system

Abstract

The system according to the embodiment aims to efficiently propose original service ideas in the cashless payment business, investigate demand for them, and commercialize them. [Solution] A system according to an embodiment includes a proposal unit, a research unit, a commercialization unit, and an evaluation unit. The proposal unit uses a generation AI to propose service ideas. The research unit investigates the demand for the ideas proposed by the proposal unit. The commercialization unit commercializes ideas whose demand has been confirmed by the research unit. The evaluation unit evaluates the effectiveness of the services commercialized by the commercialization unit.

Description

[Technical Field]

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

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

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

[0004] With conventional technology, there was a problem in that the process for efficiently proposing original service ideas, investigating demand, and commercializing them in the cashless payment business was not well established.

[0005] The system according to the embodiment aims to efficiently propose original service ideas in the cashless payment business, investigate demand for them, and commercialize them. [Means for solving the problem]

[0006] The system according to the embodiment includes a proposal unit, a research unit, a commercialization unit, and an evaluation unit. The proposal unit uses a generation AI to propose service ideas. The research unit investigates the demand for the ideas proposed by the proposal unit. The commercialization unit commercializes ideas whose demand has been confirmed by the research unit. The evaluation unit evaluates the effectiveness of the services commercialized by the commercialization unit. [Effects of the Invention]

[0007] The system according to the embodiment can efficiently propose original service ideas in the cashless payment business, investigate demand for them, and commercialize them. [Brief explanation of the drawings]

[0008] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. DETAILED DESCRIPTION OF THE INVENTION

[0009] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0010] First, the terms used in the following description will be explained.

[0011] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, the processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), or a TPU (Tensor Processing Unit).

[0012] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0013] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0014] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), and Bluetooth (registered trademark).

[0015] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0016] [First embodiment] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0017] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0018] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0019] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0020] The reception device 38 includes a touch panel 38A and a microphone 38B, and receives user input. The touch panel 38A detects contact with a pointer (for example, a pen or a finger) to receive user input by the touch of the pointer. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 (see FIG. 2) acquires the data indicating the user input.

[0021] Output device 40 includes a display 40A and a speaker 40B, and presents data to a user by outputting the data in a form of expression that the user can perceive (e.g., audio and / or text). Display 40A displays visible information such as text and images in accordance with instructions from processor 46. Speaker 40B outputs audio in accordance with instructions from processor 46. Camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0022] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0023] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0024] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0025] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0026] In the smart device 14, the specific processing is performed by the processor 46. The storage 50 stores a specific processing program 60. The specific processing program 60 is used together with the specific processing program 56 by the data processing system 10. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. Note that the smart device 14 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the specific processing unit 290 using these models.

[0027] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device (e.g., a generation server) may have the data generation model 58. In this case, the data processing device 12 obtains a processing result (prediction result, etc.) using the data generation model 58 by communicating with the server device having the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device owned by a user (e.g., a mobile phone, a robot, a home appliance, etc.). Next, an example of processing by the data processing system 10 according to the first embodiment will be described.

[0028] (Example 1) A platform according to an embodiment of the present invention uses a generation AI to propose original service ideas specifically for credit card and QR code payment services, investigate their demand, and implement a PDCA cycle for commercialization. This platform includes a process in which the generation AI proposes original service ideas related to credit cards and QR code payment services, investigates their demand, and commercializes them. For example, the generation AI analyzes past data and trends to generate new service ideas. Specific examples include a cashback service specifically for use at specific stores or a new point system using two-dimensional codes (e.g., QR Codes (registered trademark)). Next, the demand for the proposed service idea is investigated. The demand investigation is conducted through surveys and market research to evaluate whether the idea proposed by the generation AI is actually accepted by customers. For example, customer opinions are collected through surveys to identify areas for improvement in the service idea. After that, service ideas whose demand is confirmed are commercialized. In the commercialization process, the specific design and development of the service are carried out and the product is actually launched on the market. For example, a system for introducing a new cashback service or a point system using two-dimensional codes is developed. Finally, the effectiveness of the commercialized service is evaluated and the PDCA cycle is implemented. Effectiveness evaluation analyzes service usage and customer reactions to identify areas for improvement. For example, the frequency of service usage and customer satisfaction can be investigated and reflected in proposing the next service idea. In this way, by building a platform that allows the AI ​​to propose original service ideas specific to credit card and QR payment businesses, investigate demand for those ideas, and implement the PDCA cycle to commercialize them, it becomes possible to provide new value in the increasingly competitive cashless payment market. This allows the platform to have the AI ​​propose original service ideas specific to credit card and QR payment businesses, investigate demand for those ideas, and implement the PDCA cycle to commercialize them.

[0029] A platform according to an embodiment includes a proposal unit, a research unit, a commercialization unit, and an evaluation unit. The proposal unit proposes service ideas using a generation AI. The generation AI, for example, analyzes past data and trends to generate new service ideas. For example, the generation AI can propose a cashback service tailored to use at a specific store or a new point system using two-dimensional codes. The generation AI can also generate effective service ideas by analyzing past sales data and customer feedback. The research unit investigates demand for the ideas proposed by the proposal unit. The demand investigation is conducted, for example, through questionnaires or market research. For example, the research unit can conduct online questionnaires to collect customer opinions. The research unit can also conduct field research to evaluate demand in the actual market. Furthermore, the research unit can analyze existing market data through desk research to evaluate demand. The commercialization unit commercializes ideas for which demand has been confirmed. The commercialization process involves, for example, the specific design and development of the service. For example, the commercialization unit can develop a system for introducing a new cashback service. The commercialization department can also build a point system using two-dimensional codes. Furthermore, the commercialization department can evaluate the feasibility of the service through the creation of prototypes and test marketing. The evaluation department evaluates the effectiveness of the commercialized service. The effectiveness evaluation is performed, for example, by analyzing the usage status of the service and customer responses. For example, the evaluation department can survey the frequency of service use and evaluate customer satisfaction. The evaluation department can also collect customer feedback and identify areas for improvement in the service. Furthermore, the evaluation department can analyze sales data and evaluate the economic effectiveness of the service. As a result, the platform according to the embodiment can have the generation AI propose original service ideas specialized for credit card and QR payment businesses, investigate demand for the proposed ideas, and implement a PDCA cycle to commercialize them.

[0030] The suggestion unit can analyze past data or trends to generate new service ideas. The suggestion unit can, for example, analyze past sales data to generate new service ideas. For example, the suggestion unit can propose a cashback service specialized for use at a specific store based on past sales data. The suggestion unit can also analyze customer feedback to generate new service ideas. For example, the suggestion unit can propose a new point system using two-dimensional codes based on customer feedback. The suggestion unit can also analyze social media trends to generate new service ideas. For example, the suggestion unit can propose new service ideas based on trends that are popular on social media. In this way, the suggestion unit can generate more effective service ideas by analyzing past data and trends.

[0031] The research department can evaluate the demand for the proposed idea through questionnaires or market research. The research department, for example, conducts an online questionnaire to collect customer opinions. For example, the research department can evaluate the demand for the proposed service idea through an online questionnaire. The research department can also conduct field research to evaluate demand in the actual market. For example, the research department can evaluate the demand for the service idea through field research in a specific region. Furthermore, the research department can analyze existing market data and evaluate demand through desk research. For example, the research department can evaluate the demand for the proposed service idea based on existing market data. This allows the research department to accurately evaluate the demand for the proposed idea through questionnaires or market research.

[0032] The merchandising department can design or develop specific services and actually launch them on the market. The merchandising department, for example, develops systems to introduce new cashback services. For example, the merchandising department can design a system for a cashback service and actually launch it on the market. The merchandising department can also build a point system using two-dimensional codes. For example, the merchandising department can design a point system using two-dimensional codes and actually launch it on the market. Furthermore, the merchandising department can evaluate the feasibility of a service through the creation of prototypes and test marketing. For example, the merchandising department can evaluate the feasibility of a service by creating a prototype and conducting small-scale test marketing. As a result, the merchandising department can design and develop specific services and actually launch them on the market.

[0033] The evaluation department can analyze the usage status of the service or customer responses and identify areas for improvement of the service. The evaluation department, for example, investigates the frequency of service usage and evaluates customer satisfaction. For example, the evaluation department can evaluate customer satisfaction based on the frequency of service usage. The evaluation department can also collect customer feedback and identify areas for improvement of the service. For example, the evaluation department can identify areas for improvement of the service based on customer feedback. Furthermore, the evaluation department can analyze sales data and evaluate the economic effectiveness of the service. For example, the evaluation department can evaluate the economic effectiveness of the service based on sales data. In this way, the evaluation department can identify areas for improvement of the service by analyzing the usage status of the service and customer responses.

[0034] The platform further includes a data collection unit that collects data such as past success cases or failure cases, customer feedback, etc., and provides the data to the proposal unit. The data collection unit, for example, collects past success cases and provides the data to the proposal unit. For example, the data collection unit can collect past cases of increased sales and cases of improved customer satisfaction, and provide the data to the proposal unit. The data collection unit can also collect past failure cases and provide the data to the proposal unit. For example, the data collection unit can collect project failure cases and customer complaint cases, and provide the data to the proposal unit. The data collection unit can also collect customer feedback and provide the data to the proposal unit. For example, the data collection unit can collect survey results and review comments, and provide the data to the proposal unit. In this way, the data collection unit can provide useful data to the proposal unit by collecting past success cases, failure cases, and customer feedback.

[0035] The platform further includes a survey unit that collects customer opinions and identifies areas for improvement of the service idea. The survey unit, for example, conducts an online survey to collect customer opinions. For example, the survey unit can identify areas for improvement of the service idea through the online survey. The survey unit can also collect customer opinions by conducting telephone interviews. For example, the survey unit can identify areas for improvement of the service idea through the telephone interviews. The survey unit can also collect customer opinions by conducting field surveys. For example, the survey unit can identify areas for improvement of the service idea through the field surveys. In this way, the survey unit can identify areas for improvement of the service idea by collecting customer opinions.

[0036] The platform further includes a market research department that actually conducts small-scale test marketing to evaluate demand for the service idea. The market research department, for example, conducts test sales in a limited area to evaluate demand for the service idea. For example, the market research department can evaluate demand for the service idea through test sales in a specific area. The market research department can also conduct online tests to evaluate demand for the service idea. For example, the market research department can evaluate demand for the service idea through an online platform. Furthermore, the market research department can conduct field research to evaluate demand for the service idea. For example, the market research department can evaluate demand for the service idea through field research in a specific area. In this way, the market research department can evaluate demand for the service idea by actually conducting small-scale test marketing.

[0037] The platform further includes a system development department that develops a system for introducing a new cashback service. The system development department, for example, develops a system for introducing a new cashback service. For example, the system development department can design a system for a cashback service and actually launch it on the market. The system development department can also build a point system using a two-dimensional code. For example, the system development department can design a point system using a two-dimensional code and actually launch it on the market. Furthermore, the system development department can evaluate the feasibility of the service through the creation of a prototype and test marketing. For example, the system development department can evaluate the feasibility of the service by creating a prototype and conducting small-scale test marketing. This allows the system development department to develop a system for introducing a new cashback service.

[0038] The platform further includes a campaign unit that implements a service that doubles points when used during a specific time period, and a campaign specialized for use in a specific area. The campaign unit, for example, implements a service that doubles points when used during a specific time period. For example, the campaign unit can provide a service that doubles points when used during the daytime on weekdays. The campaign unit can also implement a campaign specialized for use in a specific area. For example, the campaign unit can implement a campaign specialized for use in urban areas. Furthermore, the campaign unit can implement a combination of campaigns specialized for specific time periods and areas. For example, the campaign unit can implement a campaign that doubles points when used in urban areas on weekend nights. In this way, the campaign unit can promote use by implementing campaigns specialized for specific time periods and areas.

[0039] The platform further includes a usage analysis unit that investigates the frequency of service use and customer satisfaction and reflects the results in proposing the next service idea. The usage analysis unit, for example, investigates the frequency of service use and reflects the results in proposing the next service idea. For example, the usage analysis unit can investigate the number of monthly active users and reflect the results in proposing the next service idea. The usage analysis unit can also investigate customer satisfaction and reflect the results in proposing the next service idea. For example, the usage analysis unit can investigate NPS scores and reflect the results in proposing the next service idea. Furthermore, the usage analysis unit can collect customer reviews and reflect the results in proposing the next service idea. For example, the usage analysis unit can collect online reviews and reflect the results in proposing the next service idea. In this way, the usage analysis unit can investigate the frequency of service use and customer satisfaction and reflect the results in proposing the next service idea.

[0040] The platform further includes a customer satisfaction survey unit that analyzes customer satisfaction and word-of-mouth reviews to identify areas for service improvement. The customer satisfaction survey unit, for example, surveys customer satisfaction and identifies areas for service improvement. For example, the customer satisfaction survey unit can identify areas for service improvement based on survey results. The customer satisfaction survey unit can also collect word-of-mouth reviews and identify areas for service improvement. For example, the customer satisfaction survey unit can collect online reviews and identify areas for service improvement. The customer satisfaction survey unit can also analyze social media comments and identify areas for service improvement. For example, the customer satisfaction survey unit can identify areas for service improvement based on social media comments. In this way, the customer satisfaction survey unit can identify areas for service improvement by analyzing customer satisfaction and word-of-mouth reviews.

[0041] When analyzing past data and trends, the suggestion unit can prioritize analysis of data related to specific seasons or events. For example, the suggestion unit causes the generation AI to prioritize generation of Christmas-related service ideas leading up to the Christmas season. For example, the suggestion unit can cause the generation AI to propose Christmas-related service ideas based on data related to the Christmas season. The suggestion unit can also cause the generation AI to prioritize generation of service ideas related to travel and leisure during the summer vacation period. For example, the suggestion unit can cause the generation AI to propose service ideas related to travel and leisure based on data related to the summer vacation period. Furthermore, the suggestion unit can also cause the generation AI to prioritize generation of service ideas related to gifts and dates leading up to Valentine's Day. For example, the suggestion unit can cause the generation AI to propose service ideas related to gifts and dates based on data related to Valentine's Day. In this way, the suggestion unit can generate more effective service ideas by preferentially analyzing data related to specific seasons or events.

[0042] The suggestion unit can reflect the user's purchase history and usage history in the ideas it generates. For example, the suggestion unit allows the generation AI to suggest related service ideas based on products the user has purchased in the past. For example, the suggestion unit can allow the generation AI to suggest related service ideas based on the user's purchase history. The suggestion unit can also allow the generation AI to suggest cashback services at specific stores based on stores frequently visited by the user. For example, the suggestion unit can allow the generation AI to suggest cashback services at specific stores based on the user's usage history. Furthermore, the suggestion unit can analyze the user's usage history and allow the generation AI to suggest an optimal point system. For example, the suggestion unit can allow the generation AI to suggest an optimal point system based on the user's usage history. This allows the suggestion unit to generate more personalized service ideas by reflecting the user's purchase history and usage history.

[0043] The suggestion unit can propose region-specific services in the generated ideas by taking into account the user's geographical location information. For example, if the user is in a specific region, the suggestion unit can propose cashback services available in that region. For example, the suggestion unit can propose cashback services available in that region based on the user's geographical location information. The suggestion unit can also have the generation AI propose a region-specific point system based on the user's location information. For example, the suggestion unit can have the generation AI propose a region-specific point system based on the user's location information. Furthermore, if the user is traveling, the suggestion unit can also propose benefits and services that can be used at the travel destination. For example, if the user is traveling, the suggestion unit can propose benefits and services that can be used at the travel destination. In this way, the suggestion unit can propose region-specific services by taking into account the user's geographical location information.

[0044] The suggestion unit can analyze the user's social media activity and reflect trends in the ideas it generates. For example, the suggestion unit allows the generation AI to suggest related service ideas based on content shared by the user on social media. For example, the suggestion unit can allow the generation AI to suggest related service ideas based on the user's social media activity. The suggestion unit can also analyze services used by the user's followers and friends and allow the generation AI to suggest similar services. For example, the suggestion unit can allow the generation AI to suggest similar services based on the user's social media activity. Furthermore, the suggestion unit can allow the generation AI to suggest service ideas that reflect trends that are being talked about on social media. For example, the suggestion unit can allow the generation AI to suggest related service ideas based on social media trends. In this way, the suggestion unit can generate service ideas that reflect trends by analyzing the user's social media activity.

[0045] When conducting questionnaires or market research, the research department can narrow the survey to a specific target demographic. For example, the research department can conduct a questionnaire targeting young people to understand their needs. For example, the research department can conduct a questionnaire targeting young people to understand their needs. The research department can also conduct market research targeting elderly people to evaluate services that are suitable for them. For example, the research department can conduct market research targeting elderly people to evaluate services that are suitable for them. Furthermore, the research department can conduct a questionnaire targeting users living in a specific area to understand needs that are specific to the area. For example, the research department can conduct a questionnaire targeting users living in a specific area to understand needs that are specific to the area. This allows the research department to collect more accurate data by conducting a survey that is narrowed to a specific target demographic.

[0046] The research department can compare the collected data with past survey results and analyze it. For example, the research department can compare past survey results with current results and analyze changes in trends. For example, the research department can compare past survey results with current results and analyze changes in trends. The research department can also compare past market research data with current data and evaluate changes in demand. For example, the research department can compare past market research data with current data and evaluate changes in demand. Furthermore, the research department can compare past customer feedback with current feedback and identify areas for improvement in services. For example, the research department can compare past customer feedback with current feedback and identify areas for improvement in services. In this way, the research department can grasp changes in trends by comparing and analyzing it with past survey results.

[0047] The research department can conduct region-specific research by taking into account the geographical location information of users in the collected data. For example, the research department can conduct a survey targeting users living in a specific region to understand region-specific needs. For example, the research department can conduct a survey targeting users living in a specific region to understand region-specific needs. The research department can also conduct market research for each region to evaluate demand for each region. For example, the research department can conduct market research for each region to evaluate demand for each region. Furthermore, the research department can collect feedback on region-specific services to identify areas for improvement of the services. For example, the research department can collect feedback on region-specific services to identify areas for improvement of the services. In this way, the research department can conduct region-specific research by taking into account the geographical location information of users.

[0048] The research department can reflect the user's social media activities in the collected data. For example, the research department can analyze content shared by the user on social media and reflect the results in the survey questions. For example, the research department can reflect the results in the survey questions based on the content shared by the user on social media. The research department can also research trends that are trending on social media and reflect the results in the survey questions. For example, the research department can reflect the results in the survey questions based on social media trends. Furthermore, the research department can analyze the user's social media activities and conduct surveys that narrow down the target demographic. For example, the research department can conduct surveys that narrow down the target demographic based on the user's social media activities. In this way, the research department can conduct surveys that reflect trends by reflecting the user's social media activities.

[0049] The commercialization department can reflect user feedback in design and development. The commercialization department, for example, improves the design of the service based on feedback provided by the user. For example, the commercialization department can improve the design of the service based on feedback provided by the user. The commercialization department can also develop a prototype that reflects user opinions and conduct testing. For example, the commercialization department can develop a prototype that reflects user opinions and conduct testing. The commercialization department can also add or delete functions of the service based on user feedback. For example, the commercialization department can add or delete functions of the service based on user feedback. In this way, the commercialization department can develop a product that better meets user needs by reflecting user feedback in design and development.

[0050] The commercialization department can refer to past success stories and failure stories in design and development. The commercialization department, for example, designs services based on past success stories. For example, the commercialization department can design services based on past examples of increased sales and improved customer satisfaction. The commercialization department can also analyze past failure stories and design services so as not to repeat the same mistakes. For example, the commercialization department can analyze past project failure stories and customer complaint stories and design services so as not to repeat the same mistakes. Furthermore, the commercialization department can proceed with service development while referring to past examples. For example, the commercialization department can proceed with service development based on past examples. In this way, the commercialization department can develop products more effectively by referring to past success stories and failure stories in design and development.

[0051] The merchandising department can develop region-specific products by taking into account the geographical location information of users during design and development. The merchandising department, for example, develops products targeted at users living in a specific region. For example, the merchandising department can develop products targeted at users living in a specific region. The merchandising department can also design products that reflect the needs of each region. For example, the merchandising department can design products based on the needs of each region. Furthermore, the merchandising department can develop a system for providing region-specific services. For example, the merchandising department can develop a system for providing region-specific services. In this way, the merchandising department can develop region-specific products by taking into account the geographical location information of users during design and development.

[0052] The merchandising department can reflect the user's social media activities in design and development. The merchandising department, for example, designs products based on content shared by the user on social media. For example, the merchandising department can design products based on content shared by the user on social media. The merchandising department can also develop products that reflect trends that are trending on social media. For example, the merchandising department can develop products based on social media trends. Furthermore, the merchandising department can analyze the user's social media activities and develop products that target specific demographics. For example, the merchandising department can develop products that target specific demographics based on the user's social media activities. In this way, the merchandising department can develop products that reflect trends by reflecting the user's social media activities in design and development.

[0053] The evaluation unit can compare and analyze past evaluation results in the effectiveness evaluation. For example, the evaluation unit can compare past evaluation results with current evaluation results to find areas for improvement of the service. For example, the evaluation unit can compare past evaluation results with current evaluation results to find areas for improvement of the service. The evaluation unit can also compare past evaluation data with current data to analyze changes in trends. For example, the evaluation unit can compare past evaluation data with current data to analyze changes in trends. Furthermore, the evaluation unit can compare past customer feedback with current feedback to evaluate the effectiveness of the service. For example, the evaluation unit can compare past customer feedback with current feedback to evaluate the effectiveness of the service. In this way, the evaluation unit can find areas for improvement of the service by comparing and analyzing past evaluation results.

[0054] The evaluation unit can conduct an effectiveness evaluation that is focused on a specific target demographic. For example, the evaluation unit can conduct an effectiveness evaluation targeting young people and evaluate services that meet their needs. For example, the evaluation unit can conduct an effectiveness evaluation targeting young people and evaluate services that meet their needs. The evaluation unit can also conduct an effectiveness evaluation targeting elderly people and evaluate services that are suitable for them. For example, the evaluation unit can conduct an effectiveness evaluation targeting elderly people and evaluate services that are suitable for them. Furthermore, the evaluation unit can conduct an effectiveness evaluation targeting users living in a specific area and evaluate services that meet needs that are specific to the area. For example, the evaluation unit can conduct an effectiveness evaluation targeting users living in a specific area and evaluate services that meet needs that are specific to the area. As a result, the evaluation unit can conduct an evaluation that is focused on a specific target demographic, thereby enabling a more accurate evaluation.

[0055] The evaluation unit can perform a region-specific evaluation in the effectiveness evaluation by taking into account the user's geographical location information. The evaluation unit, for example, performs an effectiveness evaluation targeting users living in a specific region and evaluates services that meet region-specific needs. For example, the evaluation unit can perform an effectiveness evaluation targeting users living in a specific region and evaluate services that meet region-specific needs. The evaluation unit can also compare evaluation results for each region and analyze demand for each region. For example, the evaluation unit can compare evaluation results for each region and analyze demand for each region. Furthermore, the evaluation unit can collect feedback on the region-specific service and identify areas for improvement of the service. For example, the evaluation unit can collect feedback on the region-specific service and identify areas for improvement of the service. In this way, the evaluation unit can perform a region-specific evaluation by taking into account the user's geographical location information.

[0056] The evaluation unit can reflect the user's social media activities in the effectiveness evaluation. The evaluation unit can evaluate the effectiveness of the service based on, for example, content shared by the user on social media. For example, the evaluation unit can evaluate the effectiveness of the service based on content shared by the user on social media. The evaluation unit can also perform an effectiveness evaluation that reflects trends that are trending on social media. For example, the evaluation unit can evaluate the effectiveness of the service based on social media trends. Furthermore, the evaluation unit can analyze the user's social media activities and perform an effectiveness evaluation that narrows down the target demographic. For example, the evaluation unit can perform an effectiveness evaluation that narrows down the target demographic based on the user's social media activities. In this way, the evaluation unit can perform an evaluation that reflects trends by reflecting the user's social media activities.

[0057] The data collection unit can prioritize collecting data related to a particular season or event in the data to be collected. For example, the data collection unit prioritizes collecting Christmas-related data in the run-up to the Christmas season. For example, the data collection unit can prioritize collecting Christmas-related data based on data related to the Christmas season. The data collection unit can also prioritize collecting data related to travel and leisure activities during the summer vacation period. For example, the data collection unit can prioritize collecting data related to travel and leisure activities based on data related to the summer vacation period. Furthermore, the data collection unit can also prioritize collecting data related to gifts and dates in the run-up to Valentine's Day. For example, the data collection unit can prioritize collecting data related to gifts and dates based on data related to Valentine's Day. In this way, the data collection unit can collect data related to a particular season or event more effectively by prioritized collection of data.

[0058] The data collection unit can refer to past success stories and failure stories when collecting data. The data collection unit, for example, collects related data based on past success stories. For example, the data collection unit can collect related data based on past cases of increased sales or cases of improved customer satisfaction. The data collection unit can also analyze past failure stories and collect data to prevent the same mistakes from being repeated. For example, the data collection unit can analyze past cases of project failure or customer complaints and collect data to prevent the same mistakes from being repeated. Furthermore, the data collection unit can proceed with data collection while referring to past cases. For example, the data collection unit can proceed with data collection based on past cases. In this way, the data collection unit can collect data more effectively by referring to past success stories and failure stories when collecting data.

[0059] The data collection unit can collect region-specific data by taking into account the geographical location information of the user when collecting data. The data collection unit, for example, collects data targeted at users living in a specific region. For example, the data collection unit can collect data targeted at users living in a specific region. The data collection unit can also compare data for each region and analyze demand for each region. For example, the data collection unit can compare data for each region and analyze demand for each region. Furthermore, the data collection unit can collect feedback on region-specific services and identify areas for improvement of the services. For example, the data collection unit can collect feedback on region-specific services and identify areas for improvement of the services. In this way, the data collection unit can collect region-specific data by taking into account the geographical location information of the user when collecting data.

[0060] The data collection unit can reflect the user's social media activities in the data it collects. The data collection unit, for example, collects data based on content shared by the user on social media. For example, the data collection unit can collect data based on content shared by the user on social media. The data collection unit can also collect data that reflects trends that are trending on social media. For example, the data collection unit can collect data based on social media trends. Furthermore, the data collection unit can analyze the user's social media activities and collect data that is targeted to a specific demographic. For example, the data collection unit can collect data that is targeted to a specific demographic based on the user's social media activities. In this way, the data collection unit can collect data that reflects trends by reflecting the user's social media activities in the data it collects.

[0061] The survey unit can compare and analyze the collected data with past survey results. For example, the survey unit can compare past survey results with current results and analyze changes in trends. For example, the survey unit can compare past survey results with current results and analyze changes in trends. The survey unit can also compare past survey data with current data and evaluate changes in demand. For example, the survey unit can compare past survey data with current data and evaluate changes in demand. Furthermore, the survey unit can compare past customer feedback with current feedback and identify areas for improvement in services. For example, the survey unit can compare past customer feedback with current feedback and identify areas for improvement in services. In this way, the survey unit can grasp changes in trends by comparing and analyzing with past survey results.

[0062] The survey unit can conduct a region-specific survey by taking into account the geographical location information of users in the collected data. The survey unit, for example, conducts a survey targeting users living in a specific region to understand region-specific needs. For example, the survey unit can conduct a survey targeting users living in a specific region to understand region-specific needs. The survey unit can also compare survey results for each region to analyze demand for each region. For example, the survey unit can compare survey results for each region to analyze demand for each region. Furthermore, the survey unit can collect feedback on region-specific services to identify areas for improvement of the services. For example, the survey unit can collect feedback on region-specific services to identify areas for improvement of the services. This allows the survey unit to conduct a region-specific survey by taking into account the geographical location information of users in the collected data.

[0063] The survey unit can reflect the user's social media activities in the data it collects. The survey unit, for example, reflects the content of the survey questions based on the content shared by the user on social media. For example, the survey unit can reflect the content of the survey questions based on the content shared by the user on social media. The survey unit can also investigate trends that are trending on social media and reflect the results in the survey questions. For example, the survey unit can reflect the results in the survey questions based on social media trends. Furthermore, the survey unit can analyze the user's social media activities and conduct a survey that narrows down to a specific target demographic. For example, the survey unit can conduct a survey that narrows down to a specific target demographic based on the user's social media activities. In this way, the survey unit can conduct a survey that reflects trends by reflecting the user's social media activities in the data it collects.

[0064] The questionnaire unit can reflect the user's past questionnaire results in the collected data. The questionnaire unit, for example, can provide a questionnaire including related questions based on the questionnaire results previously answered by the user. For example, the questionnaire unit can provide a questionnaire including related questions based on the questionnaire results previously answered by the user. The questionnaire unit can also compare the past questionnaire results with the current results and analyze changes in trends. For example, the questionnaire unit can compare the past questionnaire results with the current results and analyze changes in trends. Furthermore, the questionnaire unit can adjust the content of the questionnaire questions by referring to the past questionnaire data. For example, the questionnaire unit can adjust the content of the questionnaire questions based on the past questionnaire data. In this way, the questionnaire unit can provide more appropriate questions by reflecting the user's past questionnaire results in the collected data.

[0065] The market research department can perform comparative analysis of the collected data with past market research results. For example, the market research department can compare past market research results with current results and analyze changes in trends. For example, the market research department can compare past market research results with current results and analyze changes in trends. The market research department can also compare past market research data with current data and evaluate changes in demand. For example, the market research department can compare past market research data with current data and evaluate changes in demand. Furthermore, the market research department can compare past customer feedback with current feedback and identify areas for improvement in services. For example, the market research department can compare past customer feedback with current feedback and identify areas for improvement in services. In this way, the market research department can grasp changes in trends by performing comparative analysis with past market research results.

[0066] The market research department can conduct region-specific market research by taking into account the geographical location information of users in the collected data. The market research department, for example, conducts market research targeting users living in a specific region to understand region-specific needs. For example, the market research department can conduct market research targeting users living in a specific region to understand region-specific needs. The market research department can also compare market research results for each region to analyze demand for each region. For example, the market research department can compare market research results for each region to analyze demand for each region. Furthermore, the market research department can collect feedback on region-specific services to identify areas for improvement of the services. For example, the market research department can collect feedback on region-specific services to identify areas for improvement of the services. In this way, the market research department can conduct region-specific market research by taking into account the geographical location information of users in the collected data.

[0067] The market research department can reflect the social media activities of users in the data it collects. For example, the market research department can reflect the content of market research questions based on content shared by users on social media. For example, the market research department can reflect the content of market research questions based on content shared by users on social media. The market research department can also investigate trends that are trending on social media and reflect the results in the market research questions. For example, the market research department can reflect the results in the market research questions based on social media trends. Furthermore, the market research department can analyze the social media activities of users and conduct market research that focuses on a specific target demographic. For example, the market research department can conduct market research that focuses on a specific target demographic based on the social media activities of users. In this way, the market research department can conduct market research that reflects trends by reflecting the social media activities of users in the data it collects.

[0068] The market research department can reflect the results of past market research conducted by the user in the data it collects. For example, the market research department can provide market research including related questions based on market research results answered by the user in the past. For example, the market research department can provide market research including related questions based on market research results answered by the user in the past. The market research department can also compare the results of past market research with the current results and analyze changes in trends. For example, the market research department can compare the results of past market research with the current results and analyze changes in trends. Furthermore, the market research department can adjust the content of the market research questions by referring to the past market research data. For example, the market research department can adjust the content of the market research questions based on the past market research data. In this way, the market research department can provide more appropriate questions by reflecting the results of past market research conducted by the user in the data it collects.

[0069] The system development department can reflect user feedback in development. For example, the system development department can improve the system design based on feedback provided by the user. For example, the system development department can improve the system design based on feedback provided by the user. The system development department can also develop a prototype that reflects user opinions and conduct testing. For example, the system development department can develop a prototype that reflects user opinions and conduct testing. Furthermore, the system development department can add or delete system functions based on user feedback. For example, the system development department can add or delete system functions based on user feedback. In this way, the system development department can develop a system that better meets user needs by reflecting user feedback in development.

[0070] The system development department can refer to past success stories and failure stories in development. The system development department, for example, designs a system based on past success stories. For example, the system development department can design a system based on past examples of increased sales or improved customer satisfaction. The system development department can also analyze past failure stories and design a system to avoid repeating the same mistakes. For example, the system development department can analyze past project failure stories or customer complaint stories and design a system to avoid repeating the same mistakes. Furthermore, the system development department can proceed with system development while referring to past examples. For example, the system development department can proceed with system development based on past examples. In this way, the system development department can develop a more effective system by referring to past success stories and failure stories in development.

[0071] The system development department can develop a region-specific system by taking into account the geographical location information of users during development. The system development department, for example, develops a system targeted at users living in a specific region. For example, the system development department can develop a system targeted at users living in a specific region. The system development department can also design a system that reflects the needs of each region. For example, the system development department can design a system based on the needs of each region. Furthermore, the system development department can develop a system for providing region-specific services. For example, the system development department can develop a system for providing region-specific services. This allows the system development department to develop a region-specific system by taking into account the geographical location information of users during development.

[0072] The system development department can reflect users' social media activities in development. For example, the system development department can design a system based on content shared by users on social media. For example, the system development department can design a system based on content shared by users on social media. The system development department can also develop a system that reflects trends that are trending on social media. For example, the system development department can develop a system based on social media trends. Furthermore, the system development department can analyze users' social media activities and develop a system that narrows down the target demographic. For example, the system development department can develop a system that narrows down the target demographic based on users' social media activities. In this way, the system development department can develop a system that reflects trends by reflecting users' social media activities in development.

[0073] The campaign department can compare the results of a campaign to be implemented with those of past campaigns. For example, the campaign department can compare the results of past campaigns with the current results and analyze the difference in effectiveness. For example, the campaign department can compare the results of past campaigns with the current results and analyze the difference in effectiveness. The campaign department can also compare past campaign data with current data and evaluate changes in trends. For example, the campaign department can compare past campaign data with current data and evaluate changes in trends. Furthermore, the campaign department can compare past customer feedback with current feedback and identify areas for improvement in the campaign. For example, the campaign department can compare past customer feedback with current feedback and identify areas for improvement in the campaign. In this way, the campaign department can grasp changes in trends by performing a comparison analysis with past campaign results.

[0074] The campaign unit can implement a campaign that is focused on a specific target demographic. For example, the campaign unit can implement a campaign that targets young people and provide benefits that meet their needs. For example, the campaign unit can implement a campaign that targets young people and provide benefits that meet their needs. The campaign unit can also implement a campaign that targets elderly people and provide benefits that are suitable for them. For example, the campaign unit can implement a campaign that targets elderly people and provide benefits that meet their needs. Furthermore, the campaign unit can implement a campaign that targets users living in a specific area and provide benefits that meet the needs that are specific to the area. For example, the campaign unit can implement a campaign that targets users living in a specific area and provide benefits that meet the needs that are specific to the area. This allows the campaign unit to implement a more effective campaign by implementing a campaign that is focused on a specific target demographic.

[0075] The campaign unit can implement a region-specific campaign by taking into account the geographical location information of the user when implementing a campaign. The campaign unit, for example, implements a campaign targeted at users living in a specific region. For example, the campaign unit can implement a campaign targeted at users living in a specific region. The campaign unit can also provide a campaign that reflects the needs of each region. For example, the campaign unit can provide a campaign based on the needs of each region. Furthermore, the campaign unit can implement a campaign to provide a region-specific benefit. For example, the campaign unit can implement a campaign to provide a region-specific benefit. In this way, the campaign unit can implement a region-specific campaign by taking into account the geographical location information of the user when implementing a campaign, thereby enabling the campaign to be implemented more effectively.

[0076] The campaign unit can reflect the user's social media activities in the campaigns it implements. The campaign unit, for example, designs a campaign based on content shared by the user on social media. For example, the campaign unit can design a campaign based on content shared by the user on social media. The campaign unit can also implement a campaign that reflects trends that are trending on social media. For example, the campaign unit can implement a campaign based on social media trends. Furthermore, the campaign unit can analyze the user's social media activities and implement a campaign that narrows down to a specific target demographic. For example, the campaign unit can implement a campaign that narrows down to a specific target demographic based on the user's social media activities. In this way, the campaign unit can implement a campaign that reflects trends by reflecting the user's social media activities in the campaign it implements.

[0077] The usage analysis unit can perform a comparative analysis with past usage data in the analysis. For example, the usage analysis unit can compare past usage data with current data and analyze changes in trends. For example, the usage analysis unit can compare past usage data with current data and analyze changes in trends. The usage analysis unit can also compare past usage data with current data and evaluate changes in demand. For example, the usage analysis unit can compare past usage data with current data and evaluate changes in demand. Furthermore, the usage analysis unit can compare past customer feedback with current feedback and identify areas for improvement in the service. For example, the usage analysis unit can compare past customer feedback with current feedback and identify areas for improvement in the service. In this way, the usage analysis unit can grasp changes in trends by performing a comparative analysis with past usage data.

[0078] The usage status analysis unit can perform an analysis that is focused on a specific target demographic. For example, the usage status analysis unit can perform a usage status analysis targeting young people and evaluate services that meet their needs. For example, the usage status analysis unit can perform a usage status analysis targeting young people and evaluate services that meet their needs. The usage status analysis unit can also perform a usage status analysis targeting elderly people and evaluate services that are suitable for them. For example, the usage status analysis unit can perform a usage status analysis targeting elderly people and evaluate services that are suitable for them. Furthermore, the usage status analysis unit can perform a usage status analysis targeting users living in a specific area and evaluate services that meet needs that are specific to the area. For example, the usage status analysis unit can perform a usage status analysis targeting users living in a specific area and evaluate services that meet needs that are specific to the area. As a result, the usage status analysis unit can perform an analysis that is focused on a specific target demographic, thereby enabling more accurate analysis.

[0079] The usage analysis unit can perform a region-specific analysis by taking into account the geographical location information of the user in the analysis. The usage analysis unit, for example, performs a usage analysis targeting users living in a specific region and evaluates services that meet the region-specific needs. For example, the usage analysis unit can perform a usage analysis targeting users living in a specific region and evaluate services that meet the region-specific needs. The usage analysis unit can also compare usage data for each region and analyze demand for each region. For example, the usage analysis unit can compare usage data for each region and analyze demand for each region. Furthermore, the usage analysis unit can collect feedback on the region-specific service and identify areas for improvement of the service. For example, the usage analysis unit can collect feedback on the region-specific service and identify areas for improvement of the service. This allows the usage analysis unit to perform a region-specific analysis by taking into account the geographical location information of the user in the analysis.

[0080] The usage analysis unit can reflect the user's social media activities in the analysis. The usage analysis unit, for example, performs an analysis of usage based on content shared by the user on social media. For example, the usage analysis unit can perform an analysis of usage based on content shared by the user on social media. The usage analysis unit can also perform an analysis of usage that reflects trends that are trending on social media. For example, the usage analysis unit can perform an analysis of usage based on social media trends. Furthermore, the usage analysis unit can analyze the user's social media activities and perform an analysis of usage that narrows down to a target demographic. For example, the usage analysis unit can perform an analysis of usage that narrows down to a target demographic based on the user's social media activities. In this way, the usage analysis unit can perform an analysis that reflects trends by reflecting the user's social media activities in the analysis.

[0081] The customer satisfaction survey department can compare the collected data with past customer satisfaction survey results and analyze the results. For example, the customer satisfaction survey department can compare the results of past customer satisfaction surveys with the current results and analyze changes in trends. For example, the customer satisfaction survey department can compare the results of past customer satisfaction surveys with the current results and analyze changes in trends. The customer satisfaction survey department can also compare past customer satisfaction data with current data and evaluate changes in demand. For example, the customer satisfaction survey department can compare past customer satisfaction data with current data and evaluate changes in demand. Furthermore, the customer satisfaction survey department can compare past customer feedback with current feedback and identify areas for improvement in services. For example, the customer satisfaction survey department can compare past customer feedback with current feedback and identify areas for improvement in services. In this way, the customer satisfaction survey department can grasp changes in trends by performing a comparison and analysis with past customer satisfaction survey results.

[0082] The customer satisfaction survey unit can conduct a region-specific customer satisfaction survey by taking into account the geographical location information of users in the collected data. The customer satisfaction survey unit, for example, conducts a customer satisfaction survey targeting users living in a specific region to understand region-specific needs. For example, the customer satisfaction survey unit can conduct a customer satisfaction survey targeting users living in a specific region to understand region-specific needs. The customer satisfaction survey unit can also compare the customer satisfaction survey results for each region to analyze demand for each region. For example, the customer satisfaction survey unit can compare the customer satisfaction survey results for each region to analyze demand for each region. Furthermore, the customer satisfaction survey unit can collect feedback on region-specific services to identify areas for improvement of the services. For example, the customer satisfaction survey unit can collect feedback on region-specific services to identify areas for improvement of the services. In this way, the customer satisfaction survey unit can conduct a region-specific customer satisfaction survey by taking into account the geographical location information of users in the collected data.

[0083] The customer satisfaction survey unit can reflect the user's social media activities in the data it collects. The customer satisfaction survey unit, for example, can reflect the content of the questions in the customer satisfaction survey based on the content shared by the user on social media. For example, the customer satisfaction survey unit can reflect the content of the questions in the customer satisfaction survey based on the content shared by the user on social media. The customer satisfaction survey unit can also investigate trends that are trending on social media and reflect the results in the questions in the customer satisfaction survey. For example, the customer satisfaction survey unit can reflect the results in the questions in the customer satisfaction survey based on social media trends. Furthermore, the customer satisfaction survey unit can analyze the user's social media activities and conduct a customer satisfaction survey with a narrower target demographic. For example, the customer satisfaction survey unit can conduct a customer satisfaction survey with a narrower target demographic based on the user's social media activities. In this way, the customer satisfaction survey unit can conduct a customer satisfaction survey that reflects trends by reflecting the user's social media activities in the data it collects.

[0084] The customer satisfaction survey unit can reflect the results of past customer satisfaction surveys of the user in the collected data. For example, the customer satisfaction survey unit can provide a customer satisfaction survey including related questions based on customer satisfaction survey results previously answered by the user. For example, the customer satisfaction survey unit can provide a customer satisfaction survey including related questions based on customer satisfaction survey results previously answered by the user. The customer satisfaction survey unit can also compare the results of past customer satisfaction surveys with the current results and analyze changes in trends. For example, the customer satisfaction survey unit can compare the results of past customer satisfaction surveys with the current results and analyze changes in trends. Furthermore, the customer satisfaction survey unit can adjust the content of the questions in the customer satisfaction survey while referring to past customer satisfaction data. For example, the customer satisfaction survey unit can adjust the content of the questions in the customer satisfaction survey based on past customer satisfaction data. In this way, the customer satisfaction survey unit can provide more appropriate questions by reflecting the results of past customer satisfaction surveys of the user in the collected data.

[0085] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0086] The suggestion unit can also analyze the user's purchase history and generate individually customized service ideas. For example, the suggestion unit can suggest new related service ideas based on products or services the user has purchased in the past. The suggestion unit can also suggest cashback services that are specialized for use at specific stores based on the user's purchase history. Furthermore, the suggestion unit can analyze the user's purchase history and generate service ideas related to specific seasons or events. This allows the suggestion unit to generate more personalized service ideas by utilizing the user's purchase history.

[0087] The research department can also conduct region-specific demand surveys by taking into account the geographical location information of users. For example, the research department can conduct a survey of users living in a specific region to understand the needs specific to that region. The research department can also conduct market research by region to evaluate demand by region. Furthermore, the research department can collect feedback on region-specific services and identify areas for improvement of the services. In this way, the research department can conduct region-specific demand surveys by taking into account the geographical location information of users.

[0088] The commercialization department can also design and develop services based on user feedback. For example, the commercialization department can improve the design of a service based on feedback provided by users. The commercialization department can also develop and test prototypes that reflect user opinions. Furthermore, the commercialization department can add or remove features from a service based on user feedback. In this way, the commercialization department can develop products that better meet user needs by incorporating user feedback.

[0089] The evaluation unit can also perform region-specific effectiveness evaluation by taking into account the user's geographical location information. For example, the evaluation unit can perform an effectiveness evaluation targeting users living in a specific region and evaluate services that meet the needs specific to that region. The evaluation unit can also compare the evaluation results for each region and analyze the demand for each region. Furthermore, the evaluation unit can collect feedback on the region-specific service and identify areas for improvement of the service. In this way, the evaluation unit can perform region-specific effectiveness evaluation by taking into account the user's geographical location information.

[0090] The data collection unit can also analyze users' social media activities and collect data that reflects trends. For example, the data collection unit can collect related data based on content shared by users on social media. The data collection unit can also collect data that reflects trends that are currently trending on social media. Furthermore, the data collection unit can analyze users' social media activities and collect data that narrows down to a specific target demographic. In this way, the data collection unit can collect data that reflects trends by reflecting users' social media activities.

[0091] The processing flow of the first embodiment will be briefly explained below.

[0092] Step 1: The proposal unit uses generation AI to propose service ideas. The generation AI analyzes past data and trends to generate new service ideas. For example, it can propose a cashback service tailored to use at a specific store, or a new point system using 2D codes. The generation AI can also analyze past sales data and customer feedback to generate effective service ideas. Step 2: The research department investigates the demand for the idea proposed by the proposal department. Demand research is done through questionnaires and market research. For example, online surveys can be conducted to collect customer opinions. Field research can also be conducted to assess demand in the actual market. Furthermore, existing market data can be analyzed through desk research to assess demand. Step 3: The commercialization department commercializes ideas that have confirmed their potential. In the commercialization process, the specific design and development of the service takes place. For example, this could involve developing a system to introduce a new cashback service or building a points system using 2D codes. Furthermore, the feasibility of the service can be evaluated through the creation of prototypes and test marketing. Step 4: The evaluation department evaluates the effectiveness of the commercialized service. Effectiveness evaluation is performed by analyzing the usage status of the service and customer reactions. For example, it is possible to survey the frequency of service usage and evaluate customer satisfaction. It is also possible to collect customer feedback and identify areas for improvement in the service. Furthermore, it is possible to analyze sales data and evaluate the economic effectiveness of the service.

[0093] (Example 2) A platform according to an embodiment of the present invention uses a generation AI to propose original service ideas specific to credit card and QR code payment businesses, investigates demand for the proposed ideas, and implements a PDCA cycle to commercialize them. This platform includes a process in which the generation AI proposes original service ideas related to credit cards and QR code payment, investigates demand for the proposed ideas, and commercializes them. For example, the generation AI analyzes past data and trends to generate new service ideas. Specific examples include a cashback service specifically for use at specific stores or a new point system using two-dimensional codes (e.g., QR codes). Next, the demand for the proposed service idea is investigated. The demand investigation is conducted through surveys and market research to evaluate whether the idea proposed by the generation AI is actually accepted by customers. For example, customer opinions are collected through surveys to identify areas for improvement in the service idea. After that, service ideas whose demand is confirmed are commercialized. In the commercialization process, the specific design and development of the service are carried out and the product is actually launched on the market. For example, a system for introducing a new cashback service or a point system using two-dimensional codes is developed. Finally, the effectiveness of the commercialized service is evaluated and the PDCA cycle is implemented. Effectiveness evaluation analyzes service usage and customer reactions to identify areas for improvement. For example, the frequency of service usage and customer satisfaction can be investigated and reflected in proposing the next service idea. In this way, by building a platform that allows the AI ​​to propose original service ideas specific to credit card and QR payment businesses, investigate demand for those ideas, and implement the PDCA cycle to commercialize them, it becomes possible to provide new value in the increasingly competitive cashless payment market. This allows the platform to have the AI ​​propose original service ideas specific to credit card and QR payment businesses, investigate demand for those ideas, and implement the PDCA cycle to commercialize them.

[0094] A platform according to an embodiment includes a proposal unit, a research unit, a commercialization unit, and an evaluation unit. The proposal unit proposes service ideas using a generation AI. The generation AI, for example, analyzes past data and trends to generate new service ideas. For example, the generation AI can propose a cashback service tailored to use at a specific store or a new point system using two-dimensional codes. The generation AI can also generate effective service ideas by analyzing past sales data and customer feedback. The research unit investigates demand for the ideas proposed by the proposal unit. The demand investigation is conducted, for example, through questionnaires or market research. For example, the research unit can conduct online questionnaires to collect customer opinions. The research unit can also conduct field research to evaluate demand in the actual market. Furthermore, the research unit can analyze existing market data through desk research to evaluate demand. The commercialization unit commercializes ideas for which demand has been confirmed. The commercialization process involves, for example, the specific design and development of the service. For example, the commercialization unit can develop a system for introducing a new cashback service. The commercialization department can also build a point system using two-dimensional codes. Furthermore, the commercialization department can evaluate the feasibility of the service through the creation of prototypes and test marketing. The evaluation department evaluates the effectiveness of the commercialized service. The effectiveness evaluation is performed, for example, by analyzing the usage status of the service and customer responses. For example, the evaluation department can survey the frequency of service use and evaluate customer satisfaction. The evaluation department can also collect customer feedback and identify areas for improvement in the service. Furthermore, the evaluation department can analyze sales data and evaluate the economic effectiveness of the service. As a result, the platform according to the embodiment can have the generation AI propose original service ideas specialized for credit card and QR payment businesses, investigate demand for the proposed ideas, and implement a PDCA cycle to commercialize them.

[0095] The suggestion unit can analyze past data or trends to generate new service ideas. The suggestion unit can, for example, analyze past sales data to generate new service ideas. For example, the suggestion unit can propose a cashback service specialized for use at a specific store based on past sales data. The suggestion unit can also analyze customer feedback to generate new service ideas. For example, the suggestion unit can propose a new point system using two-dimensional codes based on customer feedback. The suggestion unit can also analyze social media trends to generate new service ideas. For example, the suggestion unit can propose new service ideas based on trends that are popular on social media. In this way, the suggestion unit can generate more effective service ideas by analyzing past data and trends.

[0096] The research department can evaluate the demand for the proposed idea through questionnaires or market research. The research department, for example, conducts an online questionnaire to collect customer opinions. For example, the research department can evaluate the demand for the proposed service idea through an online questionnaire. The research department can also conduct field research to evaluate demand in the actual market. For example, the research department can evaluate the demand for the service idea through field research in a specific region. Furthermore, the research department can analyze existing market data and evaluate demand through desk research. For example, the research department can evaluate the demand for the proposed service idea based on existing market data. This allows the research department to accurately evaluate the demand for the proposed idea through questionnaires or market research.

[0097] The merchandising department can design or develop specific services and actually launch them on the market. The merchandising department, for example, develops systems to introduce new cashback services. For example, the merchandising department can design a system for a cashback service and actually launch it on the market. The merchandising department can also build a point system using two-dimensional codes. For example, the merchandising department can design a point system using two-dimensional codes and actually launch it on the market. Furthermore, the merchandising department can evaluate the feasibility of a service through the creation of prototypes and test marketing. For example, the merchandising department can evaluate the feasibility of a service by creating a prototype and conducting small-scale test marketing. As a result, the merchandising department can design and develop specific services and actually launch them on the market.

[0098] The evaluation department can analyze the usage status of the service or customer responses and identify areas for improvement of the service. The evaluation department, for example, investigates the frequency of service usage and evaluates customer satisfaction. For example, the evaluation department can evaluate customer satisfaction based on the frequency of service usage. The evaluation department can also collect customer feedback and identify areas for improvement of the service. For example, the evaluation department can identify areas for improvement of the service based on customer feedback. Furthermore, the evaluation department can analyze sales data and evaluate the economic effectiveness of the service. For example, the evaluation department can evaluate the economic effectiveness of the service based on sales data. In this way, the evaluation department can identify areas for improvement of the service by analyzing the usage status of the service and customer responses.

[0099] The platform further includes a data collection unit that collects data such as past success cases or failure cases, customer feedback, etc., and provides the data to the proposal unit. The data collection unit, for example, collects past success cases and provides the data to the proposal unit. For example, the data collection unit can collect past cases of increased sales and cases of improved customer satisfaction, and provide the data to the proposal unit. The data collection unit can also collect past failure cases and provide the data to the proposal unit. For example, the data collection unit can collect project failure cases and customer complaint cases, and provide the data to the proposal unit. The data collection unit can also collect customer feedback and provide the data to the proposal unit. For example, the data collection unit can collect survey results and review comments, and provide the data to the proposal unit. In this way, the data collection unit can provide useful data to the proposal unit by collecting past success cases, failure cases, and customer feedback.

[0100] The platform further includes a survey unit that collects customer opinions and identifies areas for improvement of the service idea. The survey unit, for example, conducts an online survey to collect customer opinions. For example, the survey unit can identify areas for improvement of the service idea through the online survey. The survey unit can also collect customer opinions by conducting telephone interviews. For example, the survey unit can identify areas for improvement of the service idea through the telephone interviews. The survey unit can also collect customer opinions by conducting field surveys. For example, the survey unit can identify areas for improvement of the service idea through the field surveys. In this way, the survey unit can identify areas for improvement of the service idea by collecting customer opinions.

[0101] The platform further includes a market research department that actually conducts small-scale test marketing to evaluate demand for the service idea. The market research department, for example, conducts test sales in a limited area to evaluate demand for the service idea. For example, the market research department can evaluate demand for the service idea through test sales in a specific area. The market research department can also conduct online tests to evaluate demand for the service idea. For example, the market research department can evaluate demand for the service idea through an online platform. Furthermore, the market research department can conduct field research to evaluate demand for the service idea. For example, the market research department can evaluate demand for the service idea through field research in a specific area. In this way, the market research department can evaluate demand for the service idea by actually conducting small-scale test marketing.

[0102] The platform further includes a system development department that develops a system for introducing a new cashback service. The system development department, for example, develops a system for introducing a new cashback service. For example, the system development department can design a system for a cashback service and actually launch it on the market. The system development department can also build a point system using a two-dimensional code. For example, the system development department can design a point system using a two-dimensional code and actually launch it on the market. Furthermore, the system development department can evaluate the feasibility of the service through the creation of a prototype and test marketing. For example, the system development department can evaluate the feasibility of the service by creating a prototype and conducting small-scale test marketing. This allows the system development department to develop a system for introducing a new cashback service.

[0103] The platform further includes a campaign unit that implements a service that doubles points when used during a specific time period, and a campaign specialized for use in a specific area. The campaign unit, for example, implements a service that doubles points when used during a specific time period. For example, the campaign unit can provide a service that doubles points when used during the daytime on weekdays. The campaign unit can also implement a campaign specialized for use in a specific area. For example, the campaign unit can implement a campaign specialized for use in urban areas. Furthermore, the campaign unit can implement a combination of campaigns specialized for specific time periods and areas. For example, the campaign unit can implement a campaign that doubles points when used in urban areas on weekend nights. In this way, the campaign unit can promote use by implementing campaigns specialized for specific time periods and areas.

[0104] The platform further includes a usage analysis unit that investigates the frequency of service use and customer satisfaction and reflects the results in proposing the next service idea. The usage analysis unit, for example, investigates the frequency of service use and reflects the results in proposing the next service idea. For example, the usage analysis unit can investigate the number of monthly active users and reflect the results in proposing the next service idea. The usage analysis unit can also investigate customer satisfaction and reflect the results in proposing the next service idea. For example, the usage analysis unit can investigate NPS scores and reflect the results in proposing the next service idea. Furthermore, the usage analysis unit can collect customer reviews and reflect the results in proposing the next service idea. For example, the usage analysis unit can collect online reviews and reflect the results in proposing the next service idea. In this way, the usage analysis unit can investigate the frequency of service use and customer satisfaction and reflect the results in proposing the next service idea.

[0105] The platform further includes a customer satisfaction survey unit that analyzes customer satisfaction and word-of-mouth reviews to identify areas for service improvement. The customer satisfaction survey unit, for example, surveys customer satisfaction and identifies areas for service improvement. For example, the customer satisfaction survey unit can identify areas for service improvement based on survey results. The customer satisfaction survey unit can also collect word-of-mouth reviews and identify areas for service improvement. For example, the customer satisfaction survey unit can collect online reviews and identify areas for service improvement. The customer satisfaction survey unit can also analyze social media comments and identify areas for service improvement. For example, the customer satisfaction survey unit can identify areas for service improvement based on social media comments. In this way, the customer satisfaction survey unit can identify areas for service improvement by analyzing customer satisfaction and word-of-mouth reviews.

[0106] In the platform, the suggestion unit estimates the user's emotions and adjusts the timing of generating service ideas based on the estimated user emotions. The suggestion unit, for example, estimates the user's emotions and adjusts the timing of generating service ideas based on the estimated user emotions. For example, if the user is excited, the suggestion unit can cause the generation AI to immediately suggest new service ideas. Also, if the user is relaxed, the suggestion unit can cause the generation AI to generate ideas at a slower pace. Furthermore, if the user is feeling stressed, the suggestion unit can cause the generation AI to suggest simple ideas to reduce the user's burden. In this way, the suggestion unit can generate ideas at more appropriate times by adjusting the timing of generating service ideas based on the user's emotions.

[0107] When analyzing past data and trends, the suggestion unit can prioritize analysis of data related to specific seasons or events. For example, the suggestion unit causes the generation AI to prioritize generation of Christmas-related service ideas leading up to the Christmas season. For example, the suggestion unit can cause the generation AI to propose Christmas-related service ideas based on data related to the Christmas season. The suggestion unit can also cause the generation AI to prioritize generation of service ideas related to travel and leisure during the summer vacation period. For example, the suggestion unit can cause the generation AI to propose service ideas related to travel and leisure based on data related to the summer vacation period. Furthermore, the suggestion unit can also cause the generation AI to prioritize generation of service ideas related to gifts and dates leading up to Valentine's Day. For example, the suggestion unit can cause the generation AI to propose service ideas related to gifts and dates based on data related to Valentine's Day. In this way, the suggestion unit can generate more effective service ideas by preferentially analyzing data related to specific seasons or events.

[0108] The suggestion unit can reflect the user's purchase history and usage history in the ideas it generates. For example, the suggestion unit allows the generation AI to suggest related service ideas based on products the user has purchased in the past. For example, the suggestion unit can allow the generation AI to suggest related service ideas based on the user's purchase history. The suggestion unit can also allow the generation AI to suggest cashback services at specific stores based on stores frequently visited by the user. For example, the suggestion unit can allow the generation AI to suggest cashback services at specific stores based on the user's usage history. Furthermore, the suggestion unit can analyze the user's usage history and allow the generation AI to suggest an optimal point system. For example, the suggestion unit can allow the generation AI to suggest an optimal point system based on the user's usage history. This allows the suggestion unit to generate more personalized service ideas by reflecting the user's purchase history and usage history.

[0109] The suggestion unit can estimate the user's emotions and determine the priority of ideas to be generated based on the estimated user's emotions. For example, the suggestion unit can cause the generation AI to preferentially suggest new ideas when the user is excited. For example, the suggestion unit can cause the generation AI to preferentially suggest new ideas when the user is excited. Furthermore, the suggestion unit can cause the generation AI to preferentially suggest improvements to existing ideas when the user is relaxed. For example, the suggestion unit can cause the generation AI to preferentially suggest improvements to existing ideas when the user is relaxed. Furthermore, the suggestion unit can cause the generation AI to preferentially suggest ideas that are simple and easy to implement when the user is stressed. For example, the suggestion unit can cause the generation AI to preferentially suggest ideas that are simple and easy to implement when the user is stressed. In this way, the suggestion unit can preferentially suggest more appropriate ideas by determining the priority of ideas to be generated based on the user's emotions.

[0110] The suggestion unit can propose region-specific services in the generated ideas by taking into account the user's geographical location information. For example, if the user is in a specific region, the suggestion unit can propose cashback services available in that region. For example, the suggestion unit can propose cashback services available in that region based on the user's geographical location information. The suggestion unit can also have the generation AI propose a region-specific point system based on the user's location information. For example, the suggestion unit can have the generation AI propose a region-specific point system based on the user's location information. Furthermore, if the user is traveling, the suggestion unit can also propose benefits and services that can be used at the travel destination. For example, if the user is traveling, the suggestion unit can propose benefits and services that can be used at the travel destination. In this way, the suggestion unit can propose region-specific services by taking into account the user's geographical location information.

[0111] The suggestion unit can analyze the user's social media activity and reflect trends in the ideas it generates. For example, the suggestion unit allows the generation AI to suggest related service ideas based on content shared by the user on social media. For example, the suggestion unit can allow the generation AI to suggest related service ideas based on the user's social media activity. The suggestion unit can also analyze services used by the user's followers and friends and allow the generation AI to suggest similar services. For example, the suggestion unit can allow the generation AI to suggest similar services based on the user's social media activity. Furthermore, the suggestion unit can allow the generation AI to suggest service ideas that reflect trends that are being talked about on social media. For example, the suggestion unit can allow the generation AI to suggest related service ideas based on social media trends. In this way, the suggestion unit can generate service ideas that reflect trends by analyzing the user's social media activity.

[0112] The survey unit can estimate the user's emotions and adjust the content of the survey questions based on the estimated user's emotions. For example, when the user is relaxed, the survey unit can provide a survey including detailed questions. For example, when the user is relaxed, the survey unit can provide a survey including detailed questions. Furthermore, when the user is in a hurry, the survey unit can provide a concise and short survey. For example, when the user is in a hurry, the survey unit can provide a survey including interesting questions. Furthermore, when the user is excited, the survey unit can provide a survey including interesting questions. For example, when the user is excited, the survey unit can provide a survey including interesting questions. In this way, the survey unit can provide more appropriate questions by adjusting the content of the survey questions based on the user's emotions.

[0113] When conducting questionnaires or market research, the research department can narrow the survey to a specific target demographic. For example, the research department can conduct a questionnaire targeting young people to understand their needs. For example, the research department can conduct a questionnaire targeting young people to understand their needs. The research department can also conduct market research targeting elderly people to evaluate services that are suitable for them. For example, the research department can conduct market research targeting elderly people to evaluate services that are suitable for them. Furthermore, the research department can conduct a questionnaire targeting users living in a specific area to understand needs that are specific to the area. For example, the research department can conduct a questionnaire targeting users living in a specific area to understand needs that are specific to the area. This allows the research department to collect more accurate data by conducting a survey that is narrowed to a specific target demographic.

[0114] The research department can compare the collected data with past survey results and analyze it. For example, the research department can compare past survey results with current results and analyze changes in trends. For example, the research department can compare past survey results with current results and analyze changes in trends. The research department can also compare past market research data with current data and evaluate changes in demand. For example, the research department can compare past market research data with current data and evaluate changes in demand. Furthermore, the research department can compare past customer feedback with current feedback and identify areas for improvement in services. For example, the research department can compare past customer feedback with current feedback and identify areas for improvement in services. In this way, the research department can grasp changes in trends by comparing and analyzing it with past survey results.

[0115] The research unit can estimate the user's emotions and prioritize the research results based on the estimated user's emotions. For example, if the user is excited, the research unit can prioritize analyzing positive feedback. For example, if the user is excited, the research unit can prioritize analyzing positive feedback. Furthermore, if the user is relaxed, the research unit can prioritize analyzing detailed feedback. For example, if the user is relaxed, the research unit can prioritize analyzing detailed feedback. Furthermore, if the user is feeling stressed, the research unit can prioritize analyzing negative feedback. For example, if the user is feeling stressed, the research unit can prioritize analyzing negative feedback. In this way, the research unit can prioritize analyzing more important data by prioritizing the research results based on the user's emotions.

[0116] The research department can conduct region-specific research by taking into account the geographical location information of users in the collected data. For example, the research department can conduct a survey targeting users living in a specific region to understand region-specific needs. For example, the research department can conduct a survey targeting users living in a specific region to understand region-specific needs. The research department can also conduct market research for each region to evaluate demand for each region. For example, the research department can conduct market research for each region to evaluate demand for each region. Furthermore, the research department can collect feedback on region-specific services to identify areas for improvement of the services. For example, the research department can collect feedback on region-specific services to identify areas for improvement of the services. In this way, the research department can conduct region-specific research by taking into account the geographical location information of users.

[0117] The research department can reflect the user's social media activities in the collected data. For example, the research department can analyze content shared by the user on social media and reflect the results in the survey questions. For example, the research department can reflect the results in the survey questions based on the content shared by the user on social media. The research department can also research trends that are trending on social media and reflect the results in the survey questions. For example, the research department can reflect the results in the survey questions based on social media trends. Furthermore, the research department can analyze the user's social media activities and conduct surveys that narrow down the target demographic. For example, the research department can conduct surveys that narrow down the target demographic based on the user's social media activities. In this way, the research department can conduct surveys that reflect trends by reflecting the user's social media activities.

[0118] The commercialization department can estimate the user's emotions and adjust the commercialization process based on the estimated user's emotions. For example, if the user is excited, the commercialization department can quickly proceed with the commercialization process. For example, if the user is excited, the commercialization department can quickly proceed with the commercialization process. Furthermore, if the user is relaxed, the commercialization department can also proceed with the commercialization process while reflecting detailed feedback. For example, if the user is relaxed, the commercialization department can proceed with the commercialization process while reflecting detailed feedback. Furthermore, if the user is feeling stressed, the commercialization department can also proceed with a simple and easy-to-execute commercialization process. For example, if the user is feeling stressed, the commercialization department can proceed with a simple and easy-to-execute commercialization process. In this way, the commercialization department can achieve more appropriate commercialization by adjusting the commercialization process based on the user's emotions.

[0119] The commercialization department can reflect user feedback in design and development. The commercialization department, for example, improves the design of the service based on feedback provided by the user. For example, the commercialization department can improve the design of the service based on feedback provided by the user. The commercialization department can also develop a prototype that reflects user opinions and conduct testing. For example, the commercialization department can develop a prototype that reflects user opinions and conduct testing. The commercialization department can also add or delete functions of the service based on user feedback. For example, the commercialization department can add or delete functions of the service based on user feedback. In this way, the commercialization department can develop a product that better meets user needs by reflecting user feedback in design and development.

[0120] The commercialization department can refer to past success stories and failure stories in design and development. The commercialization department, for example, designs services based on past success stories. For example, the commercialization department can design services based on past examples of increased sales and improved customer satisfaction. The commercialization department can also analyze past failure stories and design services so as not to repeat the same mistakes. For example, the commercialization department can analyze past project failure stories and customer complaint stories and design services so as not to repeat the same mistakes. Furthermore, the commercialization department can proceed with service development while referring to past examples. For example, the commercialization department can proceed with service development based on past examples. In this way, the commercialization department can develop products more effectively by referring to past success stories and failure stories in design and development.

[0121] The commercialization department can estimate the user's emotions and determine priorities for commercialization based on the estimated user's emotions. For example, if the user is excited, the commercialization department can prioritize commercialization of positive feedback. For example, if the user is excited, the commercialization department can prioritize commercialization of positive feedback. Furthermore, if the user is relaxed, the commercialization department can prioritize commercialization that reflects detailed feedback. For example, if the user is relaxed, the commercialization department can prioritize commercialization that reflects detailed feedback. Furthermore, if the user is feeling stressed, the commercialization department can prioritize commercialization that is simple and easy to implement. For example, if the user is feeling stressed, the commercialization department can prioritize commercialization that is simple and easy to implement. In this way, the commercialization department can prioritize the development of more important products by determining priorities for commercialization based on the user's emotions.

[0122] The merchandising department can develop region-specific products by taking into account the geographical location information of users during design and development. The merchandising department, for example, develops products targeted at users living in a specific region. For example, the merchandising department can develop products targeted at users living in a specific region. The merchandising department can also design products that reflect the needs of each region. For example, the merchandising department can design products based on the needs of each region. Furthermore, the merchandising department can develop a system for providing region-specific services. For example, the merchandising department can develop a system for providing region-specific services. In this way, the merchandising department can develop region-specific products by taking into account the geographical location information of users during design and development.

[0123] The merchandising department can reflect the user's social media activities in design and development. The merchandising department, for example, designs products based on content shared by the user on social media. For example, the merchandising department can design products based on content shared by the user on social media. The merchandising department can also develop products that reflect trends that are trending on social media. For example, the merchandising department can develop products based on social media trends. Furthermore, the merchandising department can analyze the user's social media activities and develop products that target specific demographics. For example, the merchandising department can develop products that target specific demographics based on the user's social media activities. In this way, the merchandising department can develop products that reflect trends by reflecting the user's social media activities in design and development.

[0124] The evaluation unit can estimate the user's emotions and adjust the evaluation criteria based on the estimated user's emotions. For example, when the user is excited, the evaluation unit sets evaluation criteria that emphasize positive feedback. For example, when the user is excited, the evaluation unit can set evaluation criteria that emphasize positive feedback. Furthermore, when the user is relaxed, the evaluation unit can set evaluation criteria that emphasize detailed feedback. For example, when the user is relaxed, the evaluation unit can set evaluation criteria that emphasize detailed feedback. Furthermore, when the user is feeling stressed, the evaluation unit can set evaluation criteria that emphasize negative feedback. For example, when the user is feeling stressed, the evaluation unit can set evaluation criteria that emphasize negative feedback. In this way, the evaluation unit can perform a more appropriate evaluation by adjusting the evaluation criteria based on the user's emotions.

[0125] The evaluation unit can compare and analyze past evaluation results in the effectiveness evaluation. For example, the evaluation unit can compare past evaluation results with current evaluation results to find areas for improvement of the service. For example, the evaluation unit can compare past evaluation results with current evaluation results to find areas for improvement of the service. The evaluation unit can also compare past evaluation data with current data to analyze changes in trends. For example, the evaluation unit can compare past evaluation data with current data to analyze changes in trends. Furthermore, the evaluation unit can compare past customer feedback with current feedback to evaluate the effectiveness of the service. For example, the evaluation unit can compare past customer feedback with current feedback to evaluate the effectiveness of the service. In this way, the evaluation unit can find areas for improvement of the service by comparing and analyzing past evaluation results.

[0126] The evaluation unit can conduct an effectiveness evaluation that is focused on a specific target demographic. For example, the evaluation unit can conduct an effectiveness evaluation targeting young people and evaluate services that meet their needs. For example, the evaluation unit can conduct an effectiveness evaluation targeting young people and evaluate services that meet their needs. The evaluation unit can also conduct an effectiveness evaluation targeting elderly people and evaluate services that are suitable for them. For example, the evaluation unit can conduct an effectiveness evaluation targeting elderly people and evaluate services that are suitable for them. Furthermore, the evaluation unit can conduct an effectiveness evaluation targeting users living in a specific area and evaluate services that meet needs that are specific to the area. For example, the evaluation unit can conduct an effectiveness evaluation targeting users living in a specific area and evaluate services that meet needs that are specific to the area. As a result, the evaluation unit can conduct an evaluation that is focused on a specific target demographic, thereby enabling a more accurate evaluation.

[0127] The evaluation unit can estimate the user's emotions and determine the priority of the evaluation results based on the estimated user's emotions. For example, when the user is excited, the evaluation unit prioritizes evaluating positive feedback. For example, when the user is excited, the evaluation unit can prioritize evaluating positive feedback. Furthermore, when the user is relaxed, the evaluation unit can prioritize evaluating detailed feedback. For example, when the user is relaxed, the evaluation unit can prioritize evaluating detailed feedback. Furthermore, when the user is feeling stressed, the evaluation unit can prioritize evaluating negative feedback. For example, when the user is feeling stressed, the evaluation unit can prioritize evaluating negative feedback. In this way, the evaluation unit can prioritize evaluating more important data by determining the priority of the evaluation results based on the user's emotions.

[0128] The evaluation unit can perform a region-specific evaluation in the effectiveness evaluation by taking into account the user's geographical location information. The evaluation unit, for example, performs an effectiveness evaluation targeting users living in a specific region and evaluates services that meet region-specific needs. For example, the evaluation unit can perform an effectiveness evaluation targeting users living in a specific region and evaluate services that meet region-specific needs. The evaluation unit can also compare evaluation results for each region and analyze demand for each region. For example, the evaluation unit can compare evaluation results for each region and analyze demand for each region. Furthermore, the evaluation unit can collect feedback on the region-specific service and identify areas for improvement of the service. For example, the evaluation unit can collect feedback on the region-specific service and identify areas for improvement of the service. In this way, the evaluation unit can perform a region-specific evaluation by taking into account the user's geographical location information.

[0129] The evaluation unit can reflect the user's social media activities in the effectiveness evaluation. The evaluation unit can evaluate the effectiveness of the service based on, for example, content shared by the user on social media. For example, the evaluation unit can evaluate the effectiveness of the service based on content shared by the user on social media. The evaluation unit can also perform an effectiveness evaluation that reflects trends that are trending on social media. For example, the evaluation unit can evaluate the effectiveness of the service based on social media trends. Furthermore, the evaluation unit can analyze the user's social media activities and perform an effectiveness evaluation that narrows down the target demographic. For example, the evaluation unit can perform an effectiveness evaluation that narrows down the target demographic based on the user's social media activities. In this way, the evaluation unit can perform an evaluation that reflects trends by reflecting the user's social media activities.

[0130] The platform further includes a data collection unit that estimates the user's emotions and adjusts the timing of data collection based on the estimated user's emotions. The data collection unit, for example, performs detailed data collection when the user is relaxed. For example, the data collection unit can perform detailed data collection when the user is relaxed. Furthermore, the data collection unit can also perform brief data collection when the user is in a hurry. For example, the data collection unit can perform brief data collection when the user is in a hurry. Furthermore, the data collection unit can also perform interesting data collection when the user is excited. For example, the data collection unit can perform interesting data collection when the user is excited. In this way, the data collection unit can adjust the timing of data collection based on the user's emotions and collect data at more appropriate times.

[0131] The data collection unit can prioritize collecting data related to a particular season or event in the data to be collected. For example, the data collection unit prioritizes collecting Christmas-related data in the run-up to the Christmas season. For example, the data collection unit can prioritize collecting Christmas-related data based on data related to the Christmas season. The data collection unit can also prioritize collecting data related to travel and leisure activities during the summer vacation period. For example, the data collection unit can prioritize collecting data related to travel and leisure activities based on data related to the summer vacation period. Furthermore, the data collection unit can also prioritize collecting data related to gifts and dates in the run-up to Valentine's Day. For example, the data collection unit can prioritize collecting data related to gifts and dates based on data related to Valentine's Day. In this way, the data collection unit can collect data related to a particular season or event more effectively by prioritized collection of data.

[0132] The data collection unit can refer to past success stories and failure stories when collecting data. The data collection unit, for example, collects related data based on past success stories. For example, the data collection unit can collect related data based on past cases of increased sales or cases of improved customer satisfaction. The data collection unit can also analyze past failure stories and collect data to prevent the same mistakes from being repeated. For example, the data collection unit can analyze past cases of project failure or customer complaints and collect data to prevent the same mistakes from being repeated. Furthermore, the data collection unit can proceed with data collection while referring to past cases. For example, the data collection unit can proceed with data collection based on past cases. In this way, the data collection unit can collect data more effectively by referring to past success stories and failure stories when collecting data.

[0133] The data collection unit can estimate the user's emotions and determine the priority of data to be collected based on the estimated user's emotions. For example, when the user is excited, the data collection unit prioritizes collecting positive data. For example, when the user is excited, the data collection unit can prioritize collecting positive data. Furthermore, when the user is relaxed, the data collection unit can prioritize collecting detailed data. For example, when the user is relaxed, the data collection unit can prioritize collecting detailed data. Furthermore, when the user is feeling stressed, the data collection unit can prioritize collecting negative data. For example, when the user is feeling stressed, the data collection unit can prioritize collecting negative data. In this way, the data collection unit can prioritize collecting more important data by determining the priority of data to be collected based on the user's emotions.

[0134] The data collection unit can collect region-specific data by taking into account the geographical location information of the user when collecting data. The data collection unit, for example, collects data targeted at users living in a specific region. For example, the data collection unit can collect data targeted at users living in a specific region. The data collection unit can also compare data for each region and analyze demand for each region. For example, the data collection unit can compare data for each region and analyze demand for each region. Furthermore, the data collection unit can collect feedback on region-specific services and identify areas for improvement of the services. For example, the data collection unit can collect feedback on region-specific services and identify areas for improvement of the services. In this way, the data collection unit can collect region-specific data by taking into account the geographical location information of the user when collecting data.

[0135] The data collection unit can reflect the user's social media activities in the data it collects. The data collection unit, for example, collects data based on content shared by the user on social media. For example, the data collection unit can collect data based on content shared by the user on social media. The data collection unit can also collect data that reflects trends that are trending on social media. For example, the data collection unit can collect data based on social media trends. Furthermore, the data collection unit can analyze the user's social media activities and collect data that is targeted to a specific demographic. For example, the data collection unit can collect data that is targeted to a specific demographic based on the user's social media activities. In this way, the data collection unit can collect data that reflects trends by reflecting the user's social media activities in the data it collects.

[0136] The questionnaire unit can estimate the user's emotions and adjust the content of the questionnaire questions based on the estimated user's emotions. For example, when the user is relaxed, the questionnaire unit can provide a questionnaire including detailed questions. For example, when the user is relaxed, the questionnaire unit can provide a questionnaire including detailed questions. Furthermore, when the user is in a hurry, the questionnaire unit can provide a concise and short questionnaire. For example, when the user is in a hurry, the questionnaire unit can provide a questionnaire including interesting questions. Furthermore, when the user is excited, the questionnaire unit can provide a questionnaire including interesting questions. For example, when the user is excited, the questionnaire unit can provide a questionnaire including interesting questions. In this way, the questionnaire unit can adjust the content of the questionnaire questions based on the user's emotions, thereby providing more appropriate questions.

[0137] The survey unit can compare and analyze the collected data with past survey results. For example, the survey unit can compare past survey results with current results and analyze changes in trends. For example, the survey unit can compare past survey results with current results and analyze changes in trends. The survey unit can also compare past survey data with current data and evaluate changes in demand. For example, the survey unit can compare past survey data with current data and evaluate changes in demand. Furthermore, the survey unit can compare past customer feedback with current feedback and identify areas for improvement in services. For example, the survey unit can compare past customer feedback with current feedback and identify areas for improvement in services. In this way, the survey unit can grasp changes in trends by comparing and analyzing with past survey results.

[0138] The survey unit can conduct a region-specific survey by taking into account the geographical location information of users in the collected data. The survey unit, for example, conducts a survey targeting users living in a specific region to understand region-specific needs. For example, the survey unit can conduct a survey targeting users living in a specific region to understand region-specific needs. The survey unit can also compare survey results for each region to analyze demand for each region. For example, the survey unit can compare survey results for each region to analyze demand for each region. Furthermore, the survey unit can collect feedback on region-specific services to identify areas for improvement of the services. For example, the survey unit can collect feedback on region-specific services to identify areas for improvement of the services. This allows the survey unit to conduct a region-specific survey by taking into account the geographical location information of users in the collected data.

[0139] The questionnaire unit can estimate the user's emotions and determine the priority of the questionnaire results based on the estimated user's emotions. For example, if the user is excited, the questionnaire unit prioritizes analyzing positive feedback. For example, if the user is excited, the questionnaire unit can prioritize analyzing positive feedback. Furthermore, if the user is relaxed, the questionnaire unit can prioritize analyzing detailed feedback. For example, if the user is relaxed, the questionnaire unit can prioritize analyzing detailed feedback. Furthermore, if the user is feeling stressed, the questionnaire unit can prioritize analyzing negative feedback. For example, if the user is feeling stressed, the questionnaire unit can prioritize analyzing negative feedback. In this way, the questionnaire unit can prioritize analyzing more important data by determining the priority of the questionnaire results based on the user's emotions.

[0140] The survey unit can reflect the user's social media activities in the data it collects. The survey unit, for example, reflects the content of the survey questions based on the content shared by the user on social media. For example, the survey unit can reflect the content of the survey questions based on the content shared by the user on social media. The survey unit can also investigate trends that are trending on social media and reflect the results in the survey questions. For example, the survey unit can reflect the results in the survey questions based on social media trends. Furthermore, the survey unit can analyze the user's social media activities and conduct a survey that narrows down to a specific target demographic. For example, the survey unit can conduct a survey that narrows down to a specific target demographic based on the user's social media activities. In this way, the survey unit can conduct a survey that reflects trends by reflecting the user's social media activities in the data it collects.

[0141] The questionnaire unit can reflect the user's past questionnaire results in the collected data. The questionnaire unit, for example, can provide a questionnaire including related questions based on the questionnaire results previously answered by the user. For example, the questionnaire unit can provide a questionnaire including related questions based on the questionnaire results previously answered by the user. The questionnaire unit can also compare the past questionnaire results with the current results and analyze changes in trends. For example, the questionnaire unit can compare the past questionnaire results with the current results and analyze changes in trends. Furthermore, the questionnaire unit can adjust the content of the questionnaire questions by referring to the past questionnaire data. For example, the questionnaire unit can adjust the content of the questionnaire questions based on the past questionnaire data. In this way, the questionnaire unit can provide more appropriate questions by reflecting the user's past questionnaire results in the collected data.

[0142] The market research department can estimate the user's emotions and adjust the target of the market research based on the estimated user's emotions. For example, when the user is relaxed, the market research department can conduct detailed market research. For example, when the user is relaxed, the market research department can conduct detailed market research. Furthermore, when the user is in a hurry, the market research department can conduct brief market research. For example, when the user is in a hurry, the market research department can conduct brief market research. Furthermore, when the user is excited, the market research department can conduct interesting market research. For example, when the user is excited, the market research department can conduct interesting market research. In this way, the market research department can conduct more appropriate research by adjusting the target of the market research based on the user's emotions.

[0143] The market research department can perform comparative analysis of the collected data with past market research results. For example, the market research department can compare past market research results with current results and analyze changes in trends. For example, the market research department can compare past market research results with current results and analyze changes in trends. The market research department can also compare past market research data with current data and evaluate changes in demand. For example, the market research department can compare past market research data with current data and evaluate changes in demand. Furthermore, the market research department can compare past customer feedback with current feedback and identify areas for improvement in services. For example, the market research department can compare past customer feedback with current feedback and identify areas for improvement in services. In this way, the market research department can grasp changes in trends by performing comparative analysis with past market research results.

[0144] The market research department can conduct region-specific market research by taking into account the geographical location information of users in the collected data. The market research department, for example, conducts market research targeting users living in a specific region to understand region-specific needs. For example, the market research department can conduct market research targeting users living in a specific region to understand region-specific needs. The market research department can also compare market research results for each region to analyze demand for each region. For example, the market research department can compare market research results for each region to analyze demand for each region. Furthermore, the market research department can collect feedback on region-specific services to identify areas for improvement of the services. For example, the market research department can collect feedback on region-specific services to identify areas for improvement of the services. In this way, the market research department can conduct region-specific market research by taking into account the geographical location information of users in the collected data.

[0145] The market research department can estimate the user's emotions and prioritize market research results based on the estimated user's emotions. For example, if the user is excited, the market research department can prioritize analyzing positive feedback. For example, if the user is excited, the market research department can prioritize analyzing positive feedback. Furthermore, if the user is relaxed, the market research department can prioritize analyzing detailed feedback. For example, if the user is relaxed, the market research department can prioritize analyzing detailed feedback. Furthermore, if the user is stressed, the market research department can prioritize analyzing negative feedback. For example, if the user is stressed, the market research department can prioritize analyzing negative feedback. In this way, the market research department can prioritize analyzing more important data by prioritizing market research results based on the user's emotions.

[0146] The market research department can reflect the social media activities of users in the data it collects. For example, the market research department can reflect the content of market research questions based on content shared by users on social media. For example, the market research department can reflect the content of market research questions based on content shared by users on social media. The market research department can also investigate trends that are trending on social media and reflect the results in the market research questions. For example, the market research department can reflect the results in the market research questions based on social media trends. Furthermore, the market research department can analyze the social media activities of users and conduct market research that focuses on a specific target demographic. For example, the market research department can conduct market research that focuses on a specific target demographic based on the social media activities of users. In this way, the market research department can conduct market research that reflects trends by reflecting the social media activities of users in the data it collects.

[0147] The market research department can reflect the results of past market research conducted by the user in the data it collects. For example, the market research department can provide market research including related questions based on market research results answered by the user in the past. For example, the market research department can provide market research including related questions based on market research results answered by the user in the past. The market research department can also compare the results of past market research with the current results and analyze changes in trends. For example, the market research department can compare the results of past market research with the current results and analyze changes in trends. Furthermore, the market research department can adjust the content of the market research questions by referring to the past market research data. For example, the market research department can adjust the content of the market research questions based on the past market research data. In this way, the market research department can provide more appropriate questions by reflecting the results of past market research conducted by the user in the data it collects.

[0148] The system development department can estimate the user's emotions and adjust the system development process based on the estimated user's emotions. For example, if the user is excited, the system development department can quickly proceed with the system development process. For example, if the user is excited, the system development department can quickly proceed with the system development process. Furthermore, if the user is relaxed, the system development department can proceed with the system development process while reflecting detailed feedback. For example, if the user is relaxed, the system development department can proceed with the system development process while reflecting detailed feedback. Furthermore, if the user is feeling stressed, the system development department can proceed with a simple and easy-to-execute system development process. For example, if the user is feeling stressed, the system development department can proceed with a simple and easy-to-execute system development process. In this way, the system development department can achieve more appropriate system development by adjusting the system development process based on the user's emotions.

[0149] The system development department can reflect user feedback in development. For example, the system development department can improve the system design based on feedback provided by the user. For example, the system development department can improve the system design based on feedback provided by the user. The system development department can also develop a prototype that reflects user opinions and conduct testing. For example, the system development department can develop a prototype that reflects user opinions and conduct testing. Furthermore, the system development department can add or delete system functions based on user feedback. For example, the system development department can add or delete system functions based on user feedback. In this way, the system development department can develop a system that better meets user needs by reflecting user feedback in development.

[0150] The system development department can refer to past success stories and failure stories in development. The system development department, for example, designs a system based on past success stories. For example, the system development department can design a system based on past examples of increased sales or improved customer satisfaction. The system development department can also analyze past failure stories and design a system to avoid repeating the same mistakes. For example, the system development department can analyze past project failure stories or customer complaint stories and design a system to avoid repeating the same mistakes. Furthermore, the system development department can proceed with system development while referring to past examples. For example, the system development department can proceed with system development based on past examples. In this way, the system development department can develop a more effective system by referring to past success stories and failure stories in development.

[0151] The system development department can estimate the user's emotions and determine the priority of system development based on the estimated user's emotions. For example, if the user is excited, the system development department can prioritize reflecting positive feedback in system development. For example, if the user is excited, the system development department can prioritize reflecting positive feedback in system development. Furthermore, if the user is relaxed, the system development department can prioritize developing a system that reflects detailed feedback. For example, if the user is relaxed, the system development department can prioritize developing a system that reflects detailed feedback. Furthermore, if the user is feeling stressed, the system development department can prioritize developing a system that is simple and easy to implement. For example, if the user is feeling stressed, the system development department can prioritize developing a system that is simple and easy to implement. In this way, the system development department can prioritize developing more important systems by determining the priority of system development based on the user's emotions.

[0152] The system development department can develop a region-specific system by taking into account the geographical location information of users during development. The system development department, for example, develops a system targeted at users living in a specific region. For example, the system development department can develop a system targeted at users living in a specific region. The system development department can also design a system that reflects the needs of each region. For example, the system development department can design a system based on the needs of each region. Furthermore, the system development department can develop a system for providing region-specific services. For example, the system development department can develop a system for providing region-specific services. This allows the system development department to develop a region-specific system by taking into account the geographical location information of users during development.

[0153] The system development department can reflect users' social media activities in development. For example, the system development department can design a system based on content shared by users on social media. For example, the system development department can design a system based on content shared by users on social media. The system development department can also develop a system that reflects trends that are trending on social media. For example, the system development department can develop a system based on social media trends. Furthermore, the system development department can analyze users' social media activities and develop a system that narrows down the target demographic. For example, the system development department can develop a system that narrows down the target demographic based on users' social media activities. In this way, the system development department can develop a system that reflects trends by reflecting users' social media activities in development.

[0154] The campaign unit can estimate the user's emotions and adjust the content of the campaign based on the estimated user's emotions. For example, if the user is excited, the campaign unit can provide a campaign with many benefits. For example, if the user is excited, the campaign unit can provide a campaign with many benefits. Furthermore, if the user is relaxed, the campaign unit can provide a campaign including detailed information. For example, if the user is relaxed, the campaign unit can provide a campaign including detailed information. Furthermore, if the user is feeling stressed, the campaign unit can provide a simple and easy-to-understand campaign. For example, if the user is feeling stressed, the campaign unit can provide a simple and easy-to-understand campaign. In this way, the campaign unit can implement a more effective campaign by adjusting the content of the campaign based on the user's emotions.

[0155] The campaign department can compare the results of a campaign to be implemented with those of past campaigns. For example, the campaign department can compare the results of past campaigns with the current results and analyze the difference in effectiveness. For example, the campaign department can compare the results of past campaigns with the current results and analyze the difference in effectiveness. The campaign department can also compare past campaign data with current data and evaluate changes in trends. For example, the campaign department can compare past campaign data with current data and evaluate changes in trends. Furthermore, the campaign department can compare past customer feedback with current feedback and identify areas for improvement in the campaign. For example, the campaign department can compare past customer feedback with current feedback and identify areas for improvement in the campaign. In this way, the campaign department can grasp changes in trends by performing a comparison analysis with past campaign results.

[0156] The campaign unit can implement a campaign that is focused on a specific target demographic. For example, the campaign unit can implement a campaign that targets young people and provide benefits that meet their needs. For example, the campaign unit can implement a campaign that targets young people and provide benefits that meet their needs. The campaign unit can also implement a campaign that targets elderly people and provide benefits that are suitable for them. For example, the campaign unit can implement a campaign that targets elderly people and provide benefits that meet their needs. Furthermore, the campaign unit can implement a campaign that targets users living in a specific area and provide benefits that meet the needs that are specific to the area. For example, the campaign unit can implement a campaign that targets users living in a specific area and provide benefits that meet the needs that are specific to the area. This allows the campaign unit to implement a more effective campaign by implementing a campaign that is focused on a specific target demographic.

[0157] The campaign unit can estimate the user's emotions and determine the priority of campaigns based on the estimated user's emotions. For example, if the user is excited, the campaign unit can prioritize positive feedback in campaigns. For example, if the user is excited, the campaign unit can prioritize positive feedback in campaigns. Furthermore, if the user is relaxed, the campaign unit can prioritize campaigns that reflect detailed feedback. For example, if the user is relaxed, the campaign unit can prioritize campaigns that reflect detailed feedback. Furthermore, if the user is feeling stressed, the campaign unit can prioritize campaigns that are simple and easy to implement. For example, if the user is feeling stressed, the campaign unit can prioritize campaigns that are simple and easy to implement. In this way, the campaign unit can prioritize campaigns that are more important by determining the priority of campaigns based on the user's emotions.

[0158] The campaign unit can implement a region-specific campaign by taking into account the geographical location information of the user when implementing a campaign. The campaign unit, for example, implements a campaign targeted at users living in a specific region. For example, the campaign unit can implement a campaign targeted at users living in a specific region. The campaign unit can also provide a campaign that reflects the needs of each region. For example, the campaign unit can provide a campaign based on the needs of each region. Furthermore, the campaign unit can implement a campaign to provide a region-specific benefit. For example, the campaign unit can implement a campaign to provide a region-specific benefit. In this way, the campaign unit can implement a region-specific campaign by taking into account the geographical location information of the user when implementing a campaign, thereby enabling the campaign to be implemented more effectively.

[0159] The campaign unit can reflect the user's social media activities in the campaigns it implements. The campaign unit, for example, designs a campaign based on content shared by the user on social media. For example, the campaign unit can design a campaign based on content shared by the user on social media. The campaign unit can also implement a campaign that reflects trends that are trending on social media. For example, the campaign unit can implement a campaign based on social media trends. Furthermore, the campaign unit can analyze the user's social media activities and implement a campaign that narrows down to a specific target demographic. For example, the campaign unit can implement a campaign that narrows down to a specific target demographic based on the user's social media activities. In this way, the campaign unit can implement a campaign that reflects trends by reflecting the user's social media activities in the campaign it implements.

[0160] The usage status analysis unit can estimate the user's emotions and adjust the usage status analysis method based on the estimated user's emotions. The usage status analysis unit, for example, performs a detailed usage status analysis when the user is relaxed. For example, the usage status analysis unit can perform a detailed usage status analysis when the user is relaxed. Furthermore, the usage status analysis unit can perform a concise usage status analysis when the user is in a hurry. For example, the usage status analysis unit can perform a concise usage status analysis when the user is in a hurry. Furthermore, the usage status analysis unit can perform an interesting usage status analysis when the user is excited. For example, the usage status analysis unit can perform an interesting usage status analysis when the user is excited. As a result, the usage status analysis unit can perform a more appropriate analysis by adjusting the usage status analysis method based on the user's emotions.

[0161] The usage analysis unit can perform a comparative analysis with past usage data in the analysis. For example, the usage analysis unit can compare past usage data with current data and analyze changes in trends. For example, the usage analysis unit can compare past usage data with current data and analyze changes in trends. The usage analysis unit can also compare past usage data with current data and evaluate changes in demand. For example, the usage analysis unit can compare past usage data with current data and evaluate changes in demand. Furthermore, the usage analysis unit can compare past customer feedback with current feedback and identify areas for improvement in the service. For example, the usage analysis unit can compare past customer feedback with current feedback and identify areas for improvement in the service. In this way, the usage analysis unit can grasp changes in trends by performing a comparative analysis with past usage data.

[0162] The usage status analysis unit can perform an analysis that is focused on a specific target demographic. For example, the usage status analysis unit can perform a usage status analysis targeting young people and evaluate services that meet their needs. For example, the usage status analysis unit can perform a usage status analysis targeting young people and evaluate services that meet their needs. The usage status analysis unit can also perform a usage status analysis targeting elderly people and evaluate services that are suitable for them. For example, the usage status analysis unit can perform a usage status analysis targeting elderly people and evaluate services that are suitable for them. Furthermore, the usage status analysis unit can perform a usage status analysis targeting users living in a specific area and evaluate services that meet needs that are specific to the area. For example, the usage status analysis unit can perform a usage status analysis targeting users living in a specific area and evaluate services that meet needs that are specific to the area. As a result, the usage status analysis unit can perform an analysis that is focused on a specific target demographic, thereby enabling more accurate analysis.

[0163] The usage status analysis unit can estimate the user's emotions and determine the priority of the analysis results of the usage status based on the estimated user's emotions. For example, when the user is excited, the usage status analysis unit prioritizes analyzing positive feedback. For example, when the user is excited, the usage status analysis unit can prioritize analyzing positive feedback. Furthermore, when the user is relaxed, the usage status analysis unit can prioritize analyzing detailed feedback. For example, when the user is relaxed, the usage status analysis unit can prioritize analyzing detailed feedback. Furthermore, when the user is feeling stressed, the usage status analysis unit can prioritize analyzing negative feedback. For example, when the user is feeling stressed, the usage status analysis unit can prioritize analyzing negative feedback. In this way, the usage status analysis unit can prioritize analyzing more important data by determining the priority of the analysis results of the usage status based on the user's emotions.

[0164] The usage analysis unit can perform a region-specific analysis by taking into account the geographical location information of the user in the analysis. The usage analysis unit, for example, performs a usage analysis targeting users living in a specific region and evaluates services that meet the region-specific needs. For example, the usage analysis unit can perform a usage analysis targeting users living in a specific region and evaluate services that meet the region-specific needs. The usage analysis unit can also compare usage data for each region and analyze demand for each region. For example, the usage analysis unit can compare usage data for each region and analyze demand for each region. Furthermore, the usage analysis unit can collect feedback on the region-specific service and identify areas for improvement of the service. For example, the usage analysis unit can collect feedback on the region-specific service and identify areas for improvement of the service. This allows the usage analysis unit to perform a region-specific analysis by taking into account the geographical location information of the user in the analysis.

[0165] The usage analysis unit can reflect the user's social media activities in the analysis. The usage analysis unit, for example, performs an analysis of usage based on content shared by the user on social media. For example, the usage analysis unit can perform an analysis of usage based on content shared by the user on social media. The usage analysis unit can also perform an analysis of usage that reflects trends that are trending on social media. For example, the usage analysis unit can perform an analysis of usage based on social media trends. Furthermore, the usage analysis unit can analyze the user's social media activities and perform an analysis of usage that narrows down to a target demographic. For example, the usage analysis unit can perform an analysis of usage that narrows down to a target demographic based on the user's social media activities. In this way, the usage analysis unit can perform an analysis that reflects trends by reflecting the user's social media activities in the analysis.

[0166] The customer satisfaction survey unit can estimate the user's emotions and adjust the content of questions in the customer satisfaction survey based on the estimated user's emotions. For example, when the user is relaxed, the customer satisfaction survey unit can provide a customer satisfaction survey including detailed questions. For example, when the user is relaxed, the customer satisfaction survey unit can provide a customer satisfaction survey including detailed questions. Furthermore, when the user is in a hurry, the customer satisfaction survey unit can provide a concise and short customer satisfaction survey. For example, when the user is in a hurry, the customer satisfaction survey unit can provide a concise and short customer satisfaction survey. Furthermore, when the user is excited, the customer satisfaction survey unit can provide a customer satisfaction survey including interesting questions. For example, when the user is excited, the customer satisfaction survey unit can provide a customer satisfaction survey including interesting questions. In this way, the customer satisfaction survey unit can provide more appropriate questions by adjusting the content of questions in the customer satisfaction survey based on the user's emotions.

[0167] The customer satisfaction survey department can compare the collected data with past customer satisfaction survey results and analyze the results. For example, the customer satisfaction survey department can compare the results of past customer satisfaction surveys with the current results and analyze changes in trends. For example, the customer satisfaction survey department can compare the results of past customer satisfaction surveys with the current results and analyze changes in trends. The customer satisfaction survey department can also compare past customer satisfaction data with current data and evaluate changes in demand. For example, the customer satisfaction survey department can compare past customer satisfaction data with current data and evaluate changes in demand. Furthermore, the customer satisfaction survey department can compare past customer feedback with current feedback and identify areas for improvement in services. For example, the customer satisfaction survey department can compare past customer feedback with current feedback and identify areas for improvement in services. In this way, the customer satisfaction survey department can grasp changes in trends by performing a comparison and analysis with past customer satisfaction survey results.

[0168] The customer satisfaction survey unit can conduct a region-specific customer satisfaction survey by taking into account the geographical location information of users in the collected data. The customer satisfaction survey unit, for example, conducts a customer satisfaction survey targeting users living in a specific region to understand region-specific needs. For example, the customer satisfaction survey unit can conduct a customer satisfaction survey targeting users living in a specific region to understand region-specific needs. The customer satisfaction survey unit can also compare the customer satisfaction survey results for each region to analyze demand for each region. For example, the customer satisfaction survey unit can compare the customer satisfaction survey results for each region to analyze demand for each region. Furthermore, the customer satisfaction survey unit can collect feedback on region-specific services to identify areas for improvement of the services. For example, the customer satisfaction survey unit can collect feedback on region-specific services to identify areas for improvement of the services. In this way, the customer satisfaction survey unit can conduct a region-specific customer satisfaction survey by taking into account the geographical location information of users in the collected data.

[0169] The customer satisfaction survey unit can estimate the user's emotions and prioritize the customer satisfaction survey results based on the estimated user's emotions. For example, if the user is excited, the customer satisfaction survey unit can prioritize analyzing positive feedback. For example, if the user is excited, the customer satisfaction survey unit can prioritize analyzing positive feedback. Furthermore, if the user is relaxed, the customer satisfaction survey unit can prioritize analyzing detailed feedback. For example, if the user is relaxed, the customer satisfaction survey unit can prioritize analyzing detailed feedback. Furthermore, if the user is feeling stressed, the customer satisfaction survey unit can prioritize analyzing negative feedback. For example, if the user is feeling stressed, the customer satisfaction survey unit can prioritize analyzing negative feedback. In this way, the customer satisfaction survey unit can prioritize analyzing more important data by prioritizing the customer satisfaction survey results based on the user's emotions.

[0170] The customer satisfaction survey unit can reflect the user's social media activities in the data it collects. The customer satisfaction survey unit, for example, can reflect the content of the questions in the customer satisfaction survey based on the content shared by the user on social media. For example, the customer satisfaction survey unit can reflect the content of the questions in the customer satisfaction survey based on the content shared by the user on social media. The customer satisfaction survey unit can also investigate trends that are trending on social media and reflect the results in the questions in the customer satisfaction survey. For example, the customer satisfaction survey unit can reflect the results in the questions in the customer satisfaction survey based on social media trends. Furthermore, the customer satisfaction survey unit can analyze the user's social media activities and conduct a customer satisfaction survey with a narrower target demographic. For example, the customer satisfaction survey unit can conduct a customer satisfaction survey with a narrower target demographic based on the user's social media activities. In this way, the customer satisfaction survey unit can conduct a customer satisfaction survey that reflects trends by reflecting the user's social media activities in the data it collects.

[0171] The customer satisfaction survey unit can reflect the results of past customer satisfaction surveys of the user in the collected data. For example, the customer satisfaction survey unit can provide a customer satisfaction survey including related questions based on customer satisfaction survey results previously answered by the user. For example, the customer satisfaction survey unit can provide a customer satisfaction survey including related questions based on customer satisfaction survey results previously answered by the user. The customer satisfaction survey unit can also compare the results of past customer satisfaction surveys with the current results and analyze changes in trends. For example, the customer satisfaction survey unit can compare the results of past customer satisfaction surveys with the current results and analyze changes in trends. Furthermore, the customer satisfaction survey unit can adjust the content of the questions in the customer satisfaction survey while referring to past customer satisfaction data. For example, the customer satisfaction survey unit can adjust the content of the questions in the customer satisfaction survey based on past customer satisfaction data. In this way, the customer satisfaction survey unit can provide more appropriate questions by reflecting the results of past customer satisfaction surveys of the user in the collected data. === Hard Collateral 1-1 === Each of the above-mentioned elements, including the proposal unit, research unit, commercialization unit, evaluation unit, data collection unit, questionnaire unit, market research unit, system development unit, campaign unit, usage analysis unit, customer satisfaction survey unit, and data collection unit, is implemented, for example, by at least one of the smart device 14 and the data processing device 12. For example, the proposal unit is implemented by the control unit 46A of the smart device 14 and proposes service ideas using a generative AI. The research unit is implemented by the specific processing unit 290 of the data processing device 12 and investigates the demand for the proposed ideas. The commercialization unit is implemented by the specific processing unit 290 of the data processing device 12 and commercializes ideas whose demand has been confirmed. The evaluation unit is implemented by the specific processing unit 290 of the data processing device 12 and evaluates the effectiveness of the commercialized services. The data collection unit is implemented by the control unit 46A of the smart device 14 and collects past success stories, failure stories, and customer feedback. The questionnaire unit is implemented by the control unit 46A of the smart device 14 and collects customer opinions. The market research unit is realized by the specific processing unit 290 of the data processing device 12 and conducts small-scale test marketing. The system development unit is realized by the specific processing unit 290 of the data processing device 12 and develops systems for introducing new cashback services. The campaign unit is realized by the control unit 46A of the smart device 14 and implements campaigns specialized for specific time periods or regions. The usage analysis unit is realized by the specific processing unit 290 of the data processing device 12 and investigates the frequency of service use and customer satisfaction. The customer satisfaction survey unit is realized by the specific processing unit 290 of the data processing device 12 and analyzes customer satisfaction and word-of-mouth. The data collection unit is realized by the control unit 46A of the smart device 14 and adjusts the timing of data collection based on user sentiment. === Hard Collateral 1-2 === Each of the above-described elements, including the proposal unit, research unit, commercialization unit, evaluation unit, data collection unit, questionnaire unit, market research unit, system development unit, campaign unit, usage analysis unit, customer satisfaction survey unit, and data collection unit, is implemented, for example, by at least one of the smart glasses 214 and the data processing device 12. For example, the proposal unit is implemented by the control unit 46A of the smart glasses 214 and proposes service ideas using a generative AI. The research unit is implemented by the specific processing unit 290 of the data processing device 12 and investigates the demand for the proposed ideas. The commercialization unit is implemented by the specific processing unit 290 of the data processing device 12 and commercializes ideas whose demand has been confirmed. The evaluation unit is implemented by the specific processing unit 290 of the data processing device 12 and evaluates the effectiveness of the commercialized services. The data collection unit is implemented by the control unit 46A of the smart glasses 214 and collects past success stories, failure stories, and customer feedback. The questionnaire unit is implemented by the control unit 46A of the smart glasses 214 and collects customer opinions. The market research unit is realized by the specific processing unit 290 of the data processing device 12 and conducts small-scale test marketing. The system development unit is realized by the specific processing unit 290 of the data processing device 12 and develops a system for introducing a new cashback service. The campaign unit is realized by the control unit 46A of the smart glasses 214 and implements campaigns specialized for specific time periods or regions. The usage analysis unit is realized by the specific processing unit 290 of the data processing device 12 and investigates the frequency of service use and customer satisfaction. The customer satisfaction survey unit is realized by the specific processing unit 290 of the data processing device 12 and analyzes customer satisfaction and word-of-mouth. The data collection unit is realized by the control unit 46A of the smart glasses 214 and adjusts the timing of data collection based on user emotions. === Hard Collateral 1-3 === Each of the above-described elements, including the proposal unit, research unit, commercialization unit, evaluation unit, data collection unit, questionnaire unit, market research unit, system development unit, campaign unit, usage analysis unit, customer satisfaction survey unit, and data collection unit, is implemented, for example, by at least one of the headset type terminal 314 and the data processing device 12. For example, the proposal unit is implemented by the control unit 46A of the headset type terminal 314 and proposes service ideas using a generative AI. The research unit is implemented by the specific processing unit 290 of the data processing device 12 and investigates the demand for the proposed ideas. The commercialization unit is implemented by the specific processing unit 290 of the data processing device 12 and commercializes ideas whose demand has been confirmed. The evaluation unit is implemented by the specific processing unit 290 of the data processing device 12 and evaluates the effectiveness of the commercialized services. The data collection unit is implemented by the control unit 46A of the headset type terminal 314 and collects past success stories, failure stories, and customer feedback. The questionnaire unit is implemented by the control unit 46A of the headset type terminal 314 and collects customer opinions. The market research unit is realized by the specific processing unit 290 of the data processing device 12 and conducts small-scale test marketing. The system development unit is realized by the specific processing unit 290 of the data processing device 12 and develops systems for introducing new cashback services. The campaign unit is realized by the control unit 46A of the headset type terminal 314 and implements campaigns specialized for specific time periods or regions. The usage analysis unit is realized by the specific processing unit 290 of the data processing device 12 and investigates the frequency of service use and customer satisfaction. The customer satisfaction survey unit is realized by the specific processing unit 290 of the data processing device 12 and analyzes customer satisfaction and word-of-mouth. The data collection unit is realized by the control unit 46A of the headset type terminal 314 and adjusts the timing of data collection based on user sentiment. === Hard Collateral 1-4 === Each of the above-described elements, including the proposal unit, research unit, commercialization unit, evaluation unit, data collection unit, questionnaire unit, market research unit, system development unit, campaign unit, usage analysis unit, customer satisfaction survey unit, and data collection unit, is implemented, for example, by at least one of the robot 414 and the data processing device 12. For example, the proposal unit is implemented by the control unit 46A of the robot 414 and proposes service ideas using a generative AI. The research unit is implemented by the specific processing unit 290 of the data processing device 12 and investigates the demand for the proposed ideas. The commercialization unit is implemented by the specific processing unit 290 of the data processing device 12 and commercializes ideas whose demand has been confirmed. The evaluation unit is implemented by the specific processing unit 290 of the data processing device 12 and evaluates the effectiveness of the commercialized services. The data collection unit is implemented by the control unit 46A of the robot 414 and collects past success stories, failure stories, and customer feedback. The questionnaire unit is implemented by the control unit 46A of the robot 414 and collects customer opinions. The market research unit is realized by the specific processing unit 290 of the data processing device 12 and conducts small-scale test marketing. The system development unit is realized by the specific processing unit 290 of the data processing device 12 and develops systems for introducing new cashback services. The campaign unit is realized by the control unit 46A of the robot 414 and implements campaigns specialized for specific time periods or regions. The usage analysis unit is realized by the specific processing unit 290 of the data processing device 12 and investigates the frequency of service use and customer satisfaction. The customer satisfaction survey unit is realized by the specific processing unit 290 of the data processing device 12 and analyzes customer satisfaction and word-of-mouth. The data collection unit is realized by the control unit 46A of the robot 414 and adjusts the timing of data collection based on user sentiment.

[0172] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0173] The suggestion unit can also analyze the user's purchase history and generate individually customized service ideas. For example, the suggestion unit can suggest new related service ideas based on products or services the user has purchased in the past. The suggestion unit can also suggest cashback services that are specialized for use at specific stores based on the user's purchase history. Furthermore, the suggestion unit can analyze the user's purchase history and generate service ideas related to specific seasons or events. This allows the suggestion unit to generate more personalized service ideas by utilizing the user's purchase history.

[0174] The suggestion unit can also estimate the user's emotions and adjust the content of service ideas based on the estimated user's emotions. For example, if the user is excited, the suggestion unit can suggest bolder and more innovative service ideas. Also, if the user is relaxed, the suggestion unit can suggest service ideas that will help the user to relax more. Furthermore, if the user is feeling stressed, the suggestion unit can suggest service ideas to reduce stress. In this way, the suggestion unit can suggest more appropriate service ideas by adjusting the content of the service ideas based on the user's emotions.

[0175] The research department can also conduct region-specific demand surveys by taking into account the geographical location information of users. For example, the research department can conduct a survey of users living in a specific region to understand the needs specific to that region. The research department can also conduct market research by region to evaluate demand by region. Furthermore, the research department can collect feedback on region-specific services and identify areas for improvement of the services. In this way, the research department can conduct region-specific demand surveys by taking into account the geographical location information of users.

[0176] The survey unit can also estimate the user's emotions and adjust the content of the survey questions based on the estimated user's emotions. For example, if the user is relaxed, the survey unit can provide a survey including detailed questions. If the user is in a hurry, the survey unit can also provide a concise and short survey. Furthermore, if the user is excited, the survey unit can also provide a survey including interesting questions. In this way, the survey unit can provide more appropriate questions by adjusting the content of the survey questions based on the user's emotions.

[0177] The commercialization department can also design and develop services based on user feedback. For example, the commercialization department can improve the design of a service based on feedback provided by users. The commercialization department can also develop and test prototypes that reflect user opinions. Furthermore, the commercialization department can add or remove features from a service based on user feedback. In this way, the commercialization department can develop products that better meet user needs by incorporating user feedback.

[0178] The commercialization department can also estimate the user's emotions and adjust the commercialization process based on the estimated user's emotions. For example, if the user is excited, the commercialization department can quickly proceed with the commercialization process. Alternatively, if the user is relaxed, the commercialization department can proceed with the commercialization process while reflecting detailed feedback. Furthermore, if the user is stressed, the commercialization department can proceed with a simple and easy-to-execute commercialization process. In this way, the commercialization department can achieve more appropriate commercialization by adjusting the commercialization process based on the user's emotions.

[0179] The evaluation unit can also perform region-specific effectiveness evaluation by taking into account the user's geographical location information. For example, the evaluation unit can perform an effectiveness evaluation targeting users living in a specific region and evaluate services that meet the needs specific to that region. The evaluation unit can also compare the evaluation results for each region and analyze the demand for each region. Furthermore, the evaluation unit can collect feedback on the region-specific service and identify areas for improvement of the service. In this way, the evaluation unit can perform region-specific effectiveness evaluation by taking into account the user's geographical location information.

[0180] The evaluation unit can also estimate the user's emotions and adjust the evaluation criteria based on the estimated user's emotions. For example, if the user is excited, the evaluation unit can set evaluation criteria that emphasize positive feedback. Also, if the user is relaxed, the evaluation unit can set evaluation criteria that emphasize detailed feedback. Furthermore, if the user is stressed, the evaluation unit can set evaluation criteria that emphasize negative feedback. In this way, the evaluation unit can perform a more appropriate evaluation by adjusting the evaluation criteria based on the user's emotions.

[0181] The data collection unit can also analyze users' social media activities and collect data that reflects trends. For example, the data collection unit can collect related data based on content shared by users on social media. The data collection unit can also collect data that reflects trends that are currently trending on social media. Furthermore, the data collection unit can analyze users' social media activities and collect data that narrows down to a specific target demographic. In this way, the data collection unit can collect data that reflects trends by reflecting users' social media activities.

[0182] The data collection unit can also estimate the user's emotions and adjust the timing of data collection based on the estimated user's emotions. For example, the data collection unit can collect detailed data when the user is relaxed. Also, the data collection unit can collect brief data when the user is in a hurry. Furthermore, the data collection unit can collect interesting data when the user is excited. In this way, the data collection unit can collect data at more appropriate times by adjusting the timing of data collection based on the user's emotions.

[0183] The processing flow of the second embodiment will be briefly explained below.

[0184] Step 1: The proposal unit uses generation AI to propose service ideas. The generation AI analyzes past data and trends to generate new service ideas. For example, it can propose a cashback service tailored to use at a specific store, or a new point system using 2D codes. The generation AI can also analyze past sales data and customer feedback to generate effective service ideas. Step 2: The research department investigates the demand for the idea proposed by the proposal department. Demand research is done through questionnaires and market research. For example, online surveys can be conducted to collect customer opinions. Field research can also be conducted to assess demand in the actual market. Furthermore, existing market data can be analyzed through desk research to assess demand. Step 3: The commercialization department commercializes ideas that have confirmed their potential. In the commercialization process, the specific design and development of the service takes place. For example, this could involve developing a system to introduce a new cashback service or building a points system using 2D codes. Furthermore, the feasibility of the service can be evaluated through the creation of prototypes and test marketing. Step 4: The evaluation department evaluates the effectiveness of the commercialized service. Effectiveness evaluation is performed by analyzing the usage status of the service and customer reactions. For example, it is possible to survey the frequency of service usage and evaluate customer satisfaction. It is also possible to collect customer feedback and identify areas for improvement in the service. Furthermore, it is possible to analyze sales data and evaluate the economic effectiveness of the service.

[0185] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0186] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> Examples of the generative AI include a neural network (NN) and a neural network (NN). The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image (e.g., still image data or video data). The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in one or more data formats of voice data, text data, image data, etc. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specification processing unit 290 performs the above-mentioned specification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and may perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processing of each of the above-mentioned parts is performed by an AI, the processing may be performed in part or entirely by the AI, but is not limited to these examples. The processing performed by an AI including the generative AI may be replaced with rule-based processing, and rule-based processing may be replaced with processing performed by an AI including the generative AI.

[0187] Furthermore, the processing by the data processing system 10 described above is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart device 14, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart device 14. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the smart device 14 or an external device, and the smart device 14 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0188] The correspondence between each part and the device or control part is not limited to the example described above, and various modifications are possible.

[0189] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0190] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0191] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0192] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0193] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0194] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0195] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0196] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0197] 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.

[0198] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0199] In the smart glasses 214, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. The smart glasses 214 also have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0200] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0201] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0202] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt including an instruction, as well as inference data such as audio data indicating speech, text data indicating text, and image data indicating an image (e.g., still image data or video data). The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in one or more data formats, such as audio data, text data, and image data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation models 58 include AIs other than the generation AI. Examples of AIs other than the generation AI include, but are not limited to, linear regression, logistic regression, decision trees, random forests, support vector machines (SVMs), k-means clustering, convolutional neural networks (CNNs), recurrent neural networks (RNNs), generative adversarial networks (GANs), and naive Bayes. These AIs can perform various types of processing, but are not limited to these examples. The AI ​​may also be an AI agent. When the processing of each of the above-described parts is performed by an AI, the processing may be performed in part or entirely by the AI, but is not limited to these examples. Processing performed by an AI, including the generation AI, may be replaced with rule-based processing, and rule-based processing may be replaced with processing performed by an AI, including the generation AI.

[0203] The data processing system 210 according to the second embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 210 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart glasses 214, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart glasses 214. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the smart glasses 214 or an external device, etc., and the smart glasses 214 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0204] The correspondence between each part and the device or control part is not limited to the example described above, and various modifications are possible.

[0205] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0206] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0207] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0208] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0209] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0210] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0211] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0212] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0213] 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.

[0214] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0215] In the headset type terminal 314, the identification process is performed by the processor 46. A identification program 60 is stored in the storage 50. The processor 46 reads the identification program 60 from the storage 50 and executes the read identification program 60 on the RAM 48. The identification process is realized by the processor 46 operating as a control unit 46A in accordance with the identification program 60 executed on the RAM 48. Note that the headset type terminal 314 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the identification processing unit 290 using these models.

[0216] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0217] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0218] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt including an instruction, as well as inference data such as audio data indicating speech, text data indicating text, and image data indicating an image (e.g., still image data or video data). The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in one or more data formats, such as audio data, text data, and image data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation models 58 include AIs other than the generation AI. Examples of AIs other than the generation AI include, but are not limited to, linear regression, logistic regression, decision trees, random forests, support vector machines (SVMs), k-means clustering, convolutional neural networks (CNNs), recurrent neural networks (RNNs), generative adversarial networks (GANs), and naive Bayes. These AIs can perform various types of processing, but are not limited to these examples. The AI ​​may also be an AI agent. When the processing of each of the above-described parts is performed by an AI, the processing may be performed in part or entirely by the AI, but is not limited to these examples. Processing performed by an AI, including the generation AI, may be replaced with rule-based processing, and rule-based processing may be replaced with processing performed by an AI, including the generation AI.

[0219] The data processing system 310 according to the third embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 310 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the headset type terminal 314, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the headset type terminal 314. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the headset type terminal 314 or an external device, etc., and the headset type terminal 314 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0220] The correspondence between each part and the device or control part is not limited to the example described above, and various modifications are possible.

[0221] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0222] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0223] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0224] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[0225] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0226] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS image sensor or a CCD image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0227] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0228] The control 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 emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[0229] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0230] 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.

[0231] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0232] In the robot 414, the processor 46 performs the identification process. The storage 50 stores the identification program 60. The processor 46 reads the identification program 60 from the storage 50 and executes the read identification program 60 on the RAM 48. The identification process is realized by the processor 46 operating as the control unit 46A in accordance with the identification program 60 executed on the RAM 48. The robot 414 also has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can perform the same process as the identification processing unit 290 using these models.

[0233] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0234] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[0235] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt including an instruction, as well as inference data such as audio data indicating speech, text data indicating text, and image data indicating an image (e.g., still image data or video data). The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in one or more data formats, such as audio data, text data, and image data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation models 58 include AIs other than the generation AI. Examples of AIs other than the generation AI include, but are not limited to, linear regression, logistic regression, decision trees, random forests, support vector machines (SVMs), k-means clustering, convolutional neural networks (CNNs), recurrent neural networks (RNNs), generative adversarial networks (GANs), and naive Bayes. These AIs can perform various types of processing, but are not limited to these examples. The AI ​​may also be an AI agent. When the processing of each of the above-described parts is performed by an AI, the processing may be performed in part or entirely by the AI, but is not limited to these examples. Processing performed by an AI, including the generation AI, may be replaced with rule-based processing, and rule-based processing may be replaced with processing performed by an AI, including the generation AI.

[0236] The data processing system 410 according to the fourth embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 410 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the robot 414, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the robot 414. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the robot 414 or an external device, etc., and the robot 414 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0237] The correspondence between each part and the device or control part is not limited to the example described above, and various modifications are possible.

[0238] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0239] FIG. 9 illustrates an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and behaviors arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion encompasses both emotions and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[0240] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[0241] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[0242] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is expressed, and when they approach the ideal, a state of pleasure is expressed. Emotions can also be created for robots, cars, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is expressed, and when they approach the ideal, a state of pleasure is expressed. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on speech emotion recognition and brain physiological signal analysis systems for emotions, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the area called "reaction," where sensation is dominant. The right half of the emotion map lists emotions belonging to the area called "situation," where situational awareness is dominant.

[0243] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[0244] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[0245] In the above embodiment, an example was given in which a specific process is performed by one computer 22, but the technology disclosed herein is not limited to this, and distributed processing of the specific process may be performed by multiple computers including computer 22.

[0246] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[0247] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[0248] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[0249] The hardware resource for executing a specific process can be any of the following types of processors: A processor, for example, is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. A processor also includes a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[0250] The hardware resource that executes the specific process may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific process may be a single processor.

[0251] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[0252] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[0253] In the above example, the first to fourth embodiments have been described separately, but some or all of these embodiments may be combined. The smart device 14, smart glasses 214, headset terminal 314, and robot 414 are merely examples, and they may be combined, or other devices may be used. In the above example, the first and second embodiments have been described separately, but they may be combined.

[0254] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[0255] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[0256] [Explanation of symbols]

[0257] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot

Claims

1. A proposal unit in which the generation AI proposes service ideas; a research department that investigates the demand for the ideas proposed by the proposal department; a commercialization department that commercializes ideas whose demand has been confirmed by the research department; an evaluation unit that evaluates the effectiveness of the service commercialized by the commercialization unit; Equipped with A system characterized by:

2. The proposal unit Analyze past data or trends to generate new service ideas 2. The system of claim 1.

3. The research department Evaluate the demand for proposed ideas through surveys or market research 2. The system of claim 1.

4. The commercialization department Designing or developing specific services and bringing them to market 2. The system of claim 1.

5. The evaluation unit Analyzing service usage and customer reactions to identify areas for improvement 2. The system of claim 1.

6. Collect data such as past success stories, failure stories, and customer feedback. a data collection unit for providing the data to the suggestion unit; 2. The system of claim 1.

7. Collect customer opinions, Further establish a survey section to identify areas for improvement of service ideas 2. The system of claim 1.

8. We actually conducted small-scale test marketing, Further establish a market research department to evaluate the demand for service ideas 2. The system of claim 1.

9. Developing a system to introduce a new cashback service Further system development department 2. The system of claim 1.

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