System

Abstract

An object of a system according to an embodiment is to collectively support planning and execution of a sales strategy in a global market.SOLUTION: A system according to an embodiment includes a market analysis unit, a customer targeting unit, a translation unit, a customer support unit, and a marketing optimization unit. The market analyzer analyzes the market using the generated AI. The customer targeting unit identifies a customer segment based on the market identified by the market analysis unit. The translation unit translates the product description to the customer segment specified by the customer targeting unit. The customer support unit responds to the inquiry from the customer based on the product description translated by the translation unit. The marketing optimization unit optimizes a marketing strategy based on the data collected by the customer support unit.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] Conventional technologies do not adequately provide comprehensive support for the entire process from planning to execution of sales strategies in the global market, and there is room for improvement.

[0005] The system according to the embodiment aims to provide comprehensive support for the entire process from planning to execution of sales strategies in the global market. [Means for solving the problem]

[0006] The system according to the embodiment includes a market analysis unit, a customer targeting unit, a translation unit, a customer support unit, and a marketing optimization unit. The market analysis unit analyzes the market using generative AI. The customer targeting unit identifies a customer segment based on the market identified by the market analysis unit. The translation unit translates product descriptions for the customer segment identified by the customer targeting unit. The customer support unit responds to customer inquiries based on the product descriptions translated by the translation unit. The marketing optimization unit optimizes marketing strategies based on data collected by the customer support unit. [Effects of the Invention]

[0007] The system according to the embodiment can provide comprehensive support for the entire process from planning to execution of sales strategies in the global market. [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 nonvolatile storage devices that store various programs, various parameters, etc. Examples of nonvolatile 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 the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[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 may have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[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) The comprehensive service system for cross-border e-commerce according to an embodiment of the present invention is a system that provides comprehensive support from planning to execution of sales strategies for companies and individuals aiming to sell in the global market. As a result, the comprehensive service system for cross-border e-commerce allows companies and individuals to plan and execute sales strategies efficiently and effectively.

[0029] The comprehensive service system for cross-border e-commerce according to the embodiment includes a market analysis unit, a customer targeting unit, a translation unit, a customer support unit, and a marketing optimization unit. The market analysis unit uses a generation AI to collect and analyze global market data and identify markets suitable for sales. For example, the generation AI analyzes the economic conditions and consumer purchasing trends of each country to determine which markets are most promising. The generation AI receives input from a user prompt containing instructions on what the user wants the generation AI to do, and the generation AI performs market analysis based on the prompt. The customer targeting unit uses the generation AI to analyze consumer data to identify target customer segments. For example, the generation AI identifies the customer segment with the highest purchasing intent based on data such as age, gender, and purchase history. The generation AI receives input from a user prompt containing instructions on what the user wants the generation AI to do, and the generation AI performs customer targeting based on the prompt. The translation unit uses the generation AI to translate product descriptions into multiple languages. For example, it translates Japanese product descriptions into English, Chinese, French, etc. The generation AI receives input from the text of the product description to be translated, and the generation AI performs translation based on that text. The customer support department uses a generation AI to automatically respond to customer inquiries. For example, the generation AI generates appropriate answers to questions about product usage and return procedures. The generation AI receives input from customers, and generates answers based on that input. The marketing optimization department uses the generation AI to analyze advertising data and sales data to optimize marketing strategies. For example, the generation AI analyzes which advertisements are most effective and proposes optimal allocation of advertising budgets. The generation AI receives input from advertising data and sales data, and the generation AI optimizes marketing strategies based on that data. As a result, the comprehensive service system for cross-border e-commerce according to the embodiment can comprehensively support sales strategies in the global market. For example, the generation AI performs market analysis and identifies the most promising markets, allowing sales activities to be focused. Furthermore, customer targeting enables effective marketing to be conducted on customer segments with the highest purchasing intent.Additionally, automating product description translation and customer support can reduce costs and improve customer satisfaction.

[0030] The market analysis department uses generation AI to analyze each country's economic situation and consumer purchasing trends, and can identify the most promising markets. For example, the market analysis department uses generation AI to analyze each country's economic situation and understand consumer purchasing trends. For example, generation AI analyzes economic indicators such as each country's GDP, unemployment rate, and inflation rate to determine which markets are the most promising. In addition, generation AI analyzes data such as consumer purchasing history, purchasing frequency, and purchase amount to identify markets with the highest purchasing intent. This allows sales activities to be focused on the most promising markets.

[0031] The customer targeting department can use the generation AI to analyze at least one of the data items: age, gender, and purchase history, and identify the customer segment with the highest purchasing intent. For example, the generation AI analyzes age data to identify the purchasing intent of a specific age group. For example, the generation AI analyzes purchasing intent for each age group, such as teenagers, people in their 20s, and people in their 30s. The generation AI also analyzes gender data to identify purchasing intent for men, women, and other genders. Furthermore, the generation AI analyzes purchase history data to identify purchasing intent based on data such as past purchased products, purchase frequency, and purchase amount. This enables effective marketing by identifying the customer segment with the highest purchasing intent.

[0032] The translation unit can use the generation AI to translate a Japanese product description into at least one of English, Chinese, and French. In the translation unit, for example, the generation AI translates a Japanese product description into English. For example, the generation AI receives Japanese text as input and outputs English text. The generation AI also translates the Japanese product description into Chinese. For example, the generation AI receives Japanese text as input and outputs Chinese text. The generation AI also translates the Japanese product description into French. For example, the generation AI receives Japanese text as input and outputs French text. This makes it easier to sell in the global market by translating into multiple languages.

[0033] The customer support department can use the generation AI to generate appropriate answers to questions about how to use a product or the return procedure. For example, the customer support department uses the generation AI to generate answers to questions about how to use a product. For example, the generation AI receives text about how to use a product as input and outputs an appropriate answer. The generation AI also generates answers to questions about return procedures. For example, the generation AI receives text about return procedures as input and outputs an appropriate answer. This automates customer support, reducing costs and improving customer satisfaction.

[0034] The marketing optimization department can use the generation AI to analyze advertising data or sales data and propose optimal allocation of the advertising budget. For example, the generation AI analyzes advertising data and proposes optimal allocation of the advertising budget. For example, the generation AI analyzes data such as the number of times an ad is displayed, the number of clicks, and the conversion rate, and allocates the budget to the most effective advertising channel. The generation AI also analyzes sales data and proposes optimal allocation of the advertising budget. For example, the generation AI analyzes data such as sales volume, sales amount, and sales channel, and allocates the budget to the most effective advertising channel. This maximizes marketing effectiveness by proposing optimal allocation of the advertising budget.

[0035] The market analysis department uses generative AI to analyze the cultural background and consumer values ​​of each country, and can identify markets with high cultural adaptability. For example, the market analysis department uses generative AI to analyze the cultural background of each country and understand consumer values ​​and behavioral patterns. For example, generative AI analyzes popular product categories and consumer purchasing motivations in a particular country. Generative AI also analyzes consumer lifestyles and hobbies and preferences to identify markets with high cultural adaptability. For example, generative AI evaluates markets based on consumer lifestyles and values. This allows for the identification of markets with high cultural adaptability, enabling effective development of sales strategies.

[0036] The market analysis department uses generative AI to track market trends in real time and respond quickly to rapidly changing market trends. For example, the market analysis department uses generative AI to collect market trend data in real time and analyze rapidly changing market trends. For example, generative AI tracks trends based on data from social media and news sites. Generative AI also analyzes consumer purchasing behavior and competitor trends in real time and responds quickly to market trends. For example, generative AI adjusts market strategies based on consumer purchasing patterns and information on new products from competitors. This allows for rapid responses by responding quickly to rapidly changing market trends.

[0037] The market analysis department can use generative AI to analyze market data from different industries and discover cross-industry market opportunities. For example, generative AI analyzes market data from different industries and discovers cross-industry market opportunities. For example, generative AI identifies new market opportunities that combine the technology field and the consumer market. Generative AI also analyzes synergies between different industries and creates new business opportunities. For example, generative AI integrates data from different industries and identifies cross-industry market opportunities. This discovers cross-industry market opportunities and creates new business opportunities.

[0038] The market analysis unit can use the generation AI to visualize the market analysis results, allowing the user to intuitively understand. For example, the generation AI visualizes the market analysis results, allowing the user to intuitively understand. For example, the generation AI displays market data in graphs and charts, allowing the user to visually understand. The generation AI also displays the market analysis results as infographics, allowing the user to intuitively understand. For example, the generation AI displays market data as infographics, allowing the user to easily understand. In this way, by visualizing the market analysis results, the user can intuitively understand.

[0039] The customer targeting department can use generation AI to analyze consumers' lifestyles and hobbies and preferences to create more detailed target profiles. For example, the generation AI analyzes consumers' lifestyle data to create detailed target profiles. For example, the generation AI identifies target demographics based on consumers' hobbies and interests. The generation AI also analyzes consumers' lifestyle habits and values ​​to create target profiles. For example, the generation AI identifies target demographics based on consumers' lifestyle data. This allows for the creation of detailed target profiles, enabling more effective marketing.

[0040] The customer targeting department can use generation AI to analyze social media data and perform targeting that takes into account the influence of influencers and communities. For example, the customer targeting department uses generation AI to analyze social media data and perform targeting that takes into account the influence of influencers. For example, generation AI identifies influencers based on the number of followers and engagement rate. Generation AI also analyzes the influence of communities and performs targeting. For example, generation AI identifies the target demographic based on the number of community members and frequency of activity. This enables effective targeting by taking into account the influence of influencers and communities.

[0041] The customer targeting department can use generation AI to analyze consumer data from different regions and cultural spheres and develop a global targeting strategy. For example, the customer targeting department uses generation AI to analyze consumer data from different regions and develop a global targeting strategy. For example, generation AI identifies target demographics based on the purchasing behavior of consumers in each region. In addition, generation AI analyzes consumer data from different cultural spheres and develops a targeting strategy. For example, generation AI identifies target demographics based on the values ​​and behavior patterns of consumers in each cultural sphere. This enables effective marketing by developing a global targeting strategy.

[0042] The customer targeting department can use generation AI to visualize the customer targeting results so that the marketing team can intuitively understand them. For example, the customer targeting department can use generation AI to visualize the customer targeting results so that the marketing team can intuitively understand them. For example, generation AI can display target profiles and segmentation in graphs and charts so that the marketing team can visually understand them. In addition, generation AI can display the targeting results as infographics so that the marketing team can intuitively understand them. For example, generation AI can display target demographic data as infographics so that the marketing team can easily understand them. In this way, by visualizing the customer targeting results, the marketing team can intuitively understand them.

[0043] The translation unit can use the generation AI to not only translate product descriptions, but also to translate products that take cultural nuances and localization into account. For example, when the generation AI translates product descriptions, the translation unit takes cultural nuances into account. For example, the generation AI appropriately translates expressions and phrases in specific cultures. The generation AI also takes localization into account when translating. For example, the generation AI takes into account regional expressions and cultural adaptations when translating. This allows for more appropriate translations by taking cultural nuances and localization into account.

[0044] The translation unit can use the generation AI to automatically proofread the translation results and correct grammatical and expression errors. For example, the generation AI automatically proofreads the translation results and corrects grammatical and expression errors. For example, the generation AI checks the grammar of the translated text and corrects errors. The generation AI also proofreads the expressions in the translated text and corrects them to appropriate expressions. For example, the generation AI corrects grammatical errors based on grammatical rules and selects appropriate vocabulary. This enables high-quality translations by automatically correcting grammatical and expression errors in the translation results.

[0045] The translation department can use generative AI to translate not only product descriptions but also marketing materials and advertising copy into multiple languages. For example, generative AI translates not only product descriptions but also marketing materials and advertising copy into multiple languages. For example, generative AI translates advertising campaign text into multiple languages. Generative AI also translates product catalogs and promotional materials into multiple languages. For example, generative AI translates marketing materials into English, Chinese, French, etc. This allows for a consistent message to be delivered by translating not only product descriptions but also related marketing materials and advertising copy into multiple languages.

[0046] The translation unit can use the generation AI to visualize the translation results so that the user can intuitively understand. The translation unit, for example, uses the generation AI to visualize the translation results so that the user can intuitively understand. For example, the generation AI displays the translated text in a graph or chart so that the user can visually understand. The generation AI also displays the translation results as an infographic so that the user can intuitively understand. For example, the generation AI displays the translated text as an infographic so that the user can easily understand. In this way, by visualizing the translation results, the user can intuitively understand.

[0047] The customer support department can use the generation AI to analyze the customer's past inquiry history and provide personalized support. For example, the generation AI analyzes the customer's past inquiry history and provides personalized support. For example, the generation AI generates an appropriate answer based on the content of the past inquiry. The generation AI also analyzes customer feedback and provides personalized support. For example, the generation AI adjusts the support content based on customer feedback. In this way, personalized support can be provided by analyzing the customer's past inquiry history.

[0048] Customer support departments can use generative AI to integrate customer support across different channels (email, chat, telephone) and provide a consistent support experience. For example, generative AI integrates support content across email, chat, and telephone. Generative AI also centrally manages customer support across different channels and provides a unified support experience. For example, generative AI integrates data from different channels and provides consistent support to customers. This allows a consistent support experience to be provided by integrating customer support across different channels.

[0049] The customer support department can use generative AI to visualize the results of customer support so that the support team can intuitively understand it. For example, the customer support department can use generative AI to visualize the results of customer support so that the support team can intuitively understand it. For example, the generative AI can display the results of support in graphs and charts so that the support team can visually understand it. The generative AI can also display the results of customer support as infographics so that the support team can intuitively understand it. For example, the generative AI can display support data as infographics so that the support team can easily understand it. In this way, by visualizing the results of customer support, the support team can intuitively understand it.

[0050] The marketing optimization department uses generative AI to analyze the effectiveness of advertising campaigns in real time and can instantly adjust strategies. For example, generative AI analyzes the effectiveness of advertising campaigns in real time and can instantly adjust strategies. For example, generative AI adjusts advertising content based on ad click rates and conversion rates. Generative AI also analyzes advertising campaign data in real time and proposes effective strategies. For example, generative AI adjusts advertising budget allocation based on advertising data. This allows for instant adjustments to strategies by analyzing the effectiveness of advertising campaigns in real time.

[0051] The marketing optimization department can use the generation AI to analyze consumer purchasing behavior and identify the optimal marketing channel. For example, the generation AI analyzes consumer purchasing behavior data and identifies the optimal marketing channel. For example, the generation AI adjusts the marketing strategy based on the channel most used by consumers. The generation AI also analyzes consumer purchasing patterns and identifies effective marketing channels. For example, the generation AI selects the optimal channel based on purchasing data. In this way, the optimal marketing channel can be identified by analyzing consumer purchasing behavior.

[0052] The marketing optimization department can use generative AI to integrate different marketing channels (SNS, email, advertising) and provide a consistent marketing strategy. For example, generative AI integrates different marketing channels and provides a consistent marketing strategy. For example, generative AI integrates data from SNS, email, and advertising to create a strategy. Generative AI also centrally manages data from different channels and provides a unified marketing strategy. For example, generative AI provides a consistent message based on data from different channels. This makes it possible to provide a consistent marketing strategy by integrating different marketing channels.

[0053] The marketing optimization department can use the generative AI to visualize the results of the marketing strategy so that the marketing team can intuitively understand it. For example, the marketing optimization department uses the generative AI to visualize the results of the marketing strategy so that the marketing team can intuitively understand it. For example, the generative AI displays the results of the strategy in graphs and charts so that the marketing team can visually understand it. The generative AI also displays the results of the marketing strategy as infographics so that the marketing team can intuitively understand it. For example, the generative AI displays the results of the strategy as infographics so that the marketing team can easily understand it. In this way, by visualizing the results of the marketing strategy, the marketing team can intuitively understand it.

[0054] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0055] The comprehensive service system for cross-border e-commerce can also be equipped with a recommendation unit that makes recommendations based on a user's purchasing history. The recommendation unit analyzes the user's past purchasing history and suggests highly relevant products. For example, it can suggest products similar to products the user has previously purchased. The recommendation unit can also analyze the user's purchasing patterns and suggest products that are in line with the season or trends. Furthermore, the recommendation unit can suggest the next product that a user who has purchased the same product should purchase based on the purchasing history of other users. This can improve the user's purchasing experience and increase sales.

[0056] The Market Analysis Department can also use Generative AI to analyze each country's legal regulations and tax systems to identify markets with low legal risk. For example, Generative AI can analyze each country's import regulations and tariff rates to identify markets with low legal risk. Generative AI can also analyze each country's consumer protection laws and data protection laws to identify markets with low legal risk. Furthermore, Generative AI can analyze each country's business environment and political stability to identify markets with low legal risk. This allows companies to minimize their risk by identifying markets with low legal risk.

[0057] The customer targeting department can use generation AI to analyze consumers' life events (marriage, childbirth, moving, etc.) and target them according to those life events. For example, generation AI can analyze consumers' social media data to identify life events such as marriage and childbirth. Generation AI can also analyze consumers' purchase history to suggest products related to moving or starting a new life. Furthermore, generation AI can generate marketing messages according to consumers' life events and perform effective targeting. This enables effective marketing by targeting consumers according to their life events.

[0058] The translation unit uses generation AI to not only translate product descriptions but also speech translation. For example, generation AI can translate Japanese product descriptions into English, Chinese, French, etc. by voice. Generation AI can also accept voice input and translate into multiple languages ​​in real time. Furthermore, generation AI can display the results of speech translation as text so that users can visually confirm it. This makes speech translation suitable for users who have difficulty reading text, such as the visually impaired and elderly.

[0059] The customer support department can use generation AI to analyze a customer's past inquiry history and provide personalized support. For example, generation AI generates appropriate answers based on the content of past inquiries. Generation AI can also analyze customer feedback and provide personalized support. Furthermore, generation AI can analyze a customer's purchase history and provide related support information. This makes it possible to provide personalized support by analyzing a customer's past inquiry history.

[0060] The processing flow of the first embodiment will be briefly explained below.

[0061] Step 1: The market analysis department uses the generation AI to collect and analyze global market data and identify markets suitable for sales. For example, the generation AI analyzes each country's economic situation and consumer purchasing trends to determine which markets are most promising. The generation AI receives input from the user in the form of prompts containing instructions on what the user wants the generation AI to do, and the generation AI performs market analysis based on those prompts. Step 2: The customer targeting department analyzes consumer data to identify target customer segments using the generation AI. For example, the generation AI identifies the customer segments with the highest purchasing intent based on data such as age, gender, and purchase history. The input to the generation AI is a prompt containing instructions on what the user wants the generation AI to do, and the generation AI performs customer targeting based on that prompt. Step 3: The translation department uses the generation AI to translate the product description into multiple languages. For example, a Japanese product description can be translated into English, Chinese, French, etc. The input to the generation AI is the text of the product description to be translated, and the generation AI translates based on that text. Step 4: The customer support department uses the generation AI to automatically respond to customer inquiries. For example, the generation AI generates appropriate answers to questions about how to use a product or the return procedure. The input to the generation AI is the customer's inquiry, and the generation AI generates an answer based on that content. Step 5: The Marketing Optimization Department analyzes advertising and sales data to optimize the marketing strategy using Generative AI. For example, Generative AI analyzes which ads are most effective and suggests optimal allocation of advertising budgets. The inputs to Generative AI are advertising and sales data, and Generative AI optimizes the marketing strategy based on that data.

[0062] (Example 2) The comprehensive service system for cross-border e-commerce according to an embodiment of the present invention is a system that provides comprehensive support from planning to execution of sales strategies for companies and individuals aiming to sell in the global market. As a result, the comprehensive service system for cross-border e-commerce allows companies and individuals to plan and execute sales strategies efficiently and effectively.

[0063] The comprehensive service system for cross-border e-commerce according to the embodiment includes a market analysis unit, a customer targeting unit, a translation unit, a customer support unit, and a marketing optimization unit. The market analysis unit uses a generation AI to collect and analyze global market data and identify markets suitable for sales. For example, the generation AI analyzes the economic conditions and consumer purchasing trends of each country to determine which markets are most promising. The generation AI receives input from a user prompt containing instructions on what the user wants the generation AI to do, and the generation AI performs market analysis based on the prompt. The customer targeting unit uses the generation AI to analyze consumer data to identify target customer segments. For example, the generation AI identifies the customer segment with the highest purchasing intent based on data such as age, gender, and purchase history. The generation AI receives input from a user prompt containing instructions on what the user wants the generation AI to do, and the generation AI performs customer targeting based on the prompt. The translation unit uses the generation AI to translate product descriptions into multiple languages. For example, it translates Japanese product descriptions into English, Chinese, French, etc. The generation AI receives input from the text of the product description to be translated, and the generation AI performs translation based on that text. The customer support department uses a generation AI to automatically respond to customer inquiries. For example, the generation AI generates appropriate answers to questions about product usage and return procedures. The generation AI receives input from customers, and generates answers based on that input. The marketing optimization department uses the generation AI to analyze advertising data and sales data to optimize marketing strategies. For example, the generation AI analyzes which advertisements are most effective and proposes optimal allocation of advertising budgets. The generation AI receives input from advertising data and sales data, and the generation AI optimizes marketing strategies based on that data. As a result, the comprehensive service system for cross-border e-commerce according to the embodiment can comprehensively support sales strategies in the global market. For example, the generation AI performs market analysis and identifies the most promising markets, allowing sales activities to be focused. Furthermore, customer targeting enables effective marketing to be conducted on customer segments with the highest purchasing intent.Additionally, automating product description translation and customer support can reduce costs and improve customer satisfaction.

[0064] The market analysis department uses generation AI to analyze each country's economic situation and consumer purchasing trends, and can identify the most promising markets. For example, the market analysis department uses generation AI to analyze each country's economic situation and understand consumer purchasing trends. For example, generation AI analyzes economic indicators such as each country's GDP, unemployment rate, and inflation rate to determine which markets are the most promising. In addition, generation AI analyzes data such as consumer purchasing history, purchasing frequency, and purchase amount to identify markets with the highest purchasing intent. This allows sales activities to be focused on the most promising markets.

[0065] The customer targeting department can use the generation AI to analyze at least one of the data items: age, gender, and purchase history, and identify the customer segment with the highest purchasing intent. For example, the generation AI analyzes age data to identify the purchasing intent of a specific age group. For example, the generation AI analyzes purchasing intent for each age group, such as teenagers, people in their 20s, and people in their 30s. The generation AI also analyzes gender data to identify purchasing intent for men, women, and other genders. Furthermore, the generation AI analyzes purchase history data to identify purchasing intent based on data such as past purchased products, purchase frequency, and purchase amount. This enables effective marketing by identifying the customer segment with the highest purchasing intent.

[0066] The translation unit can use the generation AI to translate a Japanese product description into at least one of English, Chinese, and French. In the translation unit, for example, the generation AI translates a Japanese product description into English. For example, the generation AI receives Japanese text as input and outputs English text. The generation AI also translates the Japanese product description into Chinese. For example, the generation AI receives Japanese text as input and outputs Chinese text. The generation AI also translates the Japanese product description into French. For example, the generation AI receives Japanese text as input and outputs French text. This makes it easier to sell in the global market by translating into multiple languages.

[0067] The customer support department can use the generation AI to generate appropriate answers to questions about how to use a product or the return procedure. For example, the customer support department uses the generation AI to generate answers to questions about how to use a product. For example, the generation AI receives text about how to use a product as input and outputs an appropriate answer. The generation AI also generates answers to questions about return procedures. For example, the generation AI receives text about return procedures as input and outputs an appropriate answer. This automates customer support, reducing costs and improving customer satisfaction.

[0068] The marketing optimization department can use the generation AI to analyze advertising data or sales data and propose optimal allocation of the advertising budget. For example, the generation AI analyzes advertising data and proposes optimal allocation of the advertising budget. For example, the generation AI analyzes data such as the number of times an ad is displayed, the number of clicks, and the conversion rate, and allocates the budget to the most effective advertising channel. The generation AI also analyzes sales data and proposes optimal allocation of the advertising budget. For example, the generation AI analyzes data such as sales volume, sales amount, and sales channel, and allocates the budget to the most effective advertising channel. This maximizes marketing effectiveness by proposing optimal allocation of the advertising budget.

[0069] The market analysis department uses generative AI to analyze the cultural background and consumer values ​​of each country, and can identify markets with high cultural adaptability. For example, the market analysis department uses generative AI to analyze the cultural background of each country and understand consumer values ​​and behavioral patterns. For example, generative AI analyzes popular product categories and consumer purchasing motivations in a particular country. Generative AI also analyzes consumer lifestyles and hobbies and preferences to identify markets with high cultural adaptability. For example, generative AI evaluates markets based on consumer lifestyles and values. This allows for the identification of markets with high cultural adaptability, enabling effective development of sales strategies.

[0070] The market analysis department uses generative AI to track market trends in real time and respond quickly to rapidly changing market trends. For example, the market analysis department uses generative AI to collect market trend data in real time and analyze rapidly changing market trends. For example, generative AI tracks trends based on data from social media and news sites. Generative AI also analyzes consumer purchasing behavior and competitor trends in real time and responds quickly to market trends. For example, generative AI adjusts market strategies based on consumer purchasing patterns and information on new products from competitors. This allows for rapid responses by responding quickly to rapidly changing market trends.

[0071] The market analysis unit can use the generative AI to analyze consumer emotional responses using an emotion estimation function and identify emotionally positive markets. For example, the market analysis unit uses the generative AI to analyze consumer emotional responses and identify emotionally positive markets. For example, the generative AI collects emotion data from social media posts and reviews and identifies markets with many positive responses. The generative AI also evaluates markets based on consumer emotion scores and identifies emotionally positive markets. For example, the generative AI analyzes consumer emotion scores and identifies markets with many positive emotions. This allows for effective marketing by identifying emotionally positive markets.

[0072] The market analysis department can use generative AI to analyze market data from different industries and discover cross-industry market opportunities. For example, generative AI analyzes market data from different industries and discovers cross-industry market opportunities. For example, generative AI identifies new market opportunities that combine the technology field and the consumer market. Generative AI also analyzes synergies between different industries and creates new business opportunities. For example, generative AI integrates data from different industries and identifies cross-industry market opportunities. This discovers cross-industry market opportunities and creates new business opportunities.

[0073] The market analysis unit can use the generation AI to visualize the market analysis results, allowing the user to intuitively understand. For example, the generation AI visualizes the market analysis results, allowing the user to intuitively understand. For example, the generation AI displays market data in graphs and charts, allowing the user to visually understand. The generation AI also displays the market analysis results as infographics, allowing the user to intuitively understand. For example, the generation AI displays market data as infographics, allowing the user to easily understand. In this way, by visualizing the market analysis results, the user can intuitively understand.

[0074] The market analysis unit can use the generative AI and emotion estimation function to compare the emotional empathy between different markets and identify the market that is most likely to empathize. For example, the generative AI uses the emotion estimation function to compare the emotional empathy between different markets and identify the market that is most likely to empathize. For example, the generative AI evaluates markets based on consumer emotion data and identifies markets that are highly empathetic. The generative AI also compares emotional responses between different markets and identifies markets that are most likely to empathize. For example, the generative AI collects emotion data from social media posts and reviews and identifies markets that are highly empathetic. This allows for effective marketing by identifying markets that are most likely to empathize.

[0075] The customer targeting department can use generation AI to analyze consumers' lifestyles and hobbies and preferences to create more detailed target profiles. For example, the generation AI analyzes consumers' lifestyle data to create detailed target profiles. For example, the generation AI identifies target demographics based on consumers' hobbies and interests. The generation AI also analyzes consumers' lifestyle habits and values ​​to create target profiles. For example, the generation AI identifies target demographics based on consumers' lifestyle data. This allows for the creation of detailed target profiles, enabling more effective marketing.

[0076] The customer targeting department can use generation AI to analyze social media data and perform targeting that takes into account the influence of influencers and communities. For example, the customer targeting department uses generation AI to analyze social media data and perform targeting that takes into account the influence of influencers. For example, generation AI identifies influencers based on the number of followers and engagement rate. Generation AI also analyzes the influence of communities and performs targeting. For example, generation AI identifies the target demographic based on the number of community members and frequency of activity. This enables effective targeting by taking into account the influence of influencers and communities.

[0077] The customer targeting department can use the generation AI to analyze the emotional state of consumers using an emotion estimation function, and identify emotionally positive customer segments. For example, the generation AI uses the emotion estimation function to analyze the emotional state of consumers, and identify emotionally positive customer segments. For example, the generation AI identifies customer segments with many positive emotional responses based on consumer emotion data. The generation AI also analyzes consumer emotion scores, and identifies emotionally positive customer segments. For example, the generation AI identifies target segments based on consumer emotion scores. This enables effective marketing by identifying emotionally positive customer segments.

[0078] The customer targeting department can use generation AI to analyze consumer data from different regions and cultural spheres and develop a global targeting strategy. For example, the customer targeting department uses generation AI to analyze consumer data from different regions and develop a global targeting strategy. For example, generation AI identifies target demographics based on the purchasing behavior of consumers in each region. In addition, generation AI analyzes consumer data from different cultural spheres and develops a targeting strategy. For example, generation AI identifies target demographics based on the values ​​and behavior patterns of consumers in each cultural sphere. This enables effective marketing by developing a global targeting strategy.

[0079] The customer targeting department can use generation AI to visualize the customer targeting results so that the marketing team can intuitively understand them. For example, the customer targeting department can use generation AI to visualize the customer targeting results so that the marketing team can intuitively understand them. For example, generation AI can display target profiles and segmentation in graphs and charts so that the marketing team can visually understand them. In addition, generation AI can display the targeting results as infographics so that the marketing team can intuitively understand them. For example, generation AI can display target demographic data as infographics so that the marketing team can easily understand them. In this way, by visualizing the customer targeting results, the marketing team can intuitively understand them.

[0080] The customer targeting department can use the generation AI and emotion estimation function to monitor the emotional responses of the target customer segment in real time and continuously optimize the targeting strategy. For example, the generation AI can use the emotion estimation function to monitor the emotional responses of the target customer segment in real time and continuously optimize the targeting strategy. For example, the generation AI can adjust the marketing strategy based on the emotion data. The generation AI can also analyze the emotion scores of the target customer segment in real time and optimize the targeting strategy. For example, the generation AI can adjust the marketing message based on the emotion score. In this way, the targeting strategy can be continuously optimized by monitoring the emotional responses of the target customer segment in real time.

[0081] The translation unit can use the generation AI to not only translate product descriptions, but also to translate products that take cultural nuances and localization into account. For example, when the generation AI translates product descriptions, the translation unit takes cultural nuances into account. For example, the generation AI appropriately translates expressions and phrases in specific cultures. The generation AI also takes localization into account when translating. For example, the generation AI takes into account regional expressions and cultural adaptations when translating. This allows for more appropriate translations by taking cultural nuances and localization into account.

[0082] The translation unit can use the generation AI to automatically proofread the translation results and correct grammatical and expression errors. For example, the generation AI automatically proofreads the translation results and corrects grammatical and expression errors. For example, the generation AI checks the grammar of the translated text and corrects errors. The generation AI also proofreads the expressions in the translated text and corrects them to appropriate expressions. For example, the generation AI corrects grammatical errors based on grammatical rules and selects appropriate vocabulary. This enables high-quality translations by automatically correcting grammatical and expression errors in the translation results.

[0083] The translation department can use the generation AI to analyze the emotional impact that the translated product description has on consumers using the emotion estimation function and select the optimal expression. For example, the translation department uses the generation AI to analyze the emotional impact that the translated product description has on consumers using the emotion estimation function. For example, the generation AI selects expressions that elicit positive emotions based on the emotion score. The generation AI also analyzes consumers' emotional responses and selects the optimal expression. For example, the generation AI evaluates translated text based on emotion data and selects the optimal expression. This makes it possible to select the optimal expression by analyzing the emotional impact that the translated product description has on consumers.

[0084] The translation department can use generative AI to translate not only product descriptions but also marketing materials and advertising copy into multiple languages. For example, generative AI translates not only product descriptions but also marketing materials and advertising copy into multiple languages. For example, generative AI translates advertising campaign text into multiple languages. Generative AI also translates product catalogs and promotional materials into multiple languages. For example, generative AI translates marketing materials into English, Chinese, French, etc. This allows for a consistent message to be delivered by translating not only product descriptions but also related marketing materials and advertising copy into multiple languages.

[0085] The translation unit can use the generation AI to visualize the translation results so that the user can intuitively understand. The translation unit, for example, uses the generation AI to visualize the translation results so that the user can intuitively understand. For example, the generation AI displays the translated text in a graph or chart so that the user can visually understand. The generation AI also displays the translation results as an infographic so that the user can intuitively understand. For example, the generation AI displays the translated text as an infographic so that the user can easily understand. In this way, by visualizing the translation results, the user can intuitively understand.

[0086] The translation unit can use the generation AI and emotion estimation function to compare the emotional empathy between different languages ​​and select the translation that is most likely to resonate. For example, the generation AI can use the emotion estimation function to compare the emotional empathy between different languages ​​and select the translation that is most likely to resonate. For example, the generation AI can evaluate translations based on emotion scores and select translations that evoke positive emotions. The generation AI can also compare emotional responses between different languages ​​and select the translation that is most likely to resonate. For example, the generation AI can evaluate translations based on emotion data and select translations with high empathy. In this way, by comparing the emotional empathy between different languages, the translation that is most likely to resonate can be selected.

[0087] The customer support department can use the generation AI to analyze the customer's past inquiry history and provide personalized support. For example, the generation AI analyzes the customer's past inquiry history and provides personalized support. For example, the generation AI generates an appropriate answer based on the content of the past inquiry. The generation AI also analyzes customer feedback and provides personalized support. For example, the generation AI adjusts the support content based on customer feedback. In this way, personalized support can be provided by analyzing the customer's past inquiry history.

[0088] The customer support department can use the generation AI to analyze the emotional state of the customer in real time and generate an appropriate response according to the emotion. For example, the customer support department can use the generation AI to analyze the emotional state of the customer in real time and generate an appropriate response according to the emotion. For example, if the customer is angry, the generation AI will respond calmly. Also, if the customer is feeling anxious, the generation AI will generate a reassuring response. For example, the generation AI will generate an appropriate response based on the customer's emotional data. This makes it possible to generate an appropriate response according to the emotion by analyzing the customer's emotional state in real time.

[0089] The customer support department can use the generative AI to analyze the customer's emotional responses using an emotion estimation function, and provide an emotionally positive support experience. For example, the generative AI can use the emotion estimation function to analyze the customer's emotional responses, and provide an emotionally positive support experience. For example, the generative AI can generate responses that elicit positive emotions. The generative AI can also analyze the customer's emotion score, and provide an emotionally positive support experience. For example, the generative AI can adjust the support content based on the emotion data. In this way, an emotionally positive support experience can be provided by analyzing the customer's emotional responses.

[0090] Customer support departments can use generative AI to integrate customer support across different channels (email, chat, telephone) and provide a consistent support experience. For example, generative AI integrates support content across email, chat, and telephone. Generative AI also centrally manages customer support across different channels and provides a unified support experience. For example, generative AI integrates data from different channels and provides consistent support to customers. This allows a consistent support experience to be provided by integrating customer support across different channels.

[0091] The customer support department can use generative AI to visualize the results of customer support so that the support team can intuitively understand it. For example, the customer support department can use generative AI to visualize the results of customer support so that the support team can intuitively understand it. For example, the generative AI can display the results of support in graphs and charts so that the support team can visually understand it. The generative AI can also display the results of customer support as infographics so that the support team can intuitively understand it. For example, the generative AI can display support data as infographics so that the support team can easily understand it. In this way, by visualizing the results of customer support, the support team can intuitively understand it.

[0092] The customer support department can use generative AI and an emotion estimation function to monitor the effectiveness of customer support in real time and continuously optimize their support strategy. For example, the generative AI uses an emotion estimation function to monitor the effectiveness of customer support in real time and continuously optimize their support strategy. For example, the generative AI adjusts the support content based on the emotion data. The generative AI also analyzes customers' emotion scores in real time and optimizes their support strategy. For example, the generative AI adjusts the support content based on the emotion score. In this way, the support strategy can be continuously optimized by monitoring the effectiveness of customer support in real time.

[0093] The marketing optimization department uses generative AI to analyze the effectiveness of advertising campaigns in real time and can instantly adjust strategies. For example, generative AI analyzes the effectiveness of advertising campaigns in real time and can instantly adjust strategies. For example, generative AI adjusts advertising content based on ad click rates and conversion rates. Generative AI also analyzes advertising campaign data in real time and proposes effective strategies. For example, generative AI adjusts advertising budget allocation based on advertising data. This allows for instant adjustments to strategies by analyzing the effectiveness of advertising campaigns in real time.

[0094] The marketing optimization department can use the generation AI to analyze consumer purchasing behavior and identify the optimal marketing channel. For example, the generation AI analyzes consumer purchasing behavior data and identifies the optimal marketing channel. For example, the generation AI adjusts the marketing strategy based on the channel most used by consumers. The generation AI also analyzes consumer purchasing patterns and identifies effective marketing channels. For example, the generation AI selects the optimal channel based on purchasing data. In this way, the optimal marketing channel can be identified by analyzing consumer purchasing behavior.

[0095] The marketing optimization unit can use the generation AI and emotion estimation function to analyze the emotional impact that marketing messages have on consumers and select the optimal message. For example, the marketing optimization unit uses the generation AI emotion estimation function to analyze the emotional impact that marketing messages have on consumers. For example, the generation AI selects a message that elicits positive emotions based on the emotion score. The generation AI also analyzes consumers' emotional responses and selects the optimal message. For example, the generation AI evaluates marketing messages based on emotion data and selects the optimal message. In this way, the optimal message can be selected by analyzing the emotional impact that marketing messages have on consumers.

[0096] The marketing optimization department can use generative AI to integrate different marketing channels (SNS, email, advertising) and provide a consistent marketing strategy. For example, generative AI integrates different marketing channels and provides a consistent marketing strategy. For example, generative AI integrates data from SNS, email, and advertising to create a strategy. Generative AI also centrally manages data from different channels and provides a unified marketing strategy. For example, generative AI provides a consistent message based on data from different channels. This makes it possible to provide a consistent marketing strategy by integrating different marketing channels.

[0097] The marketing optimization department can use the generative AI to visualize the results of the marketing strategy so that the marketing team can intuitively understand it. For example, the marketing optimization department uses the generative AI to visualize the results of the marketing strategy so that the marketing team can intuitively understand it. For example, the generative AI displays the results of the strategy in graphs and charts so that the marketing team can visually understand it. The generative AI also displays the results of the marketing strategy as infographics so that the marketing team can intuitively understand it. For example, the generative AI displays the results of the strategy as infographics so that the marketing team can easily understand it. In this way, by visualizing the results of the marketing strategy, the marketing team can intuitively understand it.

[0098] The marketing optimization unit uses generative AI and an emotion estimation function to monitor the effectiveness of a marketing strategy in real time and continuously optimize the strategy. For example, the generative AI uses an emotion estimation function to monitor the effectiveness of a marketing strategy in real time and continuously optimize the strategy. For example, the generative AI adjusts the marketing strategy based on emotion data. The generative AI also analyzes the effectiveness of the marketing strategy in real time and proposes the optimal strategy. For example, the generative AI adjusts the marketing message based on the emotion score. This allows the strategy to be continuously optimized by monitoring the effectiveness of the marketing strategy in real time.

[0099] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0100] The comprehensive service system for cross-border e-commerce can also be equipped with a recommendation unit that makes recommendations based on a user's purchasing history. The recommendation unit analyzes the user's past purchasing history and suggests highly relevant products. For example, it can suggest products similar to products the user has previously purchased. The recommendation unit can also analyze the user's purchasing patterns and suggest products that are in line with the season or trends. Furthermore, the recommendation unit can suggest the next product that a user who has purchased the same product should purchase based on the purchasing history of other users. This can improve the user's purchasing experience and increase sales.

[0101] The Market Analysis Department can also use Generative AI to analyze each country's legal regulations and tax systems to identify markets with low legal risk. For example, Generative AI can analyze each country's import regulations and tariff rates to identify markets with low legal risk. Generative AI can also analyze each country's consumer protection laws and data protection laws to identify markets with low legal risk. Furthermore, Generative AI can analyze each country's business environment and political stability to identify markets with low legal risk. This allows companies to minimize their risk by identifying markets with low legal risk.

[0102] The customer targeting department can use generation AI to analyze consumers' life events (marriage, childbirth, moving, etc.) and target them according to those life events. For example, generation AI can analyze consumers' social media data to identify life events such as marriage and childbirth. Generation AI can also analyze consumers' purchase history to suggest products related to moving or starting a new life. Furthermore, generation AI can generate marketing messages according to consumers' life events and perform effective targeting. This enables effective marketing by targeting consumers according to their life events.

[0103] The translation unit uses generation AI to not only translate product descriptions but also speech translation. For example, generation AI can translate Japanese product descriptions into English, Chinese, French, etc. by voice. Generation AI can also accept voice input and translate into multiple languages ​​in real time. Furthermore, generation AI can display the results of speech translation as text so that users can visually confirm it. This makes speech translation suitable for users who have difficulty reading text, such as the visually impaired and elderly.

[0104] The customer support department can use generation AI to analyze a customer's past inquiry history and provide personalized support. For example, generation AI generates appropriate answers based on the content of past inquiries. Generation AI can also analyze customer feedback and provide personalized support. Furthermore, generation AI can analyze a customer's purchase history and provide related support information. This makes it possible to provide personalized support by analyzing a customer's past inquiry history.

[0105] The marketing optimization department uses generation AI and emotion estimation functions to analyze the emotional impact of marketing messages on consumers and select the optimal message. For example, generation AI selects a message that elicits positive emotions based on the emotion score. Generation AI can also analyze consumers' emotional responses and select the optimal message. Furthermore, generation AI can evaluate marketing messages based on emotion data and select the optimal message. This allows the optimal message to be selected by analyzing the emotional impact that marketing messages have on consumers.

[0106] The market analysis department can use generative AI to analyze consumer emotional responses using emotion estimation functions and identify emotionally positive markets. For example, generative AI can collect emotion data from social media posts and reviews to identify markets with many positive responses. Generative AI can also evaluate markets based on consumer emotion scores and identify emotionally positive markets. Furthermore, generative AI can analyze consumer emotion scores and identify markets with many positive emotions. This allows for effective marketing by identifying emotionally positive markets.

[0107] The customer targeting department can use the generative AI to analyze the emotional state of consumers using the emotion estimation function and identify emotionally positive customer segments. For example, the generative AI can identify customer segments with a high number of positive emotional responses based on consumer emotion data. The generative AI can also analyze consumer emotion scores to identify emotionally positive customer segments. Furthermore, the generative AI can identify target segments based on consumer emotion scores. This allows for effective marketing by identifying emotionally positive customer segments.

[0108] Customer support departments can use generative AI to analyze customers' emotional responses using emotion estimation functions to provide an emotionally positive support experience. For example, generative AI can generate responses that elicit positive emotions. Generative AI can also analyze customers' emotion scores to provide an emotionally positive support experience. Furthermore, generative AI can adjust support content based on emotion data. This allows for an emotionally positive support experience to be provided by analyzing customers' emotional responses.

[0109] The marketing optimization department uses generative AI with emotion estimation capabilities to monitor the effectiveness of marketing strategies in real time and continuously optimize them. For example, generative AI can adjust marketing strategies based on emotion data. Generative AI can also analyze the effectiveness of marketing strategies in real time and propose optimal strategies. Furthermore, generative AI can adjust marketing messages based on emotion scores. This allows the strategy to be continuously optimized by monitoring the effectiveness of marketing strategies in real time.

[0110] The processing flow of the second embodiment will be briefly explained below.

[0111] Step 1: The market analysis department uses the generation AI to collect and analyze global market data and identify markets suitable for sales. For example, the generation AI analyzes each country's economic situation and consumer purchasing trends to determine which markets are most promising. The generation AI receives input from the user in the form of prompts containing instructions on what the user wants the generation AI to do, and the generation AI performs market analysis based on those prompts. Step 2: The customer targeting department analyzes consumer data to identify target customer segments using the generation AI. For example, the generation AI identifies the customer segments with the highest purchasing intent based on data such as age, gender, and purchase history. The input to the generation AI is a prompt containing instructions on what the user wants the generation AI to do, and the generation AI performs customer targeting based on that prompt. Step 3: The translation department uses the generation AI to translate the product description into multiple languages. For example, a Japanese product description can be translated into English, Chinese, French, etc. The input to the generation AI is the text of the product description to be translated, and the generation AI translates based on that text. Step 4: The customer support department uses the generation AI to automatically respond to customer inquiries. For example, the generation AI generates appropriate answers to questions about how to use a product or the return procedure. The input to the generation AI is the customer's inquiry, and the generation AI generates an answer based on that content. Step 5: The Marketing Optimization Department analyzes advertising and sales data to optimize the marketing strategy using Generative AI. For example, Generative AI analyzes which ads are most effective and suggests optimal allocation of advertising budgets. The inputs to Generative AI are advertising and sales data, and Generative AI optimizes the marketing strategy based on that data.

[0112] 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.

[0113] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> Examples of generative AIs include the data generation model 58, such as a neural network model (e.g., a neural network model), and a neural network model (e.g., a neural network model). The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating speech, text data indicating text, and image data indicating an image is also input to the data generation model 58. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. 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 can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0114] 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.

[0115] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0116] 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0117] 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.

[0118] 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.

[0119] 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.

[0120] 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).

[0121] 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.

[0122] 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.

[0123] 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.

[0124] 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 the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0125] 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. Note that the smart glasses 214 may have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0126] 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.

[0127] 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.

[0128] 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 containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. 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 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 can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0129] 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.

[0130] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0131] 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.

[0132] 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.

[0133] 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.

[0134] 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.

[0135] 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).

[0136] 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.

[0137] 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.

[0138] 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.

[0139] 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 the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0140] 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 may also have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0141] 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.

[0142] 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.

[0143] 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 containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. 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 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 can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0144] 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.

[0145] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0146] 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0147] 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.

[0148] 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.

[0149] 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.

[0150] 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).

[0151] 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.

[0152] 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.

[0153] 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.

[0154] 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.

[0155] 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 the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0156] In the robot 414, the processor 46 performs the identification process. 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. The robot 414 may have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0157] 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.

[0158] 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.

[0159] 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 containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. 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 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 can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0160] 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.

[0161] 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.

[0162] 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.

[0163] 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.

[0164] 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).

[0165] 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.

[0166] 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."

[0167] 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.

[0168] 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.

[0169] 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.

[0170] 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.

[0171] 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.

[0172] The hardware resource for executing a specific process can be any of the following processors: A CPU is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. A dedicated electrical circuit, such as a field-programmable gate array (FPGA), a programmable logic device (PLD), or an application-specific integrated circuit (ASIC), is a processor with a circuit configuration specifically designed to execute a specific process. Each processor has built-in or connected memory, and uses the memory to execute the specific process.

[0173] 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.

[0174] 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.

[0175] 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.

[0176] 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.

[0177] 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.

[0178] 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. [Explanation of symbols]

[0179] 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 market analysis department using generative AI, a customer targeting unit that identifies a customer segment based on the market identified by the market analysis unit; a translation unit that translates product descriptions for the customer segment identified by the customer targeting unit; a customer support department that responds to customer inquiries based on the product descriptions translated by the translation department; a marketing optimization unit that optimizes a marketing strategy based on the data collected by the customer support unit. A system characterized by:

2. The market analysis department 2. The system of claim 1, wherein the generative AI is used to analyze market data from different industries to discover cross-industry market opportunities.

3. The customer targeting unit The generative AI is used to analyze consumers' lifestyles and preferences to create more detailed target profiles.

2. The system of claim 1.

4. The translation unit The generative AI is used to translate not only the product description but also the translation taking into account cultural nuances and localization.

2. The system of claim 1.

5. The customer support department The generative AI is used to analyze the customer's inquiry history and provide personalized support.

2. The system of claim 1.

6. The marketing optimization unit The generative AI is used to analyze the effectiveness of advertising campaigns in real time and adjust strategies immediately.

2. The system of claim 1.

7. The market analysis department The generative AI is used to analyze consumers' emotional responses using an emotion estimation function, thereby identifying the emotionally positive market.

2. The system of claim 1.

8. The marketing optimization unit Using the generative AI and emotion estimation function, the emotional impact of marketing messages on consumers is analyzed and the most appropriate message is selected.

2. The system of claim 1.

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