0990] Operation: The server sends the optimized promotion proposal to the advertiser's terminal and sends a confirmation notice to the advertiser. The advertiser checks the optimization proposal, makes any necessary adjustments, and presses the "Final Confirm" button to schedule the distribution.

[0991] Output: The finalized promotion plan and distribution schedule data are saved on the server.

[0992] Step 4:

[0993] Users adding LINE Official Accounts as friends

[0994] Input: A user adds a LINE Official Account as a friend.

[0995] How it works: A user opens the LINE application and adds the official account as a friend. Once the friend registration is complete, the information is sent to the server.

[0996] Output: User profile data (age, gender, region, etc.) is sent to the server.

[0997] Step 5:

[0998] Generate personalized promotion ideas and surveys

[0999] Input: User profile data.

[1000] How it works: The server sends user profile data to the generative AI model and directs its analysis using the prompt "Generate promotion ideas and surveys optimized for each target demographic."

[1001] Output: The generative AI model sends individually optimized promotion ideas and survey data back to the server.

[1002] Step 6:

[1003] Promotion ideas and survey distribution

[1004] Input: Individually optimized promotion ideas and survey data.

[1005] How it works: The server sends the optimized promotion proposal and survey to the user's device. The user receives a notification and answers the survey.

[1006] Output: The user's survey response data is sent to the server.

[1007] Step 7:

[1008] Receiving and verifying survey responses

[1009] Input: User survey response data.

[1010] Operation: The server validates the received survey response data to ensure accuracy.

[1011] Output: The verified survey response data is stored in a database.

[1012] Step 8:

[1013] Awarding reward points

[1014] Input: Validated survey response data.

[1015] Operation: The server processes the reward points to the user based on the survey responses.

[1016] Output: Reward points are reflected in the user's LINE Wallet.

[1017] Step 9:

[1018] Checking and using points

[1019] Input: Reward points awarded.

[1020] How it works: Users can view reward points in LINE Wallet and use them for purchases within LINE as needed.

[1021] Output: A record of the user's reward points usage is kept.

[1022] In this way, the system realizes effective and personalized promotions for both advertisers and users.

[1023] (Application example 1)

[1024] 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."

[1025] In today's advertising market, companies want to run effective promotions, but they face the challenge of delivering advertisements in an optimal way to target users. Furthermore, users often receive promotions and surveys that they are not interested in, which can lead to a decline in engagement. The objective of this invention is to provide a promotion delivery system that efficiently optimizes companies' promotion proposals and is both attractive and convenient for users.

[1026] 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.

[1027] In this invention, the server includes: means for a company representative to register promotion proposals; means for operating a generative AI model to optimize the registered promotion proposals; means for delivering the optimized promotion proposals to users; means including a smartphone application to be installed on the user's device; means for receiving and verifying survey responses from users; means for awarding reward points to users; and means for users to receive and answer promotion proposals and surveys via the application installed on their smartphones. This enables companies to efficiently deliver optimal promotions to target users, and enables users to actively participate in promotional content that interests them and earn rewards.

[1028] A "promotion proposal" refers to the plan and content for effectively communicating information about the products and services offered by a company to users.

[1029] "Generative AI model" refers to an artificial intelligence algorithm or system used to optimize promotional ideas.

[1030] "Optimization" means adjusting and improving the content of a promotional proposal to achieve the most effective results for a specific purpose.

[1031] "User" refers to the consumer or user who receives and responds to the promotion proposal and survey.

[1032] "Survey" refers to a survey in the form of questions to collect opinions and information from users.

[1033] "Reward points" are points that users can earn by answering surveys and can later be exchanged for specific services or products.

[1034] "Server" means the computer system that receives, analyzes, optimizes, and delivers Promotional Ideas.

[1035] "Smartphone Application" refers to software installed on a User's smartphone to receive promotional offers and surveys.

[1036] An "official account for a communication application" refers to an official communication channel operated by a company or organization that allows direct interaction with users.

[1037] The present invention is a system that allows advertisers to register promotion proposals, optimize those proposals, and deliver them to users. Users can earn reward points by answering surveys, and operate the system through a smartphone application.

[1038] System Overview

[1039] The server provides a management screen for company personnel to register promotion proposals. This management screen includes an interface for advertisers to enter details such as product information, target demographics, and distribution start date. The data entered by the advertiser is sent to the server, where the promotion proposal is analyzed and optimized by the generative AI model.

[1040] The server uses the generative AI model to optimize promotion ideas and send them to target users. Users receive promotion ideas and surveys through a dedicated application installed on their smartphones. This application works by users adding the official account of the communication application as a friend.

[1041] Overview of program processing

[1042] The server does the following:

[1043] 1. The advertiser registers a promotion proposal via the management screen.

[1044] 2. The registered promotion proposals are sent to the generation AI model to generate optimized promotion proposals.

[1045] 3. Deliver optimized promotional ideas to the user's smartphone application.

[1046] The smartphone application installed on the user's device performs the following operations:

[1047] 1. Add the official account of the communication application as a friend.

[1048] 2. Display promotion proposals and surveys received from the server.

[1049] 3. The user answers the survey and sends the answers to the server.

[1050] The server receives the survey responses from the user and performs the following actions:

[1051] 1. Verify the contents of the survey responses.

[1052] 2. Give reward points to users after verification.

[1053] 3. Save as a user report.

[1054] Hardware and software used

[1055] The hardware required includes a server, the user's smartphone, and the official account of the communication application. The software required includes an administration screen, a generative AI model, and a smartphone application. Specific examples include an application developed in Python, the LINE API, and a generative AI model.

[1056] Specific examples

[1057] For example, if Company A wants to run a free sample campaign for a new product, it enters a promotion idea into the admin screen. The server optimizes this information using a generative AI model and distributes it to target users. Users receive the promotion idea and a survey through a smartphone application, and by answering the survey, they can earn reward points. These points can be viewed and used in the user's LINE Wallet.

[1058] Prompt Sentence Examples

[1059] "Use a generative AI model to optimize promotional ideas for cosmetics for women in their 30s. Generate optimal promotional ideas and questionnaires based on behavioral data of the target demographic."

[1060] As described above, the present invention is a system that realizes efficient advertisement distribution while providing benefits to both advertisers and users.

[1061] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1062] Step 1:

[1063] The advertiser enters the promotion proposal into the management screen. The management screen provides an interface for entering details such as product information, target demographic, and distribution start date. After input, the promotion proposal is sent to the server. Input: Detailed data of the promotion proposal. Output: Promotion proposal data sent to the server.

[1064] Step 2:

[1065] The server sends the received promotion proposal to the generative AI model, which analyzes the promotion proposal and generates a promotion optimized for the target demographic. Input: Promotion proposal data. Output: Optimized promotion proposal.

[1066] Step 3:

[1067] The server receives the optimized promotion offer and delivers it to the user's smartphone application. Input: Optimized promotion offer. Output: Promotion offer sent to the user's smartphone application.

[1068] Step 4:

[1069] The user opens the application installed on their smartphone. The application adds the official account of the communication application as a friend and displays the promotion proposals and surveys received from the server. Input: Promotion proposals and surveys received from the server. Output: Displayed promotion proposals and surveys.

[1070] Step 5:

[1071] Users answer the survey and send their answers to the server via a smartphone application. Input: User's survey response data. Output: Survey response data sent to the server.

[1072] Step 6:

[1073] The server receives the survey responses from the user and verifies the responses. Once the verification is complete, reward points are awarded to the user. Input: User's survey response data. Output: Verified data and reward points.

[1074] Step 7:

[1075] The server stores the survey results as a user report. Input: Survey data after validation. Output: Stored survey result report.

[1076] 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.

[1077] This invention is a system that optimizes corporate promotional ideas for users and delivers them to them, allows users to earn points by answering questionnaires, and improves the effectiveness of promotions by using an emotion engine that recognizes users' emotions. This system is highly convenient for both advertisers and users, and realizes effective advertising delivery.

[1078] System Overview

[1079] The system consists of an advertiser terminal, a user terminal, a server, and an emotion engine. Advertisers register promotion proposals, and the server generates optimized promotions. Users add the LINE official account as a friend and receive individually optimized promotions and surveys. When users answer the survey, the server receives the answers and awards reward points after verification. The emotion engine then analyzes the user's emotions and optimizes the promotion proposals based on this information.

[1080] Program processing flow

[1081] 1. Advertiser terminal: Advertisers log in to a dedicated management screen and register new promotion proposals. The registered information includes product information, target demographics, campaign start date, etc. Once the promotion proposal is submitted, the data is sent to the server.

[1082] 2. Server: The server sends the received promotion proposal data to the generation AI model and emotion engine for content analysis and optimization. The generation AI model generates the most effective promotion for the target demographic, and the emotion engine analyzes user emotion data and feeds that information back to the generation AI model.

[1083] 3. Server: Generates an optimized promotion proposal and stores it in the database. Sends a confirmation to the advertiser, who can review the proposal and make any necessary adjustments. After final confirmation, schedules the launch of distribution.

[1084] 4. User device: The user adds the LINE Official Account as a friend. Once the friend addition is complete, the user profile data is sent to the server.

[1085] 5. Generative AI model: Analyzes user profile data and generates individually optimized promotional ideas and surveys, taking into account the user's age, gender, past behavioral data, etc.

[1086] 6. Emotion Engine: Analyzes user facial expressions, voice, and text data to recognize emotions and send the results to the generative AI model, which then uses this information to further optimize promotion ideas and surveys.

[1087] 7. Server: The optimized promotion proposals and corresponding questionnaires are stored in the database and sent to users, who then receive notifications and answer the questionnaires.

[1088] 8. User terminal: When the user answers and submits the questionnaire, the data is sent to the server.

[1089] 9. Server: Validates the received survey responses and stores them in the database. After validation, reward points are awarded to the user.

[1090] 10. User device: Users can check their points in LINE Wallet and use them as needed. Points can be used for purchases within LINE.

[1091] Specific examples

[1092] Example 1: New Product Campaign

[1093] Advertisers plan a free sample campaign for a new product and register the promotion proposal on a dedicated management screen. The server sends the received promotion proposal to a generative AI model, which optimizes it for the target demographic. An optimized campaign proposal is generated, and the emotion engine also takes user emotional data into account. The advertiser confirms the proposal and sets the distribution schedule.

[1094] When a user adds a LINE official account as a friend, their profile data and emotion data are sent to the server and analyzed by the generative AI model. A new product campaign information and a survey are sent to the user, who then answers the survey. The server receives and verifies the responses and awards the user 50 points. The user can check the reward points in their LINE Wallet and use them for purchases.

[1095] In this way, the system of the present invention provides benefits to both advertisers and users while realizing efficient advertisement distribution. By combining it with an emotion engine, even more effective promotions become possible.

[1096] The processing flow will be explained below.

[1097] Step 1:

[1098] Advertiser terminal: The advertiser logs in to the dedicated management screen, enters their login ID and password, and is authenticated.

[1099] Step 2:

[1100] Advertiser's terminal: After logging in, click the Create New Promotion Proposal button. Enter promotion information (product details, target demographic, campaign period, etc.).

[1101] Step 3:

[1102] Advertiser terminal: After all input is completed, click the send button to send the promotion proposal data to the server.

[1103] Step 4:

[1104] Server: Analyzes the received promotion proposal data and sends it to the generative AI model and emotion engine.

[1105] Step 5:

[1106] Generative AI model: Analyzes promotional proposal data and generates segment-optimized promotional proposals, taking into account the interests and preferences of target users.

[1107] Step 6:

[1108] Emotion engine: Analyzes input data about promotion ideas and extracts background emotional information (e.g., past reactions and reviews). Based on this, it creates emotional data and feeds it back to the generative AI model.

[1109] Step 7:

[1110] Generative AI model: Taking into account the received emotional data, it re-optimizes promotional suggestions, reflecting what advertising content will be most effective when the user is in a particular emotional state.

[1111] Step 8:

[1112] Server: Stores the optimized promotion proposal in a database and sends a confirmation to the advertiser.

[1113] Step 9:

[1114] Advertiser terminal: The advertiser checks the notification and reviews the optimized promotion plan on a dedicated management screen. They make any necessary adjustments and, after final confirmation, schedule the launch of the promotion.

[1115] Step 10:

[1116] User device: The user adds the LINE Official Account as a friend. Once the friend addition is complete, the user receives a notification that the friend addition is complete.

[1117] Step 11:

[1118] Server: Once the friend registration is confirmed, user profile data is generated and sent to the generative AI model.

[1119] Step 12:

[1120] Generative AI model: Analyzes user profile data to generate individually optimized promotion ideas and surveys. It also takes into account real-time emotional data from the emotion engine to generate surveys with optimal timing and content.

[1121] Step 13:

[1122] Server: Stores the generated optimized promotion proposals and surveys in a database and delivers them to users.

[1123] Step 14:

[1124] User device: The user receives a notification and answers the survey. Once the answers are complete, the user clicks the submit button to send the answers to the server.

[1125] Step 15:

[1126] Server: Receives the survey responses sent by users, stores them in a database, and verifies the responses.

[1127] Step 16:

[1128] Server: After the answer is verified, the server grants reward points to the user's account and sends a notification of the grant to the user's device.

[1129] Step 17:

[1130] User device: The user opens the LINE Wallet function and checks the points they have received. Points can be used for purchases and services within LINE.

[1131] Step 18:

[1132] Server: Records point usage history and updates user data.

[1133] Through the above processing steps, this system not only realizes effective and efficient ad delivery and reward allocation for both advertisers and users, but also enables even more personalized promotions by combining it with an emotion engine.

[1134] Example 2

[1135] 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."

[1136] In modern advertising, it is important for advertisers to efficiently deliver promotions that are optimized for specific target demographics. However, conventional systems have difficulty achieving detailed optimization based on individual user profiles, and are unable to deliver promotions that take user emotions into account. As a result, promotions are not as effective as they could be, making it difficult to achieve satisfactory results for both advertisers and users.

[1137] 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 a means for a company representative to register a promotion plan, a means for running a generative AI model to optimize the registered promotion plan, and a means for analyzing user emotion data using an emotion analysis engine and using the results to optimize the promotion. This enables more effective distribution of promotions to the target demographic.

[1138] "Company Representative" means the advertiser or marketing representative who is responsible for registering and managing promotion proposals.

[1139] A "promotion proposal" is a plan or proposal for promoting a product or service to consumers, and includes the content of the advertisement and a distribution schedule.

[1140] A "generative AI model" is a system that uses artificial intelligence to optimize promotional ideas, such as a text generation model or a machine learning algorithm.

[1141] An "emotion analysis engine" is software or algorithms for analyzing a user's emotions, and uses techniques such as facial expression analysis, voice analysis, and text analysis to understand the user's emotional state.

[1142] "User" refers to the consumer or customer who receives the promotion and responds to the survey.

[1143] A "survey" is a list of questions to gather user feedback, and is composed of multiple choice answers and free-form responses.

[1144] "Reward points" are incentives that users can receive by answering surveys, and can be used as electronic money or coupons, for example.

[1145] A "communication application account" is an account for a communication tool used on a smartphone or computer, which allows you to send and receive messages and add friends.

[1146] The present invention is a system that allows advertisers to register promotion proposals, delivers promotions optimized by a generative AI model and a sentiment analysis engine to users, and allows users to earn points by answering surveys. A specific embodiment of this system will be described.

[1147] System configuration

[1148] This system consists of an advertiser terminal, a user terminal, a server, a generative AI model, a sentiment analysis engine, and a database. The advertiser terminal and user terminal are general-purpose PCs or smartphones, and the server is located in a cloud environment.

[1149] Program processing explanation

[1150] Advertiser promotion proposal registration

[1151] Advertiser Device:

[1152] Advertisers log in to a dedicated management screen and register new promotion ideas, including product information, target demographics, and campaign start date.

[1153] For example, if you are registering a promotional proposal for a new shampoo product, you would enter "new shampoo" as the product information, "women in their 20s" as the target demographic, and "May 1, 2023" as the campaign start date.

[1154] Once registration is complete, the data is sent to the server.

[1155] Optimizing promotion ideas

[1156] server:

[1157] The server sends the received promotion proposal data to the generation AI model and sentiment analysis engine.

[1158] The generative AI model (e.g., GPT-3) generates an optimized promotion based on the received promotion proposal. The generative AI model is given a prompt like this:

[1159] Please optimize a shampoo campaign proposal aimed at women in their 20s.

[1160] The sentiment analysis engine analyzes user emotional data and feeds the results back into the generative AI model.

[1161] Sentiment analysis and promotion optimization

[1162] Sentiment Analysis Engine:

[1163] The sentiment analysis engine analyzes users' facial expressions, voice, and text data to recognize their emotions. For example, if a user responded positively to a previous promotion, it will provide positive feedback to the generative AI model.

[1164] The server receives the emotion data and sends it to the generative AI model.

[1165] Advertiser validation and delivery schedule setting

[1166] server:

[1167] An optimized promotion plan is generated and stored in a database.

[1168] Send the advertiser a confirmation of the optimized proposal.

[1169] Advertisers can check the optimization suggestions on the management screen, make any necessary adjustments, and then press the "Confirm" button to set the delivery schedule.

[1170] Promotion ideas and survey distribution

[1171] User device:

[1172] A user adds an official account of a communication application as a friend. Once the friend registration is complete, the user profile data (e.g., LINE ID, age, gender) is sent to the server.

[1173] The server sends user profile data to a generative AI model to generate individually optimized promotional ideas and surveys.

[1174] The server stores the optimized promotion proposals and corresponding questionnaires in a database and delivers them to users.

[1175] Answer surveys and receive reward points

[1176] User device:

[1177] The user answers the questionnaire and presses the send button, and the questionnaire response data is sent to the server.

[1178] server:

[1179] The server verifies the received survey responses and stores them in a database.

[1180] After verification, reward points will be awarded to the user and a notification will be sent.

[1181] User device:

[1182] Users can check their points in the wallet within the communication application and use them as electronic money, for example.

[1183] This embodiment allows advertisers to distribute effective promotions, and users can answer corresponding surveys and receive rewards. Furthermore, by using a sentiment analysis engine, optimization can be performed taking into account user sentiment data, further improving the effectiveness of promotions.

[1184] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1185] Step 1:

[1186] Advertiser promotion proposal registration

[1187] Advertiser Device:

[1188] Advertisers log in to a dedicated management screen and register new promotion proposals.

[1189] Input: Product information, target demographic, campaign start date, etc.

[1190] Data processing: These input data are organized into a single data package.

[1191] Output: Promotion proposal data sent to the server.

[1192] Specific actions: The advertiser enters product information for the "new shampoo," the target demographic of "women in their 20s," and "May 1, 2023" as the campaign start date, and clicks the submit button.

[1193] Step 2:

[1194] Optimizing promotion ideas

[1195] server:

[1196] The server sends the received promotion proposal data to the generation AI model and sentiment analysis engine.

[1197] Input: Promotion proposal data.

[1198] Data processing: Generate prompts to be passed to the generative AI model. For example, "Please optimize the shampoo campaign proposal for women in their 20s."

[1199] Output: Optimized promotion ideas returned by the generative AI model. Sentiment data feedback from the sentiment analysis engine.

[1200] Specific operation: The generative AI model optimizes promotional proposals, and the sentiment analysis engine analyzes user sentiment data and feeds the results back to the generative AI model.

[1201] Step 3:

[1202] Sentiment analysis and promotion optimization

[1203] Sentiment Analysis Engine:

[1204] The server uses an emotion analysis engine to analyze the user's facial expressions, voice, and text data.

[1205] Input: User facial expression, voice, and text data.

[1206] Data processing: Apply sentiment analysis algorithms to classify emotional states, e.g., "positive," "negative," etc.

[1207] Output: Send the analysis results to the generative AI model.

[1208] Specific behavior: For example, if a user shows a positive facial expression in response to a previous promotion, the reaction is classified as positive and fed back to the generative AI model.

[1209] Step 4:

[1210] Advertiser validation and delivery schedule setting

[1211] server:

[1212] Generate optimized promotion proposals, store them in the database, and send a confirmation to the advertiser.

[1213] Input: Optimized promotion ideas, sentiment data.

[1214] Data processing: Convert data into a format to be saved in the database. Generate a notification message to the advertiser.

[1215] Output: Database storage, advertiser notification.

[1216] Specific operation: The server stores the optimized promotion proposal in the database and sends a notification message to the advertiser requesting confirmation of the optimization proposal.

[1217] Step 5:

[1218] User's official account registration

[1219] User device:

[1220] A user adds the official account of a communication application as a friend.

[1221] Input: User's account information (e.g. LINE ID), age, gender.

[1222] Data processing: Assemble user profile data into a single data package.

[1223] Output: Sends user profile data to the server.

[1224] Specific operation: A user adds an official account of a communication application as a friend, and upon completion of the registration, the profile data is automatically sent to the server.

[1225] Step 6:

[1226] Analyzing user profile data

[1227] server:

[1228] The server sends the received user profile data to the generative AI model for analysis.

[1229] Input: User profile data.

[1230] Data processing: Generative AI models analyze profile data to generate individually optimized promotional ideas and surveys.

[1231] Output: Individually optimized promotion ideas, surveys.

[1232] Specific operation: Based on user profile data, the generative AI model automatically generates individually optimized promotion ideas and surveys.

[1233] Step 7:

[1234] Promotion ideas and survey distribution

[1235] server:

[1236] Optimized promotion ideas and surveys are stored in a database and distributed to users.

[1237] Input: individually optimized promotion ideas, surveys.

[1238] Data processing: storing data in a database and generating messages for delivery to users.

[1239] Output: User notification, database save.

[1240] Specific operation: The server stores the optimized promotion proposals and surveys in a database and delivers them to the user as messages.

[1241] Step 8:

[1242] User survey responses

[1243] User device:

[1244] The user answers the survey and presses the submit button.

[1245] Input: User's survey responses.

[1246] Data processing: Survey response data is sent to the server.

[1247] Output: Survey response data sent to the server.

[1248] Specific operation: The user answers the questionnaire and presses the send button to send the response data to the server.

[1249] Step 9:

[1250] Survey response verification and point awarding

[1251] server:

[1252] The server verifies the received survey responses and stores them in a database.

[1253] Input: User survey response data.

[1254] Data processing: Validating response data and storing it in a database.

[1255] Output: Reward points awarded to user and notification.

[1256] Specific operation: The server verifies the survey response data, stores it in the database, and then awards reward points to the user and sends a notification.

[1257] Step 10:

[1258] Check and use reward points

[1259] User device:

[1260] Users can check their points in the wallet within the communication application and use them as needed.

[1261] Input: Reward point award notification from the server.

[1262] Data processing: Update the points balance in the wallet.

[1263] Output: Point balance confirmation screen.

[1264] Specific operation: The user checks the reward points in the wallet and uses them as electronic money.

[1265] (Application example 2)

[1266] 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."

[1267] In conventional advertising systems, ad optimization was limited to the user's basic profile and behavioral data, and promotions did not reflect the user's emotional state. This limited the effectiveness of promotions. Also, while there were reward systems based on survey responses, these did not provide effective feedback to improve the user experience.

[1268] The specification processing by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes a means for a company representative to register promotion proposals, a means for operating a generative AI model to optimize the registered promotion proposals, a means for delivering the optimized promotion proposals to users, a means for receiving and verifying questionnaire responses from users, a means for awarding reward points to users, a means for operating an emotion engine that recognizes user emotions, and a means for feeding back emotion data to the generative AI model. This enables optimal promotions that reflect the user's emotional state and improves advertising effectiveness.

[1269] "Company Representative" means a member of an organization responsible for registering a Promotion Proposal.

[1270] "Promotion Proposal" means a plan that describes the implementation and content of an advertisement or campaign.

[1271] "Generative AI model" refers to an artificial intelligence algorithm that generates optimized promotional ideas based on input data.

[1272] "Optimized Promotion Ideas" means advertising or campaign content that is tailored based on user characteristics and emotional data using generative AI models.

[1273] "User" refers to a consumer who receives a company's promotion and completes a survey.

[1274] A "survey" is a form of survey that asks users questions related to a promotion proposal.

[1275] "Emotion Engine" refers to a software or hardware system that provides technology for analyzing a user's emotional state.

[1276] "Emotional data" refers to information about a user's emotional state analyzed based on facial expressions, voice, text, etc.

[1277] A "communication app" is an application that allows users to register friends and receive promotions and surveys.

[1278] This invention provides a mechanism for realizing a system that delivers optimized corporate promotional ideas to users and allows them to earn points by answering questionnaires. It also uses an emotion engine to recognize users' emotions and improve the effectiveness of promotions.

[1279] The system consists of an administration screen where company representatives can register promotion ideas, a generative AI model, an emotion engine, a server, and a user terminal.

[1280] Company personnel use the management screen to register promotion proposals. The management screen runs on a web browser and allows users to enter product information, target demographics, campaign start date, etc. This promotion proposal data is then sent to the server.

[1281] The server sends the received promotion proposal data to the generative AI model to generate optimized promotion proposals. The generative AI model generates promotions that are most effective for the target demographic and further optimizes them using feedback from the emotion engine.

[1282] The emotion engine recognizes emotions by analyzing the user's facial expressions, voice, and text data. This is done using the smartphone's camera and microphone, as well as generic services from Microsoft and Google. For example, by using the "Microsoft Azure Emotion API" or "Google Cloud Vision API," it is possible to analyze the user's emotional state in real time.

[1283] The optimized promotion ideas are managed by the server and sent to the communication app accounts of users who have registered them as friends. Users receive the promotion ideas and surveys through the app and then answer the surveys.

[1284] When a user answers a survey, the data is sent to the server. After the server verifies the received data, it grants reward points to the user. The user can view and use the reward points within the communication app.

[1285] As a concrete example, consider a situation where a new product campaign is being conducted. A company representative plans a sample campaign for the new product and registers the promotion proposal in a dedicated management screen. The following example can be considered.

[1286] Example prompt: (New product campaign) A free sample of our new shampoo is now available! Try this shampoo and answer a simple questionnaire to receive 500 points! These points can be used in the in-app store. Answer the questions and get points!

[1287] When a user receives this promotional information, their emotions are recognized from their facial expressions and voice, and a survey optimized for them is delivered. By answering the survey, they can earn reward points. In this way, promotions that reflect the user's emotional state can be optimally delivered.

[1288] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1289] Step 1:

[1290] Company personnel use the management screen to register promotion proposals, including product information, target demographics, and campaign start date. This data is then sent to the server.

[1291] Step 2:

[1292] The server analyzes the received promotion proposal data and sends it to the generative AI model, which processes the data to generate the most effective promotion proposal for the target demographic and outputs the optimized promotion proposal.

[1293] Step 3:

[1294] The emotion engine uses the smartphone's camera and microphone to analyze the user's facial expressions and voice, generating emotion data using, for example, the Microsoft Azure Emotion API or Google Cloud Vision API, and then sends the resulting emotion data to a server.

[1295] Step 4:

[1296] The server feeds back the emotion data received from the emotion engine to the generative AI model, which then further optimizes the promotion proposals.

[1297] Step 5:

[1298] The optimized promotion ideas are stored in a database by the server, which then distributes them to the communication app accounts that the user has registered as friends.

[1299] Step 6:

[1300] Users receive optimized promotional offers and surveys through the app, including promotional text (e.g., new shampoo samples are now available!) and survey questions.

[1301] Step 7:

[1302] When a user answers a questionnaire, the answer data is sent from the app to the server, which validates the input data and stores the validation results in a database.

[1303] Step 8:

[1304] The server will award reward points to the user based on the verified survey responses, which will be added to the user's reward account.

[1305] Step 9:

[1306] Users can check the points they have earned in their rewards account within the communication app and use them in in-app stores, etc.

[1307] 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.

[1308] 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.

[1309] 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.

[1310] [Fourth embodiment]

[1311] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1312] 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.

[1313] 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).

[1314] 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.

[1315] 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.

[1316] 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).

[1317] 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.

[1318] 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.

[1319] 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.

[1320] 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.

[1321] 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.

[1322] 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.

[1323] 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."

[1324] The present invention is a system that delivers optimized corporate promotional ideas to users and allows users to earn points by answering questionnaires. This system is highly convenient for both advertisers and users, and realizes effective advertising delivery.

[1325] System Overview

[1326] This system consists of an advertiser terminal, a user terminal, and a server. Advertisers register promotion proposals, and the server generates optimized promotions. Users register as friends on the LINE official account and receive individually optimized promotions and surveys. When users answer the survey, the server receives the answers and, after verification, awards reward points.

[1327] Program processing flow

[1328] 1. Advertiser terminal: Advertisers log in to a dedicated management screen and register new promotion proposals. The registered information includes product information, target demographic, distribution start date, etc. Once the promotion proposal is submitted, the data is sent to the server.

[1329] 2. Server: The server sends the promotion ideas it receives to the generative AI model, which analyzes and optimizes the content. The generative AI model then generates the most effective promotion for the target demographic and returns the information to the server.

[1330] 3. Server: Saves the optimized promotion proposal and sends a confirmation to the advertiser. The advertiser reviews the optimized proposal and makes any necessary adjustments. After final confirmation, the advertiser schedules the launch of distribution.

[1331] 4. User device: The user adds the LINE Official Account as a friend. Once the friend addition is complete, the user profile data is sent to the server.

[1332] 5. Generative AI model: Analyzes user profile data and generates individually optimized promotional ideas and surveys, taking into account the user's age, gender, past behavioral data, etc.

[1333] 6. Server: Sends the optimized promotion proposal and the corresponding survey to the user, who receives the notification and answers the survey.

[1334] 7. User terminal: When the user answers and submits the questionnaire, the data is sent to the server.

[1335] 8. Server: Validates the received survey responses and stores them in the database. After validation, reward points are awarded to the user.

[1336] 9. User device: Users can check their points in LINE Wallet and use them as needed. Points can be used for purchases within LINE.

[1337] Specific examples

[1338] Example 1: New Product Campaign

[1339] Advertisers plan a free sample campaign for a new product and register the promotion proposal on a dedicated management screen. The server sends the received promotion proposal to a generative AI model, which optimizes it for the target demographic. The optimized campaign proposal is generated, and the advertiser can review it and set the distribution schedule.

[1340] When a user adds a LINE official account as a friend, their profile data is sent to the server and analyzed by the generative AI model. A new product campaign information and a survey are sent to the user, who then answers the survey. The server receives and verifies the responses and awards the user 50 points. The user can view the reward points in their LINE Wallet and use them for purchases.

[1341] In this way, the system of the present invention provides benefits to both advertisers and users while realizing efficient advertisement distribution.

[1342] The processing flow will be explained below.

[1343] Step 1:

[1344] Advertiser terminal: The advertiser logs in to the dedicated management screen, enters login credentials, and accesses the system.

[1345] Step 2:

[1346] Advertiser terminal: Click the Create New Promotion Proposal button. Enter promotion information (product information, target demographic, campaign start date, etc.).

[1347] Step 3:

[1348] Advertiser terminal: After completing the input, click the send button to send the promotion proposal data to the server.

[1349] Step 4:

[1350] Server: Sends the received promotion proposal data to the generation AI model. The data is analyzed by AI and an optimized promotion proposal is generated.

[1351] Step 5:

[1352] Server: Stores the optimized promotion proposal in a database and sends a confirmation to the advertiser.

[1353] Step 6:

[1354] Advertiser terminal: The advertiser checks the notification and reviews the optimized promotion plan on a dedicated management screen, making fine adjustments as necessary and finalizing the plan.

[1355] Step 7:

[1356] Advertiser terminal: After final confirmation, schedule the start of distribution and click the approval button to send the final data to the server.

[1357] Step 8:

[1358] User device: The user adds the LINE Official Account as a friend. A notification is sent to the user confirming the friend addition.

[1359] Step 9:

[1360] Server: Once the friend registration is confirmed, generate user profile data and send it to the generative AI model.

[1361] Step 10:

[1362] Generative AI model: Analyzes user profile data and generates individually optimized promotional ideas and surveys.

[1363] Step 11:

[1364] Server: Stores the generated promotion ideas and questionnaires in a database and distributes them to users.

[1365] Step 12:

[1366] User device: The user receives the notification and answers the questionnaire. After completing the questionnaire, the user clicks the send button to send the answers to the server.

[1367] Step 13:

[1368] Server: Receives the survey responses sent by users, stores them in a database, and verifies the responses.

[1369] Step 14:

[1370] Server: Once verification is complete, it will credit the reward points to the user's account and send a notification to the user's device.

[1371] Step 15:

[1372] User device: The user opens the LINE Wallet function, checks the points awarded, and uses them to purchase goods and services.

[1373] Step 16:

[1374] Server: Records point usage history and updates user data.

[1375] Through the above processing steps, this system realizes effective and efficient ad delivery and reward provision for both advertisers and users.

[1376] Example 1

[1377] 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."

[1378] Conventional ad delivery systems do not optimize based on detailed user profile data, resulting in poor advertising effectiveness. Furthermore, the lack of an incentive system to encourage users to respond positively to ads presents a challenge, resulting in low ad acceptance. As a result, efficient and effective ad delivery has not been achieved for both advertisers and users.

[1379] 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.

[1380] In this invention, the server includes a means for a company representative to register promotion plans, a means for operating a generation AI model to optimize the registered promotion plans, a means for sending user profile data to the generation AI model and generating individual promotion plans and questionnaires optimized for the target demographic, a means for delivering the optimized promotion plans and questionnaires to users, a means for receiving and verifying questionnaire responses from users, and a means for awarding reward points to users. This enables optimization of promotion plans and individual responses to each user, resulting in high advertising effectiveness and improved user incentives.

[1381] "Company Representative" means a person within a company who is responsible for managing and registering promotion proposals.

[1382] "Promotion Ideas" refers to information about plans and strategies for promoting products and services.

[1383] "Generative AI models" are algorithms and systems that use artificial intelligence to analyze data and generate optimized promotional ideas based on specified criteria.

[1384] "User profile data" refers to information relating to an individual, such as the user's age, gender, location, and past behavioral history.

[1385] A "survey" is a method of asking specific questions to users and collecting their responses.

[1386] "Reward points" are points that users receive as an incentive for certain actions in the system.

[1387] A "communications application" is a software application that a user uses to exchange information with a server.

[1388] "Target demographic" refers to a specific group of users targeted for promotion.

[1389] "Delivery means" refers to the methods and techniques used to deliver promotional ideas and surveys to users.

[1390] "Verification measures" are methods or techniques for verifying the accuracy of survey responses from users.

[1391] This invention is a system that delivers optimized corporate promotional ideas to users and allows users to earn reward points by answering questionnaires. This system is composed of a server, a user terminal, and an advertiser terminal. The roles and detailed operations of each are explained below.

[1392] server

[1393] The server sends the received promotion proposals to the generative AI model and generates optimized promotion proposals. Specifically, it analyzes the promotion proposals sent from the advertiser's device and generates promotion proposals optimized for the target demographic using a prompt for the generative AI model. The generative AI model uses the prompt, "Please optimize this promotion proposal for the target demographic." After receiving the optimized promotion proposal, the server stores it in a database and notifies the advertiser. The server also analyzes the received user profile data and generates individually optimized promotion proposals and questionnaires, taking into account the user's age, gender, past behavioral data, etc.

[1394] Advertiser terminal

[1395] The advertiser terminal provides a dedicated management screen and a means for advertisers to register new promotion proposals. The advertiser enters information such as product information, target demographic, and distribution start date, and sends the promotion proposal to the server. After the optimized promotion proposal is notified by the server, the advertiser can review it, make adjustments as necessary, and set the final distribution schedule.

[1396] User Device

[1397] The user's device is primarily used by the user to add the LINE Official Account as a friend. Once friend addition is complete, the user's profile data is sent to the server. Optimized promotion ideas and surveys are then sent to the user, who receives a notification and answers the survey. Once the answers are sent to the server and verified, the user receives reward points, which can be viewed and used in the LINE Wallet.

[1398] Specific examples

[1399] Example 1: New Product Campaign

[1400] The advertiser plans a free sample campaign for a new product and registers the promotion plan on a dedicated management screen. The server sends the received promotion plan to the generation AI model, which optimizes it for the target demographic. The optimized campaign plan is generated, and the advertiser confirms it and sets the distribution schedule. When a user adds the LINE official account as a friend, their profile data is sent to the server and analyzed by the generation AI model. Information about the new product campaign and a survey are sent to the user, who then answers the survey. The server receives and verifies the responses and awards the user 50 points. The user can check the reward points in their LINE Wallet and use them for purchases.

[1401] Prompt Sentence Examples

[1402] "Please optimize this promotional idea for the target demographic."

[1403] "Optimize a new product campaign aimed at women in their 20s"

[1404] "Generate promotion ideas for male users in their 30s."

[1405] This system will enable effective and efficient ad delivery for both advertisers and users.

[1406] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1407] Step 1:

[1408] Advertiser registration of promotion proposals

[1409] Input: Receive promotional proposal data such as product information, target demographic, and distribution start date from the advertiser's terminal.

[1410] How it works: Advertisers log in to the dedicated management screen, enter each item, and press the "Submit" button to register their promotion proposal.

[1411] Output: The registered promotion proposal data is sent to the server.

[1412] Step 2:

[1413] Optimizing promotion ideas

[1414] Input: Promotion proposal data sent to the server.

[1415] Operation: The server sends the received promotion proposal to the generative AI model and instructs the generative AI model to analyze it using the prompt "Please optimize this promotion proposal for the target demographic."

[1416] Output: The optimized promotion proposal data is sent back to the server from the generative AI model.

[1417] Step 3:

[1418] Checking optimization recommendations and setting delivery schedules

[1419] Input: Optimized promotion proposal data.

[1420] Operation: The server sends the optimized promotion proposal to the advertiser's terminal and sends a confirmation notice to the advertiser. The advertiser checks the optimization proposal, makes any necessary adjustments, and presses the "Final Confirm" button to schedule the distribution.

[1421] Output: The finalized promotion plan and distribution schedule data are saved on the server.

[1422] Step 4:

[1423] Users adding LINE Official Accounts as friends

[1424] Input: A user adds a LINE Official Account as a friend.

[1425] How it works: A user opens the LINE application and adds the official account as a friend. Once the friend registration is complete, the information is sent to the server.

[1426] Output: User profile data (age, gender, region, etc.) is sent to the server.

[1427] Step 5:

[1428] Generate personalized promotion ideas and surveys

[1429] Input: User profile data.

[1430] How it works: The server sends user profile data to the generative AI model and directs its analysis using the prompt "Generate promotion ideas and surveys optimized for each target demographic."

[1431] Output: The generative AI model sends individually optimized promotion ideas and survey data back to the server.

[1432] Step 6:

[1433] Promotion ideas and survey distribution

[1434] Input: Individually optimized promotion ideas and survey data.

[1435] How it works: The server sends the optimized promotion proposal and survey to the user's device. The user receives a notification and answers the survey.

[1436] Output: The user's survey response data is sent to the server.

[1437] Step 7:

[1438] Receiving and verifying survey responses

[1439] Input: User survey response data.

[1440] Operation: The server validates the received survey response data to ensure accuracy.

[1441] Output: The verified survey response data is stored in a database.

[1442] Step 8:

[1443] Awarding reward points

[1444] Input: Validated survey response data.

[1445] Operation: The server processes the reward points to the user based on the survey responses.

[1446] Output: Reward points are reflected in the user's LINE Wallet.

[1447] Step 9:

[1448] Checking and using points

[1449] Input: Reward points awarded.

[1450] How it works: Users can view reward points in LINE Wallet and use them for purchases within LINE as needed.

[1451] Output: A record of the user's reward points usage is kept.

[1452] In this way, the system realizes effective and personalized promotions for both advertisers and users.

[1453] (Application example 1)

[1454] 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."

[1455] In today's advertising market, companies want to run effective promotions, but they face the challenge of delivering advertisements in an optimal way to target users. Furthermore, users often receive promotions and surveys that they are not interested in, which can lead to a decline in engagement. The objective of this invention is to provide a promotion delivery system that efficiently optimizes companies' promotion proposals and is both attractive and convenient for users.

[1456] 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.

[1457] In this invention, the server includes: means for a company representative to register promotion proposals; means for operating a generative AI model to optimize the registered promotion proposals; means for delivering the optimized promotion proposals to users; means including a smartphone application to be installed on the user's device; means for receiving and verifying survey responses from users; means for awarding reward points to users; and means for users to receive and answer promotion proposals and surveys via the application installed on their smartphones. This enables companies to efficiently deliver optimal promotions to target users, and enables users to actively participate in promotional content that interests them and earn rewards.

[1458] A "promotion proposal" refers to the plan and content for effectively communicating information about the products and services offered by a company to users.

[1459] "Generative AI model" refers to an artificial intelligence algorithm or system used to optimize promotional ideas.

[1460] "Optimization" means adjusting and improving the content of a promotional proposal to achieve the most effective results for a specific purpose.

[1461] "User" refers to the consumer or user who receives and responds to the promotion proposal and survey.

[1462] "Survey" refers to a survey in the form of questions to collect opinions and information from users.

[1463] "Reward points" are points that users can earn by answering surveys and can later be exchanged for specific services or products.

[1464] "Server" means the computer system that receives, analyzes, optimizes, and delivers Promotional Ideas.

[1465] "Smartphone Application" refers to software installed on a User's smartphone to receive promotional offers and surveys.

[1466] An "official account for a communication application" refers to an official communication channel operated by a company or organization that allows direct interaction with users.

[1467] The present invention is a system that allows advertisers to register promotion proposals, optimize those proposals, and deliver them to users. Users can earn reward points by answering surveys, and operate the system through a smartphone application.

[1468] System Overview

[1469] The server provides a management screen for company personnel to register promotion proposals. This management screen includes an interface for advertisers to enter details such as product information, target demographics, and distribution start date. The data entered by the advertiser is sent to the server, where the promotion proposal is analyzed and optimized by the generative AI model.

[1470] The server uses the generative AI model to optimize promotion ideas and send them to target users. Users receive promotion ideas and surveys through a dedicated application installed on their smartphones. This application works by users adding the official account of the communication application as a friend.

[1471] Overview of program processing

[1472] The server does the following:

[1473] 1. The advertiser registers a promotion proposal via the management screen.

[1474] 2. The registered promotion proposals are sent to the generation AI model to generate optimized promotion proposals.

[1475] 3. Deliver optimized promotional ideas to the user's smartphone application.

[1476] The smartphone application installed on the user's device performs the following operations:

[1477] 1. Add the official account of the communication application as a friend.

[1478] 2. Display promotion proposals and surveys received from the server.

[1479] 3. The user answers the survey and sends the answers to the server.

[1480] The server receives the survey responses from the user and performs the following actions:

[1481] 1. Verify the contents of the survey responses.

[1482] 2. Give reward points to users after verification.

[1483] 3. Save as a user report.

[1484] Hardware and software used

[1485] The hardware required includes a server, the user's smartphone, and the official account of the communication application. The software required includes an administration screen, a generative AI model, and a smartphone application. Specific examples include an application developed in Python, the LINE API, and a generative AI model.

[1486] Specific examples

[1487] For example, if Company A wants to run a free sample campaign for a new product, it enters a promotion idea into the admin screen. The server optimizes this information using a generative AI model and distributes it to target users. Users receive the promotion idea and a survey through a smartphone application, and by answering the survey, they can earn reward points. These points can be viewed and used in the user's LINE Wallet.

[1488] Prompt Sentence Examples

[1489] "Use a generative AI model to optimize promotional ideas for cosmetics for women in their 30s. Generate optimal promotional ideas and questionnaires based on behavioral data of the target demographic."

[1490] As described above, the present invention is a system that realizes efficient advertisement distribution while providing benefits to both advertisers and users.

[1491] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1492] Step 1:

[1493] The advertiser enters the promotion proposal into the management screen. The management screen provides an interface for entering details such as product information, target demographic, and distribution start date. After input, the promotion proposal is sent to the server. Input: Detailed data of the promotion proposal. Output: Promotion proposal data sent to the server.

[1494] Step 2:

[1495] The server sends the received promotion proposal to the generative AI model, which analyzes the promotion proposal and generates a promotion optimized for the target demographic. Input: Promotion proposal data. Output: Optimized promotion proposal.

[1496] Step 3:

[1497] The server receives the optimized promotion offer and delivers it to the user's smartphone application. Input: Optimized promotion offer. Output: Promotion offer sent to the user's smartphone application.

[1498] Step 4:

[1499] The user opens the application installed on their smartphone. The application adds the official account of the communication application as a friend and displays the promotion proposals and surveys received from the server. Input: Promotion proposals and surveys received from the server. Output: Displayed promotion proposals and surveys.

[1500] Step 5:

[1501] Users answer the survey and send their answers to the server via a smartphone application. Input: User's survey response data. Output: Survey response data sent to the server.

[1502] Step 6:

[1503] The server receives the survey responses from the user and verifies the responses. Once the verification is complete, reward points are awarded to the user. Input: User's survey response data. Output: Verified data and reward points.

[1504] Step 7:

[1505] The server stores the survey results as a user report. Input: Survey data after validation. Output: Stored survey result report.

[1506] 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.

[1507] This invention is a system that optimizes corporate promotional ideas for users and delivers them to them, allows users to earn points by answering questionnaires, and improves the effectiveness of promotions by using an emotion engine that recognizes users' emotions. This system is highly convenient for both advertisers and users, and realizes effective advertising delivery.

[1508] System Overview

[1509] The system consists of an advertiser terminal, a user terminal, a server, and an emotion engine. Advertisers register promotion proposals, and the server generates optimized promotions. Users add the LINE official account as a friend and receive individually optimized promotions and surveys. When users answer the survey, the server receives the answers and awards reward points after verification. The emotion engine then analyzes the user's emotions and optimizes the promotion proposals based on this information.

[1510] Program processing flow

[1511] 1. Advertiser terminal: Advertisers log in to a dedicated management screen and register new promotion proposals. The registered information includes product information, target demographics, campaign start date, etc. Once the promotion proposal is submitted, the data is sent to the server.

[1512] 2. Server: The server sends the received promotion proposal data to the generation AI model and emotion engine for content analysis and optimization. The generation AI model generates the most effective promotion for the target demographic, and the emotion engine analyzes user emotion data and feeds that information back to the generation AI model.

[1513] 3. Server: Generates an optimized promotion proposal and stores it in the database. Sends a confirmation to the advertiser, who can review the proposal and make any necessary adjustments. After final confirmation, schedules the launch of distribution.

[1514] 4. User device: The user adds the LINE Official Account as a friend. Once the friend addition is complete, the user profile data is sent to the server.

[1515] 5. Generative AI model: Analyzes user profile data and generates individually optimized promotional ideas and surveys, taking into account the user's age, gender, past behavioral data, etc.

[1516] 6. Emotion Engine: Analyzes user facial expressions, voice, and text data to recognize emotions and send the results to the generative AI model, which then uses this information to further optimize promotion ideas and surveys.

[1517] 7. Server: The optimized promotion proposals and corresponding questionnaires are stored in the database and sent to users, who then receive notifications and answer the questionnaires.

[1518] 8. User terminal: When the user answers and submits the questionnaire, the data is sent to the server.

[1519] 9. Server: Validates the received survey responses and stores them in the database. After validation, reward points are awarded to the user.

[1520] 10. User device: Users can check their points in LINE Wallet and use them as needed. Points can be used for purchases within LINE.

[1521] Specific examples

[1522] Example 1: New Product Campaign

[1523] Advertisers plan a free sample campaign for a new product and register the promotion proposal on a dedicated management screen. The server sends the received promotion proposal to a generative AI model, which optimizes it for the target demographic. An optimized campaign proposal is generated, and the emotion engine also takes user emotional data into account. The advertiser confirms the proposal and sets the distribution schedule.

[1524] When a user adds a LINE official account as a friend, their profile data and emotion data are sent to the server and analyzed by the generative AI model. A new product campaign information and a survey are sent to the user, who then answers the survey. The server receives and verifies the responses and awards the user 50 points. The user can check the reward points in their LINE Wallet and use them for purchases.

[1525] In this way, the system of the present invention provides benefits to both advertisers and users while realizing efficient advertisement distribution. By combining it with an emotion engine, even more effective promotions become possible.

[1526] The processing flow will be explained below.

[1527] Step 1:

[1528] Advertiser terminal: The advertiser logs in to the dedicated management screen, enters their login ID and password, and is authenticated.

[1529] Step 2:

[1530] Advertiser's terminal: After logging in, click the Create New Promotion Proposal button. Enter promotion information (product details, target demographic, campaign period, etc.).

[1531] Step 3:

[1532] Advertiser terminal: After all input is completed, click the send button to send the promotion proposal data to the server.

[1533] Step 4:

[1534] Server: Analyzes the received promotion proposal data and sends it to the generative AI model and emotion engine.

[1535] Step 5:

[1536] Generative AI model: Analyzes promotional proposal data and generates segment-optimized promotional proposals, taking into account the interests and preferences of target users.

[1537] Step 6:

[1538] Emotion engine: Analyzes input data about promotion ideas and extracts background emotional information (e.g., past reactions and reviews). Based on this, it creates emotional data and feeds it back to the generative AI model.

[1539] Step 7:

[1540] Generative AI model: Taking into account the received emotional data, it re-optimizes promotional suggestions, reflecting what advertising content will be most effective when the user is in a particular emotional state.

[1541] Step 8:

[1542] Server: Stores the optimized promotion proposal in a database and sends a confirmation to the advertiser.

[1543] Step 9:

[1544] Advertiser terminal: The advertiser checks the notification and reviews the optimized promotion plan on a dedicated management screen. They make any necessary adjustments and, after final confirmation, schedule the launch of the promotion.

[1545] Step 10:

[1546] User device: The user adds the LINE Official Account as a friend. Once the friend addition is complete, the user receives a notification that the friend addition is complete.

[1547] Step 11:

[1548] Server: Once the friend registration is confirmed, user profile data is generated and sent to the generative AI model.

[1549] Step 12:

[1550] Generative AI model: Analyzes user profile data to generate individually optimized promotion ideas and surveys. It also takes into account real-time emotional data from the emotion engine to generate surveys with optimal timing and content.

[1551] Step 13:

[1552] Server: Stores the generated optimized promotion proposals and surveys in a database and delivers them to users.

[1553] Step 14:

[1554] User device: The user receives a notification and answers the survey. Once the answers are complete, the user clicks the submit button to send the answers to the server.

[1555] Step 15:

[1556] Server: Receives the survey responses sent by users, stores them in a database, and verifies the responses.

[1557] Step 16:

[1558] Server: After the answer is verified, the server grants reward points to the user's account and sends a notification of the grant to the user's device.

[1559] Step 17:

[1560] User device: The user opens the LINE Wallet function and checks the points they have received. Points can be used for purchases and services within LINE.

[1561] Step 18:

[1562] Server: Records point usage history and updates user data.

[1563] Through the above processing steps, this system not only realizes effective and efficient ad delivery and reward allocation for both advertisers and users, but also enables even more personalized promotions by combining it with an emotion engine.

[1564] Example 2

[1565] 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."

[1566] In modern advertising, it is important for advertisers to efficiently deliver promotions that are optimized for specific target demographics. However, conventional systems have difficulty achieving detailed optimization based on individual user profiles, and are unable to deliver promotions that take user emotions into account. As a result, promotions are not as effective as they could be, making it difficult to achieve satisfactory results for both advertisers and users.

[1567] 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 a means for a company representative to register a promotion plan, a means for running a generative AI model to optimize the registered promotion plan, and a means for analyzing user emotion data using an emotion analysis engine and using the results to optimize the promotion. This enables more effective distribution of promotions to the target demographic.

[1568] "Company Representative" means the advertiser or marketing representative who is responsible for registering and managing promotion proposals.

[1569] A "promotion proposal" is a plan or proposal for promoting a product or service to consumers, and includes the content of the advertisement and a distribution schedule.

[1570] A "generative AI model" is a system that uses artificial intelligence to optimize promotional ideas, such as a text generation model or a machine learning algorithm.

[1571] An "emotion analysis engine" is software or algorithms for analyzing a user's emotions, and uses techniques such as facial expression analysis, voice analysis, and text analysis to understand the user's emotional state.

[1572] "User" refers to the consumer or customer who receives the promotion and responds to the survey.

[1573] A "survey" is a list of questions to gather user feedback, and is composed of multiple choice answers and free-form responses.

[1574] "Reward points" are incentives that users can receive by answering surveys, and can be used as electronic money or coupons, for example.

[1575] A "communication application account" is an account for a communication tool used on a smartphone or computer, which allows you to send and receive messages and add friends.

[1576] The present invention is a system that allows advertisers to register promotion proposals, delivers promotions optimized by a generative AI model and a sentiment analysis engine to users, and allows users to earn points by answering surveys. A specific embodiment of this system will be described.

[1577] System configuration

[1578] This system consists of an advertiser terminal, a user terminal, a server, a generative AI model, a sentiment analysis engine, and a database. The advertiser terminal and user terminal are general-purpose PCs or smartphones, and the server is located in a cloud environment.

[1579] Program processing explanation

[1580] Advertiser promotion proposal registration

[1581] Advertiser Device:

[1582] Advertisers log in to a dedicated management screen and register new promotion ideas, including product information, target demographics, and campaign start date.

[1583] For example, if you are registering a promotional proposal for a new shampoo product, you would enter "new shampoo" as the product information, "women in their 20s" as the target demographic, and "May 1, 2023" as the campaign start date.

[1584] Once registration is complete, the data is sent to the server.

[1585] Optimizing promotion ideas

[1586] server:

[1587] The server sends the received promotion proposal data to the generation AI model and sentiment analysis engine.

[1588] The generative AI model (e.g., GPT-3) generates an optimized promotion based on the received promotion proposal. The generative AI model is given a prompt like this:

[1589] Please optimize a shampoo campaign proposal aimed at women in their 20s.

[1590] The sentiment analysis engine analyzes user emotional data and feeds the results back into the generative AI model.

[1591] Sentiment analysis and promotion optimization

[1592] Sentiment Analysis Engine:

[1593] The sentiment analysis engine analyzes users' facial expressions, voice, and text data to recognize their emotions. For example, if a user responded positively to a previous promotion, it will provide positive feedback to the generative AI model.

[1594] The server receives the emotion data and sends it to the generative AI model.

[1595] Advertiser validation and delivery schedule setting

[1596] server:

[1597] An optimized promotion plan is generated and stored in a database.

[1598] Send the advertiser a confirmation of the optimized proposal.

[1599] Advertisers can check the optimization suggestions on the management screen, make any necessary adjustments, and then press the "Confirm" button to set the delivery schedule.

[1600] Promotion ideas and survey distribution

[1601] User device:

[1602] A user adds an official account of a communication application as a friend. Once the friend registration is complete, the user profile data (e.g., LINE ID, age, gender) is sent to the server.

[1603] The server sends user profile data to a generative AI model to generate individually optimized promotional ideas and surveys.

[1604] The server stores the optimized promotion proposals and corresponding questionnaires in a database and delivers them to users.

[1605] Answer surveys and receive reward points

[1606] User device:

[1607] The user answers the questionnaire and presses the send button, and the questionnaire response data is sent to the server.

[1608] server:

[1609] The server verifies the received survey responses and stores them in a database.

[1610] After verification, reward points will be awarded to the user and a notification will be sent.

[1611] User device:

[1612] Users can check their points in the wallet within the communication application and use them as electronic money, for example.

[1613] This embodiment allows advertisers to distribute effective promotions, and users can answer corresponding surveys and receive rewards. Furthermore, by using a sentiment analysis engine, optimization can be performed taking into account user sentiment data, further improving the effectiveness of promotions.

[1614] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1615] Step 1:

[1616] Advertiser promotion proposal registration

[1617] Advertiser Device:

[1618] Advertisers log in to a dedicated management screen and register new promotion proposals.

[1619] Input: Product information, target demographic, campaign start date, etc.

[1620] Data processing: These input data are organized into a single data package.

[1621] Output: Promotion proposal data sent to the server.

[1622] Specific actions: The advertiser enters product information for the "new shampoo," the target demographic of "women in their 20s," and "May 1, 2023" as the campaign start date, and clicks the submit button.

[1623] Step 2:

[1624] Optimizing promotion ideas

[1625] server:

[1626] The server sends the received promotion proposal data to the generation AI model and sentiment analysis engine.

[1627] Input: Promotion proposal data.

[1628] Data processing: Generate prompts to be passed to the generative AI model. For example, "Please optimize the shampoo campaign proposal for women in their 20s."

[1629] Output: Optimized promotion ideas returned by the generative AI model. Sentiment data feedback from the sentiment analysis engine.

[1630] Specific operation: The generative AI model optimizes promotional proposals, and the sentiment analysis engine analyzes user sentiment data and feeds the results back to the generative AI model.

[1631] Step 3:

[1632] Sentiment analysis and promotion optimization

[1633] Sentiment Analysis Engine:

[1634] The server uses an emotion analysis engine to analyze the user's facial expressions, voice, and text data.

[1635] Input: User facial expression, voice, and text data.

[1636] Data processing: Apply sentiment analysis algorithms to classify emotional states, e.g., "positive," "negative," etc.

[1637] Output: Send the analysis results to the generative AI model.

[1638] Specific behavior: For example, if a user shows a positive facial expression in response to a previous promotion, the reaction is classified as positive and fed back to the generative AI model.

[1639] Step 4:

[1640] Advertiser validation and delivery schedule setting

[1641] server:

[1642] Generate optimized promotion proposals, store them in the database, and send a confirmation to the advertiser.

[1643] Input: Optimized promotion ideas, sentiment data.

[1644] Data processing: Convert data into a format to be saved in the database. Generate a notification message to the advertiser.

[1645] Output: Database storage, advertiser notification.

[1646] Specific operation: The server stores the optimized promotion proposal in the database and sends a notification message to the advertiser requesting confirmation of the optimization proposal.

[1647] Step 5:

[1648] User's official account registration

[1649] User device:

[1650] A user adds the official account of a communication application as a friend.

[1651] Input: User's account information (e.g. LINE ID), age, gender.

[1652] Data processing: Assemble user profile data into a single data package.

[1653] Output: Sends user profile data to the server.

[1654] Specific operation: A user adds an official account of a communication application as a friend, and upon completion of the registration, the profile data is automatically sent to the server.

[1655] Step 6:

[1656] Analyzing user profile data

[1657] server:

[1658] The server sends the received user profile data to the generative AI model for analysis.

[1659] Input: User profile data.

[1660] Data processing: Generative AI models analyze profile data to generate individually optimized promotional ideas and surveys.

[1661] Output: Individually optimized promotion ideas, surveys.

[1662] Specific operation: Based on user profile data, the generative AI model automatically generates individually optimized promotion ideas and surveys.

[1663] Step 7:

[1664] Promotion ideas and survey distribution

[1665] server:

[1666] Optimized promotion ideas and surveys are stored in a database and distributed to users.

[1667] Input: individually optimized promotion ideas, surveys.

[1668] Data processing: storing data in a database and generating messages for delivery to users.

[1669] Output: User notification, database save.

[1670] Specific operation: The server stores the optimized promotion proposals and surveys in a database and delivers them to the user as messages.

[1671] Step 8:

[1672] User survey responses

[1673] User device:

[1674] The user answers the survey and presses the submit button.

[1675] Input: User's survey responses.

[1676] Data processing: Survey response data is sent to the server.

[1677] Output: Survey response data sent to the server.

[1678] Specific operation: The user answers the questionnaire and presses the send button to send the response data to the server.

[1679] Step 9:

[1680] Survey response verification and point awarding

[1681] server:

[1682] The server verifies the received survey responses and stores them in a database.

[1683] Input: User survey response data.

[1684] Data processing: Validating response data and storing it in a database.

[1685] Output: Reward points awarded to user and notification.

[1686] Specific operation: The server verifies the survey response data, stores it in the database, and then awards reward points to the user and sends a notification.

[1687] Step 10:

[1688] Check and use reward points

[1689] User device:

[1690] Users can check their points in the wallet within the communication application and use them as needed.

[1691] Input: Reward point award notification from the server.

[1692] Data processing: Update the points balance in the wallet.

[1693] Output: Point balance confirmation screen.

[1694] Specific operation: The user checks the reward points in the wallet and uses them as electronic money.

[1695] (Application example 2)

[1696] 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 robot 414 will be referred to as a "terminal."

[1697] In conventional advertising systems, ad optimization was limited to the user's basic profile and behavioral data, and promotions did not reflect the user's emotional state. This limited the effectiveness of promotions. Also, while there were reward systems based on survey responses, these did not provide effective feedback to improve the user experience.

[1698] The specification processing by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes a means for a company representative to register promotion proposals, a means for operating a generative AI model to optimize the registered promotion proposals, a means for delivering the optimized promotion proposals to users, a means for receiving and verifying questionnaire responses from users, a means for awarding reward points to users, a means for operating an emotion engine that recognizes user emotions, and a means for feeding back emotion data to the generative AI model. This enables optimal promotions that reflect the user's emotional state and improves advertising effectiveness.

[1699] "Company Representative" means a member of an organization responsible for registering a Promotion Proposal.

[1700] "Promotion Proposal" means a plan that describes the implementation and content of an advertisement or campaign.

[1701] "Generative AI model" refers to an artificial intelligence algorithm that generates optimized promotional ideas based on input data.

[1702] "Optimized Promotion Ideas" means advertising or campaign content that is tailored based on user characteristics and emotional data using generative AI models.

[1703] "User" refers to a consumer who receives a company's promotion and completes a survey.

[1704] A "survey" is a form of survey that asks users questions related to a promotion proposal.

[1705] "Emotion Engine" refers to a software or hardware system that provides technology for analyzing a user's emotional state.

[1706] "Emotional data" refers to information about a user's emotional state analyzed based on facial expressions, voice, text, etc.

[1707] A "communication app" is an application that allows users to register friends and receive promotions and surveys.

[1708] This invention provides a mechanism for realizing a system that delivers optimized corporate promotional ideas to users and allows them to earn points by answering questionnaires. It also uses an emotion engine to recognize users' emotions and improve the effectiveness of promotions.

[1709] The system consists of an administration screen where company representatives can register promotion ideas, a generative AI model, an emotion engine, a server, and a user terminal.

[1710] Company personnel use the management screen to register promotion proposals. The management screen runs on a web browser and allows users to enter product information, target demographics, campaign start date, etc. This promotion proposal data is then sent to the server.

[1711] The server sends the received promotion proposal data to the generative AI model to generate optimized promotion proposals. The generative AI model generates promotions that are most effective for the target demographic and further optimizes them using feedback from the emotion engine.

[1712] The emotion engine recognizes emotions by analyzing the user's facial expressions, voice, and text data. This is done using the smartphone's camera and microphone, as well as generic services from Microsoft and Google. For example, by using the "Microsoft Azure Emotion API" or "Google Cloud Vision API," it is possible to analyze the user's emotional state in real time.

[1713] The optimized promotion ideas are managed by the server and sent to the communication app accounts of users who have registered them as friends. Users receive the promotion ideas and surveys through the app and then answer the surveys.

[1714] When a user answers a survey, the data is sent to the server. After the server verifies the received data, it grants reward points to the user. The user can view and use the reward points within the communication app.

[1715] As a concrete example, consider a situation where a new product campaign is being conducted. A company representative plans a sample campaign for the new product and registers the promotion proposal in a dedicated management screen. The following example can be considered.

[1716] Example prompt: (New product campaign) A free sample of our new shampoo is now available! Try this shampoo and answer a simple questionnaire to receive 500 points! These points can be used in the in-app store. Answer the questions and get points!

[1717] When a user receives this promotional information, their emotions are recognized from their facial expressions and voice, and a survey optimized for them is delivered. By answering the survey, they can earn reward points. In this way, promotions that reflect the user's emotional state can be optimally delivered.

[1718] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1719] Step 1:

[1720] Company personnel use the management screen to register promotion proposals, including product information, target demographics, and campaign start date. This data is then sent to the server.

[1721] Step 2:

[1722] The server analyzes the received promotion proposal data and sends it to the generative AI model, which processes the data to generate the most effective promotion proposal for the target demographic and outputs the optimized promotion proposal.

[1723] Step 3:

[1724] The emotion engine uses the smartphone's camera and microphone to analyze the user's facial expressions and voice, generating emotion data using, for example, the Microsoft Azure Emotion API or Google Cloud Vision API, and then sends the resulting emotion data to a server.

[1725] Step 4:

[1726] The server feeds back the emotion data received from the emotion engine to the generative AI model, which then further optimizes the promotion proposals.

[1727] Step 5:

[1728] The optimized promotion ideas are stored in a database by the server, which then distributes them to the communication app accounts that the user has registered as friends.

[1729] Step 6:

[1730] Users receive optimized promotional offers and surveys through the app, including promotional text (e.g., new shampoo samples are now available!) and survey questions.

[1731] Step 7:

[1732] When a user answers a questionnaire, the answer data is sent from the app to the server, which validates the input data and stores the validation results in a database.

[1733] Step 8:

[1734] The server will award reward points to the user based on the verified survey responses, which will be added to the user's reward account.

[1735] Step 9:

[1736] Users can check the points they have earned in their rewards account within the communication app and use them in in-app stores, etc.

[1737] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice 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 voice data.

[1738] 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.

[1739] 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 robot 414.

[1740] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1741] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1742] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1743] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1744] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1745] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1746] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1747] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1748] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1749] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1750] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[1751] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1752] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1753] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1754] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1755] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1756] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1757] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1758] The following is further disclosed regarding the above embodiment.

[1759] (Claim 1)

[1760] A means for company representatives to register promotion proposals,

[1761] means for operating a generative AI model to optimize the registered promotion ideas;

[1762] A means of delivering optimized promotional ideas to users;

[1763] a means for receiving and verifying survey responses from users;

[1764] and means for awarding reward points to the user.

[1765] (Claim 2)

[1766] Feeds user profile data into a generative AI model

[1767] The system of claim 1, wherein the system generates individually optimized promotional proposals and surveys.

[1768] (Claim 3)

[1769] When users add your LINE account as a friend,

[1770] 10. The system of claim 1, wherein the profile data is analyzed.

[1771] "Example 1"

[1772] (Claim 1)

[1773] A means for company representatives to register promotion proposals,

[1774] means for operating a generative AI model to optimize the registered promotion ideas;

[1775] A means to send user profile data to a generative AI model to generate personalized promotion ideas and surveys optimized for the target audience;

[1776] A means of delivering optimized promotional ideas and surveys to users;

[1777] a means for receiving and verifying survey responses from users;

[1778] and means for awarding reward points to the user.

[1779] (Claim 2)

[1780] 10. The system of claim 1, wherein the profile data is analyzed as users register friends via a communication application.

[1781] (Claim 3)

[1782] The system of claim 1, wherein the generative AI model generates promotion ideas and surveys optimized for the target demographic based on the user's profile data.

[1783] "Application Example 1"

[1784] (Claim 1)

[1785] A means for company representatives to register promotion proposals,

[1786] means for operating a generative AI model to optimize the registered promotion ideas;

[1787] A means of delivering optimized promotional ideas to users;

[1788] a means for receiving and verifying survey responses from users;

[1789] a means for awarding reward points to users;

[1790] a means including a smartphone application installed on a user's terminal;

[1791] The system includes a means for a user to receive and respond to promotion proposals and surveys via an application installed on a smartphone.

[1792] (Claim 2)

[1793] Feeds user profile data into a generative AI model

[1794] The system of claim 1, wherein the system generates individually optimized promotional proposals and surveys.

[1795] (Claim 3)

[1796] When users add the official account of a communication application as a friend,

[1797] 10. The system of claim 1, wherein the profile data is analyzed.

[1798] "Example 2: Combining Emotion Engines"

[1799] (Claim 1)

[1800] A means for company representatives to register promotion proposals,

[1801] means for operating a generative AI model to optimize the registered promotion ideas;

[1802] A means of analyzing user emotional data using an emotion analysis engine and using the results to optimize promotions;

[1803] A means of delivering optimized promotional ideas to users;

[1804] a means for receiving and verifying survey responses from users;

[1805] and means for awarding reward points to the user.

[1806] (Claim 2)

[1807] Feeds user profile data into a generative AI model

[1808] The system of claim 1, wherein the system generates individually optimized promotional proposals and surveys.

[1809] (Claim 3)

[1810] When a user registers a communication application account as a friend,

[1811] 10. The system of claim 1, wherein the profile data and the sentiment data are analyzed.

[1812] "Application example 2 when combining emotion engines"

[1813] (Claim 1)

[1814] A means for company representatives to register promotion proposals,

[1815] means for operating a generative AI model to optimize the registered promotion ideas;

[1816] A means of delivering optimized promotional ideas to users;

[1817] a means for receiving and verifying survey responses from users;

[1818] a means for awarding reward points to users;

[1819] means for operating an emotion engine that recognizes the emotions of a user;

[1820] A means of feeding back emotion data into the generative AI model; and

[1821] A system including:

[1822] (Claim 2)

[1823] Feeds user profile data into a generative AI model

[1824] The system of claim 1, wherein the system generates individually optimized promotional proposals and surveys.

[1825] (Claim 3)

[1826] When a user registers a communication app account as a friend,

[1827] 10. The system of claim 1, wherein the profile data is analyzed. [Explanation of symbols]

[1828] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. A means for company representatives to register promotion proposals, means for operating a generative AI model to optimize the registered promotion ideas; A means of delivering optimized promotional ideas to users; a means for receiving and verifying survey responses from users; and means for awarding reward points to the user.

2. Feeds user profile data into a generative AI model The system of claim 1 , wherein the system generates individually optimized promotional offers and surveys.

3. When users add your LINE account as a friend, The system of claim 1 , wherein the profile data is analyzed.

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