system

Abstract

We provide the system. [Solution] A means for receiving a period and customer ID specified by the user, A means for extracting relevant sales data and profit data from a database, A method for organizing the extracted data and generating graphs for each product category, A means of providing the generated graph to the user, A system that includes this.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, and includes steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a 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

Summary of the Invention

Problems to be Solved by the Invention

[0004] In a conventional customer management system, there is a lack of means for easily visualizing sales and profit trends during a specified period, and there is also a problem that it is difficult to timely confirm transaction materials and contract renewal months. In addition, requests from customers via email cannot be efficiently taskified and automatically reflected in the calendar, and conference room reservations and online meeting settings often have to be done manually, resulting in a problem of reduced work efficiency.

Means for Solving the Problems

[0005] To solve the above problems, the present invention provides the following means.

[0006] 1. A system that receives a specified period and customer ID from the user, extracts the corresponding sales and profit data from the database, organizes the extracted data, generates graphs for each product category, and provides the generated graphs to the user.

[0007] 2. A system that receives a customer ID, retrieves the corresponding transaction product list and contract renewal month information from the database, and provides the retrieved information to the user.

[0008] 3. A system that monitors the mailbox, analyzes requests from received emails, registers the analyzed requests as tasks, and automatically registers the registered tasks in the calendar.

[0009] 4. A system that receives meeting date, time, and number of attendees, checks the availability of meeting rooms, automatically reserves a suitable meeting room, and provides the reservation result to the user.

[0010] 5. A system that receives the meeting date and time and participant list, sets up an online meeting, retrieves the details of the set up meeting, and notifies participants of the meeting details.

[0011] These measures can significantly improve the efficiency of customer management operations.

[0012] A "customer ID" is a unique identifier used to identify a customer.

[0013] "Sales data" refers to data showing the total revenue of a specific customer within a specified period.

[0014] "Profit data" refers to data showing the net profit of a specific customer within a specified period, calculated by subtracting total expenses from total revenue.

[0015] A "database" is a system for systematically storing and managing various data related to customers.

[0016] "Merchandise" refers to the goods and services that a company provides to its customers.

[0017] A "graph" is a chart for visually representing each data point.

[0018] A "task" refers to a series of activities or operations for achieving a specific goal.

[0019] A "calendar" is a system for managing dates and times, including those that visually display events and tasks.

[0020] A "meeting room" is a dedicated room in a physical space for holding meetings and consultations.

[0021] An "online meeting" refers to a virtual meeting conducted via the Internet.

[0022] [[ID=2,1]] "Zoom" is one of the digital platforms for conducting online meetings and webinars.

[0023] An "API" is an interface for linking different software and systems.

Brief Description of Drawings

[0024] [Figure 1] It is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] It is a conceptual diagram showing an example of the main functions of a data processing device and a smart device according to the first embodiment. [Figure 3] It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] It is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6]This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] This is a sequence diagram showing the processing flow of the data processing system in Example 2, which incorporates an emotion engine. [Figure 14] This is a sequence diagram showing the processing flow of the data processing system in Application Example 2, which combines an emotion engine. [Modes for carrying out the invention]

[0025] Hereinafter, an example of an embodiment of the system relating to the technology of this disclosure will be described with reference to the attached drawings.

[0026] First, let's explain the terminology used in the following explanation.

[0027] In the following embodiments, the signed processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Furthermore, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include CPU (Central Processing Unit), GPU (Graphics Processing Unit), GPGPU (General-Purpose computing on Graphics Processing Units), and APU (Accelerated Processing Unit).

[0028] In the following embodiments, signed RAM (Random Access Memory) is a memory that temporarily stores information and is used as work memory by the processor.

[0029] In the following embodiments, the signed storage is one or more non-volatile storage devices that store various programs and various parameters. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes.

[0030] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0031] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0032] [First Embodiment]

[0033] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0034] As shown in Figure 1, the 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.

[0035] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0036] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0037] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and 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.

[0038] 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 perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0039] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0040] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0041] As shown in Figure 2, in the data processing device 12, a specific processing 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" related to the technology of this 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 according to the specific processing program 56 executed on the RAM 30.

[0042] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0043] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0044] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0045] This invention is a system for streamlining customer management operations, including managing sales and profit data for a specified period, confirming transaction items and contract renewal months, converting requests from emails into tasks and automatically registering them in a calendar, automatically reserving meeting rooms, and automatically setting up online meetings.

[0046] Extract graphs showing sales and profit trends for each customer over a specified period (even by product category).

[0047] System operation:

[0048] 1. The user enters the period (start date and end date) and customer ID via the terminal.

[0049] 2. The terminal sends the entered information to the server as a request.

[0050] 3. The server receives the request, accesses the database, and extracts sales and profit data for the specified period.

[0051] 4. The server organizes the extracted data by product category and uses a graph generation library to create graphs showing the trends in sales and profits.

[0052] 5. The generated graph is sent back from the server to the terminal, and the user can view the graph on the terminal.

[0053] Specific example:

[0054] For example, if a user wants to see the sales and profit trends for customer ID 123 from January 1, 2023 to March 31, 2023, they would enter the period and customer ID into their device and send a request to the server. The server would then extract the relevant data from the database, organize it by product category, and generate a graph. The generated graph would then be displayed on the user's device.

[0055] Confirmation of trading products and contract renewal month

[0056] System operation:

[0057] 1. The user enters the customer ID they wish to check from their device and sends a request to the server.

[0058] 2. The server accesses the database to retrieve the customer's trading product list and contract renewal month information.

[0059] 3. The server sends the acquired information back to the user's terminal, and the user can view and confirm that information on the screen.

[0060] Specific example:

[0061] For example, if a user wants to check the list of products traded and the contract renewal month for customer ID 456, they enter the customer ID into their terminal and send a request to the server. The server retrieves the relevant information from the database and sends it back to the user's terminal. The user can then view the displayed information.

[0062] Customer requests received via email are converted into tasks and automatically registered in the calendar.

[0063] System operation:

[0064] 1. The server periodically monitors the email inbox.

[0065] 2. If there is a new email, the server analyzes its contents using natural language processing (NLP) and extracts the request.

[0066] 3. The server registers the extracted requests as tasks in the task management system.

[0067] 4. Registered tasks are automatically added to Google Calendar.

[0068] Specific example:

[0069] For example, if a customer sends an email requesting "Please schedule a meeting for next Monday," the server receives the email, analyzes its contents, and registers the meeting request as a task. This task is automatically added to Google Calendar, and the user can then view the appointment on their calendar.

[0070] Automated meeting room booking

[0071] System operation:

[0072] 1. The user enters the meeting date and time and the required number of participants from their device.

[0073] 2. The terminal sends the input information to the server.

[0074] 3. The server accesses the meeting room management system or database to check availability based on the specified date, time, and number of people.

[0075] 4. The server automatically reserves a suitable available meeting room.

[0076] 5. The reservation results are sent back from the server to the user's terminal, and the user can check the results.

[0077] Specific example:

[0078] For example, if a user wants to reserve a "meeting room for 10 people for 2 hours starting at 2:00 PM on October 15, 2023," they enter the information into their device and send it to the server. The server accesses the meeting room management system, checks availability, and then reserves a suitable meeting room. The reservation result is displayed on the user's device.

[0079] Zoom automatic setup

[0080] System operation:

[0081] 1. The user enters the meeting date and time and participant list from their device.

[0082] 2. The terminal sends the input information to the server.

[0083] 3. The server uses the Zoom API to create a new Zoom meeting.

[0084] 4. The server retrieves the meeting details (link and ID) from Zoom.

[0085] 5. The acquired meeting details will be sent via email from the server to the participant list.

[0086] Specific example:

[0087] For example, if a user wants to "set up a Zoom meeting on October 20, 2023 at 11:00 AM and send invitations to participants," they would enter that information into their device and send it to the server. The server would then use the Zoom API to create the meeting and retrieve the meeting details. After that, the server would send meeting invitation emails to the participant list. The user and participants would then receive the meeting details via email.

[0088] As described above, the system based on the present invention can automate various processes in customer management operations and significantly improve operational efficiency.

[0089] The following describes the processing flow.

[0090] Extract graphs showing sales and profit trends for each customer over a specified period (even by product category).

[0091] Processing steps:

[0092] Step 1:

[0093] The user enters the period (start and end dates) and customer ID via the device. The device then sends the entered information to the server as a request.

[0094] Step 2:

[0095] The server parses the received request and executes a query against the database based on the specified period and customer ID.

[0096] Step 3:

[0097] The server extracts the relevant sales and profit data from the database.

[0098] Step 4:

[0099] The server organizes the extracted data by product category. Sales and profit data are grouped for each product category and sorted chronologically.

[0100] Step 5:

[0101] The server uses a graph generation library to create graphs showing the trends in sales and profits. Colors and labels can be set as needed.

[0102] Step 6:

[0103] The server generates the graph as an image file or in an interactive format and sends it back to the user's terminal.

[0104] Step 7:

[0105] Users can view graphs received on their devices and check the trends in sales and profits over a specified period.

[0106] Confirmation of trading products and contract renewal month

[0107] Processing steps:

[0108] Step 1:

[0109] The user enters the customer ID they want to check on their device and sends a request to the server.

[0110] Step 2:

[0111] The server receives the request and executes a query to access the database to retrieve the customer's trading product list and contract renewal month information.

[0112] Step 3:

[0113] The server returns the list of traded products and contract renewal month information, retrieved from the database, to the user's terminal as a response.

[0114] Step 4:

[0115] Users can view the list of traded products and contract renewal month information received on their device and confirm the necessary information.

[0116] Customer requests received via email are converted into tasks and automatically registered in the calendar.

[0117] Processing steps:

[0118] Step 1:

[0119] The server periodically monitors the email inbox to detect the arrival of new emails.

[0120] Step 2:

[0121] The server analyzes the content of newly received emails using natural language processing (NLP) techniques. It extracts sentences and keywords that contain the request.

[0122] Step 3:

[0123] The server registers the extracted requests as new tasks in the task management system. Each task includes details such as the request content and deadline.

[0124] Step 4:

[0125] The server uses the Google Calendar API to automatically add tasks to the calendar based on the registered task information.

[0126] Step 5:

[0127] When a task is registered in the calendar, the server notifies the user's terminal that the task has been created and registered in the calendar.

[0128] Step 6:

[0129] Users can check their calendar on their device to see newly added tasks and appointments.

[0130] Automated meeting room booking

[0131] Processing steps:

[0132] Step 1:

[0133] The user enters the meeting date and time and the required number of participants from their device and sends a request to the server.

[0134] Step 2:

[0135] The server receives the request and accesses a system or database that manages the availability of meeting rooms to execute a query to check their availability.

[0136] Step 3:

[0137] The server retrieves a list of available meeting rooms and selects the most suitable one for the specified date, time, and number of people.

[0138] Step 4:

[0139] The server automatically reserves the selected meeting room through the reservation system.

[0140] Step 5:

[0141] Once the reservation is complete, the server will notify the user's device of the result.

[0142] Step 6:

[0143] Users can check their reservation results on their device and confirm that the meeting room has been booked.

[0144] Zoom automatic setup

[0145] Processing steps:

[0146] Step 1:

[0147] The user enters the meeting date and time and participant list from their device and sends a request to the server.

[0148] Step 2:

[0149] The server receives the request and sends a request to the Zoom server to create a new Zoom meeting using the Zoom API.

[0150] Step 3:

[0151] The server receives the meeting details (link and ID) returned from Zoom and stores that information.

[0152] Step 4:

[0153] Based on the saved meeting details, the server sends meeting invitations via email to the participants listed in the participant list.

[0154] Step 5:

[0155] Once the invitation email is sent, the server notifies the user that the Zoom meeting setup is complete.

[0156] Step 6:

[0157] Users and participants can check the meeting details in the email they receive and join the Zoom meeting at the specified date and time.

[0158] As described above, the system based on the present invention has a specific processing flow for improving the efficiency of various customer management tasks and achieves business efficiency through automation.

[0159] (Example 1)

[0160] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0161] In today's busy business environment, improving the efficiency of customer management and task management is crucial. However, traditional systems require individual tasks such as managing sales and profit data for each customer, checking transaction items and contract renewal months, converting email requests into tasks, booking meeting rooms, and setting up online meetings. This often involves manual verification and data entry, leading to inefficient operations. This increases the likelihood of human error and wastes time and resources. A system is needed to solve these problems and streamline all aspects of customer management.

[0162] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0163] In this invention, the server includes means for receiving a specified period and customer identification information from a user; means for extracting relevant sales data and profit data from an information storage device; means for organizing the extracted data and generating statistical displays by product; means for providing the generated statistical displays to the user; means for receiving the meeting date and time and participant list and creating a new meeting using a remote conferencing system; and means for notifying participants of the generated meeting details through notification means. As a result, customer management operations are centralized, and operations such as data extraction, statistical display generation, and remote meeting setup are automated, significantly improving operational efficiency.

[0164] "Specified period" refers to a time range consisting of a start date and an end date specified by the user for performing a specific action.

[0165] "Customer identification information" refers to information used to uniquely identify a specific customer, and includes customer IDs and other identifiers.

[0166] An "information storage device" is a device for storing data, and includes databases and cloud storage.

[0167] "Sales data" refers to data relating to revenue generated from sales activities within a specific period of time associated with a particular customer.

[0168] "Profit data" refers to data on net profit, which is calculated by subtracting costs from sales for a specific customer over a given period.

[0169] "Statistical display" refers to a display format such as graphs and charts that visually represent sales data and profit data.

[0170] A "remote conferencing system" is a system for setting up and managing meetings conducted remotely via the internet, and includes online conferencing services.

[0171] "Notification means" refers to a means of informing users or participants of specific information, and includes, for example, email and messaging applications.

[0172] A "product list" is a list of products that a particular customer trades.

[0173] "Contract renewal month information" refers to information about the month in which a contract with a specific customer is renewed.

[0174] A "meeting room management system" is a system used to reserve meeting rooms and check their availability.

[0175] An "electronic message box" is a box for receiving and storing emails, and it is installed on a mail server.

[0176] A "work item" is a request that has been registered as a specific task.

[0177] A "schedule" is a system for displaying and managing specific appointments or tasks in a calendar format.

[0178] A "generative AI model" is a model that uses artificial intelligence technology to automatically analyze and generate data.

[0179] A "prompt statement" is an input statement used to give specific instructions to a generative AI model.

[0180] This invention is a system designed to streamline customer management operations. This system can automate and centralize various tasks, such as managing sales and profit data for each customer, checking transaction items and contract renewal months, converting requests from emails into tasks and automatically registering them in the calendar, automatically reserving meeting rooms, and automatically setting up online meetings.

[0181] The main hardware components of this system are a server, terminals, and information storage devices. The server is responsible for processing requests, managing data, automating tasks, and providing notifications, while the terminals provide the user interface and handle information input and display. The information storage devices are used to store data such as sales data, profit data, transaction product lists, contract renewal months, tasks, and meeting room reservation status. Furthermore, software such as the Zoom API and Google Calendar API is used to set up online meetings and register them in the calendar.

[0182] Extract graphs showing sales and profit trends for each customer over a specified period (even by product category).

[0183] The user enters a specified period (start and end dates) and customer identification information via their device. The device sends this information to the server as a request. The server accesses the database and extracts sales and profit data for the specified period. Next, the server organizes the extracted data by product and creates sales and profit trend graphs using a graph generation library (e.g., Matplotlib, Chart.js). These generated graphs are sent back to the device, where the user can view them.

[0184] For example, if a user wants to view the sales and profit trends for customer ID 123 from January 1, 2023 to March 31, 2023, they would enter the period and customer ID and send a request to the server. The server would then extract the relevant data from the database, organize it by product, and generate a graph. The generated graph would then be displayed on the user's device.

[0185] Confirmation of trading products and contract renewal month

[0186] The user enters the customer identification information they wish to verify on their device and sends a request to the server. The server accesses the database and retrieves the customer's transaction product list and contract renewal month information. The retrieved information is sent back to the device, and the user can view and verify it on the screen.

[0187] As a concrete example, if a user wants to check the list of products traded and the contract renewal month for customer ID 456, they enter the customer identification information into the terminal and send a request to the server. The server retrieves the relevant information from the database and sends it back to the terminal. The user can then check the displayed information.

[0188] Requests received via email are converted into tasks and automatically registered in the calendar.

[0189] The server periodically monitors the electronic message box. If there are new messages, the server uses natural language processing (NLP) techniques to analyze the email content and extract requests. The server registers the extracted requests as work items in the task management system. These registered work items are automatically added to a calendar system such as Google Calendar.

[0190] For example, if a customer sends an email requesting "Please schedule a meeting for next Monday," the server receives the email, analyzes its contents, and registers the meeting request as a task item. This task item is automatically registered in Google Calendar, and the user can then view the appointment on their calendar.

[0191] Automated meeting room booking

[0192] The user enters the meeting date, time, and number of participants from their device. The device sends the entered information to the server. The server accesses the meeting room management system or database and checks availability based on the specified date, time, and number of participants. The server automatically reserves a suitable available meeting room and sends the result back to the device. The user can then view the result on their device.

[0193] As a concrete example, if a user wants to reserve a "meeting room for 10 people for 2 hours starting at 2:00 PM on October 15, 2023," they enter the information into their device and send it to the server. The server accesses the meeting room management system, checks the availability, and then reserves an appropriate meeting room. The reservation result is displayed on the user's device.

[0194] Zoom automatic setup

[0195] The user enters the meeting date and time and participant list from their device and sends it to the server. The server uses the Zoom API to create a new Zoom meeting and retrieves the meeting details (link and ID). The retrieved meeting details are then notified to the participant list via email or other means.

[0196] As a concrete example, if a user wants to "set up a Zoom meeting on October 20, 2023 at 11:00 AM and send invitations to participants," they would enter the meeting date and time and participant list into their device and send it to the server. The server would then use the Zoom API to create the meeting and retrieve the meeting details. After that, the server would send meeting invitation emails to the participant list. The user and participants would then receive the meeting details via email.

[0197] By implementing this invention, customer management operations can be centralized, data extraction and statistical display generation, remote meeting scheduling, and other tasks can be automated, significantly improving operational efficiency.

[0198] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0199] Extract graphs showing sales and profit trends for each customer over a specified period (even by product category).

[0200] Step 1:

[0201] The user enters the period (start and end dates) and customer identification information via their device.

[0202] Input: Period (e.g., January 1, 2023 - March 31, 2023), Customer identification information (e.g., Customer ID 123)

[0203] Output: User input data is received by the terminal.

[0204] Step 2:

[0205] The terminal generates a request containing the period and customer identification information and sends it to the server.

[0206] Input: User input data (period and customer identification information)

[0207] Output: The generated request is sent to the server.

[0208] Step 3:

[0209] The server receives the request, accesses the information storage device, and extracts sales and profit data for the specified period.

[0210] Input: Request received from the terminal, data in the information storage device.

[0211] Output: A set of sales data and profit data is extracted.

[0212] Step 4:

[0213] The server extracts data and organizes it by product. A graph generation library is then used to create graphs showing the trends in sales and profits.

[0214] Input: Extracted sales data and profit data

[0215] Output: Graphs showing sales and profit trends by product (e.g., graphs generated using Matplotlib or Chart.js)

[0216] Step 5:

[0217] The generated graph is sent back from the server to the terminal, allowing the user to view the graph on their terminal.

[0218] Input: Generated graph

[0219] Output: The graph will be displayed on the terminal.

[0220] Confirmation of trading products and contract renewal month

[0221] Step 1:

[0222] The user enters the customer identification information they wish to verify from their device.

[0223] Input: Customer identification information (e.g., Customer ID 456)

[0224] Output: User input data is received by the terminal.

[0225] Step 2:

[0226] The terminal generates customer identification information as a request and sends it to the server.

[0227] Input: Customer identification information

[0228] Output: The generated request is sent to the server.

[0229] Step 3:

[0230] The server receives the request and retrieves the customer's trading product list and contract renewal month information from its data storage device.

[0231] Input: Request received from the terminal, data in the information storage device.

[0232] Output: A list of traded products and contract renewal month information are retrieved.

[0233] Step 4:

[0234] The acquired information is sent back from the server to the terminal, and the user can view the information on the terminal.

[0235] Input: List of traded products and contract renewal month information

[0236] Output: Information is displayed on the terminal.

[0237] Requests received via email are converted into tasks and automatically registered in the calendar.

[0238] Step 1:

[0239] The server periodically monitors the electronic message box.

[0240] Input: Status of the electronic message box

[0241] Output: Checks for the presence of new messages.

[0242] Step 2:

[0243] If there is a new message, the server uses natural language processing (NLP) techniques to analyze the email content and extract the request.

[0244] Input: Content of the newly received email

[0245] Output: Request details are extracted.

[0246] Step 3:

[0247] The server registers the extracted requests as work items in the task management system.

[0248] Input: Request

[0249] Output: The work item is registered in the task management system.

[0250] Step 4:

[0251] Registered work items are automatically added to calendar systems such as Google Calendar.

[0252] Input: Work item

[0253] Output: Events registered in the calendar

[0254] Automated meeting room booking

[0255] Step 1:

[0256] The user enters the meeting date, time, and number of participants from their device.

[0257] Input: Meeting date and time (e.g., October 15, 2023, 2:00 PM for 2 hours), Number of participants (e.g., 10 people)

[0258] Output: User input data is received by the terminal.

[0259] Step 2:

[0260] The terminal generates the input information as a request and sends it to the server.

[0261] Input: User input data (meeting date and time, number of participants)

[0262] Output: The generated request is sent to the server.

[0263] Step 3:

[0264] The server accesses the meeting room management system or information storage device to check availability based on the specified date, time, and number of people.

[0265] Input: Requests received from terminals, meeting room management system, or data stored in information storage devices.

[0266] Output: Meeting room availability is checked.

[0267] Step 4:

[0268] The server automatically reserves a suitable available meeting room and sends the reservation result back to the terminal.

[0269] Input: Meeting room availability

[0270] Output: The reservation result is sent back to the device and displayed.

[0271] Zoom automatic setup

[0272] Step 1:

[0273] The user inputs the meeting date and time and the participant list from the terminal.

[0274] Input: Meeting date and time (e.g., October 20, 2023, 11:00), participant list

[0275] Output: The input data of the user is received by the terminal.

[0276] Step 2:

[0277] The terminal generates the input information as a request and sends it to the server.

[0278] Input: Meeting date and time and participant list

[0279] Output: The generated request is sent to the server.

[0280] Step 3:

[0281] The server uses the Zoom API to create a new Zoom meeting and obtains the meeting details (link and ID).

[0282] Input: The request received from the terminal

[0283] Output: The details of the Zoom meeting

[0284] Step 4:

[0285] The generated meeting details are notified from the server to the participant list through the notification means.

[0286] Input: The details of the Zoom meeting

[0287] Output: The meeting details are notified to the participants.

[0288] The above is the flow for each step of the program processing of this system.

[0289] (Application Example 1)

[0290] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0291] In traditional customer management operations, tasks such as managing sales and profit data, checking transaction products and contract renewal months, and registering tasks on a calendar were performed manually, requiring a significant amount of time and effort. Furthermore, it was difficult to check and manage this information in real time using smart devices, thus creating a need for improved operational efficiency.

[0292] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0293] In this invention, the server includes means for receiving a specified period and customer ID from the user, means for extracting relevant sales data and profit data from a database, means for organizing the extracted data and generating graphs for each product, means for providing the generated graphs to the user, and means for visualizing the sales data and profit data so that the user can efficiently check them via a smart device. This streamlines customer management operations that were previously performed manually, and enables real-time data confirmation and management using smart devices.

[0294] A "user" is someone who operates and gives instructions to a system.

[0295] A "customer ID" is a unique identification number used to identify a specific customer.

[0296] A "database" is a system that stores a collection of data and allows for the efficient retrieval and extraction of necessary information.

[0297] "Sales data" refers to information regarding the sales amount of a product over a specific period.

[0298] "Profit data" refers to information regarding profit obtained by subtracting expenses from sales during a specific period.

[0299] "Smart device" is a general term for electronic devices that can be connected to the Internet and provide various information to users.

[0300] "Graph generation" is a process of creating diagrams for visually representing data.

[0301] "Merchandise" refers to goods and services that are sold.

[0302] "Traded merchandise" refers to goods and services traded with customers.

[0303] "Contract renewal month" refers to the month in which an existing contract is scheduled to be renewed.

[0304] "Mailbox" is a virtual inbox for receiving emails.

[0305] "Task management system" is a system for registering, tracking, and managing work and tasks.

[0306] "Natural language processing" is a technology for computers to understand, analyze, and generate human language.

[0307] "Calendar" is an application for managing dates and schedules.

[0308] This invention is a system that improves customer management operations such as management of sales data and profit data, confirmation of traded merchandise and contract renewal months, task management, and calendar registration. This system receives information specified by the user, accesses a database to extract necessary data, and enables real-time data confirmation and management by visualizing or notifying through a smart device.

[0309] The server monitors the mailbox and analyzes requests from received emails using natural language processing (NLP) technology. The analyzed requests are automatically registered in a task management system, and these tasks are then automatically registered in calendar systems such as Google Calendar. For example, if a user receives an email requesting "Please schedule a meeting for next Monday," the server analyzes this content, registers it as a meeting scheduling task, and reflects it in the calendar.

[0310] Furthermore, sales and profit data are extracted from the database based on customer IDs, organized by product category, and visualized using a graph generation library. The generated graphs are provided to the user via a smart device. This allows users to check the data in real time and adjust their work accordingly. For example, if a user wants to check the sales and profit trends from January to March 2023, they enter the period and customer ID and send a request to the server. The server extracts the relevant data from the database, generates a graph, and provides it to the user.

[0311] Furthermore, it is possible to retrieve information such as the products traded and the contract renewal month from the customer ID and provide it to the user via a smart device. For example, if a user wants to check the list of products traded and the contract renewal month for a specific customer, they can enter that information, and the server will retrieve the relevant information from the database and provide it to the user via the smart device.

[0312] In this system, smart devices such as smartphones, smart glasses, and head-mounted displays can be used. For example, by using smart glasses, store staff can efficiently manage inventory and customer information.

[0313] Examples of specific prompt statements include the following:

[0314] "Please graph the sales and profit trends for customer ID: 123 from January 1, 2023 to March 31, 2023."

[0315] In this way, the system provides a way to significantly streamline customer management operations through the integration of servers and smart devices.

[0316] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0317] Step 1:

[0318] The user enters a specified period and customer ID using a device (e.g., a smartphone or smart glasses). This input data is fundamental information for retrieving and analyzing customer sales and profit data. This input is sent to the server as a request.

[0319] Step 2:

[0320] The server receives a request sent by the user. The request includes a specified period and a customer ID. Based on this information, the server accesses the database and extracts the relevant sales and profit data. This data extraction process filters the records in the database for the specified period and selects only the data related to the relevant customer ID.

[0321] Step 3:

[0322] The server organizes the extracted sales and profit data by product category. This data processing classifies the data by product category and organizes it chronologically. Furthermore, the data is visualized using a graph generation library. For example, sales and profit trends are generated as line graphs and bar graphs.

[0323] Step 4:

[0324] The generated graph is sent back from the server to the user's device. This graph is displayed on the smart device screen, allowing the user to view the data in real time. A specific visualization example is a time-series graph of sales and profits displayed on smart glasses.

[0325] Step 5:

[0326] The user sends a request from their terminal to the server, specifying their customer ID, to view a list of traded products and information about their contract renewal month. This information is necessary to manage the customer's trading status.

[0327] Step 6:

[0328] The server retrieves a list of traded products and contract renewal month information from the database based on the customer ID. This data retrieval process refers to the transaction history data and contract information database to extract the latest product list and contract renewal month corresponding to the specified customer ID.

[0329] Step 7:

[0330] The acquired list of traded products and contract renewal month information are sent back from the server to the user's device. Users can view and manage this information through the screen of their smart device.

[0331] Step 8:

[0332] The server periodically monitors the mailbox and analyzes the content of new emails as they arrive. For example, if a user receives a meeting invitation email, the server analyzes the email content using natural language processing (NLP) techniques to extract the request details.

[0333] Step 9:

[0334] The analyzed requests are automatically registered in the task management system. This task registration process writes new task information to the task management database, which is then managed for later reference.

[0335] Step 10:

[0336] Registered tasks are automatically registered by the server in a calendar system such as Google Calendar. This calendar registration process generates task details as a calendar event, set to the specified date and time. This allows users to check their task schedules in real time via their smart devices.

[0337] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0338] This invention combines a customer management system with an emotion engine that recognizes user emotions to further enhance the user experience. In addition to managing sales and profit data for specified periods, checking transaction products and contract renewal months, creating tasks from email requests and automatically registering them in the calendar, automatically booking meeting rooms, and automatically setting up online meetings, this system also provides information based on user emotions.

[0339] Extract graphs showing sales and profit trends for each customer over a specified period (even by product category).

[0340] System operation:

[0341] 1. The user enters the period (start date and end date) and customer ID via the terminal. The terminal sends the entered information to the server as a request.

[0342] 2. The server receives the request, accesses the database, and extracts sales and profit data for the specified period.

[0343] 3. The server organizes the extracted data by product category and uses a graph generation library to create graphs showing the trends in sales and profits.

[0344] 4. Before displaying the generated graph, the server uses an emotion engine to analyze the user's emotions.

[0345] 5. The server uses an emotion engine to customize the graph's colors and annotations to match the user's mood.

[0346] 6. The server returns the customized graph to the user's device, and the user can view the graph on their device.

[0347] Specific example:

[0348] For example, if a user wants to see the sales and profit trends for customer ID 123 from January 1, 2023 to March 31, 2023, they would enter the period and customer ID into their device and send a request to the server. The server would then extract the relevant data from the database, organize it by product category, and generate a graph. After that, the emotion engine would analyze the user's emotions, and if the user is feeling down, it would add an encouraging message to the graph and send it back.

[0349] Confirmation of trading products and contract renewal month

[0350] System operation:

[0351] 1. The user enters the customer ID they wish to check from their device and sends a request to the server.

[0352] 2. The server receives the request and executes a query to access the database to retrieve the customer's trading product list and contract renewal month information.

[0353] 3. The server analyzes the acquired information through an emotion engine and determines the display content that corresponds to the user's emotions.

[0354] 4. The server returns information adjusted by the emotion engine to the user's terminal, and the user can view and confirm this information on the screen.

[0355] Specific example:

[0356] For example, if a user wants to check the list of products traded and the contract renewal month for customer ID 456, they enter the customer ID into their terminal and send a request to the server. After the server retrieves the relevant information from the database, it uses an emotion engine to analyze the user's emotions. If the user is feeling stressed, the information is displayed concisely and the important points are highlighted in the response.

[0357] Customer requests received via email are converted into tasks and automatically registered in the calendar.

[0358] System operation:

[0359] 1. The server periodically monitors the email inbox and detects the arrival of new emails.

[0360] 2. The server analyzes the content of newly received emails using natural language processing (NLP) techniques and extracts the requests.

[0361] 3. The server uses an emotion engine to adjust the priority of the extracted requests based on the user's emotions.

[0362] 4. The server registers the prioritized tasks as new tasks in the task management system. The tasks include details such as the request content and deadline.

[0363] 5. Using the registered task information, the Google Calendar API is used to automatically add tasks to the calendar.

[0364] 6. When a task is registered in the calendar, the server notifies the user terminal that the task has been created and registered in the calendar.

[0365] 7. Users can check their calendar on their device to see newly added tasks and appointments.

[0366] Specific example:

[0367] For example, if a customer sends an email requesting a meeting for next Monday, the server receives the email, analyzes its content, and uses an emotion engine to analyze the user's current emotions before registering the meeting request as a task. If the user is feeling excessive pressure, the task's priority is lowered, and the email content is summarized concisely before being added to the calendar.

[0368] Automated meeting room booking

[0369] System operation:

[0370] 1. The user enters the meeting date and time and the required number of participants from their device and sends a request to the server.

[0371] 2. The server receives the request and accesses a system or database that manages the availability of meeting rooms to execute a query to check their availability.

[0372] 3. The server retrieves a list of available meeting rooms and selects the most suitable meeting room for the specified date, time, and number of people.

[0373] 4. Before booking a meeting room, the server uses an emotion engine to analyze the user's emotions.

[0374] 5. The server will make customizations based on the user's emotions, such as changing the selection of a meeting room.

[0375] 6. The server automatically reserves meeting rooms through the reservation system and notifies the user terminal of the reservation result.

[0376] 7. Users can check the reservation results on their device and confirm that the meeting room has been reserved.

[0377] Specific example:

[0378] For example, if a user wants to reserve a "meeting room for 10 people for 2 hours starting at 2:00 PM on October 15, 2023," they enter the information into their terminal and send it to the server. The server retrieves availability from the meeting room management system, selects the most suitable meeting room, and then uses an emotion engine to analyze the user's emotions. If the user is feeling anxious, the server prioritizes selecting a meeting room with a calmer environment and makes the reservation. The reservation result is then displayed on the terminal.

[0379] Zoom automatic setup

[0380] System operation:

[0381] 1. The user enters the meeting date and time and participant list from their device and sends a request to the server.

[0382] 2. The server receives the request and sends a request to the Zoom server to create a new Zoom meeting using the Zoom API.

[0383] 3. The server receives the meeting details (link and ID) returned from Zoom and stores that information.

[0384] 4. The server uses an emotion engine to analyze the user's emotions and decide how to notify them of the meeting details.

[0385] 5. Based on the saved meeting details, the server sends meeting invitations via email in the appropriate format to the participants listed in the participant list.

[0386] 6. Once the invitation email is sent, the server notifies the user that the Zoom meeting setup is complete.

[0387] 7. Users and participants can check the meeting details in the email they receive and join the Zoom meeting at the specified date and time.

[0388] Specific example:

[0389] For example, if a user wants to "set up a Zoom meeting on October 20, 2023 at 11:00 AM and send invitations to participants," they would enter that information into their device and send it to the server. The server would then use the Zoom API to create the meeting and retrieve the meeting details. The server would then use an emotion engine to analyze the user's emotions, and if, for example, the user wants to express gratitude, it would add a message to that effect to the invitation email before sending it. The user and participants would then be able to confirm the meeting details via email and join the Zoom meeting at the specified date and time.

[0390] As described above, the system based on the present invention, which incorporates an emotion engine, can automate various processes in customer management operations and further customize them according to the user's emotions, thereby significantly improving both operational efficiency and user experience.

[0391] The following describes the processing flow.

[0392] Extract graphs showing sales and profit trends for each customer over a specified period (even by product category).

[0393] Processing steps:

[0394] Step 1:

[0395] The user enters the period (start and end dates) and customer ID via the device. The device then sends the entered information to the server as a request.

[0396] Step 2:

[0397] The server receives the request and executes a query against the database based on the specified time period and customer ID.

[0398] Step 3:

[0399] The server extracts the relevant sales and profit data from the database.

[0400] Step 4:

[0401] The server organizes the extracted data by product category. Sales and profit data are grouped for each product category and sorted chronologically.

[0402] Step 5:

[0403] The server uses a graph generation library to create graphs showing the trends in sales and profits. Colors and labels can be set as needed.

[0404] Step 6:

[0405] The server uses an emotion engine to analyze the user's emotions. For example, it determines the user's current emotional state (joy, sadness, anger, etc.).

[0406] Step 7:

[0407] The graph's colors and annotations are customized based on the user's emotions, as determined by the emotion engine. For example, if the user is feeling down, an encouraging message is added.

[0408] Step 8:

[0409] The server generates customized graphs as image files or in interactive formats and sends them back to the user's terminal.

[0410] Step 9:

[0411] Users can view graphs received on their devices and check the trends in sales and profits over a specified period.

[0412] Confirmation of trading products and contract renewal month

[0413] Processing steps:

[0414] Step 1:

[0415] The user enters the customer ID they want to check on their device and sends a request to the server.

[0416] Step 2:

[0417] The server receives the request and executes a query to access the database to retrieve the customer's trading product list and contract renewal month information.

[0418] Step 3:

[0419] The server prepares a response containing a list of traded products and contract renewal month information retrieved from the database.

[0420] Step 4:

[0421] The server uses an emotion engine to analyze the user's emotions. For example, it determines the emotional state the user is in when viewing this information.

[0422] Step 5:

[0423] The information displayed is customized based on the emotion engine. For example, if the user is stressed, the information is displayed more concisely and important points are highlighted.

[0424] Step 6:

[0425] The server returns customized information to the user's device.

[0426] Step 7:

[0427] Users can view the list of traded products and contract renewal month information received on their device and confirm the necessary information.

[0428] Customer requests received via email are converted into tasks and automatically registered in the calendar.

[0429] Processing steps:

[0430] Step 1:

[0431] The server periodically monitors the email inbox to detect the arrival of new emails.

[0432] Step 2:

[0433] The server uses natural language processing (NLP) techniques to analyze the content of newly received emails and extract the requests.

[0434] Step 3:

[0435] The server processes the extracted requests through an emotion engine to analyze their importance based on the user's emotions.

[0436] Step 4:

[0437] Task priorities are adjusted based on requests analyzed by the emotion engine. If the user is experiencing stress, the priority of low-priority tasks is lowered.

[0438] Step 5:

[0439] The server registers tasks with adjusted priorities as new tasks in the task management system. These tasks include details such as the request content and deadline.

[0440] Step 6:

[0441] The server uses the Google Calendar API based on the task information to automatically add the task to the calendar.

[0442] Step 7:

[0443] When a task is registered in the calendar, the server notifies the user's terminal that the task has been created and registered in the calendar.

[0444] Step 8:

[0445] Users can check their calendar on their device to see newly added tasks and appointments.

[0446] Automated meeting room booking

[0447] Processing steps:

[0448] Step 1:

[0449] The user enters the meeting date and time and the required number of participants from their device and sends a request to the server.

[0450] Step 2:

[0451] The server receives the request and accesses a system or database that manages the availability of meeting rooms to execute a query to check their availability.

[0452] Step 3:

[0453] The server retrieves a list of available meeting rooms and selects the most suitable one for the specified date, time, and number of people.

[0454] Step 4:

[0455] Before booking a meeting room, the server uses an emotion engine to analyze the user's emotions. For example, it determines the user's current mood and stress level.

[0456] Step 5:

[0457] The server adjusts the selection of meeting rooms based on the user's emotions. For example, if the user is feeling stressed, it will choose a meeting room with a calm environment.

[0458] Step 6:

[0459] The server automatically reserves the selected meeting room through the reservation system.

[0460] Step 7:

[0461] Once the reservation is complete, the server will notify the user's device of the result.

[0462] Step 8:

[0463] Users can check their reservation results on their device and confirm that the meeting room has been booked.

[0464] Zoom automatic setup

[0465] Processing steps:

[0466] Step 1:

[0467] The user enters the meeting date and time and participant list from their device and sends a request to the server.

[0468] Step 2:

[0469] The server receives the request and sends a request to the Zoom server to create a new Zoom meeting using the Zoom API.

[0470] Step 3:

[0471] The server receives the meeting details (link and ID) returned from Zoom and stores that information.

[0472] Step 4:

[0473] The server uses an emotion engine to analyze the user's emotions and determine, for example, the user's current emotional state (joy, sadness, tension, etc.).

[0474] Step 5:

[0475] Customize meeting notification formats based on an emotion engine. For example, if a user is feeling grateful, add a message reflecting that sentiment to the invitation email.

[0476] Step 6:

[0477] Based on the saved meeting details, the server sends meeting invitations via email in the appropriate format to the participants listed in the participant list.

[0478] Step 7:

[0479] Once the invitation email is sent, the server notifies the user that the Zoom meeting setup is complete.

[0480] Step 8:

[0481] Users and participants can check the meeting details in the email they receive and join the Zoom meeting at the specified date and time.

[0482] As described above, the system based on the present invention, which incorporates an emotion engine, can automate various processes in customer management operations and further customize them according to the user's emotions, thereby significantly improving both operational efficiency and user experience.

[0483] (Example 2)

[0484] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0485] Traditional customer relationship management (CRM) systems failed to consider user emotions when displaying sales and profit data, making it difficult to enhance user satisfaction. Furthermore, tasks such as checking transaction products and contract renewal months, task-based processing of email requests, and automated meeting scheduling and booking lacked a responsiveness to user emotions. As a result, users were unable to maximize their work efficiency and often experienced stress and dissatisfaction.

[0486] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0487] In this invention, the server includes means for receiving a specified period and customer ID from the user, means for extracting relevant sales data and profit data from a database, means for organizing the extracted data and generating graphs for each product, means for analyzing the user's sentiment before providing the generated graphs, means for customizing the graph colors and annotations based on the user's sentiment, and means for providing the customized graphs to the user. This enables customization according to the user's sentiment, improving operational efficiency and the user experience.

[0488] The "specified period" refers to the range of start and end dates entered by the user, and sales and profit data are extracted within that range.

[0489] A "customer ID" is a unique identifier used to identify a specific customer and corresponds to customer information in the database.

[0490] "Sales data" refers to data that includes information on the sales amount and quantity of products within a specified period.

[0491] "Profit data" refers to data that includes information about profits obtained within a specified period.

[0492] A "database" is an information system used to store and manage sales data, profit data, transaction product lists, contract renewal month information, and other customer information.

[0493] An "emotion engine" is a software module that analyzes a user's emotions and evaluates their current mood and emotional state.

[0494] A "graph generation library" is a software tool used to visualize sales and profit data, and it has the function of generating graphs and charts.

[0495] A "task management system" is a software platform for users to register, track, and manage tasks they are responsible for.

[0496] A "calendar" is a time management tool used to visually manage and display tasks and appointments.

[0497] A "mailbox" is an electronic system for storing and managing emails that a user has received.

[0498] Natural Language Processing (NLP) is a technique for analyzing text data to understand its meaning and structure and extract information.

[0499] A "task" is a specific action or item of work that needs to be done in order to achieve a certain objective.

[0500] An "online meeting system" is a meeting system that allows multiple participants to communicate in real time via the internet.

[0501] A "meeting room management system" is software or information system used to manage the reservation and availability status of meeting rooms.

[0502] This invention relates to a system that streamlines customer management operations and improves the user experience. This system analyzes user emotions and customizes information delivery based on the results. The specific hardware and software configuration, as well as processing details, are as follows.

[0503] Overall system configuration

[0504] The system primarily consists of user terminals, servers, and databases. Users use terminals to perform various customer management operations (such as specifying time periods, entering customer IDs, and managing tasks). The server receives requests, extracts necessary information from the database, processes the data using an emotion engine and other software modules, and provides appropriate information to the user.

[0505] Hardware and software to be used

[0506] User devices: Computers, smartphones, tablets, etc.

[0507] Server: A server machine equipped with high-speed computing capabilities.

[0508] Databases: Relational database management systems such as PostgreSQL and MySQL (registered trademark).

[0509] Emotion engine: Microsoft® Azure® Emotion API, IBM Watson® Tone Analyzer, etc.

[0510] Graph generation libraries: Matplotlib, D3.js, etc.

[0511] Task management systems: Trello, Asana, etc.

[0512] Online meeting systems: Zoom, MICROSOFT TEAMS (registered trademark), etc.

[0513] Calendar API: Google Calendar API.

[0514] Natural Language Processing (NLP) technologies: Google Cloud Natural Language API, spaCy, etc.

[0515] Example processing flow: Extract graphs of sales and profit trends (or by product) for a specified period for each customer.

[0516] Specific example:

[0517] If a user wants to view the sales and profit trends for customer ID 123 from January 1, 2023 to March 31, 2023, the user enters the period and customer ID into the input fields on the device and clicks the "Submit" button. The device then sends the specified period and customer ID to the server as an HTTP request.

[0518] When the server receives a request, it accesses the database and extracts sales and profit data for the specified period. For example, it might execute a query like "SELECT FROM sales WHERE customer_id = 123 AND date BETWEEN(registered trademark) '2023-01-01' AND '2023-03-31'". The extracted data is then organized by product category.

[0519] Next, the server generates graphs that visually represent the data using graph generation libraries such as Matplotlib. Before the generated graphs are presented to the user, an emotion engine is used to analyze the user's emotions. For example, recent user interaction data is input into the emotion engine, and if the user is feeling down, the graph's colors and annotations are adjusted to alleviate that mood.

[0520] For example, if the emotion engine analyzes that "the user is feeling down," it will change the graph's colors to brighter ones and add an encouraging message such as, "Sales are recovering. Keep up the good work!" Finally, the customized graph is sent to the user's device, where they can view it.

[0521] Example processing flow: Confirmation of trading products and contract renewal month

[0522] Specific example:

[0523] If a user wants to check the list of traded products and contract renewal month for customer ID 456, they enter the customer ID into the terminal and click the "Confirm" button. This causes the terminal to send the customer ID to the server as an HTTP request.

[0524] When the server receives a request, it accesses the database and executes a query to retrieve the customer's transaction list and contract renewal month information. An example query might be "SELECT FROM contracts WHERE customer_id = 456". The retrieved information is analyzed by the sentiment engine, and the displayed content is adjusted based on the user's sentiment.

[0525] For example, if analysis indicates that a user is experiencing stress, the acquired information is displayed concisely and the key points are highlighted before being sent to the user's device. The user can then review the information on their device.

[0526] Example processing flow: Customer requests received via email are converted into tasks and automatically registered in the calendar.

[0527] Specific example:

[0528] If a customer sends an email requesting "Please schedule a meeting for next Monday," the server periodically monitors the mailbox and analyzes incoming new emails using natural language processing (NLP) techniques. The analysis extracts the request, and an emotion engine adjusts the task's priority based on the user's emotions.

[0529] The server then registers the coordinated tasks as new tasks in task management systems such as Trello or Asana. Information including task details is automatically added to the calendar using the Google Calendar API. Finally, the server notifies the user's device that task creation and calendar registration are complete. The user can then view the new tasks and appointments on their device.

[0530] Thus, the system of the present invention utilizes an emotion engine to customize the system according to the user's emotions, thereby improving the efficiency of customer management operations and enhancing the user experience. Since various data analyses and processing are automated, users can perform their tasks with minimal stress.

[0531] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0532] Extract graphs showing sales and profit trends for each customer over a specified period (even by product category).

[0533] Step 1:

[0534] The user uses their device to enter the specified period (e.g., start and end dates) and customer ID, and then sends the request to the server.

[0535] Input: Start date, End date, Customer ID

[0536] Output: HTTP request to the server

[0537] Specific actions:

[0538] The user enters the period from "January 1, 2023" to "March 31, 2023" and customer ID "123" into the input form on their device and clicks the "Submit" button. This causes the device to construct the necessary information as an HTTP request and send it to the server.

[0539] Step 2:

[0540] The server receives a request from the user, queries the database, and retrieves sales and profit data for the specified period.

[0541] Input: HTTP request (start date, end date, customer ID)

[0542] Output: Sales data and profit data

[0543] Specific actions:

[0544] The server parses the request and executes an SQL query in the database such as "SELECT FROM sales WHERE customer_id = 123 AND date BETWEEN '2023-01-01' AND '2023-03-31'". The retrieved data includes detailed sales and profit information.

[0545] Step 3:

[0546] The server organizes the data retrieved from the database by product category and uses a graph generation library to create graphs showing the trends in sales and profits.

[0547] Input: Sales data and profit data

[0548] Output: Initial graph

[0549] Specific actions:

[0550] The server groups the acquired sales and profit data by product. For example, it formats the data into sales and profits for product A, sales and profits for product B, etc., and generates line graphs of the data using Matplotlib.

[0551] Step 4:

[0552] Before displaying the generated graph, the server uses an emotion engine to analyze the user's emotions.

[0553] Input: User ID or interaction data at that time

[0554] Output: User sentiment data

[0555] Specific actions:

[0556] The server sends interaction data such as user ID, recent emails, and chat history to the emotion engine, which then analyzes the user's current emotional state using the Microsoft Azure Emotion API and IBM Watson Tone Analyzer.

[0557] Step 5:

[0558] The server customizes the graph's colors and annotations based on the results of the sentiment engine.

[0559] Input: Initial graph, sentiment data

[0560] Output: Customized graph

[0561] Specific actions:

[0562] Based on the analysis results from the emotion engine, the server customizes the graph. For example, if the user is feeling down, the graph's colors will be changed to brighter ones, and an encouraging message will be added.

[0563] Step 6:

[0564] The server sends a customized graph to the user's terminal, and the user reviews it.

[0565] Input: Customized graph

[0566] Output: HTTP response to the user terminal

[0567] Specific actions:

[0568] The customized graph is sent to the user's terminal as an HTTP response. The terminal receives the response and displays the customized graph on its screen.

[0569] Confirmation of trading products and contract renewal month

[0570] Step 1:

[0571] The user enters the customer ID they want to check on their device and sends a request to the server.

[0572] Input: Customer ID

[0573] Output: HTTP request to the server

[0574] Specific actions:

[0575] The user enters customer ID "456" into the input field on the terminal and clicks the "Confirm" button. The terminal sends this to the server as an HTTP request.

[0576] Step 2:

[0577] The server receives the request, accesses the database, and retrieves the customer's trading product list and contract renewal month information.

[0578] Input: HTTP request (customer ID)

[0579] Output: List of traded products and contract renewal month information

[0580] Specific actions:

[0581] The server executes an SQL query like "SELECT FROM contracts WHERE customer_id = 456" to retrieve the relevant information from the database.

[0582] Step 3:

[0583] The server analyzes the acquired information using an emotion engine.

[0584] Input: Acquired information, user ID, or interaction data at that time.

[0585] Output: User sentiment data

[0586] Specific actions:

[0587] The server sends the acquired information to the emotion engine, which analyzes the user's current emotional state.

[0588] Step 4:

[0589] The server customizes the displayed content based on the results of the emotion engine.

[0590] Input: Sentiment data, acquired information

[0591] Output: Customized information

[0592] Specific actions:

[0593] If the analysis indicates that the user is experiencing stress, the server will summarize the acquired information concisely, highlighting the key points and organizing the information accordingly.

[0594] Step 5:

[0595] The server sends customized information to the user's terminal, and the user confirms it.

[0596] Input: Customized information

[0597] Output: HTTP response to the user terminal

[0598] Specific actions:

[0599] Customized information is sent to the user's terminal as an HTTP response. The terminal receives the response and displays the information on its screen.

[0600] Customer requests received via email are converted into tasks and automatically registered in the calendar.

[0601] Step 1:

[0602] The server periodically monitors the email inbox to detect the arrival of new emails.

[0603] Input: Mail Inbox

[0604] Output: New email

[0605] Specific actions:

[0606] The server connects to the mail server using the IMAP protocol and checks for new mail every 5 minutes.

[0607] Step 2:

[0608] The server analyzes the content of new emails using natural language processing (NLP) techniques to extract the requests.

[0609] Input: New email

[0610] Output: Request

[0611] Specific actions:

[0612] The server sends the content of the new email to the Google Cloud Natural Language API and extracts the request, "Please schedule a meeting for next Monday."

[0613] Step 3:

[0614] The server uses an emotion engine to adjust the priority of tasks based on the user's emotions, using the extracted requests.

[0615] Input: Request details, user ID, or interaction data at that time.

[0616] Output: Tasks with adjusted priorities

[0617] Specific actions:

[0618] The server analyzes the request using an emotion engine and sets a lower priority for the task if the user is feeling excessive pressure.

[0619] Step 4:

[0620] The server registers the tasks with adjusted priorities as new tasks in the task management system.

[0621] Input: Tasks with adjusted priority

[0622] Output: New task

[0623] Specific actions:

[0624] The server uses the Trello API to create a new task titled "Schedule a meeting next Monday" with a "medium" priority.

[0625] Step 5:

[0626] The server uses the Calendar API to automatically add tasks to the calendar based on new task information.

[0627] Input: New Task

[0628] Output: Calendar Events

[0629] Specific actions:

[0630] The server uses the Google Calendar API to add an event called "Meeting next Monday" to the calendar.

[0631] Step 6:

[0632] The server notifies the user's terminal that the task has been registered in the calendar.

[0633] Input: Calendar Event

[0634] Output: Notification to user terminal

[0635] Specific actions:

[0636] The server sends a notification to the user's terminal in JSON format stating, "A new task has been added to your calendar," and the terminal displays it as a pop-up message.

[0637] Step 7:

[0638] Users check their calendar on their devices to see newly added tasks and appointments.

[0639] Input: Notification to user terminal

[0640] Output: Calendar display

[0641] Specific actions:

[0642] The user opens the calendar app on their device and sees a new meeting task added for "next Monday".

[0643] (Application Example 2)

[0644] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0645] Traditional customer management systems have a problem in that they provide uniform information without considering user emotions, making it difficult to improve the user experience. In particular, there are many situations in tasks such as data verification and task management where responses that respond to user emotions are required, and systems that do not take this into consideration can lead to decreased user satisfaction.

[0646] The specific processing performed by the specific 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 means for receiving a period and customer identifier specified by the user, means for extracting the corresponding sales data and profit data from the database, means for organizing the extracted data and generating graphs for each product, means for providing the generated graphs to the user, and means for an emotion engine that analyzes the user's emotions and customizes the display content of the graphs based on the user's emotions. This makes it possible to customize the display of data and adjust the priority of tasks according to the user's emotions.

[0647] A "user" is someone who uses a system.

[0648] "Specified period" refers to a specific period for which sales data, profit data, and other information are to be collected, as entered by the user into the system.

[0649] A "customer identifier" is a unique ID used to identify a specific customer.

[0650] A "database" is a collection of data that systematically stores information and allows it to be searched and extracted as needed.

[0651] "Sales data" refers to data that shows the sales performance of a product over a specific period.

[0652] "Profit data" refers to data that shows net profit over a specific period.

[0653] "Extraction method" refers to a method or device for retrieving necessary data from a database based on specific conditions.

[0654] "Means of organization" refers to methods or devices for compiling and structuring extracted data according to specific criteria.

[0655] "By product category" means classifying and organizing products according to the type of product being sold.

[0656] A "graph" is a diagram or chart used to visually represent the relationships between data.

[0657] "Means of providing" refers to methods and devices for conveying information to users.

[0658] An "emotion engine" refers to a technology or device that analyzes a user's emotions from their facial expressions, voice, and other data.

[0659] "Means of customization" refers to methods or devices for changing the displayed content and the way information is presented based on the analyzed emotions of the user.

[0660] A "task" is a series of tasks or activities performed to achieve a specific objective.

[0661] "Priority" refers to a criterion that indicates the order or importance of tasks.

[0662] This invention is a system that combines an emotion engine to streamline customer management operations and improve the user experience. Specific embodiments of this system are described below.

[0663] System Configuration

[0664] This system includes a user terminal, a server, a database, and an emotion engine. The user inputs a specified period and customer identifier using the user terminal and sends a request to the server. The server accesses the database to extract the necessary data, analyzes and organizes it, and provides it to the user. The server also uses the emotion engine to analyze the user's emotions and optimizes the information delivery method based on the results.

[0665] Hardware and software to use

[0666] Hardware:

[0667] User terminals (PCs, smartphones, etc.)

[0668] server

[0669] Camera device (for capturing the user's face)

[0670] Database Server

[0671] software:

[0672] Database management system (e.g., MySQL)

[0673] Emotion engine (e.g., EmotionRecognizer)

[0674] Graph generation libraries (e.g., Matplotlib)

[0675] Task management system (e.g., Google Calendar API)

[0676] Video conferencing APIs (e.g., Zoom API)

[0677] Natural language processing libraries (e.g., NLTK)

[0678] Data processing and data calculation

[0679] The server receives requests from users and extracts sales and profit data from the database. This data is passed to a graph generation library, which generates trend graphs over a specific period. The sentiment engine then analyzes the user's emotions, and the graph's colors and annotations are customized based on the analysis results. The sentiment engine is also used in task management, adjusting task priorities and calendar entries based on the user's emotions.

[0680] Specific example

[0681] 1. Check the trends in sales and profits:

[0682] If a user wants to see the sales and profit trends for customer identifier 123 from January 1, 2023 to March 31, 2023, they enter the period and customer identifier and send a request to the server. The server extracts the necessary data from the database and generates a graph. Using an emotion engine, it analyzes the user's emotions and, if the user is feeling down, adds an encouraging message to the graph and sends it back.

[0683] 2. Automatically register tasks to the calendar:

[0684] If a customer sends an email requesting a meeting for next Monday, the server receives the email, analyzes its content, and registers it as a task. It also analyzes the user's emotions; for example, if the user is stressed, it lowers the task's priority, simplifies its content, and registers it in the calendar.

[0685] Example of a prompt

[0686] "Create a program that identifies customer emotions and displays suggestions to improve customer satisfaction. For example, if a customer is angry, suggest that the employee respond calmly and politely."

[0687] Actual prompt:

[0688] "Create an application that identifies customer emotions in real time and displays specific actions to store staff based on the recognized emotions. For example, if a customer appears happy, display a message such as, 'The customer appears happy. Let's continue to be friendly!'"

[0689] The above describes the detailed embodiments for carrying out this invention.

[0690] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0691] Step 1:

[0692] The user enters the specified period and customer identifier from their device. The entered information is sent to the server as a request.

[0693] Step 2:

[0694] The server receives requests sent by users. Based on the received requests, it accesses the database and extracts the relevant sales and profit data. Specifically, it executes database queries using the period and customer identifier as conditions to retrieve the necessary data.

[0695] Step 3:

[0696] The server organizes the extracted data and separates it by product category. Furthermore, it uses a graph generation library (e.g., Matplotlib) to generate graphs showing sales and profit trends. The generated graphs are saved to the server as image files containing a visual representation of the data.

[0697] Step 4:

[0698] The server uses an emotion engine (e.g., EmotionRecognizer) to analyze the user's emotions. The input is either a user's facial image or voice data, which is passed to the emotion engine. The emotion engine outputs emotion tags (e.g., happy, sad, angry) as the result of the analysis.

[0699] Step 5:

[0700] The server customizes the display of the generated graph based on the analysis results of the emotion engine. Specifically, it adjusts the graph's colors, annotations, and messages according to the analyzed emotion. For example, if the user is feeling down, an encouraging message will be added to the graph.

[0701] Step 6:

[0702] The server returns a customized graph to the user's terminal. The returned data is in image file or HTML format, and the user can view the graph on their terminal.

[0703] Step 7:

[0704] (Specific example: When the user is feeling stressed)

[0705] When a user requests to "check the list of traded products and contract renewal month for customer identifier 456," the server retrieves the relevant information from the database and uses an emotion engine to analyze the user's emotions. For example, if the analysis indicates that the user is feeling stressed, the information is concisely organized and presented to the user with key points highlighted.

[0706] This allows for the provision of information tailored to the user's emotions, leading to increased operational efficiency and a better user experience.

[0707] 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating 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.

[0708] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0709] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0710] [Second Embodiment]

[0711] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0712] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0713] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0714] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0715] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0716] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0717] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0718] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0719] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[0720] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0721] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0722] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. 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".

[0723] This invention is a system for streamlining customer management operations, including managing sales and profit data for a specified period, confirming transaction items and contract renewal months, converting requests from emails into tasks and automatically registering them in a calendar, automatically reserving meeting rooms, and automatically setting up online meetings.

[0724] Extract graphs showing sales and profit trends for each customer over a specified period (even by product category).

[0725] System operation:

[0726] 1. The user enters the period (start date and end date) and customer ID via the terminal.

[0727] 2. The terminal sends the entered information to the server as a request.

[0728] 3. The server receives the request, accesses the database, and extracts sales and profit data for the specified period.

[0729] 4. The server organizes the extracted data by product category and uses a graph generation library to create graphs showing the trends in sales and profits.

[0730] 5. The generated graph is sent back from the server to the terminal, and the user can view the graph on the terminal.

[0731] Specific example:

[0732] For example, if a user wants to see the sales and profit trends for customer ID 123 from January 1, 2023 to March 31, 2023, they would enter the period and customer ID into their device and send a request to the server. The server would then extract the relevant data from the database, organize it by product category, and generate a graph. The generated graph would then be displayed on the user's device.

[0733] Confirmation of trading products and contract renewal month

[0734] System operation:

[0735] 1. The user enters the customer ID they wish to check from their device and sends a request to the server.

[0736] 2. The server accesses the database to retrieve the customer's trading product list and contract renewal month information.

[0737] 3. The server sends the acquired information back to the user's terminal, and the user can view and confirm that information on the screen.

[0738] Specific example:

[0739] For example, if a user wants to check the list of products traded and the contract renewal month for customer ID 456, they enter the customer ID into their terminal and send a request to the server. The server retrieves the relevant information from the database and sends it back to the user's terminal. The user can then view the displayed information.

[0740] Customer requests received via email are converted into tasks and automatically registered in the calendar.

[0741] System operation:

[0742] 1. The server periodically monitors the email inbox.

[0743] 2. If there is a new email, the server analyzes its contents using natural language processing (NLP) and extracts the request.

[0744] 3. The server registers the extracted requests as tasks in the task management system.

[0745] 4. Registered tasks are automatically added to Google Calendar.

[0746] Specific example:

[0747] For example, if a customer sends an email requesting "Please schedule a meeting for next Monday," the server receives the email, analyzes its contents, and registers the meeting request as a task. This task is automatically added to Google Calendar, and the user can then view the appointment on their calendar.

[0748] Automated meeting room booking

[0749] System operation:

[0750] 1. The user enters the meeting date and time and the required number of participants from their device.

[0751] 2. The terminal sends the input information to the server.

[0752] 3. The server accesses the meeting room management system or database to check availability based on the specified date, time, and number of people.

[0753] 4. The server automatically reserves a suitable available meeting room.

[0754] 5. The reservation results are sent back from the server to the user's terminal, and the user can check the results.

[0755] Specific example:

[0756] For example, if a user wants to reserve a "meeting room for 10 people for 2 hours starting at 2:00 PM on October 15, 2023," they enter the information into their device and send it to the server. The server accesses the meeting room management system, checks availability, and then reserves a suitable meeting room. The reservation result is displayed on the user's device.

[0757] Zoom automatic setup

[0758] System operation:

[0759] 1. The user enters the meeting date and time and participant list from their device.

[0760] 2. The terminal sends the input information to the server.

[0761] 3. The server uses the Zoom API to create a new Zoom meeting.

[0762] 4. The server retrieves the meeting details (link and ID) from Zoom.

[0763] 5. The acquired meeting details will be sent via email from the server to the participant list.

[0764] Specific example:

[0765] For example, if a user wants to "set up a Zoom meeting on October 20, 2023 at 11:00 AM and send invitations to participants," they would enter that information into their device and send it to the server. The server would then use the Zoom API to create the meeting and retrieve the meeting details. After that, the server would send meeting invitation emails to the participant list. The user and participants would then receive the meeting details via email.

[0766] As described above, the system based on the present invention can automate various processes in customer management operations and significantly improve operational efficiency.

[0767] The following describes the processing flow.

[0768] Extract graphs showing sales and profit trends for each customer over a specified period (even by product category).

[0769] Processing steps:

[0770] Step 1:

[0771] The user enters the period (start and end dates) and customer ID via the device. The device then sends the entered information to the server as a request.

[0772] Step 2:

[0773] The server parses the received request and executes a query against the database based on the specified period and customer ID.

[0774] Step 3:

[0775] The server extracts the relevant sales and profit data from the database.

[0776] Step 4:

[0777] The server organizes the extracted data by product category. Sales and profit data are grouped for each product category and sorted chronologically.

[0778] Step 5:

[0779] The server uses a graph generation library to create graphs showing the trends in sales and profits. Colors and labels can be set as needed.

[0780] Step 6:

[0781] The server generates the graph as an image file or in an interactive format and sends it back to the user's terminal.

[0782] Step 7:

[0783] Users can view graphs received on their devices and check the trends in sales and profits over a specified period.

[0784] Confirmation of trading products and contract renewal month

[0785] Processing steps:

[0786] Step 1:

[0787] The user enters the customer ID they want to check on their device and sends a request to the server.

[0788] Step 2:

[0789] The server receives the request and accesses the database to execute a query to retrieve the customer's trading product list and contract renewal month information.

[0790] Step 3:

[0791] The server returns the list of traded products and contract renewal month information, retrieved from the database, to the user's terminal as a response.

[0792] Step 4:

[0793] Users can view the list of traded products and contract renewal month information received on their device and confirm the necessary information.

[0794] Customer requests received via email are converted into tasks and automatically registered in the calendar.

[0795] Processing steps:

[0796] Step 1:

[0797] The server periodically monitors the email inbox to detect the arrival of new emails.

[0798] Step 2:

[0799] The server analyzes the content of newly received emails using natural language processing (NLP) techniques. It extracts sentences and keywords that contain the request.

[0800] Step 3:

[0801] The server registers the extracted requests as new tasks in the task management system. Each task includes details such as the request content and deadline.

[0802] Step 4:

[0803] The server uses the Google Calendar API to automatically add tasks to the calendar based on the registered task information.

[0804] Step 5:

[0805] When a task is registered in the calendar, the server notifies the user's terminal that the task has been created and registered in the calendar.

[0806] Step 6:

[0807] Users can check their calendar on their device to see newly added tasks and appointments.

[0808] Automated meeting room booking

[0809] Processing steps:

[0810] Step 1:

[0811] The user enters the meeting date and time and the required number of participants from their device and sends a request to the server.

[0812] Step 2:

[0813] The server receives the request and accesses a system or database that manages the availability of meeting rooms to execute a query to check their availability.

[0814] Step 3:

[0815] The server retrieves a list of available meeting rooms and selects the most suitable one for the specified date, time, and number of people.

[0816] Step 4:

[0817] The server automatically reserves the selected meeting room through the reservation system.

[0818] Step 5:

[0819] Once the reservation is complete, the server will notify the user's device of the result.

[0820] Step 6:

[0821] Users can check their reservation results on their device and confirm that the meeting room has been booked.

[0822] Zoom automatic setup

[0823] Processing steps:

[0824] Step 1:

[0825] The user enters the meeting date and time and participant list from their device and sends a request to the server.

[0826] Step 2:

[0827] The server receives the request and sends a request to the Zoom server to create a new Zoom meeting using the Zoom API.

[0828] Step 3:

[0829] The server receives the meeting details (link and ID) returned from Zoom and stores that information.

[0830] Step 4:

[0831] Based on the saved meeting details, the server sends meeting invitations via email to the participants listed in the participant list.

[0832] Step 5:

[0833] Once the invitation email is sent, the server notifies the user that the Zoom meeting setup is complete.

[0834] Step 6:

[0835] Users and participants can check the meeting details in the email they receive and join the Zoom meeting at the specified date and time.

[0836] As described above, the system based on the present invention has a specific processing flow for improving the efficiency of various customer management tasks and achieves business efficiency through automation.

[0837] (Example 1)

[0838] Next, we will describe Example 1. 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".

[0839] In today's busy business environment, improving the efficiency of customer management and task management is crucial. However, traditional systems require individual tasks such as managing sales and profit data for each customer, checking transaction items and contract renewal months, converting email requests into tasks, booking meeting rooms, and setting up online meetings. This often involves manual verification and data entry, leading to inefficient operations. This increases the likelihood of human error and wastes time and resources. A system is needed to solve these problems and streamline all aspects of customer management.

[0840] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0841] In this invention, the server includes means for receiving a specified period and customer identification information from a user; means for extracting relevant sales data and profit data from an information storage device; means for organizing the extracted data and generating statistical displays by product; means for providing the generated statistical displays to the user; means for receiving the meeting date and time and participant list and creating a new meeting using a remote conferencing system; and means for notifying participants of the generated meeting details through notification means. As a result, customer management operations are centralized, and operations such as data extraction, statistical display generation, and remote meeting setup are automated, significantly improving operational efficiency.

[0842] "Specified period" refers to a time range consisting of a start date and an end date specified by the user for performing a specific action.

[0843] "Customer identification information" refers to information used to uniquely identify a specific customer, and includes customer IDs and other identifiers.

[0844] An "information storage device" is a device for storing data, and includes databases and cloud storage.

[0845] "Sales data" refers to data relating to revenue generated from sales activities within a specific period of time associated with a particular customer.

[0846] "Profit data" refers to data on net profit, which is calculated by subtracting costs from sales for a specific customer over a given period.

[0847] "Statistical display" refers to a display format such as graphs and charts that visually represent sales data and profit data.

[0848] A "remote conferencing system" is a system for setting up and managing meetings conducted remotely via the internet, and includes online conferencing services.

[0849] "Notification means" refers to a means of informing users or participants of specific information, and includes, for example, email and messaging applications.

[0850] A "product list" is a list of products that a particular customer trades.

[0851] "Contract renewal month information" refers to information about the month in which a contract with a specific customer is renewed.

[0852] A "meeting room management system" is a system used to reserve meeting rooms and check their availability.

[0853] An "electronic message box" is a box for receiving and storing emails, and it is installed on a mail server.

[0854] A "work item" is a request that has been registered as a specific task.

[0855] A "schedule" is a system for displaying and managing specific appointments or tasks in a calendar format.

[0856] A "generative AI model" is a model that uses artificial intelligence technology to automatically analyze and generate data.

[0857] A "prompt statement" is an input statement used to give specific instructions to a generative AI model.

[0858] This invention is a system designed to streamline customer management operations. This system can automate and centralize various tasks, such as managing sales and profit data for each customer, checking transaction items and contract renewal months, converting requests from emails into tasks and automatically registering them in the calendar, automatically reserving meeting rooms, and automatically setting up online meetings.

[0859] The main hardware components of this system are a server, terminals, and information storage devices. The server is responsible for processing requests, managing data, automating tasks, and providing notifications, while the terminals provide the user interface and handle information input and display. The information storage devices are used to store data such as sales data, profit data, transaction product lists, contract renewal months, tasks, and meeting room reservation status. Furthermore, software such as the Zoom API and Google Calendar API is used to set up online meetings and register them in the calendar.

[0860] Extract graphs showing sales and profit trends for each customer over a specified period (even by product category).

[0861] The user enters a specified period (start and end dates) and customer identification information via their device. The device sends this information to the server as a request. The server accesses the database and extracts sales and profit data for the specified period. Next, the server organizes the extracted data by product and creates sales and profit trend graphs using a graph generation library (e.g., Matplotlib, Chart.js). These generated graphs are sent back to the device, where the user can view them.

[0862] For example, if a user wants to view the sales and profit trends for customer ID 123 from January 1, 2023 to March 31, 2023, they would enter the period and customer ID and send a request to the server. The server would then extract the relevant data from the database, organize it by product, and generate a graph. The generated graph would then be displayed on the user's device.

[0863] Confirmation of trading products and contract renewal month

[0864] The user enters the customer identification information they wish to verify on their device and sends a request to the server. The server accesses the database and retrieves the customer's transaction product list and contract renewal month information. The retrieved information is sent back to the device, and the user can view and verify it on the screen.

[0865] As a concrete example, if a user wants to check the list of products traded and the contract renewal month for customer ID 456, they enter the customer identification information into the terminal and send a request to the server. The server retrieves the relevant information from the database and sends it back to the terminal. The user can then check the displayed information.

[0866] Requests received via email are converted into tasks and automatically registered in the calendar.

[0867] The server periodically monitors the electronic message box. If there are new messages, the server uses natural language processing (NLP) techniques to analyze the email content and extract requests. The server registers the extracted requests as work items in the task management system. These registered work items are automatically added to a calendar system such as Google Calendar.

[0868] For example, if a customer sends an email requesting "Please schedule a meeting for next Monday," the server receives the email, analyzes its contents, and registers the meeting request as a task item. This task item is automatically registered in Google Calendar, and the user can then view the appointment on their calendar.

[0869] Automated meeting room booking

[0870] The user enters the meeting date, time, and number of participants from their device. The device sends the entered information to the server. The server accesses the meeting room management system or database and checks availability based on the specified date, time, and number of participants. The server automatically reserves a suitable available meeting room and sends the result back to the device. The user can then view the result on their device.

[0871] As a concrete example, if a user wants to reserve a "meeting room for 10 people for 2 hours starting at 2:00 PM on October 15, 2023," they enter the information into their device and send it to the server. The server accesses the meeting room management system, checks the availability, and then reserves an appropriate meeting room. The reservation result is displayed on the user's device.

[0872] Zoom automatic setup

[0873] The user enters the meeting date and time and participant list from their device and sends it to the server. The server uses the Zoom API to create a new Zoom meeting and retrieves the meeting details (link and ID). The retrieved meeting details are then notified to the participant list via email or other means.

[0874] As a concrete example, if a user wants to "set up a Zoom meeting on October 20, 2023 at 11:00 AM and send invitations to participants," they would enter the meeting date and time and participant list into their device and send it to the server. The server would then use the Zoom API to create the meeting and retrieve the meeting details. After that, the server would send meeting invitation emails to the participant list. The user and participants would then receive the meeting details via email.

[0875] By implementing this invention, customer management operations can be centralized, data extraction and statistical display generation, remote meeting scheduling, and other tasks can be automated, significantly improving operational efficiency.

[0876] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0877] Extract graphs showing sales and profit trends for each customer over a specified period (even by product category).

[0878] Step 1:

[0879] The user enters the period (start and end dates) and customer identification information via their device.

[0880] Input: Period (e.g., January 1, 2023 - March 31, 2023), Customer identification information (e.g., Customer ID 123)

[0881] Output: User input data is received by the terminal.

[0882] Step 2:

[0883] The terminal generates a request containing the period and customer identification information and sends it to the server.

[0884] Input: User input data (period and customer identification information)

[0885] Output: The generated request is sent to the server.

[0886] Step 3:

[0887] The server receives the request, accesses the information storage device, and extracts sales and profit data for the specified period.

[0888] Input: Request received from the terminal, data in the information storage device.

[0889] Output: A set of sales data and profit data is extracted.

[0890] Step 4:

[0891] The server extracts data and organizes it by product. A graph generation library is then used to create graphs showing the trends in sales and profits.

[0892] Input: Extracted sales data and profit data

[0893] Output: Graphs showing sales and profit trends by product (e.g., graphs generated using Matplotlib or Chart.js)

[0894] Step 5:

[0895] The generated graph is sent back from the server to the terminal, allowing the user to view the graph on their terminal.

[0896] Input: Generated graph

[0897] Output: The graph will be displayed on the terminal.

[0898] Confirmation of trading products and contract renewal month

[0899] Step 1:

[0900] The user enters the customer identification information they wish to verify from their device.

[0901] Input: Customer identification information (e.g., Customer ID 456)

[0902] Output: User input data is received by the terminal.

[0903] Step 2:

[0904] The terminal generates customer identification information as a request and sends it to the server.

[0905] Input: Customer identification information

[0906] Output: The generated request is sent to the server.

[0907] Step 3:

[0908] The server receives the request and retrieves the customer's trading product list and contract renewal month information from its data storage device.

[0909] Input: Request received from the terminal, data in the information storage device.

[0910] Output: A list of traded products and contract renewal month information are retrieved.

[0911] Step 4:

[0912] The acquired information is sent back from the server to the terminal, and the user can view the information on the terminal.

[0913] Input: List of traded products and contract renewal month information

[0914] Output: Information is displayed on the terminal.

[0915] Requests received via email are converted into tasks and automatically registered in the calendar.

[0916] Step 1:

[0917] The server periodically monitors the electronic message box.

[0918] Input: Status of the electronic message box

[0919] Output: Checks for the presence of new messages.

[0920] Step 2:

[0921] If there is a new message, the server uses natural language processing (NLP) techniques to analyze the email content and extract the request.

[0922] Input: Content of the newly received email

[0923] Output: Request details are extracted.

[0924] Step 3:

[0925] The server registers the extracted requests as work items in the task management system.

[0926] Input: Request

[0927] Output: The work item is registered in the task management system.

[0928] Step 4:

[0929] Registered work items are automatically added to calendar systems such as Google Calendar.

[0930] Input: Work item

[0931] Output: Events registered in the calendar

[0932] Automated meeting room booking

[0933] Step 1:

[0934] The user enters the meeting date, time, and number of participants from their device.

[0935] Input: Meeting date and time (e.g., October 15, 2023, 2:00 PM for 2 hours), Number of participants (e.g., 10 people)

[0936] Output: User input data is received by the terminal.

[0937] Step 2:

[0938] The terminal generates the input information as a request and sends it to the server.

[0939] Input: User input data (meeting date and time, number of participants)

[0940] Output: The generated request is sent to the server.

[0941] Step 3:

[0942] The server accesses the meeting room management system or information storage device to check availability based on the specified date, time, and number of people.

[0943] Input: Requests received from terminals, meeting room management system, or data stored in information storage devices.

[0944] Output: Meeting room availability is checked.

[0945] Step 4:

[0946] The server automatically reserves a suitable available meeting room and sends the reservation result back to the terminal.

[0947] Input: Meeting room availability

[0948] Output: The reservation result is sent back to the device and displayed.

[0949] Zoom automatic setup

[0950] Step 1:

[0951] The user enters the meeting date and time and participant list from their device.

[0952] Input: Meeting date and time (e.g., October 20, 2023, 11:00), participant list

[0953] Output: User input data is received by the terminal.

[0954] Step 2:

[0955] The terminal generates the input information as a request and sends it to the server.

[0956] Input: Meeting date and time and participant list

[0957] Output: The generated request is sent to the server.

[0958] Step 3:

[0959] The server uses the Zoom API to create a new Zoom meeting and retrieves the meeting details (link and ID).

[0960] Input: Request received from the terminal

[0961] Output: Zoom meeting details

[0962] Step 4:

[0963] The generated meeting details are notified from the server to the participant list via a notification system.

[0964] Input: Zoom meeting details

[0965] Output: Meeting details will be sent to participants.

[0966] The above outlines the step-by-step flow of the program processing for this system.

[0967] (Application Example 1)

[0968] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0969] In traditional customer management operations, tasks such as managing sales and profit data, checking transaction products and contract renewal months, and registering tasks on a calendar were performed manually, requiring a significant amount of time and effort. Furthermore, it was difficult to check and manage this information in real time using smart devices, thus creating a need for improved operational efficiency.

[0970] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0971] In this invention, the server includes means for receiving a specified period and customer ID from the user, means for extracting relevant sales data and profit data from a database, means for organizing the extracted data and generating graphs for each product, means for providing the generated graphs to the user, and means for visualizing the sales data and profit data so that the user can efficiently check them via a smart device. This streamlines customer management operations that were previously performed manually, and enables real-time data confirmation and management using smart devices.

[0972] A "user" is someone who operates and gives instructions to a system.

[0973] A "customer ID" is a unique identification number used to identify a specific customer.

[0974] A "database" is a system that stores a collection of data and allows for the efficient retrieval and extraction of necessary information.

[0975] "Sales data" refers to information regarding the sales amount of a product over a specific period.

[0976] "Profit data" refers to information about profits obtained by subtracting expenses from sales during a specific period.

[0977] A "smart device" is a general term for electronic devices that can connect to the internet and provide users with various types of information.

[0978] "Graph generation" is the process of creating diagrams to visually represent data.

[0979] "Merchandise" refers to the goods or services that are sold.

[0980] "Traded goods" refer to products or services that are traded between customers and the service provider.

[0981] "Contract renewal month" refers to the month in which an existing contract is scheduled to be renewed.

[0982] A "mailbox" is a virtual inbox for receiving emails.

[0983] A "task management system" is a system for registering, tracking, and managing tasks and work.

[0984] "Natural language processing" is a technology that enables computers to understand, analyze, and generate human language.

[0985] A "calendar" is an application used to manage dates and appointments.

[0986] This invention is a system that streamlines customer management tasks such as managing sales and profit data, checking transaction items and contract renewal months, and task management and calendar registration. The system receives information specified by the user, accesses a database to extract the necessary data, and visualizes or notifies the user via a smart device, enabling real-time data confirmation and management.

[0987] The server monitors the mailbox and analyzes requests from received emails using natural language processing (NLP) technology. The analyzed requests are automatically registered in a task management system, and these tasks are then automatically registered in calendar systems such as Google Calendar. For example, if a user receives an email requesting "Please schedule a meeting for next Monday," the server analyzes this content, registers it as a meeting scheduling task, and reflects it in the calendar.

[0988] Furthermore, sales and profit data are extracted from the database based on customer IDs, organized by product category, and visualized using a graph generation library. The generated graphs are provided to the user via a smart device. This allows users to check the data in real time and adjust their work accordingly. For example, if a user wants to check the sales and profit trends from January to March 2023, they enter the period and customer ID and send a request to the server. The server extracts the relevant data from the database, generates a graph, and provides it to the user.

[0989] Furthermore, it is possible to retrieve information such as the products traded and the contract renewal month from the customer ID and provide it to the user via a smart device. For example, if a user wants to check the list of products traded and the contract renewal month for a specific customer, they can enter that information, and the server will retrieve the relevant information from the database and provide it to the user via the smart device.

[0990] In this system, smart devices such as smartphones, smart glasses, and head-mounted displays can be used. For example, by using smart glasses, store staff can efficiently manage inventory and customer information.

[0991] Examples of specific prompt statements include the following:

[0992] "Please graph the sales and profit trends for customer ID: 123 from January 1, 2023 to March 31, 2023."

[0993] In this way, the system provides a way to significantly streamline customer management operations through the integration of servers and smart devices.

[0994] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0995] Step 1:

[0996] The user enters a specified period and customer ID using a device (e.g., a smartphone or smart glasses). This input data is fundamental information for retrieving and analyzing customer sales and profit data. This input is sent to the server as a request.

[0997] Step 2:

[0998] The server receives a request sent by the user. The request includes a specified period and a customer ID. Based on this information, the server accesses the database and extracts the relevant sales and profit data. This data extraction process filters the records in the database for the specified period and selects only the data related to the relevant customer ID.

[0999] Step 3:

[1000] The server organizes the extracted sales and profit data by product category. This data processing classifies the data by product category and organizes it chronologically. Furthermore, the data is visualized using a graph generation library. For example, sales and profit trends are generated as line graphs and bar graphs.

[1001] Step 4:

[1002] The generated graph is sent back from the server to the user's device. This graph is displayed on the smart device screen, allowing the user to view the data in real time. A specific visualization example is a time-series graph of sales and profits displayed on smart glasses.

[1003] Step 5:

[1004] The user sends a request from their terminal to the server, specifying their customer ID, to view a list of traded products and information about their contract renewal month. This information is necessary to manage the customer's trading status.

[1005] Step 6:

[1006] The server retrieves a list of traded products and contract renewal month information from the database based on the customer ID. This data retrieval process refers to the transaction history data and contract information database to extract the latest product list and contract renewal month corresponding to the specified customer ID.

[1007] Step 7:

[1008] The acquired list of traded products and contract renewal month information are sent back from the server to the user's device. Users can view and manage this information through the screen of their smart device.

[1009] Step 8:

[1010] The server periodically monitors the mailbox and analyzes the content of new emails as they arrive. For example, if a user receives a meeting invitation email, the server analyzes the email content using natural language processing (NLP) techniques to extract the request details.

[1011] Step 9:

[1012] The analyzed requests are automatically registered in the task management system. This task registration process writes new task information to the task management database, which is then managed for later reference.

[1013] Step 10:

[1014] Registered tasks are automatically registered by the server in a calendar system such as Google Calendar. This calendar registration process generates task details as a calendar event, set to the specified date and time. This allows users to check their task schedules in real time via their smart devices.

[1015] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[1016] This invention combines a customer management system with an emotion engine that recognizes user emotions to further enhance the user experience. In addition to managing sales and profit data for specified periods, checking transaction products and contract renewal months, creating tasks from email requests and automatically registering them in the calendar, automatically booking meeting rooms, and automatically setting up online meetings, this system also provides information based on user emotions.

[1017] Extract graphs showing sales and profit trends for each customer over a specified period (even by product category).

[1018] System operation:

[1019] 1. The user enters the period (start date and end date) and customer ID via the terminal. The terminal sends the entered information to the server as a request.

[1020] 2. The server receives the request, accesses the database, and extracts sales and profit data for the specified period.

[1021] 3. The server organizes the extracted data by product category and uses a graph generation library to create graphs showing the trends in sales and profits.

[1022] 4. Before displaying the generated graph, the server uses an emotion engine to analyze the user's emotions.

[1023] 5. The server uses an emotion engine to customize the graph's colors and annotations to match the user's mood.

[1024] 6. The server returns the customized graph to the user's device, and the user can view the graph on their device.

[1025] Specific example:

[1026] For example, if a user wants to see the sales and profit trends for customer ID 123 from January 1, 2023 to March 31, 2023, they would enter the period and customer ID into their device and send a request to the server. The server would then extract the relevant data from the database, organize it by product category, and generate a graph. After that, the emotion engine would analyze the user's emotions, and if the user is feeling down, it would add an encouraging message to the graph and send it back.

[1027] Confirmation of trading products and contract renewal month

[1028] System operation:

[1029] 1. The user enters the customer ID they wish to check from their device and sends a request to the server.

[1030] 2. The server receives the request and executes a query to access the database to retrieve the customer's trading product list and contract renewal month information.

[1031] 3. The server analyzes the acquired information through an emotion engine and determines the display content that corresponds to the user's emotions.

[1032] 4. The server returns information adjusted by the emotion engine to the user's terminal, and the user can view and confirm this information on the screen.

[1033] Specific example:

[1034] For example, if a user wants to check the list of products traded and the contract renewal month for customer ID 456, they enter the customer ID into their terminal and send a request to the server. After the server retrieves the relevant information from the database, it uses an emotion engine to analyze the user's emotions. If the user is feeling stressed, the information is displayed concisely and the important points are highlighted in the response.

[1035] Customer requests received via email are converted into tasks and automatically registered in the calendar.

[1036] System operation:

[1037] 1. The server periodically monitors the email inbox and detects the arrival of new emails.

[1038] 2. The server analyzes the content of newly received emails using natural language processing (NLP) techniques and extracts the requests.

[1039] 3. The server uses an emotion engine to adjust the priority of the extracted requests based on the user's emotions.

[1040] 4. The server registers the prioritized tasks as new tasks in the task management system. The tasks include details such as the request content and deadline.

[1041] 5. Using the registered task information, the Google Calendar API is used to automatically add tasks to the calendar.

[1042] 6. When a task is registered in the calendar, the server notifies the user terminal that the task has been created and registered in the calendar.

[1043] 7. Users can check their calendar on their device to see newly added tasks and appointments.

[1044] Specific example:

[1045] For example, if a customer sends an email requesting a meeting for next Monday, the server receives the email, analyzes its content, and uses an emotion engine to analyze the user's current emotions before registering the meeting request as a task. If the user is feeling excessive pressure, the task's priority is lowered, and the email content is summarized concisely before being added to the calendar.

[1046] Automated meeting room booking

[1047] System operation:

[1048] 1. The user enters the meeting date and time and the required number of participants from their device and sends a request to the server.

[1049] 2. The server receives the request and accesses a system or database that manages the availability of meeting rooms to execute a query to check their availability.

[1050] 3. The server retrieves a list of available meeting rooms and selects the most suitable meeting room for the specified date, time, and number of people.

[1051] 4. Before booking a meeting room, the server uses an emotion engine to analyze the user's emotions.

[1052] 5. The server will make customizations based on the user's emotions, such as changing the selection of a meeting room.

[1053] 6. The server automatically reserves meeting rooms through the reservation system and notifies the user terminal of the reservation result.

[1054] 7. Users can check the reservation results on their device and confirm that the meeting room has been reserved.

[1055] Specific example:

[1056] For example, if a user wants to reserve a "meeting room for 10 people for 2 hours starting at 2:00 PM on October 15, 2023," they enter the information into their terminal and send it to the server. The server retrieves availability from the meeting room management system, selects the most suitable meeting room, and then uses an emotion engine to analyze the user's emotions. If the user is feeling anxious, the server prioritizes selecting a meeting room with a calmer environment and makes the reservation. The reservation result is then displayed on the terminal.

[1057] Zoom automatic setup

[1058] System operation:

[1059] 1. The user enters the meeting date and time and participant list from their device and sends a request to the server.

[1060] 2. The server receives the request and sends a request to the Zoom server to create a new Zoom meeting using the Zoom API.

[1061] 3. The server receives the meeting details (link and ID) returned from Zoom and stores that information.

[1062] 4. The server uses an emotion engine to analyze the user's emotions and decide how to notify them of the meeting details.

[1063] 5. Based on the saved meeting details, the server sends meeting invitations via email in the appropriate format to the participants listed in the participant list.

[1064] 6. Once the invitation email is sent, the server notifies the user that the Zoom meeting setup is complete.

[1065] 7. Users and participants can check the meeting details in the email they receive and join the Zoom meeting at the specified date and time.

[1066] Specific example:

[1067] For example, if a user wants to "set up a Zoom meeting on October 20, 2023 at 11:00 AM and send invitations to participants," they would enter that information into their device and send it to the server. The server would then use the Zoom API to create the meeting and retrieve the meeting details. The server would then use an emotion engine to analyze the user's emotions, and if, for example, the user wants to express gratitude, it would add a message to that effect to the invitation email before sending it. The user and participants would then be able to confirm the meeting details via email and join the Zoom meeting at the specified date and time.

[1068] As described above, the system based on the present invention, which incorporates an emotion engine, can automate various processes in customer management operations and further customize them according to the user's emotions, thereby significantly improving both operational efficiency and user experience.

[1069] The following describes the processing flow.

[1070] Extract graphs showing sales and profit trends for each customer over a specified period (even by product category).

[1071] Processing steps:

[1072] Step 1:

[1073] The user enters the period (start and end dates) and customer ID via the device. The device then sends the entered information to the server as a request.

[1074] Step 2:

[1075] The server receives the request and executes a query against the database based on the specified time period and customer ID.

[1076] Step 3:

[1077] The server extracts the relevant sales and profit data from the database.

[1078] Step 4:

[1079] The server organizes the extracted data by product category. Sales and profit data are grouped for each product category and sorted chronologically.

[1080] Step 5:

[1081] The server uses a graph generation library to create graphs showing the trends in sales and profits. Colors and labels can be set as needed.

[1082] Step 6:

[1083] The server uses an emotion engine to analyze the user's emotions. For example, it determines the user's current emotional state (joy, sadness, anger, etc.).

[1084] Step 7:

[1085] The graph's colors and annotations are customized based on the user's emotions, as determined by the emotion engine. For example, if the user is feeling down, an encouraging message is added.

[1086] Step 8:

[1087] The server generates customized graphs as image files or in interactive formats and sends them back to the user's terminal.

[1088] Step 9:

[1089] Users can view graphs received on their devices and check the trends in sales and profits over a specified period.

[1090] Confirmation of trading products and contract renewal month

[1091] Processing steps:

[1092] Step 1:

[1093] The user enters the customer ID they want to check on their device and sends a request to the server.

[1094] Step 2:

[1095] The server receives the request and executes a query to access the database to retrieve the customer's trading product list and contract renewal month information.

[1096] Step 3:

[1097] The server prepares a response containing a list of traded products and contract renewal month information retrieved from the database.

[1098] Step 4:

[1099] The server uses an emotion engine to analyze the user's emotions. For example, it determines the emotional state the user is in when viewing this information.

[1100] Step 5:

[1101] The information displayed is customized based on the emotion engine. For example, if the user is stressed, the information is displayed more concisely and important points are highlighted.

[1102] Step 6:

[1103] The server returns customized information to the user's device.

[1104] Step 7:

[1105] Users can view the list of traded products and contract renewal month information received on their device and confirm the necessary information.

[1106] Customer requests received via email are converted into tasks and automatically registered in the calendar.

[1107] Processing steps:

[1108] Step 1:

[1109] The server periodically monitors the email inbox to detect the arrival of new emails.

[1110] Step 2:

[1111] The server uses natural language processing (NLP) techniques to analyze the content of newly received emails and extract the requests.

[1112] Step 3:

[1113] The server processes the extracted requests through an emotion engine to analyze their importance based on the user's emotions.

[1114] Step 4:

[1115] Task priorities are adjusted based on requests analyzed by the emotion engine. If the user is experiencing stress, the priority of low-priority tasks is lowered.

[1116] Step 5:

[1117] The server registers tasks with adjusted priorities as new tasks in the task management system. These tasks include details such as the request content and deadline.

[1118] Step 6:

[1119] The server uses the Google Calendar API based on the task information to automatically add the task to the calendar.

[1120] Step 7:

[1121] When a task is registered in the calendar, the server notifies the user's terminal that the task has been created and registered in the calendar.

[1122] Step 8:

[1123] Users can check their calendar on their device to see newly added tasks and appointments.

[1124] Automated meeting room booking

[1125] Processing steps:

[1126] Step 1:

[1127] The user enters the meeting date and time and the required number of participants from their device and sends a request to the server.

[1128] Step 2:

[1129] The server receives the request and accesses a system or database that manages the availability of meeting rooms to execute a query to check their availability.

[1130] Step 3:

[1131] The server retrieves a list of available meeting rooms and selects the most suitable one for the specified date, time, and number of people.

[1132] Step 4:

[1133] Before booking a meeting room, the server uses an emotion engine to analyze the user's emotions. For example, it determines the user's current mood and stress level.

[1134] Step 5:

[1135] The server adjusts the selection of meeting rooms based on the user's emotions. For example, if the user is feeling stressed, it will choose a meeting room with a calm environment.

[1136] Step 6:

[1137] The server automatically reserves the selected meeting room through the reservation system.

[1138] Step 7:

[1139] Once the reservation is complete, the server will notify the user's device of the result.

[1140] Step 8:

[1141] Users can check their reservation results on their device and confirm that the meeting room has been booked.

[1142] Zoom automatic setup

[1143] Processing steps:

[1144] Step 1:

[1145] The user enters the meeting date and time and participant list from their device and sends a request to the server.

[1146] Step 2:

[1147] The server receives the request and sends a request to the Zoom server to create a new Zoom meeting using the Zoom API.

[1148] Step 3:

[1149] The server receives the meeting details (link and ID) returned from Zoom and stores that information.

[1150] Step 4:

[1151] The server uses an emotion engine to analyze the user's emotions and determine, for example, the user's current emotional state (joy, sadness, tension, etc.).

[1152] Step 5:

[1153] Customize meeting notification formats based on an emotion engine. For example, if a user is feeling grateful, add a message reflecting that sentiment to the invitation email.

[1154] Step 6:

[1155] Based on the saved meeting details, the server sends meeting invitations via email in the appropriate format to the participants listed in the participant list.

[1156] Step 7:

[1157] Once the invitation email is sent, the server notifies the user that the Zoom meeting setup is complete.

[1158] Step 8:

[1159] Users and participants can check the meeting details in the email they receive and join the Zoom meeting at the specified date and time.

[1160] As described above, the system based on the present invention, which incorporates an emotion engine, can automate various processes in customer management operations and further customize them according to the user's emotions, thereby significantly improving both operational efficiency and user experience.

[1161] (Example 2)

[1162] Next, we will describe Example 2. 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".

[1163] Traditional customer relationship management (CRM) systems failed to consider user emotions when displaying sales and profit data, making it difficult to enhance user satisfaction. Furthermore, tasks such as checking transaction products and contract renewal months, task-based processing of email requests, and automated meeting scheduling and booking lacked a responsiveness to user emotions. As a result, users were unable to maximize their work efficiency and often experienced stress and dissatisfaction.

[1164] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[1165] In this invention, the server includes means for receiving a specified period and customer ID from the user, means for extracting relevant sales data and profit data from a database, means for organizing the extracted data and generating graphs for each product, means for analyzing the user's sentiment before providing the generated graphs, means for customizing the graph colors and annotations based on the user's sentiment, and means for providing the customized graphs to the user. This enables customization according to the user's sentiment, improving operational efficiency and the user experience.

[1166] The "specified period" refers to the range of start and end dates entered by the user, and sales and profit data are extracted within that range.

[1167] A "customer ID" is a unique identifier used to identify a specific customer and corresponds to customer information in the database.

[1168] "Sales data" refers to data that includes information on the sales amount and quantity of products within a specified period.

[1169] "Profit data" refers to data that includes information about profits obtained within a specified period.

[1170] A "database" is an information system used to store and manage sales data, profit data, transaction product lists, contract renewal month information, and other customer information.

[1171] An "emotion engine" is a software module that analyzes a user's emotions and evaluates their current mood and emotional state.

[1172] A "graph generation library" is a software tool used to visualize sales and profit data, and it has the function of generating graphs and charts.

[1173] A "task management system" is a software platform for users to register, track, and manage tasks they are responsible for.

[1174] A "calendar" is a time management tool used to visually manage and display tasks and appointments.

[1175] A "mailbox" is an electronic system for storing and managing emails that a user has received.

[1176] Natural Language Processing (NLP) is a technique for analyzing text data to understand its meaning and structure and extract information.

[1177] A "task" is a specific action or item of work that needs to be done in order to achieve a certain objective.

[1178] An "online meeting system" is a meeting system that allows multiple participants to communicate in real time via the internet.

[1179] A "meeting room management system" is software or information system used to manage the reservation and availability status of meeting rooms.

[1180] This invention relates to a system that streamlines customer management operations and improves the user experience. This system analyzes user emotions and customizes information delivery based on the results. The specific hardware and software configuration, as well as processing details, are as follows.

[1181] Overall system configuration

[1182] The system primarily consists of user terminals, servers, and databases. Users use terminals to perform various customer management operations (such as specifying time periods, entering customer IDs, and managing tasks). The server receives requests, extracts necessary information from the database, processes the data using an emotion engine and other software modules, and provides appropriate information to the user.

[1183] Hardware and software to be used

[1184] User devices: Computers, smartphones, tablets, etc.

[1185] Server: A server machine equipped with high-speed computing capabilities.

[1186] Databases: Relational database management systems such as PostgreSQL and MySQL.

[1187] Emotion engines: Microsoft Azure Emotion API, IBM Watson Tone Analyzer, etc.

[1188] Graph generation libraries: Matplotlib, D3.js, etc.

[1189] Task management systems: Trello, Asana, etc.

[1190] Online meeting systems: Zoom, Microsoft Teams, etc.

[1191] Calendar API: Google Calendar API.

[1192] Natural Language Processing (NLP) technologies: Google Cloud Natural Language API, spaCy, etc.

[1193] Example processing flow: Extract graphs of sales and profit trends (or by product) for a specified period for each customer.

[1194] Specific example:

[1195] If a user wants to view the sales and profit trends for customer ID 123 from January 1, 2023 to March 31, 2023, the user enters the period and customer ID into the input fields on the device and clicks the "Submit" button. The device then sends the specified period and customer ID to the server as an HTTP request.

[1196] When the server receives a request, it accesses the database and extracts sales and profit data for the specified period. For example, it might execute a query like "SELECT FROM sales WHERE customer_id = 123 AND date BETWEEN '2023-01-01' AND '2023-03-31'". The extracted data is then organized by product category.

[1197] Next, the server generates graphs that visually represent the data using graph generation libraries such as Matplotlib. Before the generated graphs are presented to the user, an emotion engine is used to analyze the user's emotions. For example, recent user interaction data is input into the emotion engine, and if the user is feeling down, the graph's colors and annotations are adjusted to alleviate that mood.

[1198] For example, if the emotion engine analyzes that "the user is feeling down," it will change the graph's colors to brighter ones and add an encouraging message such as, "Sales are recovering. Keep up the good work!" Finally, the customized graph is sent to the user's device, where they can view it.

[1199] Example processing flow: Confirmation of trading products and contract renewal month

[1200] Specific example:

[1201] If a user wants to check the list of traded products and contract renewal month for customer ID 456, they enter the customer ID into the terminal and click the "Confirm" button. This causes the terminal to send the customer ID to the server as an HTTP request.

[1202] When the server receives a request, it accesses the database and executes a query to retrieve the customer's transaction list and contract renewal month information. An example query might be "SELECT FROM contracts WHERE customer_id = 456". The retrieved information is analyzed by the sentiment engine, and the displayed content is adjusted based on the user's sentiment.

[1203] For example, if analysis indicates that a user is experiencing stress, the acquired information is displayed concisely and the key points are highlighted before being sent to the user's device. The user can then review the information on their device.

[1204] Example processing flow: Customer requests received via email are converted into tasks and automatically registered in the calendar.

[1205] Specific example:

[1206] If a customer sends an email requesting "Please schedule a meeting for next Monday," the server periodically monitors the mailbox and analyzes incoming new emails using natural language processing (NLP) techniques. The analysis extracts the request, and an emotion engine adjusts the task's priority based on the user's emotions.

[1207] The server then registers the coordinated tasks as new tasks in task management systems such as Trello or Asana. Information including task details is automatically added to the calendar using the Google Calendar API. Finally, the server notifies the user's device that task creation and calendar registration are complete. The user can then view the new tasks and appointments on their device.

[1208] Thus, the system of the present invention utilizes an emotion engine to customize the system according to the user's emotions, thereby improving the efficiency of customer management operations and enhancing the user experience. Since various data analyses and processing are automated, users can perform their tasks with minimal stress.

[1209] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1210] Extract graphs showing sales and profit trends for each customer over a specified period (even by product category).

[1211] Step 1:

[1212] The user uses their device to enter the specified period (e.g., start and end dates) and customer ID, and then sends the request to the server.

[1213] Input: Start date, End date, Customer ID

[1214] Output: HTTP request to the server

[1215] Specific actions:

[1216] The user enters the period from "January 1, 2023" to "March 31, 2023" and customer ID "123" into the input form on their device and clicks the "Submit" button. This causes the device to construct the necessary information as an HTTP request and send it to the server.

[1217] Step 2:

[1218] The server receives a request from the user, queries the database, and retrieves sales and profit data for the specified period.

[1219] Input: HTTP request (start date, end date, customer ID)

[1220] Output: Sales data and profit data

[1221] Specific actions:

[1222] The server parses the request and executes an SQL query in the database such as "SELECT FROM sales WHERE customer_id = 123 AND date BETWEEN '2023-01-01' AND '2023-03-31'". The retrieved data includes detailed sales and profit information.

[1223] Step 3:

[1224] The server organizes the data retrieved from the database by product category and uses a graph generation library to create graphs showing the trends in sales and profits.

[1225] Input: Sales data and profit data

[1226] Output: Initial graph

[1227] Specific actions:

[1228] The server groups the acquired sales and profit data by product. For example, it formats the data into sales and profits for product A, sales and profits for product B, etc., and generates line graphs of the data using Matplotlib.

[1229] Step 4:

[1230] Before displaying the generated graph, the server uses an emotion engine to analyze the user's emotions.

[1231] Input: User ID or interaction data at that time

[1232] Output: User sentiment data

[1233] Specific actions:

[1234] The server sends interaction data such as user ID, recent emails, and chat history to the emotion engine, which then analyzes the user's current emotional state using the Microsoft Azure Emotion API and IBM Watson Tone Analyzer.

[1235] Step 5:

[1236] The server customizes the graph's colors and annotations based on the results of the sentiment engine.

[1237] Input: Initial graph, sentiment data

[1238] Output: Customized graph

[1239] Specific actions:

[1240] Based on the analysis results from the emotion engine, the server customizes the graph. For example, if the user is feeling down, the graph's colors will be changed to brighter ones, and an encouraging message will be added.

[1241] Step 6:

[1242] The server sends a customized graph to the user's terminal, and the user reviews it.

[1243] Input: Customized graph

[1244] Output: HTTP response to the user terminal

[1245] Specific actions:

[1246] The customized graph is sent to the user's terminal as an HTTP response. The terminal receives the response and displays the customized graph on its screen.

[1247] Confirmation of trading products and contract renewal month

[1248] Step 1:

[1249] The user enters the customer ID they want to check on their device and sends a request to the server.

[1250] Input: Customer ID

[1251] Output: HTTP request to the server

[1252] Specific actions:

[1253] The user enters customer ID "456" into the input field on the terminal and clicks the "Confirm" button. The terminal sends this to the server as an HTTP request.

[1254] Step 2:

[1255] The server receives the request, accesses the database, and retrieves the customer's trading product list and contract renewal month information.

[1256] Input: HTTP request (customer ID)

[1257] Output: List of traded products and contract renewal month information

[1258] Specific actions:

[1259] The server executes an SQL query like "SELECT FROM contracts WHERE customer_id = 456" to retrieve the relevant information from the database.

[1260] Step 3:

[1261] The server analyzes the acquired information using an emotion engine.

[1262] Input: Acquired information, user ID, or interaction data at that time.

[1263] Output: User sentiment data

[1264] Specific actions:

[1265] The server sends the acquired information to the emotion engine, which analyzes the user's current emotional state.

[1266] Step 4:

[1267] The server customizes the displayed content based on the results of the emotion engine.

[1268] Input: Sentiment data, acquired information

[1269] Output: Customized information

[1270] Specific actions:

[1271] If the analysis indicates that the user is experiencing stress, the server will summarize the acquired information concisely, highlighting the key points and organizing the information accordingly.

[1272] Step 5:

[1273] The server sends customized information to the user's terminal, and the user confirms it.

[1274] Input: Customized information

[1275] Output: HTTP response to the user terminal

[1276] Specific actions:

[1277] Customized information is sent to the user's terminal as an HTTP response. The terminal receives the response and displays the information on its screen.

[1278] Customer requests received via email are converted into tasks and automatically registered in the calendar.

[1279] Step 1:

[1280] The server periodically monitors the email inbox to detect the arrival of new emails.

[1281] Input: Mail Inbox

[1282] Output: New email

[1283] Specific actions:

[1284] The server connects to the mail server using the IMAP protocol and checks for new mail every 5 minutes.

[1285] Step 2:

[1286] The server analyzes the content of new emails using natural language processing (NLP) techniques to extract the requests.

[1287] Input: New email

[1288] Output: Request

[1289] Specific actions:

[1290] The server sends the content of the new email to the Google Cloud Natural Language API and extracts the request, "Please schedule a meeting for next Monday."

[1291] Step 3:

[1292] The server uses an emotion engine to adjust the priority of tasks based on the user's emotions, using the extracted requests.

[1293] Input: Request details, user ID, or interaction data at that time.

[1294] Output: Tasks with adjusted priorities

[1295] Specific actions:

[1296] The server analyzes the request using an emotion engine and sets a lower priority for the task if the user is feeling excessive pressure.

[1297] Step 4:

[1298] The server registers the tasks with adjusted priorities as new tasks in the task management system.

[1299] Input: Tasks with adjusted priority

[1300] Output: New task

[1301] Specific actions:

[1302] The server uses the Trello API to create a new task titled "Schedule a meeting next Monday" with a "medium" priority.

[1303] Step 5:

[1304] The server uses the Calendar API to automatically add tasks to the calendar based on new task information.

[1305] Input: New Task

[1306] Output: Calendar Events

[1307] Specific actions:

[1308] The server uses the Google Calendar API to add an event called "Meeting next Monday" to the calendar.

[1309] Step 6:

[1310] The server notifies the user's terminal that the task has been registered in the calendar.

[1311] Input: Calendar Event

[1312] Output: Notification to user terminal

[1313] Specific actions:

[1314] The server sends a notification to the user's terminal in JSON format stating, "A new task has been added to your calendar," and the terminal displays it as a pop-up message.

[1315] Step 7:

[1316] Users check their calendar on their devices to see newly added tasks and appointments.

[1317] Input: Notification to user terminal

[1318] Output: Calendar display

[1319] Specific actions:

[1320] The user opens the calendar app on their device and sees a new meeting task added for "next Monday".

[1321] (Application Example 2)

[1322] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[1323] Traditional customer management systems have a problem in that they provide uniform information without considering user emotions, making it difficult to improve the user experience. In particular, there are many situations in tasks such as data verification and task management where responses that respond to user emotions are required, and systems that do not take this into consideration can lead to decreased user satisfaction.

[1324] The specific processing performed by the specific 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 means for receiving a period and customer identifier specified by the user, means for extracting the corresponding sales data and profit data from the database, means for organizing the extracted data and generating graphs for each product, means for providing the generated graphs to the user, and means for an emotion engine that analyzes the user's emotions and customizes the display content of the graphs based on the user's emotions. This makes it possible to customize the display of data and adjust the priority of tasks according to the user's emotions.

[1325] A "user" is someone who uses a system.

[1326] "Specified period" refers to a specific period for which sales data, profit data, and other information are to be collected, as entered by the user into the system.

[1327] A "customer identifier" is a unique ID used to identify a specific customer.

[1328] A "database" is a collection of data that systematically stores information and allows it to be searched and extracted as needed.

[1329] "Sales data" refers to data that shows the sales performance of a product over a specific period.

[1330] "Profit data" refers to data that shows net profit over a specific period.

[1331] "Extraction method" refers to a method or device for retrieving necessary data from a database based on specific conditions.

[1332] "Means of organization" refers to methods or devices for compiling and structuring extracted data according to specific criteria.

[1333] "By product category" means classifying and organizing products according to the type of product being sold.

[1334] A "graph" is a diagram or chart used to visually represent the relationships between data.

[1335] "Means of providing" refers to methods and devices for conveying information to users.

[1336] An "emotion engine" refers to a technology or device that analyzes a user's emotions from their facial expressions, voice, and other data.

[1337] "Means of customization" refers to methods or devices for changing the displayed content and the way information is presented based on the analyzed emotions of the user.

[1338] A "task" is a series of tasks or activities performed to achieve a specific objective.

[1339] "Priority" refers to a criterion that indicates the order or importance of tasks.

[1340] This invention is a system that combines an emotion engine to streamline customer management operations and improve the user experience. Specific embodiments of this system are described below.

[1341] System Configuration

[1342] This system includes a user terminal, a server, a database, and an emotion engine. The user inputs a specified period and customer identifier using the user terminal and sends a request to the server. The server accesses the database to extract the necessary data, analyzes and organizes it, and provides it to the user. The server also uses the emotion engine to analyze the user's emotions and optimizes the information delivery method based on the results.

[1343] Hardware and software to use

[1344] Hardware:

[1345] User terminals (PCs, smartphones, etc.)

[1346] server

[1347] Camera device (for capturing the user's face)

[1348] Database Server

[1349] software:

[1350] Database management system (e.g., MySQL)

[1351] Emotion engine (e.g., EmotionRecognizer)

[1352] Graph generation libraries (e.g., Matplotlib)

[1353] Task management system (e.g., Google Calendar API)

[1354] Video conferencing APIs (e.g., Zoom API)

[1355] Natural language processing libraries (e.g., NLTK)

[1356] Data processing and data calculation

[1357] The server receives requests from users and extracts sales and profit data from the database. This data is passed to a graph generation library, which generates trend graphs over a specific period. The sentiment engine then analyzes the user's emotions, and the graph's colors and annotations are customized based on the analysis results. The sentiment engine is also used in task management, adjusting task priorities and calendar entries based on the user's emotions.

[1358] Specific example

[1359] 1. Check the trends in sales and profits:

[1360] If a user wants to see the sales and profit trends for customer identifier 123 from January 1, 2023 to March 31, 2023, they enter the period and customer identifier and send a request to the server. The server extracts the necessary data from the database and generates a graph. Using an emotion engine, it analyzes the user's emotions and, if the user is feeling down, adds an encouraging message to the graph and sends it back.

[1361] 2. Automatically register tasks to the calendar:

[1362] If a customer sends an email requesting a meeting for next Monday, the server receives the email, analyzes its content, and registers it as a task. It also analyzes the user's emotions; for example, if the user is stressed, it lowers the task's priority, simplifies its content, and registers it in the calendar.

[1363] Example of a prompt

[1364] "Create a program that identifies customer emotions and displays suggestions to improve customer satisfaction. For example, if a customer is angry, suggest that the employee respond calmly and politely."

[1365] Actual prompt:

[1366] "Create an application that identifies customer emotions in real time and displays specific actions to store staff based on the recognized emotions. For example, if a customer appears happy, display a message such as, 'The customer appears happy. Let's continue to be friendly!'"

[1367] The above describes the detailed embodiments for carrying out this invention.

[1368] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1369] Step 1:

[1370] The user enters the specified period and customer identifier from their device. The entered information is sent to the server as a request.

[1371] Step 2:

[1372] The server receives requests sent by users. Based on the received requests, it accesses the database and extracts the relevant sales and profit data. Specifically, it executes database queries using the period and customer identifier as conditions to retrieve the necessary data.

[1373] Step 3:

[1374] The server organizes the extracted data and separates it by product category. Furthermore, it uses a graph generation library (e.g., Matplotlib) to generate graphs showing sales and profit trends. The generated graphs are saved to the server as image files containing a visual representation of the data.

[1375] Step 4:

[1376] The server uses an emotion engine (e.g., EmotionRecognizer) to analyze the user's emotions. The input is either a user's facial image or voice data, which is passed to the emotion engine. The emotion engine outputs emotion tags (e.g., happy, sad, angry) as the result of the analysis.

[1377] Step 5:

[1378] The server customizes the display of the generated graph based on the analysis results of the emotion engine. Specifically, it adjusts the graph's colors, annotations, and messages according to the analyzed emotion. For example, if the user is feeling down, an encouraging message will be added to the graph.

[1379] Step 6:

[1380] The server returns a customized graph to the user's terminal. The returned data is in image file or HTML format, and the user can view the graph on their terminal.

[1381] Step 7:

[1382] (Specific example: When the user is feeling stressed)

[1383] When a user requests to "check the list of traded products and contract renewal month for customer identifier 456," the server retrieves the relevant information from the database and uses an emotion engine to analyze the user's emotions. For example, if the analysis indicates that the user is feeling stressed, the information is concisely organized and presented to the user with key points highlighted.

[1384] This allows for the provision of information tailored to the user's emotions, leading to increased operational efficiency and a better user experience.

[1385] 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[1386] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1387] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[1388] [Third Embodiment]

[1389] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[1390] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[1391] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1392] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[1393] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[1394] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[1395] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[1396] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[1397] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[1398] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1399] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[1400] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[1401] This invention is a system for streamlining customer management operations, including managing sales and profit data for a specified period, confirming transaction items and contract renewal months, converting requests from emails into tasks and automatically registering them in a calendar, automatically reserving meeting rooms, and automatically setting up online meetings.

[1402] Extract graphs showing sales and profit trends for each customer over a specified period (even by product category).

[1403] System operation:

[1404] 1. The user enters the period (start date and end date) and customer ID via the terminal.

[1405] 2. The terminal sends the entered information to the server as a request.

[1406] 3. The server receives the request, accesses the database, and extracts sales and profit data for the specified period.

[1407] 4. The server organizes the extracted data by product category and uses a graph generation library to create graphs showing the trends in sales and profits.

[1408] 5. The generated graph is sent back from the server to the terminal, and the user can view the graph on the terminal.

[1409] Specific example:

[1410] For example, if a user wants to see the sales and profit trends for customer ID 123 from January 1, 2023 to March 31, 2023, they would enter the period and customer ID into their device and send a request to the server. The server would then extract the relevant data from the database, organize it by product category, and generate a graph. The generated graph would then be displayed on the user's device.

[1411] Confirmation of trading products and contract renewal month

[1412] System operation:

[1413] 1. The user enters the customer ID they wish to check from their device and sends a request to the server.

[1414] 2. The server accesses the database to retrieve the customer's trading product list and contract renewal month information.

[1415] 3. The server sends the acquired information back to the user's terminal, and the user can view and confirm that information on the screen.

[1416] Specific example:

[1417] For example, if a user wants to check the list of products traded and the contract renewal month for customer ID 456, they enter the customer ID into their terminal and send a request to the server. The server retrieves the relevant information from the database and sends it back to the user's terminal. The user can then view the displayed information.

[1418] Customer requests received via email are converted into tasks and automatically registered in the calendar.

[1419] System operation:

[1420] 1. The server periodically monitors the email inbox.

[1421] 2. If there is a new email, the server analyzes its contents using natural language processing (NLP) and extracts the request.

[1422] 3. The server registers the extracted requests as tasks in the task management system.

[1423] 4. Registered tasks are automatically added to Google Calendar.

[1424] Specific example:

[1425] For example, if a customer sends an email requesting "Please schedule a meeting for next Monday," the server receives the email, analyzes its contents, and registers the meeting request as a task. This task is automatically added to Google Calendar, and the user can then view the appointment on their calendar.

[1426] Automated meeting room booking

[1427] System operation:

[1428] 1. The user enters the meeting date and time and the required number of participants from their device.

[1429] 2. The terminal sends the input information to the server.

[1430] 3. The server accesses the meeting room management system or database to check availability based on the specified date, time, and number of people.

[1431] 4. The server automatically reserves a suitable available meeting room.

[1432] 5. The reservation results are sent back from the server to the user's terminal, and the user can check the results.

[1433] Specific example:

[1434] For example, if a user wants to reserve a "meeting room for 10 people for 2 hours starting at 2:00 PM on October 15, 2023," they enter the information into their device and send it to the server. The server accesses the meeting room management system, checks availability, and then reserves a suitable meeting room. The reservation result is displayed on the user's device.

[1435] Zoom automatic setup

[1436] System operation:

[1437] 1. The user enters the meeting date and time and participant list from their device.

[1438] 2. The terminal sends the input information to the server.

[1439] 3. The server uses the Zoom API to create a new Zoom meeting.

[1440] 4. The server retrieves the meeting details (link and ID) from Zoom.

[1441] 5. The acquired meeting details will be sent via email from the server to the participant list.

[1442] Specific example:

[1443] For example, if a user wants to "set up a Zoom meeting on October 20, 2023 at 11:00 AM and send invitations to participants," they would enter that information into their device and send it to the server. The server would then use the Zoom API to create the meeting and retrieve the meeting details. After that, the server would send meeting invitation emails to the participant list. The user and participants would then receive the meeting details via email.

[1444] As described above, the system based on the present invention can automate various processes in customer management operations and significantly improve operational efficiency.

[1445] The following describes the processing flow.

[1446] Extract graphs showing sales and profit trends for each customer over a specified period (even by product category).

[1447] Processing steps:

[1448] Step 1:

[1449] The user enters the period (start and end dates) and customer ID via the device. The device then sends the entered information to the server as a request.

[1450] Step 2:

[1451] The server parses the received request and executes a query against the database based on the specified period and customer ID.

[1452] Step 3:

[1453] The server extracts the relevant sales and profit data from the database.

[1454] Step 4:

[1455] The server organizes the extracted data by product category. Sales and profit data are grouped for each product category and sorted chronologically.

[1456] Step 5:

[1457] The server uses a graph generation library to create graphs showing the trends in sales and profits. Colors and labels can be set as needed.

[1458] Step 6:

[1459] The server generates the graph as an image file or in an interactive format and sends it back to the user's terminal.

[1460] Step 7:

[1461] Users can view graphs received on their devices and check the trends in sales and profits over a specified period.

[1462] Confirmation of trading products and contract renewal month

[1463] Processing steps:

[1464] Step 1:

[1465] The user enters the customer ID they want to check on their device and sends a request to the server.

[1466] Step 2:

[1467] The server receives the request and accesses the database to execute a query to retrieve the customer's trading product list and contract renewal month information.

[1468] Step 3:

[1469] The server returns the list of traded products and contract renewal month information, retrieved from the database, to the user's terminal as a response.

[1470] Step 4:

[1471] Users can view the list of traded products and contract renewal month information received on their device and confirm the necessary information.

[1472] Customer requests received via email are converted into tasks and automatically registered in the calendar.

[1473] Processing steps:

[1474] Step 1:

[1475] The server periodically monitors the email inbox to detect the arrival of new emails.

[1476] Step 2:

[1477] The server analyzes the content of newly received emails using natural language processing (NLP) techniques. It extracts sentences and keywords that contain the request.

[1478] Step 3:

[1479] The server registers the extracted requests as new tasks in the task management system. Each task includes details such as the request content and deadline.

[1480] Step 4:

[1481] The server uses the Google Calendar API to automatically add tasks to the calendar based on the registered task information.

[1482] Step 5:

[1483] When a task is registered in the calendar, the server notifies the user's terminal that the task has been created and registered in the calendar.

[1484] Step 6:

[1485] Users can check their calendar on their device to see newly added tasks and appointments.

[1486] Automated meeting room booking

[1487] Processing steps:

[1488] Step 1:

[1489] The user enters the meeting date and time and the required number of participants from their device and sends a request to the server.

[1490] Step 2:

[1491] The server receives the request and accesses a system or database that manages the availability of meeting rooms to execute a query to check their availability.

[1492] Step 3:

[1493] The server retrieves a list of available meeting rooms and selects the most suitable one for the specified date, time, and number of people.

[1494] Step 4:

[1495] The server automatically reserves the selected meeting room through the reservation system.

[1496] Step 5:

[1497] Once the reservation is complete, the server will notify the user's device of the result.

[1498] Step 6:

[1499] Users can check their reservation results on their device and confirm that the meeting room has been booked.

[1500] Zoom automatic setup

[1501] Processing steps:

[1502] Step 1:

[1503] The user enters the meeting date and time and participant list from their device and sends a request to the server.

[1504] Step 2:

[1505] The server receives the request and sends a request to the Zoom server to create a new Zoom meeting using the Zoom API.

[1506] Step 3:

[1507] The server receives the meeting details (link and ID) returned from Zoom and stores that information.

[1508] Step 4:

[1509] Based on the saved meeting details, the server sends meeting invitations via email to the participants listed in the participant list.

[1510] Step 5:

[1511] Once the invitation email is sent, the server notifies the user that the Zoom meeting setup is complete.

[1512] Step 6:

[1513] Users and participants can check the meeting details in the email they receive and join the Zoom meeting at the specified date and time.

[1514] As described above, the system based on the present invention has a specific processing flow for improving the efficiency of various customer management tasks and achieves business efficiency through automation.

[1515] (Example 1)

[1516] Next, we will describe Example 1. 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."

[1517] In today's busy business environment, improving the efficiency of customer management and task management is crucial. However, traditional systems require individual tasks such as managing sales and profit data for each customer, checking transaction items and contract renewal months, converting email requests into tasks, booking meeting rooms, and setting up online meetings. This often involves manual verification and data entry, leading to inefficient operations. This increases the likelihood of human error and wastes time and resources. A system is needed to solve these problems and streamline all aspects of customer management.

[1518] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[1519] In this invention, the server includes means for receiving a specified period and customer identification information from a user; means for extracting relevant sales data and profit data from an information storage device; means for organizing the extracted data and generating statistical displays by product; means for providing the generated statistical displays to the user; means for receiving the meeting date and time and participant list and creating a new meeting using a remote conferencing system; and means for notifying participants of the generated meeting details through notification means. As a result, customer management operations are centralized, and operations such as data extraction, statistical display generation, and remote meeting setup are automated, significantly improving operational efficiency.

[1520] "Specified period" refers to a time range consisting of a start date and an end date specified by the user for performing a specific action.

[1521] "Customer identification information" refers to information used to uniquely identify a specific customer, and includes customer IDs and other identifiers.

[1522] An "information storage device" is a device for storing data, and includes databases and cloud storage.

[1523] "Sales data" refers to data relating to revenue generated from sales activities within a specific period of time associated with a particular customer.

[1524] "Profit data" refers to data on net profit, which is calculated by subtracting costs from sales for a specific customer over a given period.

[1525] "Statistical display" refers to a display format such as graphs and charts that visually represent sales data and profit data.

[1526] A "remote conferencing system" is a system for setting up and managing meetings conducted remotely via the internet, and includes online conferencing services.

[1527] "Notification means" refers to a means of informing users or participants of specific information, and includes, for example, email and messaging applications.

[1528] A "product list" is a list of products that a particular customer trades.

[1529] "Contract renewal month information" refers to information about the month in which a contract with a specific customer is renewed.

[1530] A "meeting room management system" is a system used to reserve meeting rooms and check their availability.

[1531] An "electronic message box" is a box for receiving and storing emails, and it is installed on a mail server.

[1532] A "work item" is a request that has been registered as a specific task.

[1533] A "schedule" is a system for displaying and managing specific appointments or tasks in a calendar format.

[1534] A "generative AI model" is a model that uses artificial intelligence technology to automatically analyze and generate data.

[1535] A "prompt statement" is an input statement used to give specific instructions to a generative AI model.

[1536] This invention is a system designed to streamline customer management operations. This system can automate and centralize various tasks, such as managing sales and profit data for each customer, checking transaction items and contract renewal months, converting requests from emails into tasks and automatically registering them in the calendar, automatically reserving meeting rooms, and automatically setting up online meetings.

[1537] The main hardware components of this system are a server, terminals, and information storage devices. The server is responsible for processing requests, managing data, automating tasks, and providing notifications, while the terminals provide the user interface and handle information input and display. The information storage devices are used to store data such as sales data, profit data, transaction product lists, contract renewal months, tasks, and meeting room reservation status. Furthermore, software such as the Zoom API and Google Calendar API is used to set up online meetings and register them in the calendar.

[1538] Extract graphs showing sales and profit trends for each customer over a specified period (even by product category).

[1539] The user enters a specified period (start and end dates) and customer identification information via their device. The device sends this information to the server as a request. The server accesses the database and extracts sales and profit data for the specified period. Next, the server organizes the extracted data by product and creates sales and profit trend graphs using a graph generation library (e.g., Matplotlib, Chart.js). These generated graphs are sent back to the device, where the user can view them.

[1540] For example, if a user wants to view the sales and profit trends for customer ID 123 from January 1, 2023 to March 31, 2023, they would enter the period and customer ID and send a request to the server. The server would then extract the relevant data from the database, organize it by product, and generate a graph. The generated graph would then be displayed on the user's device.

[1541] Confirmation of trading products and contract renewal month

[1542] The user enters the customer identification information they wish to verify on their device and sends a request to the server. The server accesses the database and retrieves the customer's transaction product list and contract renewal month information. The retrieved information is sent back to the device, and the user can view and verify it on the screen.

[1543] As a concrete example, if a user wants to check the list of products traded and the contract renewal month for customer ID 456, they enter the customer identification information into the terminal and send a request to the server. The server retrieves the relevant information from the database and sends it back to the terminal. The user can then check the displayed information.

[1544] Requests received via email are converted into tasks and automatically registered in the calendar.

[1545] The server periodically monitors the electronic message box. If there are new messages, the server uses natural language processing (NLP) techniques to analyze the email content and extract requests. The server registers the extracted requests as work items in the task management system. These registered work items are automatically added to a calendar system such as Google Calendar.

[1546] For example, if a customer sends an email requesting "Please schedule a meeting for next Monday," the server receives the email, analyzes its contents, and registers the meeting request as a task item. This task item is automatically registered in Google Calendar, and the user can then view the appointment on their calendar.

[1547] Automated meeting room booking

[1548] The user enters the meeting date, time, and number of participants from their device. The device sends the entered information to the server. The server accesses the meeting room management system or database and checks availability based on the specified date, time, and number of participants. The server automatically reserves a suitable available meeting room and sends the result back to the device. The user can then view the result on their device.

[1549] As a concrete example, if a user wants to reserve a "meeting room for 10 people for 2 hours starting at 2:00 PM on October 15, 2023," they enter the information into their device and send it to the server. The server accesses the meeting room management system, checks the availability, and then reserves an appropriate meeting room. The reservation result is displayed on the user's device.

[1550] Zoom automatic setup

[1551] The user enters the meeting date and time and participant list from their device and sends it to the server. The server uses the Zoom API to create a new Zoom meeting and retrieves the meeting details (link and ID). The retrieved meeting details are then notified to the participant list via email or other means.

[1552] As a concrete example, if a user wants to "set up a Zoom meeting on October 20, 2023 at 11:00 AM and send invitations to participants," they would enter the meeting date and time and participant list into their device and send it to the server. The server would then use the Zoom API to create the meeting and retrieve the meeting details. After that, the server would send meeting invitation emails to the participant list. The user and participants would then receive the meeting details via email.

[1553] By implementing this invention, customer management operations can be centralized, data extraction and statistical display generation, remote meeting scheduling, and other tasks can be automated, significantly improving operational efficiency.

[1554] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1555] Extract graphs showing sales and profit trends for each customer over a specified period (even by product category).

[1556] Step 1:

[1557] The user enters the period (start and end dates) and customer identification information via their device.

[1558] Input: Period (e.g., January 1, 2023 - March 31, 2023), Customer identification information (e.g., Customer ID 123)

[1559] Output: User input data is received by the terminal.

[1560] Step 2:

[1561] The terminal generates a request containing the period and customer identification information and sends it to the server.

[1562] Input: User input data (period and customer identification information)

[1563] Output: The generated request is sent to the server.

[1564] Step 3:

[1565] The server receives the request, accesses the information storage device, and extracts sales and profit data for the specified period.

[1566] Input: Request received from the terminal, data in the information storage device.

[1567] Output: A set of sales data and profit data is extracted.

[1568] Step 4:

[1569] The server extracts data and organizes it by product. A graph generation library is then used to create graphs showing the trends in sales and profits.

[1570] Input: Extracted sales data and profit data

[1571] Output: Graphs showing sales and profit trends by product (e.g., graphs generated using Matplotlib or Chart.js)

[1572] Step 5:

[1573] The generated graph is sent back from the server to the terminal, allowing the user to view the graph on their terminal.

[1574] Input: Generated graph

[1575] Output: The graph will be displayed on the terminal.

[1576] Confirmation of trading products and contract renewal month

[1577] Step 1:

[1578] The user enters the customer identification information they wish to verify from their device.

[1579] Input: Customer identification information (e.g., Customer ID 456)

[1580] Output: User input data is received by the terminal.

[1581] Step 2:

[1582] The terminal generates customer identification information as a request and sends it to the server.

[1583] Input: Customer identification information

[1584] Output: The generated request is sent to the server.

[1585] Step 3:

[1586] The server receives the request and retrieves the customer's trading product list and contract renewal month information from its data storage device.

[1587] Input: Request received from the terminal, data in the information storage device.

[1588] Output: A list of traded products and contract renewal month information are retrieved.

[1589] Step 4:

[1590] The acquired information is sent back from the server to the terminal, and the user can view the information on the terminal.

[1591] Input: List of traded products and contract renewal month information

[1592] Output: Information is displayed on the terminal.

[1593] Requests received via email are converted into tasks and automatically registered in the calendar.

[1594] Step 1:

[1595] The server periodically monitors the electronic message box.

[1596] Input: Status of the electronic message box

[1597] Output: Checks for the presence of new messages.

[1598] Step 2:

[1599] If there is a new message, the server uses natural language processing (NLP) techniques to analyze the email content and extract the request.

[1600] Input: Content of the newly received email

[1601] Output: Request details are extracted.

[1602] Step 3:

[1603] The server registers the extracted requests as work items in the task management system.

[1604] Input: Request

[1605] Output: The work item is registered in the task management system.

[1606] Step 4:

[1607] Registered work items are automatically added to calendar systems such as Google Calendar.

[1608] Input: Work item

[1609] Output: Events registered in the calendar

[1610] Automated meeting room booking

[1611] Step 1:

[1612] The user enters the meeting date, time, and number of participants from their device.

[1613] Input: Meeting date and time (e.g., October 15, 2023, 2:00 PM for 2 hours), Number of participants (e.g., 10 people)

[1614] Output: User input data is received by the terminal.

[1615] Step 2:

[1616] The terminal generates the input information as a request and sends it to the server.

[1617] Input: User input data (meeting date and time, number of participants)

[1618] Output: The generated request is sent to the server.

[1619] Step 3:

[1620] The server accesses the meeting room management system or information storage device to check availability based on the specified date, time, and number of people.

[1621] Input: Requests received from terminals, meeting room management system, or data stored in information storage devices.

[1622] Output: Meeting room availability is checked.

[1623] Step 4:

[1624] The server automatically reserves a suitable available meeting room and sends the reservation result back to the terminal.

[1625] Input: Meeting room availability

[1626] Output: The reservation result is sent back to the device and displayed.

[1627] Zoom automatic setup

[1628] Step 1:

[1629] The user enters the meeting date and time and participant list from their device.

[1630] Input: Meeting date and time (e.g., October 20, 2023, 11:00), participant list

[1631] Output: User input data is received by the terminal.

[1632] Step 2:

[1633] The terminal generates the input information as a request and sends it to the server.

[1634] Input: Meeting date and time and participant list

[1635] Output: The generated request is sent to the server.

[1636] Step 3:

[1637] The server uses the Zoom API to create a new Zoom meeting and retrieves the meeting details (link and ID).

[1638] Input: Request received from the terminal

[1639] Output: Zoom meeting details

[1640] Step 4:

[1641] The generated meeting details are notified from the server to the participant list via a notification system.

[1642] Input: Zoom meeting details

[1643] Output: Meeting details will be sent to participants.

[1644] The above outlines the step-by-step flow of the program processing for this system.

[1645] (Application Example 1)

[1646] Next, we will explain Application Example 1. In the following explanation, 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."

[1647] In traditional customer management operations, tasks such as managing sales and profit data, checking transaction products and contract renewal months, and registering tasks on a calendar were performed manually, requiring a significant amount of time and effort. Furthermore, it was difficult to check and manage this information in real time using smart devices, thus creating a need for improved operational efficiency.

[1648] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[1649] In this invention, the server includes means for receiving a specified period and customer ID from the user, means for extracting relevant sales data and profit data from a database, means for organizing the extracted data and generating graphs for each product, means for providing the generated graphs to the user, and means for visualizing the sales data and profit data so that the user can efficiently check them via a smart device. This streamlines customer management operations that were previously performed manually, and enables real-time data confirmation and management using smart devices.

[1650] A "user" is someone who operates and gives instructions to a system.

[1651] A "customer ID" is a unique identification number used to identify a specific customer.

[1652] A "database" is a system that stores a collection of data and allows for the efficient retrieval and extraction of necessary information.

[1653] "Sales data" refers to information regarding the sales amount of a product over a specific period.

[1654] "Profit data" refers to information about profits obtained by subtracting expenses from sales during a specific period.

[1655] A "smart device" is a general term for electronic devices that can connect to the internet and provide users with various types of information.

[1656] "Graph generation" is the process of creating diagrams to visually represent data.

[1657] "Merchandise" refers to the goods or services that are sold.

[1658] "Traded goods" refer to products or services that are traded between customers and the service provider.

[1659] "Contract renewal month" refers to the month in which an existing contract is scheduled to be renewed.

[1660] A "mailbox" is a virtual inbox for receiving emails.

[1661] A "task management system" is a system for registering, tracking, and managing tasks and work.

[1662] "Natural language processing" is a technology that enables computers to understand, analyze, and generate human language.

[1663] A "calendar" is an application used to manage dates and appointments.

[1664] This invention is a system that streamlines customer management tasks such as managing sales and profit data, checking transaction items and contract renewal months, and task management and calendar registration. The system receives information specified by the user, accesses a database to extract the necessary data, and visualizes or notifies the user via a smart device, enabling real-time data confirmation and management.

[1665] The server monitors the mailbox and analyzes requests from received emails using natural language processing (NLP) technology. The analyzed requests are automatically registered in a task management system, and these tasks are then automatically registered in calendar systems such as Google Calendar. For example, if a user receives an email requesting "Please schedule a meeting for next Monday," the server analyzes this content, registers it as a meeting scheduling task, and reflects it in the calendar.

[1666] Furthermore, sales and profit data are extracted from the database based on customer IDs, organized by product category, and visualized using a graph generation library. The generated graphs are provided to the user via a smart device. This allows users to check the data in real time and adjust their work accordingly. For example, if a user wants to check the sales and profit trends from January to March 2023, they enter the period and customer ID and send a request to the server. The server extracts the relevant data from the database, generates a graph, and provides it to the user.

[1667] Furthermore, it is possible to retrieve information such as the products traded and the contract renewal month from the customer ID and provide it to the user via a smart device. For example, if a user wants to check the list of products traded and the contract renewal month for a specific customer, they can enter that information, and the server will retrieve the relevant information from the database and provide it to the user via the smart device.

[1668] In this system, smart devices such as smartphones, smart glasses, and head-mounted displays can be used. For example, by using smart glasses, store staff can efficiently manage inventory and customer information.

[1669] Examples of specific prompt statements include the following:

[1670] "Please graph the sales and profit trends for customer ID: 123 from January 1, 2023 to March 31, 2023."

[1671] In this way, the system provides a way to significantly streamline customer management operations through the integration of servers and smart devices.

[1672] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1673] Step 1:

[1674] The user enters a specified period and customer ID using a device (e.g., a smartphone or smart glasses). This input data is fundamental information for retrieving and analyzing customer sales and profit data. This input is sent to the server as a request.

[1675] Step 2:

[1676] The server receives a request sent by the user. The request includes a specified period and a customer ID. Based on this information, the server accesses the database and extracts the relevant sales and profit data. This data extraction process filters the records in the database for the specified period and selects only the data related to the relevant customer ID.

[1677] Step 3:

[1678] The server organizes the extracted sales and profit data by product category. This data processing classifies the data by product category and organizes it chronologically. Furthermore, the data is visualized using a graph generation library. For example, sales and profit trends are generated as line graphs and bar graphs.

[1679] Step 4:

[1680] The generated graph is sent back from the server to the user's device. This graph is displayed on the smart device screen, allowing the user to view the data in real time. A specific visualization example is a time-series graph of sales and profits displayed on smart glasses.

[1681] Step 5:

[1682] The user sends a request from their terminal to the server, specifying their customer ID, to view a list of traded products and information about their contract renewal month. This information is necessary to manage the customer's trading status.

[1683] Step 6:

[1684] The server retrieves a list of traded products and contract renewal month information from the database based on the customer ID. This data retrieval process refers to the transaction history data and contract information database to extract the latest product list and contract renewal month corresponding to the specified customer ID.

[1685] Step 7:

[1686] The acquired list of traded products and contract renewal month information are sent back from the server to the user's device. Users can view and manage this information through the screen of their smart device.

[1687] Step 8:

[1688] The server periodically monitors the mailbox and analyzes the content of new emails as they arrive. For example, if a user receives a meeting invitation email, the server analyzes the email content using natural language processing (NLP) techniques to extract the request details.

[1689] Step 9:

[1690] The analyzed requests are automatically registered in the task management system. This task registration process writes new task information to the task management database, which is then managed for later reference.

[1691] Step 10:

[1692] Registered tasks are automatically registered by the server in a calendar system such as Google Calendar. This calendar registration process generates task details as a calendar event, set to the specified date and time. This allows users to check their task schedules in real time via their smart devices.

[1693] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[1694] This invention combines a customer management system with an emotion engine that recognizes user emotions to further enhance the user experience. In addition to managing sales and profit data for specified periods, checking transaction products and contract renewal months, creating tasks from email requests and automatically registering them in the calendar, automatically booking meeting rooms, and automatically setting up online meetings, this system also provides information based on user emotions.

[1695] Extract graphs showing sales and profit trends for each customer over a specified period (even by product category).

[1696] System operation:

[1697] 1. The user enters the period (start date and end date) and customer ID via the terminal. The terminal sends the entered information to the server as a request.

[1698] 2. The server receives the request, accesses the database, and extracts sales and profit data for the specified period.

[1699] 3. The server organizes the extracted data by product category and uses a graph generation library to create graphs showing the trends in sales and profits.

[1700] 4. Before displaying the generated graph, the server uses an emotion engine to analyze the user's emotions.

[1701] 5. The server uses an emotion engine to customize the graph's colors and annotations to match the user's mood.

[1702] 6. The server returns the customized graph to the user's device, and the user can view the graph on their device.

[1703] Specific example:

[1704] For example, if a user wants to see the sales and profit trends for customer ID 123 from January 1, 2023 to March 31, 2023, they would enter the period and customer ID into their device and send a request to the server. The server would then extract the relevant data from the database, organize it by product category, and generate a graph. After that, the emotion engine would analyze the user's emotions, and if the user is feeling down, it would add an encouraging message to the graph and send it back.

[1705] Confirmation of trading products and contract renewal month

[1706] System operation:

[1707] 1. The user enters the customer ID they wish to check from their device and sends a request to the server.

[1708] 2. The server receives the request and executes a query to access the database to retrieve the customer's trading product list and contract renewal month information.

[1709] 3. The server analyzes the acquired information through an emotion engine and determines the display content that corresponds to the user's emotions.

[1710] 4. The server returns information adjusted by the emotion engine to the user's terminal, and the user can view and confirm this information on the screen.

[1711] Specific example:

[1712] For example, if a user wants to check the list of products traded and the contract renewal month for customer ID 456, they enter the customer ID into their terminal and send a request to the server. After the server retrieves the relevant information from the database, it uses an emotion engine to analyze the user's emotions. If the user is feeling stressed, the information is displayed concisely and the important points are highlighted in the response.

[1713] Customer requests received via email are converted into tasks and automatically registered in the calendar.

[1714] System operation:

[1715] 1. The server periodically monitors the email inbox and detects the arrival of new emails.

[1716] 2. The server analyzes the content of newly received emails using natural language processing (NLP) techniques and extracts the requests.

[1717] 3. The server uses an emotion engine to adjust the priority of the extracted requests based on the user's emotions.

[1718] 4. The server registers the prioritized tasks as new tasks in the task management system. The tasks include details such as the request content and deadline.

[1719] 5. Using the registered task information, the Google Calendar API is used to automatically add tasks to the calendar.

[1720] 6. When a task is registered in the calendar, the server notifies the user terminal that the task has been created and registered in the calendar.

[1721] 7. Users can check their calendar on their device to see newly added tasks and appointments.

[1722] Specific example:

[1723] For example, if a customer sends an email requesting a meeting for next Monday, the server receives the email, analyzes its content, and uses an emotion engine to analyze the user's current emotions before registering the meeting request as a task. If the user is feeling excessive pressure, the task's priority is lowered, and the email content is summarized concisely before being added to the calendar.

[1724] Automated meeting room booking

[1725] System operation:

[1726] 1. The user enters the meeting date and time and the required number of participants from their device and sends a request to the server.

[1727] 2. The server receives the request and accesses a system or database that manages the availability of meeting rooms to execute a query to check their availability.

[1728] 3. The server retrieves a list of available meeting rooms and selects the most suitable meeting room for the specified date, time, and number of people.

[1729] 4. Before booking a meeting room, the server uses an emotion engine to analyze the user's emotions.

[1730] 5. The server will make customizations based on the user's emotions, such as changing the selection of a meeting room.

[1731] 6. The server automatically reserves meeting rooms through the reservation system and notifies the user terminal of the reservation result.

[1732] 7. Users can check the reservation results on their device and confirm that the meeting room has been reserved.

[1733] Specific example:

[1734] For example, if a user wants to reserve a "meeting room for 10 people for 2 hours starting at 2:00 PM on October 15, 2023," they enter the information into their terminal and send it to the server. The server retrieves availability from the meeting room management system, selects the most suitable meeting room, and then uses an emotion engine to analyze the user's emotions. If the user is feeling anxious, the server prioritizes selecting a meeting room with a calmer environment and makes the reservation. The reservation result is then displayed on the terminal.

[1735] Zoom automatic setup

[1736] System operation:

[1737] 1. The user enters the meeting date and time and participant list from their device and sends a request to the server.

[1738] 2. The server receives the request and sends a request to the Zoom server to create a new Zoom meeting using the Zoom API.

[1739] 3. The server receives the meeting details (link and ID) returned from Zoom and stores that information.

[1740] 4. The server uses an emotion engine to analyze the user's emotions and decide how to notify them of the meeting details.

[1741] 5. Based on the saved meeting details, the server sends meeting invitations via email in the appropriate format to the participants listed in the participant list.

[1742] 6. Once the invitation email is sent, the server notifies the user that the Zoom meeting setup is complete.

[1743] 7. Users and participants can check the meeting details in the email they receive and join the Zoom meeting at the specified date and time.

[1744] Specific example:

[1745] For example, if a user wants to "set up a Zoom meeting on October 20, 2023 at 11:00 AM and send invitations to participants," they would enter that information into their device and send it to the server. The server would then use the Zoom API to create the meeting and retrieve the meeting details. The server would then use an emotion engine to analyze the user's emotions, and if, for example, the user wants to express gratitude, it would add a message to that effect to the invitation email before sending it. The user and participants would then be able to confirm the meeting details via email and join the Zoom meeting at the specified date and time.

[1746] As described above, the system based on the present invention, which incorporates an emotion engine, can automate various processes in customer management operations and further customize them according to the user's emotions, thereby significantly improving both operational efficiency and user experience.

[1747] The following describes the processing flow.

[1748] Extract graphs showing sales and profit trends for each customer over a specified period (even by product category).

[1749] Processing steps:

[1750] Step 1:

[1751] The user enters the period (start and end dates) and customer ID via the device. The device then sends the entered information to the server as a request.

[1752] Step 2:

[1753] The server receives the request and executes a query against the database based on the specified time period and customer ID.

[1754] Step 3:

[1755] The server extracts the relevant sales and profit data from the database.

[1756] Step 4:

[1757] The server organizes the extracted data by product category. Sales and profit data are grouped for each product category and sorted chronologically.

[1758] Step 5:

[1759] The server uses a graph generation library to create graphs showing the trends in sales and profits. Colors and labels can be set as needed.

[1760] Step 6:

[1761] The server uses an emotion engine to analyze the user's emotions. For example, it determines the user's current emotional state (joy, sadness, anger, etc.).

[1762] Step 7:

[1763] The graph's colors and annotations are customized based on the user's emotions, as determined by the emotion engine. For example, if the user is feeling down, an encouraging message is added.

[1764] Step 8:

[1765] The server generates customized graphs as image files or in interactive formats and sends them back to the user's terminal.

[1766] Step 9:

[1767] Users can view graphs received on their devices and check the trends in sales and profits over a specified period.

[1768] Confirmation of trading products and contract renewal month

[1769] Processing steps:

[1770] Step 1:

[1771] The user enters the customer ID they want to check on their device and sends a request to the server.

[1772] Step 2:

[1773] The server receives the request and accesses the database to execute a query to retrieve the customer's trading product list and contract renewal month information.

[1774] Step 3:

[1775] The server prepares a response containing a list of traded products and contract renewal month information retrieved from the database.

[1776] Step 4:

[1777] The server uses an emotion engine to analyze the user's emotions. For example, it determines the emotional state the user is in when viewing this information.

[1778] Step 5:

[1779] The information displayed is customized based on the emotion engine. For example, if the user is stressed, the information is displayed more concisely and important points are highlighted.

[1780] Step 6:

[1781] The server returns customized information to the user's device.

[1782] Step 7:

[1783] Users can view the list of traded products and contract renewal month information received on their device and confirm the necessary information.

[1784] Customer requests received via email are converted into tasks and automatically registered in the calendar.

[1785] Processing steps:

[1786] Step 1:

[1787] The server periodically monitors the email inbox to detect the arrival of new emails.

[1788] Step 2:

[1789] The server uses natural language processing (NLP) techniques to analyze the content of newly received emails and extract the requests.

[1790] Step 3:

[1791] The server processes the extracted requests through an emotion engine to analyze their importance based on the user's emotions.

[1792] Step 4:

[1793] The system adjusts task priorities based on requests analyzed by the emotion engine. If the user is experiencing stress, it lowers the priority of less important tasks.

[1794] Step 5:

[1795] The server registers tasks with adjusted priorities as new tasks in the task management system. These tasks include details such as the request content and deadline.

[1796] Step 6:

[1797] The server uses the Google Calendar API based on the task information to automatically add the task to the calendar.

[1798] Step 7:

[1799] When a task is registered in the calendar, the server notifies the user's terminal that the task has been created and registered in the calendar.

[1800] Step 8:

[1801] Users can check their calendar on their device to see newly added tasks and appointments.

[1802] Automated meeting room booking

[1803] Processing steps:

[1804] Step 1:

[1805] The user enters the meeting date and time and the required number of participants from their device and sends a request to the server.

[1806] Step 2:

[1807] The server receives the request and accesses a system or database that manages the availability of meeting rooms to execute a query to check their availability.

[1808] Step 3:

[1809] The server retrieves a list of available meeting rooms and selects the most suitable one for the specified date, time, and number of people.

[1810] Step 4:

[1811] Before booking a meeting room, the server uses an emotion engine to analyze the user's emotions. For example, it determines the user's current mood and stress level.

[1812] Step 5:

[1813] The server adjusts the selection of meeting rooms based on the user's emotions. For example, if the user is feeling stressed, it will choose a meeting room with a calm environment.

[1814] Step 6:

[1815] The server automatically reserves the selected meeting room through the reservation system.

[1816] Step 7:

[1817] Once the reservation is complete, the server will notify the user's device of the result.

[1818] Step 8:

[1819] Users can check their reservation results on their device and confirm that the meeting room has been booked.

[1820] Zoom automatic setup

[1821] Processing steps:

[1822] Step 1:

[1823] The user enters the meeting date and time and participant list from their device and sends a request to the server.

[1824] Step 2:

[1825] The server receives the request and sends a request to the Zoom server to create a new Zoom meeting using the Zoom API.

[1826] Step 3:

[1827] The server receives the meeting details (link and ID) returned from Zoom and stores that information.

[1828] Step 4:

[1829] The server uses an emotion engine to analyze the user's emotions and determine, for example, the user's current emotional state (joy, sadness, tension, etc.).

[1830] Step 5:

[1831] Customize meeting notification formats based on an emotion engine. For example, if a user is feeling grateful, add a message reflecting that sentiment to the invitation email.

[1832] Step 6:

[1833] Based on the saved meeting details, the server sends meeting invitations via email in the appropriate format to the participants listed in the participant list.

[1834] Step 7:

[1835] Once the invitation email is sent, the server notifies the user that the Zoom meeting setup is complete.

[1836] Step 8:

[1837] Users and participants can check the meeting details in the email they receive and join the Zoom meeting at the specified date and time.

[1838] As described above, the system based on the present invention, which incorporates an emotion engine, can automate various processes in customer management operations and further customize them according to the user's emotions, thereby significantly improving both operational efficiency and user experience.

[1839] (Example 2)

[1840] Next, we will describe Example 2. 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."

[1841] Traditional customer relationship management (CRM) systems failed to consider user emotions when displaying sales and profit data, making it difficult to enhance user satisfaction. Furthermore, tasks such as checking transaction products and contract renewal months, task-based processing of email requests, and automated meeting scheduling and booking lacked a responsiveness to user emotions. As a result, users were unable to maximize their work efficiency and often experienced stress and dissatisfaction.

[1842] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[1843] In this invention, the server includes means for receiving a specified period and customer ID from the user, means for extracting relevant sales data and profit data from a database, means for organizing the extracted data and generating graphs for each product, means for analyzing the user's sentiment before providing the generated graphs, means for customizing the graph colors and annotations based on the user's sentiment, and means for providing the customized graphs to the user. This enables customization according to the user's sentiment, improving operational efficiency and the user experience.

[1844] The "specified period" refers to the range of start and end dates entered by the user, and sales and profit data are extracted within that range.

[1845] A "customer ID" is a unique identifier used to identify a specific customer and corresponds to customer information in the database.

[1846] "Sales data" refers to data that includes information on the sales amount and quantity of products within a specified period.

[1847] "Profit data" refers to data that includes information about profits obtained within a specified period.

[1848] A "database" is an information system used to store and manage sales data, profit data, transaction product lists, contract renewal month information, and other customer information.

[1849] An "emotion engine" is a software module that analyzes a user's emotions and evaluates their current mood and emotional state.

[1850] A "graph generation library" is a software tool used to visualize sales and profit data, and it has the function of generating graphs and charts.

[1851] A "task management system" is a software platform for users to register, track, and manage tasks they are responsible for.

[1852] A "calendar" is a time management tool used to visually manage and display tasks and appointments.

[1853] A "mailbox" is an electronic system for storing and managing emails that a user has received.

[1854] Natural Language Processing (NLP) is a technique for analyzing text data to understand its meaning and structure and extract information.

[1855] A "task" is a specific action or item of work that needs to be done in order to achieve a certain objective.

[1856] An "online meeting system" is a meeting system that allows multiple participants to communicate in real time via the internet.

[1857] A "meeting room management system" is software or information system used to manage the reservation and availability status of meeting rooms.

[1858] This invention relates to a system that streamlines customer management operations and improves the user experience. This system analyzes user emotions and customizes information delivery based on the results. The specific hardware and software configuration, as well as processing details, are as follows.

[1859] Overall system configuration

[1860] The system primarily consists of user terminals, servers, and databases. Users use terminals to perform various customer management operations (such as specifying time periods, entering customer IDs, and managing tasks). The server receives requests, extracts necessary information from the database, processes the data using an emotion engine and other software modules, and provides appropriate information to the user.

[1861] Hardware and software to be used

[1862] User devices: Computers, smartphones, tablets, etc.

[1863] Server: A server machine equipped with high-speed computing capabilities.

[1864] Databases: Relational database management systems such as PostgreSQL and MySQL.

[1865] Emotion engines: Microsoft Azure Emotion API, IBM Watson Tone Analyzer, etc.

[1866] Graph generation libraries: Matplotlib, D3.js, etc.

[1867] Task management systems: Trello, Asana, etc.

[1868] Online meeting systems: Zoom, Microsoft Teams, etc.

[1869] Calendar API: Google Calendar API.

[1870] Natural Language Processing (NLP) technologies: Google Cloud Natural Language API, spaCy, etc.

[1871] Example processing flow: Extract graphs of sales and profit trends (or by product) for a specified period for each customer.

[1872] Specific example:

[1873] If a user wants to view the sales and profit trends for customer ID 123 from January 1, 2023 to March 31, 2023, the user enters the period and customer ID into the input fields on the device and clicks the "Submit" button. The device then sends the specified period and customer ID to the server as an HTTP request.

[1874] When the server receives a request, it accesses the database and extracts sales and profit data for the specified period. For example, it might execute a query like "SELECT FROM sales WHERE customer_id = 123 AND date BETWEEN '2023-01-01' AND '2023-03-31'". The extracted data is then organized by product category.

[1875] Next, the server generates graphs that visually represent the data using graph generation libraries such as Matplotlib. Before the generated graphs are presented to the user, an emotion engine is used to analyze the user's emotions. For example, recent user interaction data is input into the emotion engine, and if the user is feeling down, the graph's colors and annotations are adjusted to alleviate that mood.

[1876] For example, if the emotion engine analyzes that "the user is feeling down," it will change the graph's colors to brighter ones and add an encouraging message such as, "Sales are recovering. Keep up the good work!" Finally, the customized graph is sent to the user's device, where they can view it.

[1877] Example processing flow: Confirmation of trading products and contract renewal month

[1878] Specific example:

[1879] If a user wants to check the list of traded products and contract renewal month for customer ID 456, they enter the customer ID into the terminal and click the "Confirm" button. The terminal then sends the customer ID to the server as an HTTP request.

[1880] When the server receives a request, it accesses the database and executes a query to retrieve the customer's transaction list and contract renewal month information. An example query might be "SELECT FROM contracts WHERE customer_id = 456". The retrieved information is analyzed by the sentiment engine, and the displayed content is adjusted based on the user's sentiment.

[1881] For example, if analysis indicates that a user is experiencing stress, the acquired information is displayed concisely and the key points are highlighted before being sent to the user's device. The user can then review the information on their device.

[1882] Example processing flow: Customer requests received via email are converted into tasks and automatically registered in the calendar.

[1883] Specific example:

[1884] If a customer sends an email requesting "Please schedule a meeting for next Monday," the server periodically monitors the mailbox and analyzes incoming new emails using natural language processing (NLP) techniques. The analysis extracts the request, and an emotion engine adjusts the task's priority based on the user's emotions.

[1885] The server then registers the coordinated tasks as new tasks in task management systems such as Trello or Asana. Information including task details is automatically added to the calendar using the Google Calendar API. Finally, the server notifies the user's device that task creation and calendar registration are complete. The user can then view the new tasks and appointments on their device.

[1886] Thus, the system of the present invention utilizes an emotion engine to customize the system according to the user's emotions, thereby improving the efficiency of customer management operations and enhancing the user experience. Since various data analyses and processing are automated, users can perform their tasks with minimal stress.

[1887] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1888] Extract graphs showing sales and profit trends for each customer over a specified period (even by product category).

[1889] Step 1:

[1890] The user uses their device to enter the specified period (e.g., start and end dates) and customer ID, and then sends the request to the server.

[1891] Input: Start date, End date, Customer ID

[1892] Output: HTTP request to the server

[1893] Specific actions:

[1894] The user enters the period from "January 1, 2023" to "March 31, 2023" and customer ID "123" into the input form on their device and clicks the "Submit" button. This causes the device to construct the necessary information as an HTTP request and send it to the server.

[1895] Step 2:

[1896] The server receives a request from the user, queries the database, and retrieves sales and profit data for the specified period.

[1897] Input: HTTP request (start date, end date, customer ID)

[1898] Output: Sales data and profit data

[1899] Specific actions:

[1900] The server parses the request and executes an SQL query in the database such as "SELECT FROM sales WHERE customer_id = 123 AND date BETWEEN '2023-01-01' AND '2023-03-31'". The retrieved data includes detailed sales and profit information.

[1901] Step 3:

[1902] The server organizes the data retrieved from the database by product category and uses a graph generation library to create graphs showing the trends in sales and profits.

[1903] Input: Sales data and profit data

[1904] Output: Initial graph

[1905] Specific actions:

[1906] The server groups the acquired sales and profit data by product. For example, it formats the data into sales and profits for product A, sales and profits for product B, etc., and uses Matplotlib to generate line graphs of the data.

[1907] Step 4:

[1908] Before displaying the generated graph, the server uses an emotion engine to analyze the user's emotions.

[1909] Input: User ID or interaction data at that time

[1910] Output: User sentiment data

[1911] Specific actions:

[1912] The server sends interaction data such as user ID, recent emails, and chat history to the emotion engine, which then analyzes the user's current emotional state using the Microsoft Azure Emotion API and IBM Watson Tone Analyzer.

[1913] Step 5:

[1914] The server customizes the graph's colors and annotations based on the results of the sentiment engine.

[1915] Input: Initial graph, sentiment data

[1916] Output: Customized graph

[1917] Specific actions:

[1918] Based on the analysis results from the emotion engine, the server customizes the graph. For example, if the user is feeling down, the graph's colors will be changed to brighter ones, and an encouraging message will be added.

[1919] Step 6:

[1920] The server sends a customized graph to the user's terminal, and the user reviews it.

[1921] Input: Customized graph

[1922] Output: HTTP response to the user terminal

[1923] Specific actions:

[1924] The customized graph is sent to the user's terminal as an HTTP response. The terminal receives the response and displays the customized graph on its screen.

[1925] Confirmation of trading products and contract renewal month

[1926] Step 1:

[1927] The user enters the customer ID they want to check on their device and sends a request to the server.

[1928] Input: Customer ID

[1929] Output: HTTP request to the server

[1930] Specific actions:

[1931] The user enters customer ID "456" into the input field on the terminal and clicks the "Confirm" button. The terminal sends this to the server as an HTTP request.

[1932] Step 2:

[1933] The server receives the request, accesses the database, and retrieves the customer's trading product list and contract renewal month information.

[1934] Input: HTTP request (customer ID)

[1935] Output: List of traded products and contract renewal month information

[1936] Specific actions:

[1937] The server executes an SQL query like "SELECT FROM contracts WHERE customer_id = 456" to retrieve the relevant information from the database.

[1938] Step 3:

[1939] The server analyzes the acquired information using an emotion engine.

[1940] Input: Acquired information, user ID, or interaction data at that time.

[1941] Output: User sentiment data

[1942] Specific actions:

[1943] The server sends the acquired information to the emotion engine, which analyzes the user's current emotional state.

[1944] Step 4:

[1945] The server customizes the displayed content based on the results of the emotion engine.

[1946] Input: Sentiment data, acquired information

[1947] Output: Customized information

[1948] Specific actions:

[1949] If the analysis indicates that the user is experiencing stress, the server will summarize the acquired information concisely, highlighting the key points and organizing the information accordingly.

[1950] Step 5:

[1951] The server sends customized information to the user's terminal, and the user confirms it.

[1952] Input: Customized information

[1953] Output: HTTP response to the user terminal

[1954] Specific actions:

[1955] Customized information is sent to the user's terminal as an HTTP response. The terminal receives the response and displays the information on its screen.

[1956] Customer requests received via email are converted into tasks and automatically registered in the calendar.

[1957] Step 1:

[1958] The server periodically monitors the email inbox to detect the arrival of new emails.

[1959] Input: Mail Inbox

[1960] Output: New email

[1961] Specific actions:

[1962] The server connects to the mail server using the IMAP protocol and checks for new mail every 5 minutes.

[1963] Step 2:

[1964] The server analyzes the content of new emails using natural language processing (NLP) techniques to extract the requests.

[1965] Input: New email

[1966] Output: Request

[1967] Specific actions:

[1968] The server sends the content of the new email to the Google Cloud Natural Language API and extracts the request, "Please schedule a meeting for next Monday."

[1969] Step 3:

[1970] The server uses an emotion engine to adjust the priority of tasks based on the user's emotions, using the extracted requests.

[1971] Input: Request details, user ID, or interaction data at that time.

[1972] Output: Tasks with adjusted priorities

[1973] Specific actions:

[1974] The server analyzes the request using an emotion engine and sets a lower priority for the task if the user is feeling excessive pressure.

[1975] Step 4:

[1976] The server registers the tasks with adjusted priorities as new tasks in the task management system.

[1977] Input: Tasks with adjusted priority

[1978] Output: New task

[1979] Specific actions:

[1980] The server uses the Trello API to create a new task titled "Schedule a meeting next Monday" with a "medium" priority.

[1981] Step 5:

[1982] The server uses the Calendar API to automatically add tasks to the calendar based on new task information.

[1983] Input: New Task

[1984] Output: Calendar Events

[1985] Specific actions:

[1986] The server uses the Google Calendar API to add an event called "Meeting next Monday" to the calendar.

[1987] Step 6:

[1988] The server notifies the user's terminal that the task has been registered in the calendar.

[1989] Input: Calendar Event

[1990] Output: Notification to user terminal

[1991] Specific actions:

[1992] The server sends a notification to the user's terminal in JSON format stating, "A new task has been added to your calendar," and the terminal displays it as a pop-up message.

[1993] Step 7:

[1994] Users check their calendar on their devices to see newly added tasks and appointments.

[1995] Input: Notification to user terminal

[1996] Output: Calendar display

[1997] Specific actions:

[1998] The user opens the calendar app on their device and sees a new meeting task added for "next Monday".

[1999] (Application Example 2)

[2000] Next, we will explain application example 2. In the following explanation, 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."

[2001] Traditional customer management systems have a problem in that they provide uniform information without considering user emotions, making it difficult to improve the user experience. In particular, there are many situations in tasks such as data verification and task management where responses that respond to user emotions are required, and systems that do not take this into consideration can lead to decreased user satisfaction.

[2002] The specific processing performed by the specific 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 means for receiving a period and customer identifier specified by the user, means for extracting the corresponding sales data and profit data from the database, means for organizing the extracted data and generating graphs for each product, means for providing the generated graphs to the user, and means for an emotion engine that analyzes the user's emotions and customizes the display content of the graphs based on the user's emotions. This makes it possible to customize the display of data and adjust the priority of tasks according to the user's emotions.

[2003] A "user" is someone who uses a system.

[2004] "Specified period" refers to a specific period for which sales data, profit data, and other information are to be collected, as entered by the user into the system.

[2005] A "customer identifier" is a unique ID used to identify a specific customer.

[2006] A "database" is a collection of data that systematically stores information and allows it to be searched and extracted as needed.

[2007] "Sales data" refers to data that shows the sales performance of a product over a specific period.

[2008] "Profit data" refers to data that shows net profit over a specific period.

[2009] "Extraction method" refers to a method or device for retrieving necessary data from a database based on specific conditions.

[2010] "Means of organization" refers to methods or devices for compiling and structuring extracted data according to specific criteria.

[2011] "By product category" means classifying and organizing products according to the type of product being sold.

[2012] A "graph" is a diagram or chart used to visually represent the relationships between data.

[2013] "Means of providing" refers to methods and devices for conveying information to users.

[2014] An "emotion engine" refers to a technology or device that analyzes a user's emotions from their facial expressions, voice, and other data.

[2015] "Means of customization" refers to methods or devices for changing the displayed content and the way information is presented based on the analyzed emotions of the user.

[2016] A "task" is a series of tasks or activities performed to achieve a specific objective.

[2017] "Priority" refers to a criterion that indicates the order or importance of tasks.

[2018] This invention is a system that combines an emotion engine to streamline customer management operations and improve the user experience. Specific embodiments of this system are described below.

[2019] System Configuration

[2020] This system includes a user terminal, a server, a database, and an emotion engine. The user inputs a specified period and customer identifier using the user terminal and sends a request to the server. The server accesses the database to extract the necessary data, analyzes and organizes it, and provides it to the user. The server also uses the emotion engine to analyze the user's emotions and optimizes the information delivery method based on the results.

[2021] Hardware and software to use

[2022] Hardware:

[2023] User terminals (PCs, smartphones, etc.)

[2024] server

[2025] Camera device (for capturing the user's face)

[2026] Database Server

[2027] software:

[2028] Database management system (e.g., MySQL)

[2029] Emotion engine (e.g., EmotionRecognizer)

[2030] Graph generation libraries (e.g., Matplotlib)

[2031] Task management system (e.g., Google Calendar API)

[2032] Video conferencing APIs (e.g., Zoom API)

[2033] Natural language processing libraries (e.g., NLTK)

[2034] Data processing and data calculation

[2035] The server receives requests from users and extracts sales and profit data from the database. This data is passed to a graph generation library, which generates trend graphs over a specific period. The sentiment engine then analyzes the user's emotions, and the graph's colors and annotations are customized based on the analysis results. The sentiment engine is also used in task management, adjusting task priorities and calendar entries based on the user's emotions.

[2036] Specific example

[2037] 1. Check the trends in sales and profits:

[2038] If a user wants to see the sales and profit trends for customer identifier 123 from January 1, 2023 to March 31, 2023, they enter the period and customer identifier and send a request to the server. The server extracts the necessary data from the database and generates a graph. Using an emotion engine, it analyzes the user's emotions and, if the user is feeling down, adds an encouraging message to the graph and sends it back.

[2039] 2. Automatically register tasks to the calendar:

[2040] If a customer sends an email requesting a meeting for next Monday, the server receives the email, analyzes its content, and registers it as a task. It also analyzes the user's emotions; for example, if the user is stressed, it lowers the task's priority, simplifies its content, and registers it in the calendar.

[2041] Example of a prompt

[2042] "Create a program that identifies customer emotions and displays suggestions to improve customer satisfaction. For example, if a customer is angry, suggest that the employee respond calmly and politely."

[2043] Actual prompt:

[2044] "Create an application that identifies customer emotions in real time and displays specific actions to store staff based on the recognized emotions. For example, if a customer appears happy, display a message such as, 'The customer appears happy. Let's continue to be friendly!'"

[2045] The above describes the detailed embodiments for carrying out this invention.

[2046] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[2047] Step 1:

[2048] The user enters the specified period and customer identifier from their device. The entered information is sent to the server as a request.

[2049] Step 2:

[2050] The server receives requests sent by users. Based on the received requests, it accesses the database and extracts the relevant sales and profit data. Specifically, it executes database queries using the period and customer identifier as conditions to retrieve the necessary data.

[2051] Step 3:

[2052] The server organizes the extracted data and separates it by product category. Furthermore, it uses a graph generation library (e.g., Matplotlib) to generate graphs showing sales and profit trends. The generated graphs are saved to the server as image files containing a visual representation of the data.

[2053] Step 4:

[2054] The server uses an emotion engine (e.g., EmotionRecognizer) to analyze the user's emotions. The input is either a user's facial image or voice data, which is passed to the emotion engine. The emotion engine outputs emotion tags (e.g., happy, sad, angry) as the result of the analysis.

[2055] Step 5:

[2056] The server customizes the display of the generated graph based on the analysis results of the emotion engine. Specifically, it adjusts the graph's colors, annotations, and messages according to the analyzed emotion. For example, if the user is feeling down, an encouraging message will be added to the graph.

[2057] Step 6:

[2058] The server returns a customized graph to the user's terminal. The returned data is in image file or HTML format, and the user can view the graph on their terminal.

[2059] Step 7:

[2060] (Specific example: When the user is feeling stressed)

[2061] When a user requests to "check the list of traded products and contract renewal month for customer identifier 456," the server retrieves the relevant information from the database and uses an emotion engine to analyze the user's emotions. For example, if the analysis indicates that the user is feeling stressed, the information is concisely organized and presented to the user with key points highlighted.

[2062] This allows for the provision of information tailored to the user's emotions, leading to increased operational efficiency and a better user experience.

[2063] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[2064] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[2065] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[2066] [Fourth Embodiment]

[2067] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[2068] As shown in Figure 7, the 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.

[2069] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[2070] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[2071] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[2072] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[2073] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[2074] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive 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 robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[2075] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[2076] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[2077] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[2078] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[2079] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[2080] This invention is a system for streamlining customer management operations, including managing sales and profit data for a specified period, confirming transaction items and contract renewal months, converting requests from emails into tasks and automatically registering them in a calendar, automatically reserving meeting rooms, and automatically setting up online meetings.

[2081] Extract graphs showing sales and profit trends for each customer over a specified period (even by product category).

[2082] System operation:

[2083] 1. The user enters the period (start date and end date) and customer ID via the terminal.

[2084] 2. The terminal sends the entered information to the server as a request.

[2085] 3. The server receives the request, accesses the database, and extracts sales and profit data for the specified period.

[2086] 4. The server organizes the extracted data by product category and uses a graph generation library to create graphs showing the trends in sales and profits.

[2087] 5. The generated graph is sent back from the server to the terminal, and the user can view the graph on the terminal.

[2088] Specific example:

[2089] For example, if a user wants to see the sales and profit trends for customer ID 123 from January 1, 2023 to March 31, 2023, they would enter the period and customer ID into their device and send a request to the server. The server would then extract the relevant data from the database, organize it by product category, and generate a graph. The generated graph would then be displayed on the user's device.

[2090] Confirmation of trading products and contract renewal month

[2091] System operation:

[2092] 1. The user enters the customer ID they wish to check from their device and sends a request to the server.

[2093] 2. The server accesses the database to retrieve the customer's trading product list and contract renewal month information.

[2094] 3. The server sends the acquired information back to the user's terminal, and the user can view and confirm that information on the screen.

[2095] Specific example:

[2096] For example, if a user wants to check the list of products traded and the contract renewal month for customer ID 456, they enter the customer ID into their terminal and send a request to the server. The server retrieves the relevant information from the database and sends it back to the user's terminal. The user can then view the displayed information.

[2097] Customer requests received via email are converted into tasks and automatically registered in the calendar.

[2098] System operation:

[2099] 1. The server periodically monitors the email inbox.

[2100] 2. If there is a new email, the server analyzes its contents using natural language processing (NLP) and extracts the request.

[2101] 3. The server registers the extracted requests as tasks in the task management system.

[2102] 4. Registered tasks are automatically added to Google Calendar.

[2103] Specific example:

[2104] For example, if a customer sends an email requesting "Please schedule a meeting for next Monday," the server receives the email, analyzes its contents, and registers the meeting request as a task. This task is automatically added to Google Calendar, and the user can then view the appointment on their calendar.

[2105] Automated meeting room booking

[2106] System operation:

[2107] 1. The user enters the meeting date and time and the required number of participants from their device.

[2108] 2. The terminal sends the input information to the server.

[2109] 3. The server accesses the meeting room management system or database to check availability based on the specified date, time, and number of people.

[2110] 4. The server automatically reserves a suitable available meeting room.

[2111] 5. The reservation results are sent back from the server to the user's terminal, and the user can check the results.

[2112] Specific example:

[2113] For example, if a user wants to reserve a "meeting room for 10 people for 2 hours starting at 2:00 PM on October 15, 2023," they enter the information into their device and send it to the server. The server accesses the meeting room management system, checks availability, and then reserves a suitable meeting room. The reservation result is displayed on the user's device.

[2114] Zoom automatic setup

[2115] System operation:

[2116] 1. The user enters the meeting date and time and participant list from their device.

[2117] 2. The terminal sends the input information to the server.

[2118] 3. The server uses the Zoom API to create a new Zoom meeting.

[2119] 4. The server retrieves the meeting details (link and ID) from Zoom.

[2120] 5. The acquired meeting details will be sent via email from the server to the participant list.

[2121] Specific example:

[2122] For example, if a user wants to "set up a Zoom meeting on October 20, 2023 at 11:00 AM and send invitations to participants," they would enter that information into their device and send it to the server. The server would then use the Zoom API to create the meeting and retrieve the meeting details. After that, the server would send meeting invitation emails to the participant list. The user and participants would then receive the meeting details via email.

[2123] As described above, the system based on the present invention can automate various processes in customer management operations and significantly improve operational efficiency.

[2124] The following describes the processing flow.

[2125] Extract graphs showing sales and profit trends for each customer over a specified period (even by product category).

[2126] Processing steps:

[2127] Step 1:

[2128] The user enters the period (start and end dates) and customer ID via the device. The device then sends the entered information to the server as a request.

[2129] Step 2:

[2130] The server parses the received request and executes a query against the database based on the specified period and customer ID.

[2131] Step 3:

[2132] The server extracts the relevant sales and profit data from the database.

[2133] Step 4:

[2134] The server organizes the extracted data by product category. Sales and profit data are grouped for each product category and sorted chronologically.

[2135] Step 5:

[2136] The server uses a graph generation library to create graphs showing the trends in sales and profits. Colors and labels can be set as needed.

[2137] Step 6:

[2138] The server generates the graph as an image file or in an interactive format and sends it back to the user's terminal.

[2139] Step 7:

[2140] Users can view graphs received on their devices and check the trends in sales and profits over a specified period.

[2141] Confirmation of trading products and contract renewal month

[2142] Processing steps:

[2143] Step 1:

[2144] The user enters the customer ID they want to check on their device and sends a request to the server.

[2145] Step 2:

[2146] The server receives the request and accesses the database to execute a query to retrieve the customer's trading product list and contract renewal month information.

[2147] Step 3:

[2148] The server returns the list of traded products and contract renewal month information, retrieved from the database, to the user's terminal as a response.

[2149] Step 4:

[2150] Users can view the list of traded products and contract renewal month information received on their device and confirm the necessary information.

[2151] Customer requests received via email are converted into tasks and automatically registered in the calendar.

[2152] Processing steps:

[2153] Step 1:

[2154] The server periodically monitors the email inbox to detect the arrival of new emails.

[2155] Step 2:

[2156] The server analyzes the content of newly received emails using natural language processing (NLP) techniques. It extracts sentences and keywords that contain the request.

[2157] Step 3:

[2158] The server registers the extracted requests as new tasks in the task management system. Each task includes details such as the request content and deadline.

[2159] Step 4:

[2160] The server uses the Google Calendar API to automatically add tasks to the calendar based on the registered task information.

[2161] Step 5:

[2162] When a task is registered in the calendar, the server notifies the user's terminal that the task has been created and registered in the calendar.

[2163] Step 6:

[2164] Users can check their calendar on their device to see newly added tasks and appointments.

[2165] Automated meeting room booking

[2166] Processing steps:

[2167] Step 1:

[2168] The user enters the meeting date and time and the required number of participants from their device and sends a request to the server.

[2169] Step 2:

[2170] The server receives the request and accesses a system or database that manages the availability of meeting rooms to execute a query to check their availability.

[2171] Step 3:

[2172] The server retrieves a list of available meeting rooms and selects the most suitable one for the specified date, time, and number of people.

[2173] Step 4:

[2174] The server automatically reserves the selected meeting room through the reservation system.

[2175] Step 5:

[2176] Once the reservation is complete, the server will notify the user's device of the result.

[2177] Step 6:

[2178] Users can check their reservation results on their device and confirm that the meeting room has been booked.

[2179] Zoom automatic setup

[2180] Processing steps:

[2181] Step 1:

[2182] The user enters the meeting date and time and participant list from their device and sends a request to the server.

[2183] Step 2:

[2184] The server receives the request and sends a request to the Zoom server to create a new Zoom meeting using the Zoom API.

[2185] Step 3:

[2186] The server receives the meeting details (link and ID) returned from Zoom and stores that information.

[2187] Step 4:

[2188] Based on the saved meeting details, the server sends meeting invitations via email to the participants listed in the participant list.

[2189] Step 5:

[2190] Once the invitation email is sent, the server notifies the user that the Zoom meeting setup is complete.

[2191] Step 6:

[2192] Users and participants can check the meeting details in the email they receive and join the Zoom meeting at the specified date and time.

[2193] As described above, the system based on the present invention has a specific processing flow for improving the efficiency of various customer management tasks and achieves business efficiency through automation.

[2194] (Example 1)

[2195] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[2196] In today's busy business environment, improving the efficiency of customer management and task management is crucial. However, traditional systems require individual tasks such as managing sales and profit data for each customer, checking transaction items and contract renewal months, converting email requests into tasks, booking meeting rooms, and setting up online meetings. This often involves manual verification and data entry, leading to inefficient operations. This increases the likelihood of human error and wastes time and resources. A system is needed to solve these problems and streamline all aspects of customer management.

[2197] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[2198] In this invention, the server includes means for receiving a specified period and customer identification information from a user; means for extracting relevant sales data and profit data from an information storage device; means for organizing the extracted data and generating statistical displays by product; means for providing the generated statistical displays to the user; means for receiving the meeting date and time and participant list and creating a new meeting using a remote conferencing system; and means for notifying participants of the generated meeting details through notification means. As a result, customer management operations are centralized, and operations such as data extraction, statistical display generation, and remote meeting setup are automated, significantly improving operational efficiency.

[2199] "Specified period" refers to a time range consisting of a start date and an end date specified by the user for performing a specific action.

[2200] "Customer identification information" refers to information used to uniquely identify a specific customer, and includes customer IDs and other identifiers.

[2201] An "information storage device" is a device for storing data, and includes databases and cloud storage.

[2202] "Sales data" refers to data relating to revenue generated from sales activities within a specific period of time associated with a particular customer.

[2203] "Profit data" refers to data on net profit, which is calculated by subtracting costs from sales for a specific customer over a given period.

[2204] "Statistical display" refers to a display format such as graphs and charts that visually represent sales data and profit data.

[2205] A "remote conferencing system" is a system for setting up and managing meetings conducted remotely via the internet, and includes online conferencing services.

[2206] "Notification means" refers to a means of informing users or participants of specific information, and includes, for example, email and messaging applications.

[2207] A "product list" is a list of products that a particular customer trades.

[2208] "Contract renewal month information" refers to information about the month in which a contract with a specific customer is renewed.

[2209] A "meeting room management system" is a system used to reserve meeting rooms and check their availability.

[2210] An "electronic message box" is a box for receiving and storing emails, and it is installed on a mail server.

[2211] A "work item" is a request that has been registered as a specific task.

[2212] A "schedule" is a system for displaying and managing specific appointments or tasks in a calendar format.

[2213] A "generative AI model" is a model that uses artificial intelligence technology to automatically analyze and generate data.

[2214] A "prompt statement" is an input statement used to give specific instructions to a generative AI model.

[2215] This invention is a system designed to streamline customer management operations. This system can automate and centralize various tasks, such as managing sales and profit data for each customer, checking transaction items and contract renewal months, converting requests from emails into tasks and automatically registering them in the calendar, automatically reserving meeting rooms, and automatically setting up online meetings.

[2216] The main hardware components of this system are a server, terminals, and information storage devices. The server is responsible for processing requests, managing data, automating tasks, and providing notifications, while the terminals provide the user interface and handle information input and display. The information storage devices are used to store data such as sales data, profit data, transaction product lists, contract renewal months, tasks, and meeting room reservation status. Furthermore, software such as the Zoom API and Google Calendar API is used to set up online meetings and register them in the calendar.

[2217] Extract graphs showing sales and profit trends for each customer over a specified period (even by product category).

[2218] The user enters a specified period (start and end dates) and customer identification information via their device. The device sends this information to the server as a request. The server accesses the database and extracts sales and profit data for the specified period. Next, the server organizes the extracted data by product and creates sales and profit trend graphs using a graph generation library (e.g., Matplotlib, Chart.js). These generated graphs are sent back to the device, where the user can view them.

[2219] For example, if a user wants to view the sales and profit trends for customer ID 123 from January 1, 2023 to March 31, 2023, they would enter the period and customer ID and send a request to the server. The server would then extract the relevant data from the database, organize it by product, and generate a graph. The generated graph would then be displayed on the user's device.

[2220] Confirmation of trading products and contract renewal month

[2221] The user enters the customer identification information they wish to verify on their device and sends a request to the server. The server accesses the database and retrieves the customer's transaction product list and contract renewal month information. The retrieved information is sent back to the device, and the user can view and verify it on the screen.

[2222] As a concrete example, if a user wants to check the list of products traded and the contract renewal month for customer ID 456, they enter the customer identification information into the terminal and send a request to the server. The server retrieves the relevant information from the database and sends it back to the terminal. The user can then check the displayed information.

[2223] Requests received via email are converted into tasks and automatically registered in the calendar.

[2224] The server periodically monitors the electronic message box. If there are new messages, the server uses natural language processing (NLP) techniques to analyze the email content and extract requests. The server registers the extracted requests as work items in the task management system. These registered work items are automatically added to a calendar system such as Google Calendar.

[2225] For example, if a customer sends an email requesting "Please schedule a meeting for next Monday," the server receives the email, analyzes its contents, and registers the meeting request as a task item. This task item is automatically registered in Google Calendar, and the user can then view the appointment on their calendar.

[2226] Automated meeting room booking

[2227] The user enters the meeting date, time, and number of participants from their device. The device sends the entered information to the server. The server accesses the meeting room management system or database and checks availability based on the specified date, time, and number of participants. The server automatically reserves a suitable available meeting room and sends the result back to the device. The user can then view the result on their device.

[2228] As a concrete example, if a user wants to reserve a "meeting room for 10 people for 2 hours starting at 2:00 PM on October 15, 2023," they enter the information into their device and send it to the server. The server accesses the meeting room management system, checks the availability, and then reserves an appropriate meeting room. The reservation result is displayed on the user's device.

[2229] Zoom automatic setup

[2230] The user enters the meeting date and time and participant list from their device and sends it to the server. The server uses the Zoom API to create a new Zoom meeting and retrieves the meeting details (link and ID). The retrieved meeting details are then notified to the participant list via email or other means.

[2231] As a concrete example, if a user wants to "set up a Zoom meeting on October 20, 2023 at 11:00 AM and send invitations to participants," they would enter the meeting date and time and participant list into their device and send it to the server. The server would then use the Zoom API to create the meeting and retrieve the meeting details. After that, the server would send meeting invitation emails to the participant list. The user and participants would then receive the meeting details via email.

[2232] By implementing this invention, customer management operations can be centralized, data extraction and statistical display generation, remote meeting scheduling, and other tasks can be automated, significantly improving operational efficiency.

[2233] The flow of the specific processing in Example 1 will be explained using Figure 11.

[2234] Extract graphs showing sales and profit trends for each customer over a specified period (even by product category).

[2235] Step 1:

[2236] The user enters the period (start and end dates) and customer identification information via their device.

[2237] Input: Period (e.g., January 1, 2023 - March 31, 2023), Customer identification information (e.g., Customer ID 123)

[2238] Output: User input data is received by the terminal.

[2239] Step 2:

[2240] The terminal generates a request containing the period and customer identification information and sends it to the server.

[2241] Input: User input data (period and customer identification information)

[2242] Output: The generated request is sent to the server.

[2243] Step 3:

[2244] The server receives the request, accesses the information storage device, and extracts sales and profit data for the specified period.

[2245] Input: Request received from the terminal, data in the information storage device.

[2246] Output: A set of sales data and profit data is extracted.

[2247] Step 4:

[2248] The server extracts data and organizes it by product. A graph generation library is then used to create graphs showing the trends in sales and profits.

[2249] Input: Extracted sales data and profit data

[2250] Output: Graphs showing sales and profit trends by product (e.g., graphs generated using Matplotlib or Chart.js)

[2251] Step 5:

[2252] The generated graph is sent back from the server to the terminal, allowing the user to view the graph on their terminal.

[2253] Input: Generated graph

[2254] Output: The graph will be displayed on the terminal.

[2255] Confirmation of trading products and contract renewal month

[2256] Step 1:

[2257] The user enters the customer identification information they wish to verify from their device.

[2258] Input: Customer identification information (e.g., Customer ID 456)

[2259] Output: User input data is received by the terminal.

[2260] Step 2:

[2261] The terminal generates customer identification information as a request and sends it to the server.

[2262] Input: Customer identification information

[2263] Output: The generated request is sent to the server.

[2264] Step 3:

[2265] The server receives the request and retrieves the customer's trading product list and contract renewal month information from its data storage device.

[2266] Input: Request received from the terminal, data in the information storage device.

[2267] Output: A list of traded products and contract renewal month information are retrieved.

[2268] Step 4:

[2269] The acquired information is sent back from the server to the terminal, and the user can view the information on the terminal.

[2270] Input: List of traded products and contract renewal month information

[2271] Output: Information is displayed on the terminal.

[2272] Requests received via email are converted into tasks and automatically registered in the calendar.

[2273] Step 1:

[2274] The server periodically monitors the electronic message box.

[2275] Input: Status of the electronic message box

[2276] Output: Checks for the presence of new messages.

[2277] Step 2:

[2278] If there is a new message, the server uses natural language processing (NLP) techniques to analyze the email content and extract the request.

[2279] Input: Content of the newly received email

[2280] Output: Request details are extracted.

[2281] Step 3:

[2282] The server registers the extracted requests as work items in the task management system.

[2283] Input: Request

[2284] Output: The work item is registered in the task management system.

[2285] Step 4:

[2286] Registered work items are automatically added to calendar systems such as Google Calendar.

[2287] Input: Work item

[2288] Output: Events registered in the calendar

[2289] Automated meeting room booking

[2290] Step 1:

[2291] The user enters the meeting date, time, and number of participants from their device.

[2292] Input: Meeting date and time (e.g., October 15, 2023, 2:00 PM for 2 hours), Number of participants (e.g., 10 people)

[2293] Output: User input data is received by the terminal.

[2294] Step 2:

[2295] The terminal generates the input information as a request and sends it to the server.

[2296] Input: User input data (meeting date and time, number of participants)

[2297] Output: The generated request is sent to the server.

[2298] Step 3:

[2299] The server accesses the meeting room management system or information storage device to check availability based on the specified date, time, and number of people.

[2300] Input: Requests received from terminals, meeting room management system, or data stored in information storage devices.

[2301] Output: Meeting room availability is checked.

[2302] Step 4:

[2303] The server automatically reserves a suitable available meeting room and sends the reservation result back to the terminal.

[2304] Input: Meeting room availability

[2305] Output: The reservation result is sent back to the device and displayed.

[2306] Zoom automatic setup

[2307] Step 1:

[2308] The user enters the meeting date and time and participant list from their device.

[2309] Input: Meeting date and time (e.g., October 20, 2023, 11:00), participant list

[2310] Output: User input data is received by the terminal.

[2311] Step 2:

[2312] The terminal generates the input information as a request and sends it to the server.

[2313] Input: Meeting date and time and participant list

[2314] Output: The generated request is sent to the server. ...

Claims

1. A means of receiving a period and customer ID specified by the user, A means for extracting relevant sales data and profit data from a database, A method for organizing the extracted data and generating graphs for each product category, A means of providing the generated graph to the user, A system that includes this.

2. A means of receiving a customer ID and retrieving the corresponding transaction product list and contract renewal month information from the database, Means of providing the acquired information to the user, The system according to claim 1, including the following:

3. A means of monitoring mailboxes and analyzing requests from received emails, A means of registering the analyzed request as a task, A method for automatically registering registered tasks to the calendar, The system according to claim 1, including the following:

4. A means to receive the meeting date and time and the number of attendees, and to check the availability of the meeting room, A method for automatically booking a suitable meeting room, A means of providing the reservation results to the user, The system according to claim 1, including the following:

5. A means to receive the meeting date and time and participant list, and to set up the meeting. Means of obtaining the details of the scheduled meeting, A means of notifying participants of the meeting details, The system according to claim 1, including the following:

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