System

Abstract

A system is provided.SOLUTION: The system includes a means for receiving basic information on a business idea from a user, a means for collecting related data from an internal database and an external source, a means for generating the business idea by using an AI generated based on the collected data, and a means for providing the generated business idea to the user.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] Startups must efficiently handle a wide range of tasks within limited resources and time. They are particularly required to complete complex tasks, such as generating business ideas, conducting market research, creating business plans, and formulating marketing strategies, in a short space of time. However, traditional methods often require manual processes, which are time-consuming and costly, and do not guarantee consistent results. Furthermore, there is a shortage of personnel with the expertise to carry out these tasks efficiently. As a result, startups find it difficult to grow their businesses quickly and effectively. [Means for solving the problem]

[0005] The present invention provides a system that utilizes generative AI to improve the operational efficiency of startup companies. The system includes the following means:

[0006] 1. A means for receiving basic information about a business idea from a user;

[0007] 2. Means of collecting relevant data from internal databases and external sources;

[0008] 3. A method to generate business ideas using AI based on collected data,

[0009] 4. A means for providing the generated business ideas to users;

[0010] 5. A means for receiving market-specific information from users;

[0011] 6. Means of collecting market data from internal databases and external sources;

[0012] 7. A means of analyzing the collected data and providing it in the form of reports;

[0013] 8. A means of receiving basic information about new businesses from users;

[0014] 9. A means for generating a business plan template based on the received information;

[0015] 10. A means for generating and providing a detailed business plan to the user;

[0016] 11. A means of receiving basic project information from users;

[0017] 12. A means of analyzing past campaign data and market trends;

[0018] 13. A means for generating and providing optimal marketing strategies to users;

[0019] This allows startups to make the most of their limited resources and carry out their work quickly and effectively.

[0020] "User" refers to an individual or organization that uses the system to generate business ideas, conduct market research, create business plans, and develop marketing strategies.

[0021] "Basic information" is initial data such as a business idea, target market, and competitive information provided by the user.

[0022] The "internal database" is a database that stores information such as past data, trend information, and success stories held by the system.

[0023] "External sources" are information sources obtained from outside, such as the Internet, statistical data, and research reports.

[0024] "Generative AI" is an artificial intelligence technology that generates new ideas and strategies based on collected data.

[0025] "Related data" is information related to a business or market that is collected based on information input by a user.

[0026] A "business idea" is a concept or proposal for a new business, product, or service.

[0027] A "project" is a planned set of activities or tasks to achieve a specific goal.

[0028] A "template" is a format or model for a business plan, marketing strategy, etc.

[0029] A "report" is a document that summarizes collected data and the results of its analysis.

[0030] A "marketing strategy" is a plan for promotion, advertising, PR activities, etc. when launching a product or service into the market.

[0031] "Data analysis" is the process of analyzing collected data to extract useful information and insights. [Brief explanation of the drawings]

[0032] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13]FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0033] 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.

[0034] First, the terms used in the following description will be explained.

[0035] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0036] 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.

[0037] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0038] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0039] 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."

[0040] [First embodiment]

[0041] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0042] 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.

[0043] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0044] 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.

[0045] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0046] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0047] 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.

[0048] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0049] 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.

[0050] 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.

[0051] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0052] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0053] This invention provides a system that utilizes generative AI to improve the operational efficiency of startup companies. This system enables users to efficiently generate business ideas, conduct market research, create business plans, and develop marketing strategies.

[0054] Specifically, the system works as follows:

[0055] Brainstorming business ideas

[0056] The user enters basic information about their business idea into the device, including areas of interest, target market, and existing challenges. The device then sends this information to the server, which collects relevant data from internal databases and external sources. Generative AI is then used to generate a business idea, which is then provided to the user by the server via the device. For example, if a user requests "new ideas for sustainable products," the server will suggest specific ideas such as "a fashion brand made from recycled materials."

[0057] Market Research

[0058] The user inputs information about the specific market they wish to research into their device. This information includes the target market, region, and time range. The device then sends this information to the server, which collects relevant market data from internal databases and external sources. The collected data is analyzed by the server and sent to the device in the form of a report, which is then displayed to the user. For example, if a user wants to research "demand for e-books in the Japanese market," the server will aggregate statistical data, consumer trends, and competitive analysis and provide it as a report.

[0059] Creating a business plan

[0060] The user enters basic information about their new business into the device. The device then sends this information to the server, which then uses it to generate a business plan template. A detailed business plan is created using generative AI and provided to the user by the server via the device. For example, if a user enters detailed information about "launching a new health food brand," the server will create a business plan that includes market analysis, target market, competitive analysis, and financial plan.

[0061] Creating a marketing strategy

[0062] The user enters basic information about a new project and its marketing goals into the device. The device then sends the information to the server, which analyzes past campaign data and market trends. An optimal marketing strategy is created using generative AI and provided to the user by the server via the device. For example, if the user requests a "marketing strategy for a new product launch," the server will propose a plan that includes a social media strategy, advertising campaign, and PR activities.

[0063] This system allows startups to efficiently utilize their limited resources and time, enabling them to rapidly expand their business. The system, which utilizes generative AI, supports the growth of companies by quickly responding to user needs and providing high-quality output.

[0064] The processing flow will be explained below.

[0065] Specific steps for brainstorming business ideas

[0066] Step 1:

[0067] The user enters basic information about their business idea (area of ​​interest, target market, existing challenges, etc.) into the terminal.

[0068] Step 2:

[0069] The terminal sends the entered basic information to the server.

[0070] Step 3:

[0071] The server collects relevant data from internal databases and external sources (Internet, statistical data, etc.).

[0072] Step 4:

[0073] Multiple business ideas are generated using generative AI based on the relevant data collected by the server.

[0074] Step 5:

[0075] The server transmits the generated business idea to the terminal.

[0076] Step 6:

[0077] The user checks the provided business idea on the terminal.

[0078] Specific steps in market research

[0079] Step 1:

[0080] The user inputs information about a specific market (market name, target area, time range, etc.) into the terminal.

[0081] Step 2:

[0082] The terminal sends the request information to the server.

[0083] Step 3:

[0084] The server collects relevant market data from internal databases and external sources (statistical data, research reports, etc.).

[0085] Step 4:

[0086] The server analyzes the collected market data.

[0087] Step 5:

[0088] The server compiles the analysis results into a report.

[0089] Step 6:

[0090] The server sends the generated report to the device.

[0091] Step 7:

[0092] The user checks the report on the device.

[0093] Specific steps in creating a business plan

[0094] Step 1:

[0095] The user enters basic information about the new business (business details, target market, competitive information, etc.) into the terminal.

[0096] Step 2:

[0097] The terminal sends the entered basic information to the server.

[0098] Step 3:

[0099] The server generates a business plan template based on the received information.

[0100] Step 4:

[0101] The server uses generated AI to create a detailed business plan (market analysis, target market, competitive analysis, financial plan, etc.).

[0102] Step 5:

[0103] The server transmits the generated business plan to the terminal.

[0104] Step 6:

[0105] The user checks the detailed business plan on the device.

[0106] Specific process steps for creating a marketing strategy

[0107] Step 1:

[0108] The user enters basic information and marketing goals for the new project into the terminal.

[0109] Step 2:

[0110] The terminal sends the entered basic information to the server.

[0111] Step 3:

[0112] The server collects and analyzes past campaign data and market trends from internal databases and external sources.

[0113] Step 4:

[0114] The server uses generative AI to create the optimal marketing strategy.

[0115] Step 5:

[0116] The server transmits the generated marketing strategy to the terminal.

[0117] Step 6:

[0118] The user checks the marketing strategy on the device.

[0119] Specific steps for fundraising

[0120] Step 1:

[0121] The user inputs their fundraising request (amount of funds needed, outline of business plan, etc.) into the terminal.

[0122] Step 2:

[0123] The terminal transmits the input request to the server.

[0124] Step 3:

[0125] The server collects and analyzes investor information and past fundraising cases from internal databases and external sources.

[0126] Step 4:

[0127] Based on the analysis results, the server generates a list of fundraising methods and investors suitable for the user.

[0128] Step 5:

[0129] The server sends the generated fundraising methods and investor list to the terminal.

[0130] Step 6:

[0131] The user checks fundraising methods and investor list on the terminal.

[0132] Example 1

[0133] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0134] Traditional business processes in startups consume a lot of time and resources and lack efficiency. In particular, key tasks such as brainstorming business ideas, market research, creating business plans, and formulating marketing strategies require a great deal of effort, making it difficult to rapidly develop a business. Furthermore, these processes rely on experience and expertise, which is a major barrier faced by startups. To solve these challenges, a system utilizing generative AI is needed.

[0135] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0136] In this invention, the server includes means for receiving basic information about a business idea from a user, means for collecting related data from an internal database and external sources, means for generating business ideas using a generative AI model based on the collected data, and means for providing the generated business ideas to the user, thereby enabling the user to quickly obtain high-quality business ideas.

[0137] The server also includes means for receiving information about a particular market from a user, means for collecting market data from an internal database and external sources, and means for analyzing the collected data and providing it in the form of a report, thereby enabling the user to quickly gain in-depth insight into the market.

[0138] Furthermore, the server includes means for receiving basic information about a new business from a user, means for generating a business plan template based on the received information, and means for generating a detailed business plan using a generative AI model and providing the detailed business plan to the user, thereby enabling startup companies to create detailed business plans while saving time and resources.

[0139] Finally, the server includes means for receiving basic information and marketing goals for a new project from a user, means for analyzing past campaign data and market trends, and means for generating a marketing strategy using a generative AI model and providing it to the user, thereby enabling the user to quickly formulate and implement an effective marketing strategy.

[0140] "User" means any person who uses the System to generate business ideas, market research, business plans, or marketing strategies.

[0141] "Basic information about business ideas" refers to the basic information required to generate business ideas, such as the user's areas of interest, target market, and existing challenges.

[0142] "Database" refers to an information resource that stores and manages relevant data for generating business ideas, market research, business plans, and marketing strategies.

[0143] "External sources" refer to data providers or information sources that exist outside the system, such as public information on the Internet or APIs.

[0144] A "generative AI model" refers to an artificial intelligence algorithm that generates new ideas, strategies, reports, etc. based on given prompts.

[0145] "Prompt" refers to the instructions a generative AI model uses to generate new ideas and data.

[0146] "Report format" refers to the document format in which collected and analyzed data is provided to the user.

[0147] A "business plan template" refers to a template or format that makes creating a business plan more efficient.

[0148] "Marketing objectives" refer to the specific goals to be achieved regarding promotional activities and market development for a new project.

[0149] "Historical Campaign Data" means data containing details of or results from previously conducted marketing or promotional activities.

[0150] "Market trends" refers to data that includes current trends and future predictions for a particular market.

[0151] The present invention relates to a system that utilizes generative AI to enable users to efficiently generate business ideas, conduct market research, create business plans, and develop marketing strategies. Specific embodiments of this system are described below.

[0152] Brainstorming business ideas

[0153] The user enters basic information about their business idea into the device. The entered information is sent to the server via a REST API. The server collects relevant data from an internal database (e.g., an RDBMS) and external sources (e.g., APIs on the Internet). Specific examples include data collection using Amazon Aurora and Google News API. Based on the collected data, the server inputs a prompt to a generative AI model (e.g., GPT-4) saying, "Please propose new ideas for sustainable products." The server then sends the generated ideas (e.g., "A fashion brand made from recycled materials") to the device for the user to confirm.

[0154] Market Research

[0155] The user inputs the market information they wish to research into their device. This includes the target market, region, and time range. The input information is sent to the server via a REST API. The server calls external data sources such as the Statista API to collect e-book market data. Based on the collected data, the server inputs a prompt to the generation AI: "Please create a detailed report on e-book demand in the Japanese market." The server then sends the generated report to the device, where the user can review it.

[0156] Creating a business plan

[0157] The user enters basic information about a new business into the device. The entered information is sent to the server via a REST API. The server generates a business plan template based on the received information and inputs it into the generative AI model. For example, a user enters detailed information about "launching a new health food brand" and inputs the prompt "Please create a business plan for the health food brand" into the generative AI. The server then sends a detailed business plan, including the target market, competitive analysis, and financial plan, to the device for the user to review.

[0158] Creating a marketing strategy

[0159] The user enters basic information and marketing goals for a new project into the device. The entered information is sent to the server via a REST API. The server collects and analyzes past campaign data and market trends. To do this, it uses the AdEspresso API, among others. Based on the collected data, the server inputs a prompt to the generation AI: "Please propose the optimal marketing strategy for the new product launch." The server then sends the generated marketing strategy (e.g., social media strategy, advertising campaign, PR activities) to the device, where the user can confirm it.

[0160] This system allows startups to efficiently utilize their limited resources and time, enabling them to rapidly expand their business. By utilizing generative AI, they can quickly respond to user needs and provide high-quality output.

[0161] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0162] Brainstorming business ideas

[0163] Step 1:

[0164] The user enters basic information about their business idea into the device, such as areas of interest, target market, existing challenges, etc. The entered information is saved in JSON format on the device.

[0165] Step 2:

[0166] The device sends the input information to the server via the REST API. At this time, the device sends JSON format data to the server using an HTTP POST request.

[0167] Step 3:

[0168] The server receives the information you enter and collects relevant data from internal databases (e.g., RDBMS) and external sources (e.g., Google News API), which are then stored on the server in a structured data format.

[0169] Step 4:

[0170] Based on the data collected by the server, a prompt sentence is input to the generative AI model (e.g., GPT-4). Specifically, the prompt sentence is input as "Please propose new ideas for sustainable products."

[0171] Step 5:

[0172] The server receives business ideas (e.g., "a fashion brand made from recycled materials") obtained from the generative AI model and organizes the data in JSON format.

[0173] Step 6:

[0174] The server sends the generated business idea to the terminal, where the generated idea is sent as an HTTP response.

[0175] Step 7:

[0176] The user checks the generated business idea on the device's display screen, and the device displays the received data in UI elements.

[0177] Market Research

[0178] Step 1:

[0179] The user inputs the market information they wish to research (e.g., target market, region, time range) into the terminal. The input information is saved in JSON format on the terminal.

[0180] Step 2:

[0181] The device sends the entered information to the server via the REST API. The device sends JSON format data to the server via an HTTP POST request.

[0182] Step 3:

[0183] Based on the information received, the server collects relevant market data from external data sources such as the Statista API, and stores the collected data in a structured data format on the server.

[0184] Step 4:

[0185] The server analyzes the collected data and inputs a prompt to the generation AI: "Please create a detailed report on the demand for e-books in the Japanese market."

[0186] Step 5:

[0187] The server receives the generated report and organizes the data in JSON format.

[0188] Step 6:

[0189] The server sends the generated report to the terminal as an HTTP response.

[0190] Step 7:

[0191] The user checks the generated report on the device's display screen, and the device displays the received data in UI elements.

[0192] Creating a business plan

[0193] Step 1:

[0194] The user enters basic information about their new business into the device, including the business concept, target market, and competitors. The information is then saved in JSON format on the device.

[0195] Step 2:

[0196] The device sends the entered information to the server via the REST API. The device sends JSON format data to the server via an HTTP POST request.

[0197] Step 3:

[0198] The server generates a business plan template based on the received information and stores the generated template on the server.

[0199] Step 4:

[0200] Based on the generated template, the server inputs the prompt statement "Please create a business plan for a health food brand" into the generative AI model.

[0201] Step 5:

[0202] The server receives the results from the generative AI model and adds details to the business plan, including target markets, competitive analysis, and financial plans.

[0203] Step 6:

[0204] The server organizes the generated business plan in JSON format and sends it to the terminal. At this time, the generated business plan is sent to the terminal as an HTTP response.

[0205] Step 7:

[0206] The user checks the generated business plan on the device's display screen, and the device displays the received data in UI elements.

[0207] Creating a marketing strategy

[0208] Step 1:

[0209] The user enters basic information about the new project and marketing goals into the device, such as the product name, target audience, budget range, etc. The entered information is saved in JSON format on the device.

[0210] Step 2:

[0211] The device sends the entered information to the server via the REST API. The device sends JSON format data to the server via an HTTP POST request.

[0212] Step 3:

[0213] Based on the information received, the server collects and analyzes past campaign data and market trends. For this purpose, it uses external data sources such as the AdEspresso API. The collected data is stored on the server.

[0214] Step 4:

[0215] Based on the data collected and analyzed by the server, the generative AI model is given a prompt: "Please suggest the optimal marketing strategy for the launch of a new product."

[0216] Step 5:

[0217] The server receives the results from the generative AI model and designs a detailed marketing strategy, including social media strategies, advertising campaigns, and PR activities.

[0218] Step 6:

[0219] The server organizes the generated marketing strategy in JSON format and sends it to the terminal. At this time, the generated strategy is sent to the terminal as an HTTP response.

[0220] Step 7:

[0221] The user checks the generated marketing strategy on the device's display screen, and the device displays the received data in UI elements.

[0222] (Application example 1)

[0223] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0224] For startups, it is extremely important to develop business ideas and marketing strategies while efficiently utilizing limited resources and time. However, with previous systems, users needed a great deal of effort and specialized knowledge to plan and create effective advertising campaigns. Furthermore, existing methods made it difficult to collect and analyze market information in real time and quickly generate advertising campaign plans. This led to delays in business development and the risk of losing competitiveness.

[0225] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0226] In this invention, the server includes means for receiving basic information about a business idea from a user, means for collecting related data from an internal database and external sources, means for generating business ideas using a generation AI based on the collected data, means for providing the generated business ideas to the user, and means for generating an advertising campaign plan based on advertising campaign requirements entered by the user. This allows users to efficiently obtain market information and quickly develop optimal advertising strategies. This allows startup companies to make the most of their limited resources and develop competitive businesses.

[0227] "User" means an individual or organization that uses a particular system or service.

[0228] A "business idea" is a concept or plan for a new business, product, or service.

[0229] An "internal database" is a database that accumulates data managed within a company.

[0230] "External sources" refer to data or information sources that can be obtained from outside.

[0231] "Relevant data" refers to information or numerical data that is relevant to a particular topic or purpose.

[0232] "Generative AI" refers to systems or models that use artificial intelligence technology to generate new ideas and information.

[0233] An "advertising campaign" is a series of advertising activities designed to promote a particular product or service.

[0234] A "means" is a method or device used to achieve a particular purpose.

[0235] A "server" is a computer that provides data and services over a network.

[0236] "Requirements" are the conditions or criteria necessary to carry out a particular task or project.

[0237] "Data collection" is the process of gathering specific information or data.

[0238] "Market information" refers to data such as market conditions, trends, and competitive information.

[0239] An "advertising strategy" is a plan or method for successfully running a particular advertising campaign.

[0240] This invention is a system that allows users to freely generate business ideas and advertising campaigns and quickly and effectively realize them. This system consists of a server, a terminal, and a generative AI model. The following explains the details of each component and how they interact with each other.

[0241] Data input from the user

[0242] Users input basic information about their business idea and advertising campaign through a device such as a smartphone. For example, users input the requirements for their advertising campaign (purpose, market, target audience, format, period, budget). For example,

[0243] Advertising campaign requirements:

[0244] Purpose: Increase awareness

[0245] Market: Japanese market

[0246] Target Audience: Young people (18-25 years old)

[0247] Format: Social Media Ad

[0248] Duration: 3 months

[0249] Budget: 5 million yen

[0250] Data submission and collection

[0251] The device sends user input data to a server, which then collects relevant data from an internal database and external sources. This process utilizes natural language processing (NLP) and machine learning algorithms. Specific technologies include accessing external data sources via APIs to obtain the latest market information and trend data.

[0252] Idea generation and campaign proposals using generative AI

[0253] The server uses generative AI models based on the collected data to generate business ideas and elements of advertising campaigns. The generated ideas and strategies are then returned to the device and provided to the user.

[0254] For example, a generative AI model might work like this:

[0255] Business idea generation: Based on the basic information entered by the user, the server generates specific ideas such as "a fashion brand made from recycled materials."

[0256] Advertising campaign generation: The server generates a campaign plan (keyword selection, ad copy, image and video themes, distribution method, etc.) based on the advertising requirements entered by the user.

[0257] Report Generation and Simulation

[0258] The advertising campaign plan created by the generative AI is simulated to show expected results, and the results are provided to the user as a report. This simulation is performed by analyzing past campaign data and market trends.

[0259] Specific examples

[0260] If a user wants a "marketing strategy for a new product launch," they can send the following prompt to the generative AI model:

[0261] New product launch marketing strategy:

[0262] Target market: North American market

[0263] Target audience: IT engineers aged 25-35

[0264] Primary goal: 1,000 sales in the first month

[0265] Budget: 10 million yen

[0266] Based on this input, the generative AI will suggest optimal marketing strategies (social media strategies, advertising campaigns, PR activities, etc.).

[0267] This allows users to quickly and effectively develop business ideas and advertising strategies with minimal expertise or effort, helping startups make the most of their limited resources and increase their competitiveness.

[0268] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0269] Step 1:

[0270] The user inputs the requirements for the advertising campaign. The user inputs basic information such as the advertising objective, market, target audience, format, period, budget, etc. in text format via a device such as a smartphone. This input data is used in the next processing step.

[0271] Step 2:

[0272] The device sends the input data to the server. The advertising campaign requirements entered by the user are recorded on the device and transmitted to the server using a secure communication protocol (e.g. HTTPS). This data forms the basis for collecting related data on the server.

[0273] Step 3:

[0274] The server collects relevant data from internal databases and external sources. The server uses NLP and web scraping techniques to gather the necessary information from internal databases (e.g., past advertising campaign data) and external sources (e.g., market research reports and public data). This data is used as training material for the generative AI model.

[0275] Step 4:

[0276] The server analyzes the collected data and generates an advertising campaign plan using a generative AI model. The server inputs the preprocessed data into a generative AI model (e.g., OpenAI's GPT series) to generate each element of the advertising campaign (keywords, ad copy, image theme, distribution method, etc.) based on the user's requirements and market insights. This generated plan is the output presented to the user.

[0277] Step 5:

[0278] The server sends the generated advertising campaign plan to the device. The advertising campaign plan created by the generative AI model is returned to the user's device using a secure communication protocol. The device receives this data and displays it through a user interface.

[0279] Step 6:

[0280] The user checks the generated advertising campaign plan. The user checks the advertising campaign plan displayed on the terminal screen and makes corrections or feedback as necessary. This feedback is sent back to the server for further optimization.

[0281] Step 7:

[0282] The server simulates the advertising campaign plan and generates the results in a report. The server simulates the effectiveness of the generated advertising campaign plan based on past data and trends, and summarizes the results in a report. This report is provided to the user and is useful for making final campaign decisions.

[0283] Step 8:

[0284] The server sends the final report to the terminal. The generated simulation report is then sent to the user's terminal again using a secure communication protocol, and the user can review this report and proceed with preparations for the actual advertising campaign.

[0285] These steps provide a system that allows users to efficiently plan and execute advertising campaigns without requiring specialized knowledge.

[0286] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0287] This invention provides a system that combines generative AI and an emotion engine to improve the operational efficiency of startup companies. This system enables users to efficiently generate business ideas, conduct market research, create business plans, and develop marketing strategies, and provides optimized results by taking user emotions into account.

[0288] Specifically, the system works as follows:

[0289] Brainstorming business ideas

[0290] The user enters basic information about their business idea (areas of interest, target market, existing challenges, etc.) into the device. At this time, the emotion engine analyzes the user's input and recognizes emotions. The device then sends the basic information and emotion data to the server, which collects related data from an internal database and external sources. Generative AI is used to generate business ideas, and the server provides optimized business ideas based on the emotion data to the user via the device. For example, if a user requests "new ideas for sustainable products," the server will suggest specific ideas such as "a fashion brand made from recycled materials," but if the user is expressing positive emotions, it will suggest more innovative ideas.

[0291] Market Research

[0292] The user inputs information about a specific market (such as the market name, target region, and time range) into the device. The emotion engine then analyzes the user's input and recognizes emotions. The device then sends the request information and emotion data to the server, which then collects relevant market data from internal databases and external sources. The collected data is analyzed by the server and sent to the device in the form of a report optimized based on the emotion data, which is then displayed to the user. For example, if a user wants to research "demand for e-books in the Japanese market," the server aggregates statistical data, consumer trends, and competitive analysis, and provides a particularly detailed analysis if the user expresses concerns.

[0293] Creating a business plan

[0294] The user enters basic information about their new business (business details, target market, competitive information, etc.) into the device. At this time, an emotion engine analyzes the user's input and recognizes emotions. The device then sends the basic information and emotional data to the server, which then generates a business plan template based on that information. A detailed business plan is created using generative AI, and the server provides the plan to the user via the device, adjusted based on the emotional data. For example, if a user enters detailed information about "launching a new health food brand," the server will create a business plan that includes market analysis, target market, competitive analysis, and financial plan, and will also include a risk analysis if the user expresses any concerns.

[0295] Creating a marketing strategy

[0296] The user enters basic information and marketing goals for a new project into the device. The emotion engine analyzes the user's input and recognizes emotions. The device then sends the basic information and emotion data to the server, which collects and analyzes past campaign data and market trends from internal databases and external sources. An optimal marketing strategy is created using generative AI, and the strategy, adjusted based on the emotion data, is provided to the user from the server via the device. For example, if the user requests a "marketing strategy for a new product launch," the server will propose plans for social media strategies, advertising campaigns, PR activities, and more, including bolder strategies if the user expresses excitement.

[0297] This system allows startups to efficiently utilize limited resources and time, and rapidly expand their business by receiving more personalized support based on emotions.The system, which utilizes generative AI and an emotion engine, supports the growth of companies by quickly responding to users' needs and emotions and providing high-quality output.

[0298] The processing flow will be explained below.

[0299] Specific steps for brainstorming business ideas

[0300] Step 1:

[0301] The user inputs basic information about their business idea (areas of interest, target market, existing challenges, etc.) into the device, and the emotion engine analyzes the user's input and recognizes their emotions.

[0302] Step 2:

[0303] The device transmits basic information and recognized emotion data to the server.

[0304] Step 3:

[0305] The server collects relevant data from internal databases and external sources (Internet, statistical data, etc.).

[0306] Step 4:

[0307] Generate multiple business ideas using generative AI based on relevant data collected by the server.

[0308] Step 5:

[0309] The server takes into account the user's emotional data to optimize the generated business ideas, for example, highlighting more innovative ideas if the user shows positive emotions.

[0310] Step 6:

[0311] The server sends the optimized business idea to the terminal.

[0312] Step 7:

[0313] The system checks the business ideas provided by the user on the device, and if the user responds positively, it will also suggest additional ideas.

[0314] Specific steps in market research

[0315] Step 1:

[0316] The user inputs information about a specific market (market name, target area, time range, etc.) into the terminal, and the emotion engine analyzes the user's input and recognizes emotions.

[0317] Step 2:

[0318] The device sends the request information and emotion data to the server.

[0319] Step 3:

[0320] The server collects relevant market data from internal databases and external sources (statistical data, research reports, etc.).

[0321] Step 4:

[0322] The server analyzes the collected market data.

[0323] Step 5:

[0324] The server takes into account the sentiment data and compiles the analysis results into a report, for example, including a detailed risk analysis if the user expresses anxiety.

[0325] Step 6:

[0326] The server sends the generated report to the device.

[0327] Step 7:

[0328] The user reviews the report on their device, and if they express anxiety, it includes specific suggestions for action.

[0329] Specific steps in creating a business plan

[0330] Step 1:

[0331] The user inputs basic information about their new business (business details, target market, competitive information, etc.) into the terminal. At this time, the emotion engine analyzes the user's input and recognizes their emotions.

[0332] Step 2:

[0333] The device sends the input basic information and emotion data to the server.

[0334] Step 3:

[0335] The server generates a business plan template based on the received information.

[0336] Step 4:

[0337] The server uses generative AI to create a detailed business plan and adjusts it based on the user's sentiment data, for example detailing a risk management plan if the user expresses concerns.

[0338] Step 5:

[0339] The server sends the adjusted business plan to the terminal.

[0340] Step 6:

[0341] Users review the detailed business plan on their devices and provide feedback on any areas of particular interest or concern.

[0342] Specific process steps for creating a marketing strategy

[0343] Step 1:

[0344] The user inputs basic information about the new project and its marketing goals into the device, and the emotion engine analyzes the user's input and recognizes their emotions.

[0345] Step 2:

[0346] The device sends the input basic information and emotion data to the server.

[0347] Step 3:

[0348] The server collects and analyzes past campaign data and market trends from internal databases and external sources.

[0349] Step 4:

[0350] The server uses generative AI to create optimal marketing strategies and adjusts them by taking into account sentiment data, for example, adopting a more aggressive strategy if users express excitement.

[0351] Step 5:

[0352] The server transmits the adjusted marketing strategy to the terminal.

[0353] Step 6:

[0354] Users can view marketing strategies on their devices and receive detailed recommendations for strategies that interest them.

[0355] Specific steps for fundraising

[0356] Step 1:

[0357] The user inputs their fundraising request (such as the amount of funds needed and an outline of their business plan) into the terminal. At this time, the emotion engine analyzes the user's input and recognizes their emotion.

[0358] Step 2:

[0359] The terminal transmits the input request and emotion data to the server.

[0360] Step 3:

[0361] The server collects and analyzes investor information and past fundraising cases from internal databases and external sources.

[0362] Step 4:

[0363] The server takes emotional data into account to generate a list of investors and fundraising methods suited to the user. For example, if the user shows signs of nervousness, it will recommend investors with relatively low risk.

[0364] Step 5:

[0365] The server sends the generated fundraising methods and investor list to the terminal.

[0366] Step 6:

[0367] Users can check fundraising methods and investor lists on their device, and if they're feeling nervous, they can also receive specific negotiation advice.

[0368] Example 2

[0369] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0370] Startups need to operate efficiently within limited resources and time constraints, but conventional systems have struggled to provide optimal support that takes user emotions into account. In particular, there has been no technology that provides results that reflect user emotions when generating business ideas, conducting market research, creating business plans, or formulating marketing strategies. Therefore, there is a need for personalized support based on user emotions to improve the quality of user decision-making.

[0371] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for receiving basic information from a user, means for analyzing the received input and recognizing emotions, means for transmitting the analysis results and related data to the server, means for collecting related data from an internal database and external sources, means for processing the collected data using a generative AI model, means for optimizing the generated results based on emotion data, and means for providing the optimized results to the user. This makes it possible to create optimal business ideas, market research, business plans, and marketing strategies based on user emotions.

[0372] A "user" is an entity that uses this system to develop business ideas, market research, business plans, or marketing strategies.

[0373] "Basic information" refers to input data about a business provided by a user, including business details, target market, competitive information, and the like.

[0374] "Emotion data" is data that indicates the user's emotional state, analyzed by the emotion engine based on the user's input.

[0375] A "terminal" is a hardware or software device through which a user interacts with the system.

[0376] The "server" is the central device that executes various processes in this system and collects, analyzes, generates, and optimizes data.

[0377] "Generative AI model" refers to an artificial intelligence model that automatically generates business ideas, market research reports, business plans, or marketing strategies based on user requests.

[0378] "Internal Database" means a collection of information stored within the server that the system uses to gather relevant data needed.

[0379] "External Source" means an external information source, other than the internal database, that the system connects to to gather relevant data.

[0380] "Optimization" refers to the process of adjusting generated business ideas, reports, business plans, or marketing strategies based on user sentiment data to make them more effective.

[0381] "Analysis" refers to the process of processing received user input data to recognize its content and sentiment.

[0382] A "report" is output data in document format that organizes and presents the results of market research, etc.

[0383] This invention provides a system that combines a generative AI model and an emotion engine to improve the operational efficiency of startup companies. This system takes user emotions into account and provides optimized results in generating business ideas, conducting market research, creating business plans, and formulating marketing strategies.

[0384] System configuration

[0385] The system consists of a device used by the user, a server that analyzes and generates data, and an internal database and external sources. Basic business information provided by the user is received by the device, and its content and emotional data are analyzed. The analyzed data is sent to the server, which collects related data from the internal database and external sources. The collected data is processed by the server, and the required output is generated using a generative AI model. This output is optimized based on the user's emotional data and provided to the user via the device.

[0386] Brainstorming business ideas

[0387] When a user enters basic information about their business idea into the device, the emotion engine analyzes the input and recognizes emotions. The basic information along with the emotion data is sent to the server, which collects relevant data from its internal database and external sources. The server uses a generative AI model to generate business ideas and provides them to the user via the device, optimized based on the emotion data.

[0388] For example, if a user requests "new ideas for sustainable products," specific suggestions such as "fashion brands that use recycled materials" may be given. An example of a prompt for the generative AI model is "Please generate new business ideas for sustainable products."

[0389] Market Research

[0390] When a user inputs information about a specific market into the terminal, the emotion engine analyzes the input and recognizes emotions. The request information along with the emotion data is sent to the server, which collects relevant market data from internal databases and external sources. The server analyzes the collected data and generates an optimized report based on the emotion data, which is then provided to the user via the terminal.

[0391] For example, if a user wants to research "demand for e-books in the Japanese market," a report containing statistical data, consumer trends, and competitive analysis will be generated. An example of a prompt for the generative AI model is, "Please research demand for e-books in the Japanese market and create a detailed report."

[0392] Creating a business plan

[0393] When a user enters basic information about a new business into the device, the emotion engine analyzes the input and recognizes emotions. The basic information along with the emotion data is sent to the server, which then generates a basic business plan based on a template. A generative AI model is then used to create a detailed business plan, which is then adjusted based on the emotion data and provided to the user via the device.

[0394] For example, if a user enters details about "launching a new health food brand," a business plan will be created that includes market analysis, financial planning, and competitive analysis. An example prompt for the generative AI model is, "Please create a business plan for a new health food brand."

[0395] Creating a marketing strategy

[0396] When a user enters basic information about a new project and marketing goals into their device, the emotion engine analyzes the input and recognizes emotions. The basic information along with the emotion data is sent to a server, which then collects and analyzes past campaign data and market trends from internal databases and external sources. An optimal marketing strategy is created using a generative AI model, and the strategy, adjusted based on the emotion data, is provided to the user via their device.

[0397] For example, if a user requests a "marketing strategy for a new product launch," plans for a social media strategy, advertising campaign, and PR activities will be suggested. An example of a prompt for the generative AI model is, "Please create a marketing strategy for a new product launch."

[0398] This system allows startups to utilize limited resources and time and rapidly expand their business by receiving optimal support based on user emotions. Utilizing a generative AI model and emotion engine, the system responds quickly to user needs and emotions, providing high-quality output and supporting business growth.

[0399] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0400] Brainstorming business ideas

[0401] Step 1:

[0402] The user inputs basic information about their business idea into the device, such as areas of interest, target market, existing challenges, etc. The input at this stage is text data.

[0403] Step 2:

[0404] The device sends the input information to an emotion engine to recognize emotions. For example, it uses natural language processing technology to analyze text data and extract emotions such as positive and negative. The output at this point is analyzed emotion data.

[0405] Step 3:

[0406] The device sends basic information and emotion data to the server. This data transmission allows the server to start the necessary processing. At this point, the input is a set of basic information and emotion data.

[0407] Step 4:

[0408] The server collects relevant data from internal databases and external sources, for example, market data and trend information relevant to the business, and consolidates this data. The output at this point is the collected relevant data.

[0409] Step 5:

[0410] The server uses a generative AI model to generate business ideas based on the collected data. Specifically, it gives the AI ​​model a prompt to start the idea generation process. An example of a prompt is, "Please generate a new business idea for a sustainable product." The output at this point is the generated business idea.

[0411] Step 6:

[0412] The server optimizes the generated business ideas based on the sentiment data. For example, if the sentiment is positive, it adds novel ideas, and if it is negative, it generates ideas that minimize risk. The output at this point is an optimized business idea.

[0413] Step 7:

[0414] The server returns the optimized business idea to the terminal. This data transmission prepares the idea to be presented directly to the user. The output at this point is the optimized business idea.

[0415] Step 8:

[0416] The terminal provides the optimized business idea to the user, for example, by displaying the business idea on a screen or by providing it in a downloadable format, and the output at this point is the specific business idea provided to the user.

[0417] Market Research

[0418] Step 1:

[0419] The user inputs information about a specific market into the terminal. Specifically, the user inputs information such as the market name, target area, time range, etc. The input at this point is text data.

[0420] Step 2:

[0421] The device sends the input information to an emotion engine for emotion recognition. Emotions are extracted from text data using natural language processing techniques. The output at this point is analyzed emotion data.

[0422] Step 3:

[0423] The device sends request information and emotion data to the server. This data transmission starts processing on the server side. The input at this point is a set of request information and emotion data.

[0424] Step 4:

[0425] The server collects market-related data from internal databases and external sources, such as market statistics and consumer trend information, and aggregates them. The output at this point is market-related data.

[0426] Step 5:

[0427] The server analyzes the collected data and uses generative AI models to create a detailed report. The output at this point is a report containing the analysis results.

[0428] Step 6:

[0429] The server optimizes the report based on the emotion data, for example if the user indicates anxiety it will create a report with a particularly detailed analysis. The output at this point is the optimized report.

[0430] Step 7:

[0431] The server returns the optimized report to the terminal. This data transmission prepares the report to be provided directly to the user. The output at this point is the optimized report.

[0432] Step 8:

[0433] The terminal provides an optimized report to the user, for example by displaying the report on the screen or by providing it in a downloadable format. The output at this point is a detailed report provided to the user.

[0434] Creating a business plan

[0435] Step 1:

[0436] The user inputs basic information about the new business into the terminal, such as the business description, target market, and competitive information. At this stage, the input is text data.

[0437] Step 2:

[0438] The device sends the input information to the emotion engine, which recognizes emotions. The emotion data is analyzed using natural language processing technology. The output at this point is the analyzed emotion data.

[0439] Step 3:

[0440] The device sends basic information and emotion data to the server. This data transmission starts processing on the server side. At this point, the input is a set of basic information and emotion data.

[0441] Step 4:

[0442] The server generates a business plan template based on the basic information. This template includes basic items such as market analysis, competitive analysis, and financial plan. The output at this point is a business plan template.

[0443] Step 5:

[0444] The server uses a generative AI model to create a detailed business plan based on the generated template. An example prompt is, "Please create a business plan for a new health food brand." The output at this point is a detailed business plan.

[0445] Step 6:

[0446] The server optimizes the business plan based on the sentiment data, for example, if the user expresses concerns, it creates a plan that specifically includes a risk analysis. The output at this point is an optimized business plan.

[0447] Step 7:

[0448] The server returns the optimized business plan to the terminal. This data transmission prepares the business plan to be provided directly to the user. The output at this point is the optimized business plan.

[0449] Step 8:

[0450] The terminal provides the optimized business plan to the user, for example, by displaying the plan on a screen or by providing it in a downloadable format. The output at this point is a specific business plan provided to the user.

[0451] Creating a marketing strategy

[0452] Step 1:

[0453] The user inputs basic information and marketing goals for the new project into the terminal, including the sales promotion plan, target market, advertising goals, etc. The input at this stage is text data.

[0454] Step 2:

[0455] The device sends the input information to the emotion engine, which recognizes emotions. The emotion data is analyzed using natural language processing technology. The output at this point is the analyzed emotion data.

[0456] Step 3:

[0457] The device sends basic information and emotion data to the server. This data transmission starts processing on the server side. At this point, the input is a set of basic information and emotion data.

[0458] Step 4:

[0459] The server collects historical campaign data and market trends from internal databases and external sources, and the output at this point is the collected relevant data.

[0460] Step 5:

[0461] The server uses a generative AI model to create a marketing strategy. An example prompt is "Please create a marketing strategy for a new product launch." The output at this point is a detailed marketing strategy.

[0462] Step 6:

[0463] The server optimizes the marketing strategy based on the emotion data. For example, if the user expresses excitement, it adds a bold strategy. The output at this point is the optimized marketing strategy.

[0464] Step 7:

[0465] The server returns the optimized marketing strategy to the terminal. This data transmission prepares the strategy to be provided directly to the user. The output at this point is the optimized marketing strategy.

[0466] Step 8:

[0467] The terminal provides the optimized marketing strategy to the user, for example by displaying the strategy on a screen or by providing it in a downloadable format. The output at this point is the specific marketing strategy provided to the user.

[0468] Through these steps, the system provides optimal support based on the user's emotions, improving work efficiency.

[0469] (Application example 2)

[0470] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0471] Store managers are required to develop effective business strategies and implement measures within limited resources and time. However, the information gathering and planning required for this is cumbersome, and the results can be disappointing, especially since optimization is not based on the emotions of individual store managers. Therefore, there is a need for a system that can efficiently generate business ideas and optimize them while taking emotions into account.

[0472] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving basic information about a business idea from a user, means for collecting related data from an internal database and external sources, means for generating business ideas using a generation AI based on the collected data, means for providing the generated business idea to the user, and means for analyzing user emotions using an emotion engine and optimizing the generated business idea based on the emotion data. This enables managers of physical stores to quickly develop and implement optimized business ideas and strategies based on emotions.

[0473] 1. A "business idea" is a concept or plan for a new business that a user wants to start.

[0474] 2. "Basic information" refers to the basic data required to develop a business idea, as well as information about users' interests, target markets, and existing challenges.

[0475] 3. "Internal Database" means the collection of data stored within the System.

[0476] 4. "External Source" means a source of data collected from outside the System.

[0477] 5. "Emotion Engine" refers to a system component that analyzes user input data and recognizes their emotional state.

[0478] 6. "Generative AI" refers to artificial intelligence that uses large amounts of data to generate new content or ideas based on specific prompts.

[0479] 7. "Optimization" is the process of adjusting something to best suit a particular purpose or condition.

[0480] 8. "Market Data" means data such as statistics, consumer trends, and competitive analysis relating to a particular market.

[0481] 9. A "business plan template" is a basic business plan template for building a new business.

[0482] To implement this invention, it is important to build a system that combines generative AI and an emotion engine, allowing store managers to efficiently generate business ideas and provide plans optimized based on emotions.

[0483] System Configuration

[0484] The system consists of a terminal operated by the user, a server that processes data, and a generative AI and emotion engine for generating and optimizing business ideas.

[0485] Program Overview

[0486] 1. The terminal receives basic information about the business idea from the user.

[0487] 2. The terminal sends the received basic information to the server.

[0488] 3. Based on the received basic information, the server collects relevant data from its internal database and external sources.

[0489] 4. The server uses an emotion engine to analyze emotions from the user's basic information input.

[0490] 5. The server uses generative AI to generate business ideas based on the collected data and analyzed emotional data.

[0491] 6. The server optimizes the generated business ideas based on the emotion data.

[0492] 7. The server sends the optimized business idea to the terminal and provides it to the user.

[0493] Hardware and Software Use

[0494] This system uses the user's smartphone as the terminal. To process data and perform sentiment analysis, a server runs on a cloud platform such as Amazon Web Services (AWS). The generative AI uses the OpenAI API, and modules such as the "sentiment_analysis_module" for the sentiment engine and the "database_connector" for database connection are used.

[0495] Data processing and calculation

[0496] Basic information entered on the device is sent to the server as text data. The server then uses an emotion engine to perform sentiment analysis of the text data and recognize positive, negative, and neutral emotional states. Data collected from internal databases and external sources is normalized and aggregated in a database management system (DBMS). The generative AI generates prompt responses based on the data and further optimizes them based on the emotional data.

[0497] Examples of concrete examples and prompts

[0498] For example, if a user is looking for new business ideas for "summer sales promotions," they input basic information from their device. The server analyzes this information with an emotion engine, and if it determines that the user is expressing positive emotions, it uses generative AI to generate novel ideas such as "beach party-themed sales events."

[0499] An example of a prompt is:

[0500] Generate new business ideas for "Summer Sale Promotion" when users are feeling positive.

[0501] This allows store owners to quickly obtain business ideas that are optimized based on emotions, allowing them to plan and implement more effective strategies.

[0502] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0503] Step 1:

[0504] The user uses a terminal to input basic information about their business idea, including their interests, areas of interest, target market, and existing challenges. This input data is then passed on to the next step.

[0505] Step 2:

[0506] The device sends the basic information entered in step 1 to the server. The data is passed to the server in text format, and data analysis is performed based on this.

[0507] Step 3:

[0508] The server sends the received basic information to the emotion engine, which analyzes the user's emotions. The emotion engine analyzes the text data and outputs a positive, negative, or neutral emotional state. The analysis results are used in the next step.

[0509] Step 4:

[0510] The server collects relevant data from internal databases and external sources based on the basic information and sentiment analysis results. The collected data includes market trends and competitive information, and this data is normalized and aggregated in a database management system (DBMS). This processed data is used in the next step.

[0511] Step 5:

[0512] The server calls the generation AI based on the collected data and the results of sentiment analysis to generate new business ideas. Specific prompts are provided to the generation AI, and an example of a prompt is "Generate a new business idea for a 'summer sales promotion' when the user is feeling positive." The generation AI outputs new ideas based on this.

[0513] Step 6:

[0514] The server optimizes the generated business ideas based on the emotional data. For example, if the user shows positive emotions, it will adjust the idea to be more innovative. This optimized business idea is sent to the next step.

[0515] Step 7:

[0516] The server sends the optimized business idea to the terminal, which displays it to the user. The user can check the optimized business idea and use it to plan and execute a specific business strategy.

[0517] Through the above processing steps, brick-and-mortar store managers can efficiently generate business ideas and obtain optimized plans based on emotions.

[0518] 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.

[0519] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0520] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0521] [Second embodiment]

[0522] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0523] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0524] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0525] 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.

[0526] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0527] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0528] 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.

[0529] 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.

[0530] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0531] 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.

[0532] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0533] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0534] This invention provides a system that utilizes generative AI to improve the operational efficiency of startup companies. This system enables users to efficiently generate business ideas, conduct market research, create business plans, and develop marketing strategies.

[0535] Specifically, the system works as follows:

[0536] Brainstorming business ideas

[0537] The user enters basic information about their business idea into the device, including areas of interest, target market, and existing challenges. The device then sends this information to the server, which collects relevant data from internal databases and external sources. Generative AI is then used to generate a business idea, which is then provided to the user by the server via the device. For example, if a user requests "new ideas for sustainable products," the server will suggest specific ideas such as "a fashion brand made from recycled materials."

[0538] Market Research

[0539] The user inputs information about the specific market they wish to research into their device. This information includes the target market, region, and time range. The device then sends this information to the server, which collects relevant market data from internal databases and external sources. The collected data is analyzed by the server and sent to the device in the form of a report, which is then displayed to the user. For example, if a user wants to research "demand for e-books in the Japanese market," the server will aggregate statistical data, consumer trends, and competitive analysis and provide it as a report.

[0540] Creating a business plan

[0541] The user enters basic information about their new business into the device. The device then sends this information to the server, which then uses it to generate a business plan template. A detailed business plan is created using generative AI and provided to the user by the server via the device. For example, if a user enters detailed information about "launching a new health food brand," the server will create a business plan that includes market analysis, target market, competitive analysis, and financial plan.

[0542] Creating a marketing strategy

[0543] The user enters basic information about a new project and its marketing goals into the device. The device then sends the information to the server, which analyzes past campaign data and market trends. An optimal marketing strategy is created using generative AI and provided to the user by the server via the device. For example, if the user requests a "marketing strategy for a new product launch," the server will propose a plan that includes a social media strategy, advertising campaign, and PR activities.

[0544] This system allows startups to efficiently utilize their limited resources and time, enabling them to rapidly expand their business. The system, which utilizes generative AI, supports the growth of companies by quickly responding to user needs and providing high-quality output.

[0545] The processing flow will be explained below.

[0546] Specific steps for brainstorming business ideas

[0547] Step 1:

[0548] The user enters basic information about their business idea (area of ​​interest, target market, existing challenges, etc.) into the terminal.

[0549] Step 2:

[0550] The terminal sends the entered basic information to the server.

[0551] Step 3:

[0552] The server collects relevant data from internal databases and external sources (Internet, statistical data, etc.).

[0553] Step 4:

[0554] Multiple business ideas are generated using generative AI based on the relevant data collected by the server.

[0555] Step 5:

[0556] The server transmits the generated business idea to the terminal.

[0557] Step 6:

[0558] The user checks the provided business idea on the terminal.

[0559] Specific steps in market research

[0560] Step 1:

[0561] The user inputs information about a specific market (market name, target area, time range, etc.) into the terminal.

[0562] Step 2:

[0563] The terminal sends the request information to the server.

[0564] Step 3:

[0565] The server collects relevant market data from internal databases and external sources (statistical data, research reports, etc.).

[0566] Step 4:

[0567] The server analyzes the collected market data.

[0568] Step 5:

[0569] The server compiles the analysis results into a report.

[0570] Step 6:

[0571] The server sends the generated report to the device.

[0572] Step 7:

[0573] The user checks the report on the device.

[0574] Specific steps in creating a business plan

[0575] Step 1:

[0576] The user enters basic information about the new business (business details, target market, competitive information, etc.) into the terminal.

[0577] Step 2:

[0578] The terminal sends the entered basic information to the server.

[0579] Step 3:

[0580] The server generates a business plan template based on the received information.

[0581] Step 4:

[0582] The server uses generated AI to create a detailed business plan (market analysis, target market, competitive analysis, financial plan, etc.).

[0583] Step 5:

[0584] The server transmits the generated business plan to the terminal.

[0585] Step 6:

[0586] The user checks the detailed business plan on the device.

[0587] Specific process steps for creating a marketing strategy

[0588] Step 1:

[0589] The user enters basic information and marketing goals for the new project into the terminal.

[0590] Step 2:

[0591] The terminal sends the entered basic information to the server.

[0592] Step 3:

[0593] The server collects and analyzes past campaign data and market trends from internal databases and external sources.

[0594] Step 4:

[0595] The server uses generative AI to create the optimal marketing strategy.

[0596] Step 5:

[0597] The server transmits the generated marketing strategy to the terminal.

[0598] Step 6:

[0599] The user checks the marketing strategy on the device.

[0600] Specific steps for fundraising

[0601] Step 1:

[0602] The user inputs their fundraising request (amount of funds needed, outline of business plan, etc.) into the terminal.

[0603] Step 2:

[0604] The terminal transmits the input request to the server.

[0605] Step 3:

[0606] The server collects and analyzes investor information and past fundraising cases from internal databases and external sources.

[0607] Step 4:

[0608] Based on the analysis results, the server generates a list of fundraising methods and investors suitable for the user.

[0609] Step 5:

[0610] The server sends the generated fundraising methods and investor list to the terminal.

[0611] Step 6:

[0612] The user checks fundraising methods and investor list on the terminal.

[0613] Example 1

[0614] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0615] Traditional business processes in startups consume a lot of time and resources and lack efficiency. In particular, key tasks such as brainstorming business ideas, market research, creating business plans, and formulating marketing strategies require a great deal of effort, making it difficult to rapidly develop a business. Furthermore, these processes rely on experience and expertise, which is a major barrier faced by startups. To solve these challenges, a system utilizing generative AI is needed.

[0616] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0617] In this invention, the server includes means for receiving basic information about a business idea from a user, means for collecting related data from an internal database and external sources, means for generating business ideas using a generative AI model based on the collected data, and means for providing the generated business ideas to the user, thereby enabling the user to quickly obtain high-quality business ideas.

[0618] The server also includes means for receiving information about a particular market from a user, means for collecting market data from an internal database and external sources, and means for analyzing the collected data and providing it in the form of a report, thereby enabling the user to quickly gain in-depth insight into the market.

[0619] Furthermore, the server includes means for receiving basic information about a new business from a user, means for generating a business plan template based on the received information, and means for generating a detailed business plan using a generative AI model and providing the detailed business plan to the user, thereby enabling startup companies to create detailed business plans while saving time and resources.

[0620] Finally, the server includes means for receiving basic information and marketing goals for a new project from a user, means for analyzing past campaign data and market trends, and means for generating a marketing strategy using a generative AI model and providing it to the user, thereby enabling the user to quickly formulate and implement an effective marketing strategy.

[0621] "User" means any person who uses the System to generate business ideas, market research, business plans, or marketing strategies.

[0622] "Basic information about business ideas" refers to the basic information required to generate business ideas, such as the user's areas of interest, target market, and existing challenges.

[0623] "Database" refers to an information resource that stores and manages relevant data for generating business ideas, market research, business plans, and marketing strategies.

[0624] "External sources" refer to data providers or information sources that exist outside the system, such as public information on the Internet or APIs.

[0625] A "generative AI model" refers to an artificial intelligence algorithm that generates new ideas, strategies, reports, etc. based on given prompts.

[0626] "Prompt" refers to the instructions a generative AI model uses to generate new ideas and data.

[0627] "Report format" refers to the document format in which collected and analyzed data is provided to the user.

[0628] A "business plan template" refers to a template or format that makes creating a business plan more efficient.

[0629] "Marketing objectives" refer to the specific goals to be achieved regarding promotional activities and market development for a new project.

[0630] "Historical Campaign Data" means data containing details of or results from previously conducted marketing or promotional activities.

[0631] "Market trends" refers to data that includes current trends and future predictions for a particular market.

[0632] The present invention relates to a system that utilizes generative AI to enable users to efficiently generate business ideas, conduct market research, create business plans, and develop marketing strategies. Specific embodiments of this system are described below.

[0633] Brainstorming business ideas

[0634] The user enters basic information about their business idea into the device. The entered information is sent to the server via a REST API. The server collects relevant data from an internal database (e.g., an RDBMS) and external sources (e.g., APIs on the Internet). Specific examples include data collection using Amazon Aurora and Google News API. Based on the collected data, the server inputs a prompt to a generative AI model (e.g., GPT-4) saying, "Please propose new ideas for sustainable products." The server then sends the generated ideas (e.g., "A fashion brand made from recycled materials") to the device for the user to confirm.

[0635] Market Research

[0636] The user inputs the market information they wish to research into their device. This includes the target market, region, and time range. The input information is sent to the server via a REST API. The server calls external data sources such as the Statista API to collect e-book market data. Based on the collected data, the server inputs a prompt to the generation AI: "Please create a detailed report on e-book demand in the Japanese market." The server then sends the generated report to the device, where the user can review it.

[0637] Creating a business plan

[0638] The user enters basic information about a new business into the device. The entered information is sent to the server via a REST API. The server generates a business plan template based on the received information and inputs it into the generative AI model. For example, a user enters detailed information about "launching a new health food brand" and inputs the prompt "Please create a business plan for the health food brand" into the generative AI. The server then sends a detailed business plan, including the target market, competitive analysis, and financial plan, to the device for the user to review.

[0639] Creating a marketing strategy

[0640] The user enters basic information and marketing goals for a new project into the device. The entered information is sent to the server via a REST API. The server collects and analyzes past campaign data and market trends. To do this, it uses the AdEspresso API, among others. Based on the collected data, the server inputs a prompt to the generation AI: "Please propose the optimal marketing strategy for the new product launch." The server then sends the generated marketing strategy (e.g., social media strategy, advertising campaign, PR activities) to the device, where the user can confirm it.

[0641] This system allows startups to efficiently utilize their limited resources and time, enabling them to rapidly expand their business. By utilizing generative AI, they can quickly respond to user needs and provide high-quality output.

[0642] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0643] Brainstorming business ideas

[0644] Step 1:

[0645] The user enters basic information about their business idea into the device, such as areas of interest, target market, existing challenges, etc. The entered information is saved in JSON format on the device.

[0646] Step 2:

[0647] The device sends the input information to the server via the REST API. At this time, the device sends JSON format data to the server using an HTTP POST request.

[0648] Step 3:

[0649] The server receives the information you enter and collects relevant data from internal databases (e.g., RDBMS) and external sources (e.g., Google News API), which are then stored on the server in a structured data format.

[0650] Step 4:

[0651] Based on the data collected by the server, a prompt sentence is input to the generative AI model (e.g., GPT-4). Specifically, the prompt sentence is input as "Please propose new ideas for sustainable products."

[0652] Step 5:

[0653] The server receives business ideas (e.g., "a fashion brand made from recycled materials") obtained from the generative AI model and organizes the data in JSON format.

[0654] Step 6:

[0655] The server sends the generated business idea to the terminal, where the generated idea is sent as an HTTP response.

[0656] Step 7:

[0657] The user checks the generated business idea on the device's display screen, and the device displays the received data in UI elements.

[0658] Market Research

[0659] Step 1:

[0660] The user inputs the market information they wish to research (e.g., target market, region, time range) into the terminal. The input information is saved in JSON format on the terminal.

[0661] Step 2:

[0662] The device sends the entered information to the server via the REST API. The device sends JSON format data to the server via an HTTP POST request.

[0663] Step 3:

[0664] Based on the information received, the server collects relevant market data from external data sources such as the Statista API, and stores the collected data in a structured data format on the server.

[0665] Step 4:

[0666] The server analyzes the collected data and inputs a prompt to the generation AI: "Please create a detailed report on the demand for e-books in the Japanese market."

[0667] Step 5:

[0668] The server receives the generated report and organizes the data in JSON format.

[0669] Step 6:

[0670] The server sends the generated report to the terminal as an HTTP response.

[0671] Step 7:

[0672] The user checks the generated report on the device's display screen, and the device displays the received data in UI elements.

[0673] Creating a business plan

[0674] Step 1:

[0675] The user enters basic information about their new business into the device, including the business concept, target market, and competitors. The information is then saved in JSON format on the device.

[0676] Step 2:

[0677] The device sends the entered information to the server via the REST API. The device sends JSON format data to the server via an HTTP POST request.

[0678] Step 3:

[0679] The server generates a business plan template based on the received information and stores the generated template on the server.

[0680] Step 4:

[0681] Based on the generated template, the server inputs the prompt statement "Please create a business plan for a health food brand" into the generative AI model.

[0682] Step 5:

[0683] The server receives the results from the generative AI model and adds details to the business plan, including target markets, competitive analysis, and financial plans.

[0684] Step 6:

[0685] The server organizes the generated business plan in JSON format and sends it to the terminal. At this time, the generated business plan is sent to the terminal as an HTTP response.

[0686] Step 7:

[0687] The user checks the generated business plan on the device's display screen, and the device displays the received data in UI elements.

[0688] Creating a marketing strategy

[0689] Step 1:

[0690] The user enters basic information about the new project and marketing goals into the device, such as the product name, target audience, budget range, etc. The entered information is saved in JSON format on the device.

[0691] Step 2:

[0692] The device sends the entered information to the server via the REST API. The device sends JSON format data to the server via an HTTP POST request.

[0693] Step 3:

[0694] Based on the information received, the server collects and analyzes past campaign data and market trends. For this purpose, it uses external data sources such as the AdEspresso API. The collected data is stored on the server.

[0695] Step 4:

[0696] Based on the data collected and analyzed by the server, the generative AI model is given a prompt: "Please suggest the optimal marketing strategy for the launch of a new product."

[0697] Step 5:

[0698] The server receives the results from the generative AI model and designs a detailed marketing strategy, including social media strategies, advertising campaigns, and PR activities.

[0699] Step 6:

[0700] The server organizes the generated marketing strategy in JSON format and sends it to the terminal. At this time, the generated strategy is sent to the terminal as an HTTP response.

[0701] Step 7:

[0702] The user checks the generated marketing strategy on the device's display screen, and the device displays the received data in UI elements.

[0703] (Application example 1)

[0704] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0705] For startups, it is extremely important to develop business ideas and marketing strategies while efficiently utilizing limited resources and time. However, with previous systems, users needed a great deal of effort and specialized knowledge to plan and create effective advertising campaigns. Furthermore, existing methods made it difficult to collect and analyze market information in real time and quickly generate advertising campaign plans. This led to delays in business development and the risk of losing competitiveness.

[0706] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0707] In this invention, the server includes means for receiving basic information about a business idea from a user, means for collecting related data from an internal database and external sources, means for generating business ideas using a generation AI based on the collected data, means for providing the generated business ideas to the user, and means for generating an advertising campaign plan based on advertising campaign requirements entered by the user. This allows users to efficiently obtain market information and quickly develop optimal advertising strategies. This allows startup companies to make the most of their limited resources and develop competitive businesses.

[0708] "User" means an individual or organization that uses a particular system or service.

[0709] A "business idea" is a concept or plan for a new business, product, or service.

[0710] An "internal database" is a database that accumulates data managed within a company.

[0711] "External sources" refer to data or information sources that can be obtained from outside.

[0712] "Relevant data" refers to information or numerical data that is relevant to a particular topic or purpose.

[0713] "Generative AI" refers to systems or models that use artificial intelligence technology to generate new ideas and information.

[0714] An "advertising campaign" is a series of advertising activities designed to promote a particular product or service.

[0715] A "means" is a method or device used to achieve a particular purpose.

[0716] A "server" is a computer that provides data and services over a network.

[0717] "Requirements" are the conditions or criteria necessary to carry out a particular task or project.

[0718] "Data collection" is the process of gathering specific information or data.

[0719] "Market information" refers to data such as market conditions, trends, and competitive information.

[0720] An "advertising strategy" is a plan or method for successfully running a particular advertising campaign.

[0721] This invention is a system that allows users to freely generate business ideas and advertising campaigns and quickly and effectively realize them. This system consists of a server, a terminal, and a generative AI model. The following explains the details of each component and how they interact with each other.

[0722] Data input from the user

[0723] Users input basic information about their business idea and advertising campaign through a device such as a smartphone. For example, users input the requirements for their advertising campaign (purpose, market, target audience, format, period, budget). For example,

[0724] Advertising campaign requirements:

[0725] Purpose: Increase awareness

[0726] Market: Japanese market

[0727] Target Audience: Young people (18-25 years old)

[0728] Format: Social Media Ad

[0729] Duration: 3 months

[0730] Budget: 5 million yen

[0731] Data submission and collection

[0732] The device sends user input data to a server, which then collects relevant data from an internal database and external sources. This process utilizes natural language processing (NLP) and machine learning algorithms. Specific technologies include accessing external data sources via APIs to obtain the latest market information and trend data.

[0733] Idea generation and campaign proposals using generative AI

[0734] The server uses generative AI models based on the collected data to generate business ideas and elements of advertising campaigns. The generated ideas and strategies are then returned to the device and provided to the user.

[0735] For example, a generative AI model might work like this:

[0736] Business idea generation: Based on the basic information entered by the user, the server generates specific ideas such as "a fashion brand made from recycled materials."

[0737] Advertising campaign generation: The server generates a campaign plan (keyword selection, ad copy, image and video themes, distribution method, etc.) based on the advertising requirements entered by the user.

[0738] Report Generation and Simulation

[0739] The advertising campaign plan created by the generative AI is simulated to show expected results, and the results are provided to the user as a report. This simulation is performed by analyzing past campaign data and market trends.

[0740] Specific examples

[0741] If a user wants a "marketing strategy for a new product launch," they can send the following prompt to the generative AI model:

[0742] New product launch marketing strategy:

[0743] Target market: North American market

[0744] Target audience: IT engineers aged 25-35

[0745] Primary goal: 1,000 sales in the first month

[0746] Budget: 10 million yen

[0747] Based on this input, the generative AI will suggest optimal marketing strategies (social media strategies, advertising campaigns, PR activities, etc.).

[0748] This allows users to quickly and effectively develop business ideas and advertising strategies with minimal expertise or effort, helping startups maximize their limited resources and increase their competitiveness.

[0749] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0750] Step 1:

[0751] The user inputs the requirements for the advertising campaign. The user inputs basic information such as the advertising objective, market, target audience, format, period, budget, etc. in text format via a device such as a smartphone. This input data is used in the next processing step.

[0752] Step 2:

[0753] The device sends the input data to the server. The advertising campaign requirements entered by the user are recorded on the device and transmitted to the server using a secure communication protocol (e.g. HTTPS). This data forms the basis for collecting related data on the server.

[0754] Step 3:

[0755] The server collects relevant data from internal databases and external sources. The server uses NLP and web scraping techniques to gather the necessary information from internal databases (e.g., past advertising campaign data) and external sources (e.g., market research reports and public data). This data is used as training material for the generative AI model.

[0756] Step 4:

[0757] The server analyzes the collected data and generates an advertising campaign plan using a generative AI model. The server inputs the preprocessed data into a generative AI model (e.g., OpenAI's GPT series) to generate each element of the advertising campaign (keywords, ad copy, image theme, distribution method, etc.) based on the user's requirements and market insights. This generated plan is the output presented to the user.

[0758] Step 5:

[0759] The server sends the generated advertising campaign plan to the device. The advertising campaign plan created by the generative AI model is returned to the user's device, again using a secure communication protocol. The device receives this data and displays it through a user interface.

[0760] Step 6:

[0761] The user checks the generated advertising campaign plan. The user checks the advertising campaign plan displayed on the terminal screen and makes corrections or feedback as necessary. This feedback is sent back to the server for further optimization.

[0762] Step 7:

[0763] The server simulates the advertising campaign plan and generates the results in a report. The server simulates the effectiveness of the generated advertising campaign plan based on past data and trends, and summarizes the results in a report. This report is provided to the user and is useful for making final campaign decisions.

[0764] Step 8:

[0765] The server sends the final report to the terminal. The generated simulation report is then sent to the user's terminal again using a secure communication protocol, and the user can review this report and proceed with preparations for the actual advertising campaign.

[0766] These steps provide a system that allows users to efficiently plan and execute advertising campaigns without requiring specialized knowledge.

[0767] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0768] This invention provides a system that combines generative AI and an emotion engine to improve the operational efficiency of startup companies. This system enables users to efficiently generate business ideas, conduct market research, create business plans, and develop marketing strategies, and provides optimized results by taking user emotions into account.

[0769] Specifically, the system works as follows:

[0770] Brainstorming business ideas

[0771] The user enters basic information about their business idea (areas of interest, target market, existing challenges, etc.) into the device. At this time, the emotion engine analyzes the user's input and recognizes emotions. The device then sends the basic information and emotion data to the server, which collects related data from an internal database and external sources. Generative AI is used to generate business ideas, and the server provides optimized business ideas based on the emotion data to the user via the device. For example, if a user requests "new ideas for sustainable products," the server will suggest specific ideas such as "a fashion brand made from recycled materials," but if the user is expressing positive emotions, it will suggest more innovative ideas.

[0772] Market Research

[0773] The user inputs information about a specific market (such as the market name, target region, and time range) into the device. The emotion engine then analyzes the user's input and recognizes emotions. The device then sends the request information and emotion data to the server, which then collects relevant market data from internal databases and external sources. The collected data is analyzed by the server and sent to the device in the form of a report optimized based on the emotion data, which is then displayed to the user. For example, if a user wants to research "demand for e-books in the Japanese market," the server aggregates statistical data, consumer trends, and competitive analysis, and provides a particularly detailed analysis if the user expresses concerns.

[0774] Creating a business plan

[0775] The user enters basic information about their new business (business details, target market, competitive information, etc.) into the device. At this time, an emotion engine analyzes the user's input and recognizes emotions. The device then sends the basic information and emotional data to the server, which then generates a business plan template based on that information. A detailed business plan is created using generative AI, and the server provides the plan to the user via the device, adjusted based on the emotional data. For example, if a user enters detailed information about "launching a new health food brand," the server will create a business plan that includes market analysis, target market, competitive analysis, and financial plan, and will also include a risk analysis if the user expresses any concerns.

[0776] Creating a marketing strategy

[0777] The user enters basic information and marketing goals for a new project into the device. The emotion engine analyzes the user's input and recognizes emotions. The device then sends the basic information and emotion data to the server, which collects and analyzes past campaign data and market trends from internal databases and external sources. An optimal marketing strategy is created using generative AI, and the strategy, adjusted based on the emotion data, is provided to the user from the server via the device. For example, if the user requests a "marketing strategy for a new product launch," the server will propose plans for social media strategies, advertising campaigns, PR activities, and more, including bolder strategies if the user expresses excitement.

[0778] This system allows startups to efficiently utilize limited resources and time, and rapidly expand their business by receiving more personalized support based on emotions.The system, which utilizes generative AI and an emotion engine, supports the growth of companies by quickly responding to users' needs and emotions and providing high-quality output.

[0779] The processing flow will be explained below.

[0780] Specific steps for brainstorming business ideas

[0781] Step 1:

[0782] The user inputs basic information about their business idea (areas of interest, target market, existing challenges, etc.) into the device, and the emotion engine analyzes the user's input and recognizes their emotions.

[0783] Step 2:

[0784] The device transmits basic information and recognized emotion data to the server.

[0785] Step 3:

[0786] The server collects relevant data from internal databases and external sources (Internet, statistical data, etc.).

[0787] Step 4:

[0788] Generate multiple business ideas using generative AI based on relevant data collected by the server.

[0789] Step 5:

[0790] The server takes into account the user's emotional data to optimize the generated business ideas, for example, highlighting more innovative ideas if the user shows positive emotions.

[0791] Step 6:

[0792] The server sends the optimized business idea to the terminal.

[0793] Step 7:

[0794] The system checks the business ideas provided by the user on the device, and if the user responds positively, it will also suggest additional ideas.

[0795] Specific steps in market research

[0796] Step 1:

[0797] The user inputs information about a specific market (market name, target area, time range, etc.) into the terminal, and the emotion engine analyzes the user's input and recognizes emotions.

[0798] Step 2:

[0799] The device sends the request information and emotion data to the server.

[0800] Step 3:

[0801] The server collects relevant market data from internal databases and external sources (statistical data, research reports, etc.).

[0802] Step 4:

[0803] The server analyzes the collected market data.

[0804] Step 5:

[0805] The server takes into account the sentiment data and compiles the analysis results into a report, for example, including a detailed risk analysis if the user expresses anxiety.

[0806] Step 6:

[0807] The server sends the generated report to the device.

[0808] Step 7:

[0809] The user reviews the report on their device, and if they express anxiety, it includes specific suggestions for action.

[0810] Specific steps in creating a business plan

[0811] Step 1:

[0812] The user inputs basic information about their new business (business details, target market, competitive information, etc.) into the terminal. At this time, the emotion engine analyzes the user's input and recognizes their emotions.

[0813] Step 2:

[0814] The device sends the input basic information and emotion data to the server.

[0815] Step 3:

[0816] The server generates a business plan template based on the received information.

[0817] Step 4:

[0818] The server uses generative AI to create a detailed business plan and adjusts it based on the user's sentiment data, for example detailing a risk management plan if the user expresses concerns.

[0819] Step 5:

[0820] The server sends the adjusted business plan to the terminal.

[0821] Step 6:

[0822] Users review the detailed business plan on their devices and provide feedback on any areas of particular interest or concern.

[0823] Specific process steps for creating a marketing strategy

[0824] Step 1:

[0825] The user inputs basic information about the new project and its marketing goals into the device, and the emotion engine analyzes the user's input and recognizes their emotions.

[0826] Step 2:

[0827] The device sends the input basic information and emotion data to the server.

[0828] Step 3:

[0829] The server collects and analyzes past campaign data and market trends from internal databases and external sources.

[0830] Step 4:

[0831] The server uses generative AI to create optimal marketing strategies and adjusts them by taking into account sentiment data, for example, adopting a more aggressive strategy if users express excitement.

[0832] Step 5:

[0833] The server transmits the adjusted marketing strategy to the terminal.

[0834] Step 6:

[0835] Users can view marketing strategies on their devices and receive detailed recommendations for strategies that interest them.

[0836] Specific steps for fundraising

[0837] Step 1:

[0838] The user inputs their fundraising request (such as the amount of funds needed and an outline of their business plan) into the terminal. At this time, the emotion engine analyzes the user's input and recognizes their emotion.

[0839] Step 2:

[0840] The terminal transmits the input request and emotion data to the server.

[0841] Step 3:

[0842] The server collects and analyzes investor information and past fundraising cases from internal databases and external sources.

[0843] Step 4:

[0844] The server takes emotional data into account to generate a list of investors and fundraising methods suited to the user. For example, if the user shows signs of nervousness, it will recommend investors with relatively low risk.

[0845] Step 5:

[0846] The server sends the generated fundraising methods and investor list to the terminal.

[0847] Step 6:

[0848] Users can check fundraising methods and investor lists on their device, and if they're feeling nervous, they can also receive specific negotiation advice.

[0849] Example 2

[0850] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0851] Startups need to operate efficiently within limited resources and time constraints, but conventional systems have struggled to provide optimal support that takes user emotions into account. In particular, there has been no technology that provides results that reflect user emotions when generating business ideas, conducting market research, creating business plans, or formulating marketing strategies. Therefore, personalized support based on user emotions is needed to improve the quality of user decision-making.

[0852] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for receiving basic information from a user, means for analyzing the received input and recognizing emotions, means for transmitting the analysis results and related data to the server, means for collecting related data from an internal database and external sources, means for processing the collected data using a generative AI model, means for optimizing the generated results based on emotion data, and means for providing the optimized results to the user. This makes it possible to create optimal business ideas, market research, business plans, and marketing strategies based on user emotions.

[0853] A "user" is an entity that uses this system to develop business ideas, market research, business plans, or marketing strategies.

[0854] "Basic information" refers to input data about a business provided by a user, including business details, target market, competitive information, and the like.

[0855] "Emotion data" is data that indicates the user's emotional state, analyzed by the emotion engine based on the user's input.

[0856] A "terminal" is a hardware or software device through which a user interacts with the system.

[0857] The "server" is the central device that executes various processes in this system and collects, analyzes, generates, and optimizes data.

[0858] "Generative AI model" refers to an artificial intelligence model that automatically generates business ideas, market research reports, business plans, or marketing strategies based on user requests.

[0859] "Internal Database" means a collection of information stored within the server that the system uses to gather relevant data needed.

[0860] "External Source" means an external information source, other than the internal database, that the system connects to to gather relevant data.

[0861] "Optimization" refers to the process of adjusting a generated business idea, report, business plan, or marketing strategy based on user sentiment data to make it more effective.

[0862] "Analysis" refers to the process of processing received user input data to recognize its content and sentiment.

[0863] A "report" is output data in document format that organizes and presents the results of market research, etc.

[0864] This invention provides a system that combines a generative AI model and an emotion engine to improve the operational efficiency of startup companies. This system takes user emotions into account and provides optimized results in generating business ideas, conducting market research, creating business plans, and formulating marketing strategies.

[0865] System configuration

[0866] The system consists of a device used by the user, a server that analyzes and generates data, and an internal database and external sources. Basic business information provided by the user is received by the device, and its content and emotional data are analyzed. The analyzed data is sent to the server, which collects related data from the internal database and external sources. The collected data is processed by the server, and the required output is generated using a generative AI model. This output is optimized based on the user's emotional data and provided to the user via the device.

[0867] Brainstorming business ideas

[0868] When a user enters basic information about their business idea into the device, the emotion engine analyzes the input and recognizes emotions. The basic information along with the emotion data is sent to the server, which collects relevant data from its internal database and external sources. The server uses a generative AI model to generate business ideas and provides them to the user via the device, optimized based on the emotion data.

[0869] For example, if a user requests "new ideas for sustainable products," specific suggestions such as "fashion brands that use recycled materials" may be given. An example of a prompt for the generative AI model is "Please generate new business ideas for sustainable products."

[0870] Market Research

[0871] When a user inputs information about a specific market into the terminal, the emotion engine analyzes the input and recognizes emotions. The request information along with the emotion data is sent to the server, which collects relevant market data from internal databases and external sources. The server analyzes the collected data and generates an optimized report based on the emotion data, which is then provided to the user via the terminal.

[0872] For example, if a user wants to research "demand for e-books in the Japanese market," a report containing statistical data, consumer trends, and competitive analysis will be generated. An example of a prompt for the generative AI model is, "Please research demand for e-books in the Japanese market and create a detailed report."

[0873] Creating a business plan

[0874] When a user enters basic information about a new business into the device, the emotion engine analyzes the input and recognizes emotions. The basic information along with the emotion data is sent to the server, which then generates a basic business plan based on a template. A generative AI model is then used to create a detailed business plan, which is then adjusted based on the emotion data and provided to the user via the device.

[0875] For example, if a user enters details about "launching a new health food brand," a business plan will be created that includes market analysis, financial planning, and competitive analysis. An example prompt for the generative AI model is, "Please create a business plan for a new health food brand."

[0876] Creating a marketing strategy

[0877] When a user enters basic information about a new project and marketing goals into their device, the emotion engine analyzes the input and recognizes emotions. The basic information along with the emotion data is sent to a server, which then collects and analyzes past campaign data and market trends from internal databases and external sources. An optimal marketing strategy is created using a generative AI model, and the strategy, adjusted based on the emotion data, is provided to the user via their device.

[0878] For example, if a user requests a "marketing strategy for a new product launch," plans for a social media strategy, advertising campaign, and PR activities will be suggested. An example of a prompt for the generative AI model is, "Please create a marketing strategy for a new product launch."

[0879] This system allows startups to utilize limited resources and time and rapidly expand their business by receiving optimal support based on user emotions. Utilizing a generative AI model and emotion engine, the system responds quickly to user needs and emotions, providing high-quality output and supporting business growth.

[0880] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0881] Brainstorming business ideas

[0882] Step 1:

[0883] The user inputs basic information about their business idea into the device, such as areas of interest, target market, existing challenges, etc. The input at this stage is text data.

[0884] Step 2:

[0885] The device sends the input information to an emotion engine to recognize emotions. For example, it uses natural language processing technology to analyze text data and extract emotions such as positive and negative. The output at this point is analyzed emotion data.

[0886] Step 3:

[0887] The device sends basic information and emotion data to the server. This data transmission allows the server to start the necessary processing. At this point, the input is a set of basic information and emotion data.

[0888] Step 4:

[0889] The server collects relevant data from internal databases and external sources, for example, market data and trend information relevant to the business, and consolidates this data. The output at this point is the collected relevant data.

[0890] Step 5:

[0891] The server uses a generative AI model to generate business ideas based on the collected data. Specifically, it gives the AI ​​model a prompt to start the idea generation process. An example of a prompt is, "Please generate a new business idea for a sustainable product." The output at this point is the generated business idea.

[0892] Step 6:

[0893] The server optimizes the generated business ideas based on the sentiment data. For example, if the sentiment is positive, it adds novel ideas, and if it is negative, it generates ideas that minimize risk. The output at this point is an optimized business idea.

[0894] Step 7:

[0895] The server returns the optimized business idea to the terminal. This data transmission prepares the idea to be presented directly to the user. The output at this point is the optimized business idea.

[0896] Step 8:

[0897] The terminal provides the optimized business idea to the user, for example, by displaying the business idea on a screen or by providing it in a downloadable format, and the output at this point is the specific business idea provided to the user.

[0898] Market Research

[0899] Step 1:

[0900] The user inputs information about a specific market into the terminal. Specifically, the user inputs information such as the market name, target area, time range, etc. The input at this point is text data.

[0901] Step 2:

[0902] The device sends the input information to an emotion engine for emotion recognition. Emotions are extracted from text data using natural language processing techniques. The output at this point is analyzed emotion data.

[0903] Step 3:

[0904] The device sends request information and emotion data to the server. This data transmission starts processing on the server side. The input at this point is a set of request information and emotion data.

[0905] Step 4:

[0906] The server collects market-related data from internal databases and external sources, such as market statistics and consumer trend information, and aggregates them. The output at this point is market-related data.

[0907] Step 5:

[0908] The server analyzes the collected data and uses generative AI models to create a detailed report. The output at this point is a report containing the analysis results.

[0909] Step 6:

[0910] The server optimizes the report based on the emotion data, for example if the user indicates anxiety it will create a report with a particularly detailed analysis. The output at this point is the optimized report.

[0911] Step 7:

[0912] The server returns the optimized report to the terminal. This data transmission prepares the report to be provided directly to the user. The output at this point is the optimized report.

[0913] Step 8:

[0914] The terminal provides an optimized report to the user, for example by displaying the report on the screen or by providing it in a downloadable format. The output at this point is a detailed report provided to the user.

[0915] Creating a business plan

[0916] Step 1:

[0917] The user inputs basic information about the new business into the terminal, such as the business description, target market, and competitive information. At this stage, the input is text data.

[0918] Step 2:

[0919] The device sends the input information to the emotion engine, which recognizes emotions. The emotion data is analyzed using natural language processing technology. The output at this point is the analyzed emotion data.

[0920] Step 3:

[0921] The device sends basic information and emotion data to the server. This data transmission starts processing on the server side. At this point, the input is a set of basic information and emotion data.

[0922] Step 4:

[0923] The server generates a business plan template based on the basic information. This template includes basic items such as market analysis, competitive analysis, and financial plan. The output at this point is a business plan template.

[0924] Step 5:

[0925] The server uses a generative AI model to create a detailed business plan based on the generated template. An example prompt is, "Please create a business plan for a new health food brand." The output at this point is a detailed business plan.

[0926] Step 6:

[0927] The server optimizes the business plan based on the sentiment data, for example, if the user expresses concerns, it creates a plan that specifically includes a risk analysis. The output at this point is an optimized business plan.

[0928] Step 7:

[0929] The server returns the optimized business plan to the terminal. This data transmission prepares the business plan to be provided directly to the user. The output at this point is the optimized business plan.

[0930] Step 8:

[0931] The terminal provides the optimized business plan to the user, for example, by displaying the plan on a screen or by providing it in a downloadable format. The output at this point is a specific business plan provided to the user.

[0932] Creating a marketing strategy

[0933] Step 1:

[0934] The user inputs basic information and marketing goals for the new project into the terminal, including the sales promotion plan, target market, advertising goals, etc. The input at this stage is text data.

[0935] Step 2:

[0936] The device sends the input information to the emotion engine, which recognizes emotions. The emotion data is analyzed using natural language processing technology. The output at this point is the analyzed emotion data.

[0937] Step 3:

[0938] The device sends basic information and emotion data to the server. This data transmission starts processing on the server side. At this point, the input is a set of basic information and emotion data.

[0939] Step 4:

[0940] The server collects historical campaign data and market trends from internal databases and external sources. The output at this point is the collected relevant data.

[0941] Step 5:

[0942] The server uses a generative AI model to create a marketing strategy. An example prompt is "Please create a marketing strategy for a new product launch." The output at this point is a detailed marketing strategy.

[0943] Step 6:

[0944] The server optimizes the marketing strategy based on the emotion data. For example, if the user expresses excitement, it adds a bold strategy. The output at this point is the optimized marketing strategy.

[0945] Step 7:

[0946] The server returns the optimized marketing strategy to the terminal. This data transmission prepares the strategy to be provided directly to the user. The output at this point is the optimized marketing strategy.

[0947] Step 8:

[0948] The terminal provides the optimized marketing strategy to the user, for example by displaying the strategy on a screen or by providing it in a downloadable format. The output at this point is the specific marketing strategy provided to the user.

[0949] Through these steps, the system provides optimal support based on the user's emotions, improving work efficiency.

[0950] (Application example 2)

[0951] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0952] Store managers are required to develop effective business strategies and implement measures within limited resources and time. However, the information gathering and planning required for this is cumbersome, and the results can be disappointing, especially since optimization is not based on the emotions of individual store managers. Therefore, there is a need for a system that can efficiently generate business ideas and optimize them while taking emotions into account.

[0953] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving basic information about a business idea from a user, means for collecting related data from an internal database and external sources, means for generating business ideas using a generation AI based on the collected data, means for providing the generated business idea to the user, and means for analyzing user emotions using an emotion engine and optimizing the generated business idea based on the emotion data. This enables managers of physical stores to quickly develop and implement optimized business ideas and strategies based on emotions.

[0954] 1. A "business idea" is a concept or plan for a new business that a user wants to start.

[0955] 2. "Basic information" refers to the basic data required to develop a business idea, as well as information about users' interests, target markets, and existing challenges.

[0956] 3. "Internal Database" means the collection of data stored within the System.

[0957] 4. "External Source" means a source of data collected from outside the System.

[0958] 5. "Emotion Engine" refers to a system component that analyzes user input data and recognizes their emotional state.

[0959] 6. "Generative AI" refers to artificial intelligence that uses large amounts of data to generate new content or ideas based on specific prompts.

[0960] 7. "Optimization" is the process of adjusting something to best suit a particular purpose or condition.

[0961] 8. "Market Data" means data such as statistics, consumer trends, and competitive analysis relating to a particular market.

[0962] 9. A "business plan template" is a basic business plan template for building a new business.

[0963] To implement this invention, it is important to build a system that combines generative AI and an emotion engine, allowing store managers to efficiently generate business ideas and provide plans optimized based on emotions.

[0964] System Configuration

[0965] The system consists of a terminal operated by the user, a server that processes data, and a generative AI and emotion engine for generating and optimizing business ideas.

[0966] Program Overview

[0967] 1. The terminal receives basic information about the business idea from the user.

[0968] 2. The terminal sends the received basic information to the server.

[0969] 3. Based on the received basic information, the server collects relevant data from its internal database and external sources.

[0970] 4. The server uses an emotion engine to analyze emotions from the user's basic information input.

[0971] 5. The server uses generative AI to generate business ideas based on the collected data and analyzed emotional data.

[0972] 6. The server optimizes the generated business ideas based on the emotion data.

[0973] 7. The server sends the optimized business idea to the terminal and provides it to the user.

[0974] Hardware and Software Use

[0975] This system uses the user's smartphone as the terminal. To process data and perform sentiment analysis, a server runs on a cloud platform such as Amazon Web Services (AWS). The generative AI uses the OpenAI API, and modules such as the "sentiment_analysis_module" for the sentiment engine and the "database_connector" for database connection are used.

[0976] Data processing and calculation

[0977] Basic information entered on the device is sent to the server as text data. The server then uses an emotion engine to perform sentiment analysis of the text data and recognize positive, negative, and neutral emotional states. Data collected from internal databases and external sources is normalized and aggregated in a database management system (DBMS). The generative AI generates prompt responses based on the data and further optimizes them based on the emotional data.

[0978] Examples of concrete examples and prompts

[0979] For example, if a user is looking for new business ideas for "summer sales promotions," they input basic information from their device. The server analyzes this information with an emotion engine, and if it determines that the user is expressing positive emotions, it uses generative AI to generate novel ideas such as "beach party-themed sales events."

[0980] An example of a prompt is:

[0981] Generate new business ideas for "Summer Sale Promotion" when users are feeling positive.

[0982] This allows store owners to quickly obtain business ideas that are optimized based on emotions, allowing them to plan and implement more effective strategies.

[0983] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0984] Step 1:

[0985] The user uses a terminal to input basic information about their business idea, including their interests, areas of interest, target market, and existing challenges. This input data is then passed on to the next step.

[0986] Step 2:

[0987] The device sends the basic information entered in step 1 to the server. The data is passed to the server in text format, and data analysis is performed based on this.

[0988] Step 3:

[0989] The server sends the received basic information to the emotion engine, which analyzes the user's emotions. The emotion engine analyzes the text data and outputs a positive, negative, or neutral emotional state. The analysis results are used in the next step.

[0990] Step 4:

[0991] The server collects relevant data from internal databases and external sources based on the basic information and sentiment analysis results. The collected data includes market trends and competitive information, and this data is normalized and aggregated in a database management system (DBMS). This processed data is used in the next step.

[0992] Step 5:

[0993] The server calls the generation AI based on the collected data and the results of sentiment analysis to generate new business ideas. Specific prompts are provided to the generation AI, and an example of a prompt is "Generate a new business idea for a 'summer sales promotion' when the user is feeling positive." The generation AI outputs new ideas based on this.

[0994] Step 6:

[0995] The server optimizes the generated business ideas based on the emotional data. For example, if the user shows positive emotions, it will adjust the idea to be more innovative. This optimized business idea is sent to the next step.

[0996] Step 7:

[0997] The server sends the optimized business idea to the terminal, which displays it to the user. The user can check the optimized business idea and use it to plan and execute a specific business strategy.

[0998] Through the above processing steps, brick-and-mortar store managers can efficiently generate business ideas and obtain optimized plans based on emotions.

[0999] 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.

[1000] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1001] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[1002] [Third embodiment]

[1003] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1004] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[1005] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1006] 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.

[1007] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1008] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1009] 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.

[1010] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1011] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1012] 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.

[1013] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1014] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[1015] This invention provides a system that utilizes generative AI to improve the operational efficiency of startup companies. This system enables users to efficiently generate business ideas, conduct market research, create business plans, and develop marketing strategies.

[1016] Specifically, the system works as follows:

[1017] Brainstorming business ideas

[1018] The user enters basic information about their business idea into the device, including areas of interest, target market, and existing challenges. The device then sends this information to the server, which collects relevant data from internal databases and external sources. Generative AI is then used to generate a business idea, which is then provided to the user by the server via the device. For example, if a user requests "new ideas for sustainable products," the server will suggest specific ideas such as "a fashion brand made from recycled materials."

[1019] Market Research

[1020] The user inputs information about the specific market they wish to research into their device. This information includes the target market, region, and time range. The device then sends this information to the server, which collects relevant market data from internal databases and external sources. The collected data is analyzed by the server and sent to the device in the form of a report, which is then displayed to the user. For example, if a user wants to research "demand for e-books in the Japanese market," the server will aggregate statistical data, consumer trends, and competitive analysis and provide it as a report.

[1021] Creating a business plan

[1022] The user enters basic information about their new business into the device. The device then sends this information to the server, which then uses it to generate a business plan template. A detailed business plan is created using generative AI and provided to the user by the server via the device. For example, if a user enters detailed information about "launching a new health food brand," the server will create a business plan that includes market analysis, target market, competitive analysis, and financial plan.

[1023] Creating a marketing strategy

[1024] The user enters basic information about a new project and its marketing goals into the device. The device then sends the information to the server, which analyzes past campaign data and market trends. An optimal marketing strategy is created using generative AI and provided to the user by the server via the device. For example, if the user requests a "marketing strategy for a new product launch," the server will propose a plan that includes a social media strategy, advertising campaign, and PR activities.

[1025] This system allows startups to efficiently utilize their limited resources and time, enabling them to rapidly expand their business. The system, which utilizes generative AI, supports the growth of companies by quickly responding to user needs and providing high-quality output.

[1026] The processing flow will be explained below.

[1027] Specific steps for brainstorming business ideas

[1028] Step 1:

[1029] The user enters basic information about their business idea (area of ​​interest, target market, existing challenges, etc.) into the terminal.

[1030] Step 2:

[1031] The terminal sends the entered basic information to the server.

[1032] Step 3:

[1033] The server collects relevant data from internal databases and external sources (Internet, statistical data, etc.).

[1034] Step 4:

[1035] Multiple business ideas are generated using generative AI based on the relevant data collected by the server.

[1036] Step 5:

[1037] The server transmits the generated business idea to the terminal.

[1038] Step 6:

[1039] The user checks the provided business idea on the terminal.

[1040] Specific steps in market research

[1041] Step 1:

[1042] The user inputs information about a specific market (market name, target area, time range, etc.) into the terminal.

[1043] Step 2:

[1044] The terminal sends the request information to the server.

[1045] Step 3:

[1046] The server collects relevant market data from internal databases and external sources (statistical data, research reports, etc.).

[1047] Step 4:

[1048] The server analyzes the collected market data.

[1049] Step 5:

[1050] The server compiles the analysis results into a report.

[1051] Step 6:

[1052] The server sends the generated report to the device.

[1053] Step 7:

[1054] The user checks the report on the device.

[1055] Specific steps in creating a business plan

[1056] Step 1:

[1057] The user enters basic information about the new business (business details, target market, competitive information, etc.) into the terminal.

[1058] Step 2:

[1059] The terminal sends the entered basic information to the server.

[1060] Step 3:

[1061] The server generates a business plan template based on the received information.

[1062] Step 4:

[1063] The server uses generated AI to create a detailed business plan (market analysis, target market, competitive analysis, financial plan, etc.).

[1064] Step 5:

[1065] The server transmits the generated business plan to the terminal.

[1066] Step 6:

[1067] The user checks the detailed business plan on the device.

[1068] Specific process steps for creating a marketing strategy

[1069] Step 1:

[1070] The user enters basic information and marketing goals for the new project into the terminal.

[1071] Step 2:

[1072] The terminal sends the entered basic information to the server.

[1073] Step 3:

[1074] The server collects and analyzes past campaign data and market trends from internal databases and external sources.

[1075] Step 4:

[1076] The server uses generative AI to create the optimal marketing strategy.

[1077] Step 5:

[1078] The server transmits the generated marketing strategy to the terminal.

[1079] Step 6:

[1080] The user checks the marketing strategy on the device.

[1081] Specific steps for fundraising

[1082] Step 1:

[1083] The user inputs their fundraising request (amount of funds needed, outline of business plan, etc.) into the terminal.

[1084] Step 2:

[1085] The terminal transmits the input request to the server.

[1086] Step 3:

[1087] The server collects and analyzes investor information and past fundraising cases from internal databases and external sources.

[1088] Step 4:

[1089] Based on the analysis results, the server generates a list of fundraising methods and investors suitable for the user.

[1090] Step 5:

[1091] The server sends the generated fundraising methods and investor list to the terminal.

[1092] Step 6:

[1093] The user checks fundraising methods and investor list on the terminal.

[1094] Example 1

[1095] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1096] Traditional business processes in startups consume a lot of time and resources and lack efficiency. In particular, key tasks such as brainstorming business ideas, market research, creating business plans, and formulating marketing strategies require a great deal of effort, making it difficult to rapidly develop a business. Furthermore, these processes rely on experience and expertise, which is a major barrier faced by startups. To solve these challenges, a system utilizing generative AI is needed.

[1097] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1098] In this invention, the server includes means for receiving basic information about a business idea from a user, means for collecting related data from an internal database and external sources, means for generating business ideas using a generative AI model based on the collected data, and means for providing the generated business ideas to the user, thereby enabling the user to quickly obtain high-quality business ideas.

[1099] The server also includes means for receiving information about a particular market from a user, means for collecting market data from an internal database and external sources, and means for analyzing the collected data and providing it in the form of a report, thereby enabling the user to quickly gain in-depth insight into the market.

[1100] Furthermore, the server includes means for receiving basic information about a new business from a user, means for generating a business plan template based on the received information, and means for generating a detailed business plan using a generative AI model and providing the detailed business plan to the user, thereby enabling startup companies to create detailed business plans while saving time and resources.

[1101] Finally, the server includes means for receiving basic information and marketing goals for a new project from a user, means for analyzing past campaign data and market trends, and means for generating a marketing strategy using a generative AI model and providing it to the user, thereby enabling the user to quickly develop and implement an effective marketing strategy.

[1102] "User" means any person who uses the System to generate business ideas, market research, business plans, or marketing strategies.

[1103] "Basic information about business ideas" refers to the basic information required to generate business ideas, such as the user's areas of interest, target market, and existing challenges.

[1104] "Database" refers to an information resource that stores and manages relevant data for generating business ideas, market research, business plans, and marketing strategies.

[1105] "External sources" refer to data providers or information sources that exist outside the system, such as public information on the Internet or APIs.

[1106] A "generative AI model" refers to an artificial intelligence algorithm that generates new ideas, strategies, reports, etc. based on given prompts.

[1107] "Prompt" refers to the instructions a generative AI model uses to generate new ideas and data.

[1108] "Report format" refers to the document format in which collected and analyzed data is provided to the user.

[1109] A "business plan template" refers to a template or format that makes creating a business plan more efficient.

[1110] "Marketing objectives" refer to the specific goals to be achieved regarding promotional activities and market development for a new project.

[1111] "Historical Campaign Data" means data containing details of or results from previously conducted marketing or promotional activities.

[1112] "Market trends" refers to data that includes current trends and future predictions for a particular market.

[1113] The present invention relates to a system that utilizes generative AI to enable users to efficiently generate business ideas, conduct market research, create business plans, and develop marketing strategies. Specific embodiments of this system are described below.

[1114] Brainstorming business ideas

[1115] The user enters basic information about their business idea into the device. The entered information is sent to the server via a REST API. The server collects relevant data from an internal database (e.g., an RDBMS) and external sources (e.g., APIs on the Internet). Specific examples include data collection using Amazon Aurora and Google News API. Based on the collected data, the server inputs a prompt to a generative AI model (e.g., GPT-4) saying, "Please propose new ideas for sustainable products." The server then sends the generated ideas (e.g., "A fashion brand made from recycled materials") to the device for the user to confirm.

[1116] Market Research

[1117] The user inputs the market information they wish to research into their device. This includes the target market, region, and time range. The input information is sent to the server via a REST API. The server calls external data sources such as the Statista API to collect e-book market data. Based on the collected data, the server inputs a prompt to the generation AI: "Please create a detailed report on e-book demand in the Japanese market." The server then sends the generated report to the device, where the user can review it.

[1118] Creating a business plan

[1119] The user enters basic information about a new business into the device. The entered information is sent to the server via a REST API. The server generates a business plan template based on the received information and inputs it into the generative AI model. For example, a user enters detailed information about "launching a new health food brand" and inputs the prompt "Please create a business plan for the health food brand" into the generative AI. The server then sends a detailed business plan, including the target market, competitive analysis, and financial plan, to the device for the user to review.

[1120] Creating a marketing strategy

[1121] The user enters basic information and marketing goals for a new project into the device. The entered information is sent to the server via a REST API. The server collects and analyzes past campaign data and market trends. To do this, it uses the AdEspresso API, among others. Based on the collected data, the server inputs a prompt to the generation AI: "Please propose the optimal marketing strategy for the new product launch." The server then sends the generated marketing strategy (e.g., social media strategy, advertising campaign, PR activities) to the device, where the user can confirm it.

[1122] This system allows startups to efficiently utilize their limited resources and time, enabling them to rapidly expand their business. By utilizing generative AI, they can quickly respond to user needs and provide high-quality output.

[1123] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1124] Brainstorming business ideas

[1125] Step 1:

[1126] The user enters basic information about their business idea into the device, such as areas of interest, target market, existing challenges, etc. The entered information is saved in JSON format on the device.

[1127] Step 2:

[1128] The device sends the input information to the server via the REST API. At this time, the device sends JSON format data to the server using an HTTP POST request.

[1129] Step 3:

[1130] The server receives the information you enter and collects relevant data from internal databases (e.g., RDBMS) and external sources (e.g., Google News API), which are then stored on the server in a structured data format.

[1131] Step 4:

[1132] Based on the data collected by the server, a prompt sentence is input to the generative AI model (e.g., GPT-4). Specifically, the prompt sentence is input as "Please propose new ideas for sustainable products."

[1133] Step 5:

[1134] The server receives business ideas (e.g., "a fashion brand made from recycled materials") obtained from the generative AI model and organizes the data in JSON format.

[1135] Step 6:

[1136] The server sends the generated business idea to the terminal, where the generated idea is sent as an HTTP response.

[1137] Step 7:

[1138] The user checks the generated business idea on the device's display screen, and the device displays the received data in UI elements.

[1139] Market Research

[1140] Step 1:

[1141] The user inputs the market information they wish to research (e.g., target market, region, time range) into the terminal. The input information is saved in JSON format on the terminal.

[1142] Step 2:

[1143] The device sends the entered information to the server via the REST API. The device sends JSON format data to the server via an HTTP POST request.

[1144] Step 3:

[1145] Based on the information received, the server collects relevant market data from external data sources such as the Statista API, and stores the collected data in a structured data format on the server.

[1146] Step 4:

[1147] The server analyzes the collected data and inputs a prompt to the generation AI: "Please create a detailed report on the demand for e-books in the Japanese market."

[1148] Step 5:

[1149] The server receives the generated report and organizes the data in JSON format.

[1150] Step 6:

[1151] The server sends the generated report to the terminal as an HTTP response.

[1152] Step 7:

[1153] The user checks the generated report on the device's display screen, and the device displays the received data in UI elements.

[1154] Creating a business plan

[1155] Step 1:

[1156] The user enters basic information about their new business into the device, including the business concept, target market, and competitors. The information is then saved in JSON format on the device.

[1157] Step 2:

[1158] The device sends the entered information to the server via the REST API. The device sends JSON format data to the server via an HTTP POST request.

[1159] Step 3:

[1160] The server generates a business plan template based on the received information and stores the generated template on the server.

[1161] Step 4:

[1162] Based on the generated template, the server inputs the prompt statement "Please create a business plan for a health food brand" into the generative AI model.

[1163] Step 5:

[1164] The server receives the results from the generative AI model and adds details to the business plan, including target markets, competitive analysis, and financial plans.

[1165] Step 6:

[1166] The server organizes the generated business plan in JSON format and sends it to the terminal. At this time, the generated business plan is sent to the terminal as an HTTP response.

[1167] Step 7:

[1168] The user checks the generated business plan on the device's display screen, and the device displays the received data in UI elements.

[1169] Creating a marketing strategy

[1170] Step 1:

[1171] The user enters basic information about the new project and marketing goals into the device, such as the product name, target audience, budget range, etc. The entered information is saved in JSON format on the device.

[1172] Step 2:

[1173] The device sends the entered information to the server via the REST API. The device sends JSON format data to the server via an HTTP POST request.

[1174] Step 3:

[1175] Based on the information received, the server collects and analyzes past campaign data and market trends. For this purpose, it uses external data sources such as the AdEspresso API. The collected data is stored on the server.

[1176] Step 4:

[1177] Based on the data collected and analyzed by the server, the generative AI model is given a prompt: "Please suggest the optimal marketing strategy for the launch of a new product."

[1178] Step 5:

[1179] The server receives the results from the generative AI model and designs a detailed marketing strategy, including social media strategies, advertising campaigns, and PR activities.

[1180] Step 6:

[1181] The server organizes the generated marketing strategy in JSON format and sends it to the terminal. At this time, the generated strategy is sent to the terminal as an HTTP response.

[1182] Step 7:

[1183] The user checks the generated marketing strategy on the device's display screen, and the device displays the received data in UI elements.

[1184] (Application example 1)

[1185] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1186] For startups, it is extremely important to develop business ideas and marketing strategies while efficiently utilizing limited resources and time. However, with previous systems, users needed a great deal of effort and specialized knowledge to plan and create effective advertising campaigns. Furthermore, existing methods made it difficult to collect and analyze market information in real time and quickly generate advertising campaign plans. This led to delays in business development and the risk of losing competitiveness.

[1187] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1188] In this invention, the server includes means for receiving basic information about a business idea from a user, means for collecting related data from an internal database and external sources, means for generating business ideas using a generation AI based on the collected data, means for providing the generated business ideas to the user, and means for generating an advertising campaign plan based on advertising campaign requirements entered by the user. This allows users to efficiently obtain market information and quickly develop optimal advertising strategies. This allows startup companies to make the most of their limited resources and develop competitive businesses.

[1189] "User" means an individual or organization that uses a particular system or service.

[1190] A "business idea" is a concept or plan for a new business, product, or service.

[1191] An "internal database" is a database that accumulates data managed within a company.

[1192] "External sources" refer to data or information sources that can be obtained from outside.

[1193] "Relevant data" refers to information or numerical data that is relevant to a particular topic or purpose.

[1194] "Generative AI" refers to systems or models that use artificial intelligence technology to generate new ideas and information.

[1195] An "advertising campaign" is a series of advertising activities designed to promote a particular product or service.

[1196] A "means" is a method or device used to achieve a particular purpose.

[1197] A "server" is a computer that provides data and services over a network.

[1198] "Requirements" are the conditions or criteria necessary to carry out a particular task or project.

[1199] "Data collection" is the process of gathering specific information or data.

[1200] "Market information" refers to data such as market conditions, trends, and competitive information.

[1201] An "advertising strategy" is a plan or method for successfully running a particular advertising campaign.

[1202] This invention is a system that allows users to freely generate business ideas and advertising campaigns and quickly and effectively realize them. This system consists of a server, a terminal, and a generative AI model. The following explains the details of each component and how they interact with each other.

[1203] Data input from the user

[1204] Users input basic information about their business idea and advertising campaign through a device such as a smartphone. For example, users input the requirements for their advertising campaign (purpose, market, target audience, format, period, budget). For example,

[1205] Advertising campaign requirements:

[1206] Purpose: Increase awareness

[1207] Market: Japanese market

[1208] Target Audience: Young people (18-25 years old)

[1209] Format: Social Media Ad

[1210] Duration: 3 months

[1211] Budget: 5 million yen

[1212] Data submission and collection

[1213] The device sends user input data to a server, which then collects relevant data from an internal database and external sources. This process utilizes natural language processing (NLP) and machine learning algorithms. Specific technologies include accessing external data sources via APIs to obtain the latest market information and trend data.

[1214] Idea generation and campaign proposals using generative AI

[1215] The server uses generative AI models based on the collected data to generate business ideas and elements of advertising campaigns. The generated ideas and strategies are then returned to the device and provided to the user.

[1216] For example, a generative AI model might work like this:

[1217] Business idea generation: Based on the basic information entered by the user, the server generates specific ideas such as "a fashion brand made from recycled materials."

[1218] Advertising campaign generation: The server generates a campaign plan (keyword selection, ad copy, image and video themes, distribution method, etc.) based on the advertising requirements entered by the user.

[1219] Report Generation and Simulation

[1220] The advertising campaign plan created by the generative AI is simulated to show expected results, and the results are provided to the user as a report. This simulation is performed by analyzing past campaign data and market trends.

[1221] Specific examples

[1222] If a user wants a "marketing strategy for a new product launch," they can send the following prompt to the generative AI model:

[1223] New product launch marketing strategy:

[1224] Target market: North American market

[1225] Target audience: IT engineers aged 25-35

[1226] Primary goal: 1,000 sales in the first month

[1227] Budget: 10 million yen

[1228] Based on this input, the generative AI will suggest optimal marketing strategies (social media strategies, advertising campaigns, PR activities, etc.).

[1229] This allows users to quickly and effectively develop business ideas and advertising strategies with minimal expertise or effort, helping startups maximize their limited resources and increase their competitiveness.

[1230] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1231] Step 1:

[1232] The user inputs the requirements for the advertising campaign. The user inputs basic information such as the advertising objective, market, target audience, format, period, budget, etc. in text format via a device such as a smartphone. This input data is used in the next processing step.

[1233] Step 2:

[1234] The device sends the input data to the server. The advertising campaign requirements entered by the user are recorded on the device and transmitted to the server using a secure communication protocol (e.g. HTTPS). This data forms the basis for collecting related data on the server.

[1235] Step 3:

[1236] The server collects relevant data from internal databases and external sources. The server uses NLP and web scraping techniques to gather the necessary information from internal databases (e.g., past advertising campaign data) and external sources (e.g., market research reports and public data). This data is used as training material for the generative AI model.

[1237] Step 4:

[1238] The server analyzes the collected data and generates an advertising campaign plan using a generative AI model. The server inputs the preprocessed data into a generative AI model (e.g., OpenAI's GPT series) to generate each element of the advertising campaign (keywords, ad copy, image theme, distribution method, etc.) based on the user's requirements and market insights. This generated plan is the output presented to the user.

[1239] Step 5:

[1240] The server sends the generated advertising campaign plan to the device. The advertising campaign plan created by the generative AI model is returned to the user's device, again using a secure communication protocol. The device receives this data and displays it through a user interface.

[1241] Step 6:

[1242] The user checks the generated advertising campaign plan. The user checks the advertising campaign plan displayed on the terminal screen and makes corrections or feedback as necessary. This feedback is sent back to the server for further optimization.

[1243] Step 7:

[1244] The server simulates the advertising campaign plan and generates the results in a report. The server simulates the effectiveness of the generated advertising campaign plan based on past data and trends, and summarizes the results in a report. This report is provided to the user and is useful for making final campaign decisions.

[1245] Step 8:

[1246] The server sends the final report to the terminal. The generated simulation report is then sent to the user's terminal again using a secure communication protocol, and the user can review this report and proceed with preparations for the actual advertising campaign.

[1247] These steps provide a system that allows users to efficiently plan and execute advertising campaigns without requiring specialized knowledge.

[1248] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1249] This invention provides a system that combines generative AI and an emotion engine to improve the operational efficiency of startup companies. This system enables users to efficiently generate business ideas, conduct market research, create business plans, and develop marketing strategies, and provides optimized results by taking user emotions into account.

[1250] Specifically, the system works as follows:

[1251] Brainstorming business ideas

[1252] The user enters basic information about their business idea (areas of interest, target market, existing challenges, etc.) into the device. At this time, the emotion engine analyzes the user's input and recognizes emotions. The device then sends the basic information and emotion data to the server, which collects related data from an internal database and external sources. Generative AI is used to generate business ideas, and the server provides optimized business ideas based on the emotion data to the user via the device. For example, if a user requests "new ideas for sustainable products," the server will suggest specific ideas such as "a fashion brand made from recycled materials," but if the user is expressing positive emotions, it will suggest more innovative ideas.

[1253] Market Research

[1254] The user inputs information about a specific market (such as the market name, target region, and time range) into the device. The emotion engine then analyzes the user's input and recognizes emotions. The device then sends the request information and emotion data to the server, which then collects relevant market data from internal databases and external sources. The collected data is analyzed by the server and sent to the device in the form of a report optimized based on the emotion data, which is then displayed to the user. For example, if a user wants to research "demand for e-books in the Japanese market," the server aggregates statistical data, consumer trends, and competitive analysis, and provides a particularly detailed analysis if the user expresses concerns.

[1255] Creating a business plan

[1256] The user enters basic information about their new business (business details, target market, competitive information, etc.) into the device. At this time, an emotion engine analyzes the user's input and recognizes emotions. The device then sends the basic information and emotional data to the server, which then generates a business plan template based on that information. A detailed business plan is created using generative AI, and the server provides the plan to the user via the device, adjusted based on the emotional data. For example, if a user enters detailed information about "launching a new health food brand," the server will create a business plan that includes market analysis, target market, competitive analysis, and financial plan, and will also include a risk analysis if the user expresses any concerns.

[1257] Creating a marketing strategy

[1258] The user enters basic information and marketing goals for a new project into the device. The emotion engine analyzes the user's input and recognizes emotions. The device then sends the basic information and emotion data to the server, which collects and analyzes past campaign data and market trends from internal databases and external sources. An optimal marketing strategy is created using generative AI, and the strategy, adjusted based on the emotion data, is provided to the user from the server via the device. For example, if the user requests a "marketing strategy for a new product launch," the server will propose plans for social media strategies, advertising campaigns, PR activities, and more, including bolder strategies if the user expresses excitement.

[1259] This system allows startups to efficiently utilize limited resources and time, and rapidly expand their business by receiving more personalized support based on emotions.The system, which utilizes generative AI and an emotion engine, supports the growth of companies by quickly responding to users' needs and emotions and providing high-quality output.

[1260] The processing flow will be explained below.

[1261] Specific steps for brainstorming business ideas

[1262] Step 1:

[1263] The user inputs basic information about their business idea (areas of interest, target market, existing challenges, etc.) into the device, and the emotion engine analyzes the user's input and recognizes their emotions.

[1264] Step 2:

[1265] The device transmits basic information and recognized emotion data to the server.

[1266] Step 3:

[1267] The server collects relevant data from internal databases and external sources (Internet, statistical data, etc.).

[1268] Step 4:

[1269] Generate multiple business ideas using generative AI based on relevant data collected by the server.

[1270] Step 5:

[1271] The server takes into account the user's emotional data to optimize the generated business ideas, for example, highlighting more innovative ideas if the user shows positive emotions.

[1272] Step 6:

[1273] The server sends the optimized business idea to the terminal.

[1274] Step 7:

[1275] The system checks the business ideas provided by the user on the device, and if the user responds positively, it will also suggest additional ideas.

[1276] Specific steps in market research

[1277] Step 1:

[1278] The user inputs information about a specific market (market name, target area, time range, etc.) into the terminal, and the emotion engine analyzes the user's input and recognizes emotions.

[1279] Step 2:

[1280] The device sends the request information and emotion data to the server.

[1281] Step 3:

[1282] The server collects relevant market data from internal databases and external sources (statistical data, research reports, etc.).

[1283] Step 4:

[1284] The server analyzes the collected market data.

[1285] Step 5:

[1286] The server takes into account the sentiment data and compiles the analysis results into a report, for example, including a detailed risk analysis if the user expresses anxiety.

[1287] Step 6:

[1288] The server sends the generated report to the device.

[1289] Step 7:

[1290] The user reviews the report on their device, and if they express anxiety, it includes specific suggestions for action.

[1291] Specific steps in creating a business plan

[1292] Step 1:

[1293] The user inputs basic information about their new business (business details, target market, competitive information, etc.) into the terminal. At this time, the emotion engine analyzes the user's input and recognizes their emotions.

[1294] Step 2:

[1295] The device sends the input basic information and emotion data to the server.

[1296] Step 3:

[1297] The server generates a business plan template based on the received information.

[1298] Step 4:

[1299] The server uses generative AI to create a detailed business plan and adjusts it based on the user's sentiment data, for example detailing a risk management plan if the user expresses concerns.

[1300] Step 5:

[1301] The server sends the adjusted business plan to the terminal.

[1302] Step 6:

[1303] Users review the detailed business plan on their devices and provide feedback on any areas of particular interest or concern.

[1304] Specific process steps for creating a marketing strategy

[1305] Step 1:

[1306] The user inputs basic information about the new project and its marketing goals into the device, and the emotion engine analyzes the user's input and recognizes their emotions.

[1307] Step 2:

[1308] The device sends the input basic information and emotion data to the server.

[1309] Step 3:

[1310] The server collects and analyzes past campaign data and market trends from internal databases and external sources.

[1311] Step 4:

[1312] The server uses generative AI to create optimal marketing strategies and adjusts them by taking into account sentiment data, for example, adopting a more aggressive strategy if users express excitement.

[1313] Step 5:

[1314] The server transmits the adjusted marketing strategy to the terminal.

[1315] Step 6:

[1316] Users can view marketing strategies on their devices and receive detailed recommendations for strategies that interest them.

[1317] Specific steps for fundraising

[1318] Step 1:

[1319] The user inputs their fundraising request (such as the amount of funds needed and an outline of their business plan) into the terminal. At this time, the emotion engine analyzes the user's input and recognizes their emotion.

[1320] Step 2:

[1321] The terminal transmits the input request and emotion data to the server.

[1322] Step 3:

[1323] The server collects and analyzes investor information and past fundraising cases from internal databases and external sources.

[1324] Step 4:

[1325] The server takes emotional data into account to generate a list of investors and fundraising methods suited to the user. For example, if the user shows signs of nervousness, it will recommend investors with relatively low risk.

[1326] Step 5:

[1327] The server sends the generated fundraising methods and investor list to the terminal.

[1328] Step 6:

[1329] Users can check fundraising methods and investor lists on their device, and if they're feeling nervous, they can also receive specific negotiation advice.

[1330] Example 2

[1331] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1332] Startups need to operate efficiently within limited resources and time constraints, but conventional systems have struggled to provide optimal support that takes user emotions into account. In particular, there has been no technology that provides results that reflect user emotions when generating business ideas, conducting market research, creating business plans, or formulating marketing strategies. Therefore, there is a need for personalized support based on user emotions to improve the quality of user decision-making.

[1333] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for receiving basic information from a user, means for analyzing the received input and recognizing emotions, means for transmitting the analysis results and related data to the server, means for collecting related data from an internal database and external sources, means for processing the collected data using a generative AI model, means for optimizing the generated results based on emotion data, and means for providing the optimized results to the user. This makes it possible to create optimal business ideas, market research, business plans, and marketing strategies based on user emotions.

[1334] A "user" is an entity that uses this system to develop business ideas, market research, business plans, or marketing strategies.

[1335] "Basic information" refers to input data about a business provided by a user, including business details, target market, competitive information, and the like.

[1336] "Emotion data" is data that indicates the user's emotional state, analyzed by the emotion engine based on the user's input.

[1337] A "terminal" is a hardware or software device through which a user interacts with the system.

[1338] The "server" is the central device that executes various processes in this system and collects, analyzes, generates, and optimizes data.

[1339] "Generative AI model" refers to an artificial intelligence model that automatically generates business ideas, market research reports, business plans, or marketing strategies based on user requests.

[1340] "Internal Database" means a collection of information stored within the server that the system uses to gather relevant data needed.

[1341] "External Source" means an external information source, other than the internal database, that the system connects to to gather relevant data.

[1342] "Optimization" refers to the process of adjusting a generated business idea, report, business plan, or marketing strategy based on user sentiment data to make it more effective.

[1343] "Analysis" refers to the process of processing received user input data to recognize its content and sentiment.

[1344] A "report" is output data in document format that organizes and presents the results of market research, etc.

[1345] This invention provides a system that combines a generative AI model and an emotion engine to improve the operational efficiency of startup companies. This system takes user emotions into account and provides optimized results in generating business ideas, conducting market research, creating business plans, and formulating marketing strategies.

[1346] System configuration

[1347] The system consists of a device used by the user, a server that analyzes and generates data, and an internal database and external sources. Basic business information provided by the user is received by the device, and its content and emotional data are analyzed. The analyzed data is sent to the server, which collects related data from the internal database and external sources. The collected data is processed by the server, and the required output is generated using a generative AI model. This output is optimized based on the user's emotional data and provided to the user via the device.

[1348] Brainstorming business ideas

[1349] When a user enters basic information about their business idea into the device, the emotion engine analyzes the input and recognizes emotions. The basic information along with the emotion data is sent to the server, which collects relevant data from its internal database and external sources. The server uses a generative AI model to generate business ideas and provides them to the user via the device, optimized based on the emotion data.

[1350] For example, if a user requests "new ideas for sustainable products," specific suggestions such as "fashion brands that use recycled materials" may be given. An example of a prompt for the generative AI model is "Please generate new business ideas for sustainable products."

[1351] Market Research

[1352] When a user inputs information about a specific market into the terminal, the emotion engine analyzes the input and recognizes emotions. The request information along with the emotion data is sent to the server, which collects relevant market data from internal databases and external sources. The server analyzes the collected data and generates an optimized report based on the emotion data, which is then provided to the user via the terminal.

[1353] For example, if a user wants to research "demand for e-books in the Japanese market," a report containing statistical data, consumer trends, and competitive analysis will be generated. An example of a prompt for the generative AI model is, "Please research demand for e-books in the Japanese market and create a detailed report."

[1354] Creating a business plan

[1355] When a user enters basic information about a new business into the device, the emotion engine analyzes the input and recognizes emotions. The basic information along with the emotion data is sent to the server, which then generates a basic business plan based on a template. A generative AI model is then used to create a detailed business plan, which is then adjusted based on the emotion data and provided to the user via the device.

[1356] For example, if a user enters details about "launching a new health food brand," a business plan will be created that includes market analysis, financial planning, and competitive analysis. An example prompt for the generative AI model is, "Please create a business plan for a new health food brand."

[1357] Creating a marketing strategy

[1358] When a user enters basic information about a new project and marketing goals into their device, the emotion engine analyzes the input and recognizes emotions. The basic information along with the emotion data is sent to a server, which then collects and analyzes past campaign data and market trends from internal databases and external sources. An optimal marketing strategy is created using a generative AI model, and the strategy, adjusted based on the emotion data, is provided to the user via their device.

[1359] For example, if a user requests a "marketing strategy for a new product launch," plans for a social media strategy, advertising campaign, and PR activities will be suggested. An example of a prompt for the generative AI model is, "Please create a marketing strategy for a new product launch."

[1360] This system allows startups to utilize limited resources and time and rapidly expand their business by receiving optimal support based on user emotions. Utilizing a generative AI model and emotion engine, the system responds quickly to user needs and emotions, providing high-quality output and supporting business growth.

[1361] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1362] Brainstorming business ideas

[1363] Step 1:

[1364] The user inputs basic information about their business idea into the device, such as areas of interest, target market, existing challenges, etc. The input at this stage is text data.

[1365] Step 2:

[1366] The device sends the input information to an emotion engine to recognize emotions. For example, it uses natural language processing technology to analyze text data and extract emotions such as positive and negative. The output at this point is analyzed emotion data.

[1367] Step 3:

[1368] The device sends basic information and emotion data to the server. This data transmission allows the server to start the necessary processing. At this point, the input is a set of basic information and emotion data.

[1369] Step 4:

[1370] The server collects relevant data from internal databases and external sources, for example, market data and trend information relevant to the business, and consolidates this data. The output at this point is the collected relevant data.

[1371] Step 5:

[1372] The server uses a generative AI model to generate business ideas based on the collected data. Specifically, it gives the AI ​​model a prompt to start the idea generation process. An example of a prompt is, "Please generate a new business idea for a sustainable product." The output at this point is the generated business idea.

[1373] Step 6:

[1374] The server optimizes the generated business ideas based on the sentiment data. For example, if the sentiment is positive, it adds novel ideas, and if it is negative, it generates ideas that minimize risk. The output at this point is an optimized business idea.

[1375] Step 7:

[1376] The server returns the optimized business idea to the terminal. This data transmission prepares the idea to be presented directly to the user. The output at this point is the optimized business idea.

[1377] Step 8:

[1378] The terminal provides the optimized business idea to the user, for example, by displaying the business idea on a screen or by providing it in a downloadable format, and the output at this point is the specific business idea provided to the user.

[1379] Market Research

[1380] Step 1:

[1381] The user inputs information about a specific market into the terminal. Specifically, the user inputs information such as the market name, target area, time range, etc. The input at this point is text data.

[1382] Step 2:

[1383] The device sends the input information to an emotion engine for emotion recognition. Emotions are extracted from text data using natural language processing techniques. The output at this point is analyzed emotion data.

[1384] Step 3:

[1385] The device sends request information and emotion data to the server. This data transmission starts processing on the server side. The input at this point is a set of request information and emotion data.

[1386] Step 4:

[1387] The server collects market-related data from internal databases and external sources, such as market statistics and consumer trend information, and aggregates them. The output at this point is market-related data.

[1388] Step 5:

[1389] The server analyzes the collected data and uses generative AI models to create a detailed report. The output at this point is a report containing the analysis results.

[1390] Step 6:

[1391] The server optimizes the report based on the emotion data, for example if the user indicates anxiety it will create a report with a particularly detailed analysis. The output at this point is the optimized report.

[1392] Step 7:

[1393] The server returns the optimized report to the terminal. This data transmission prepares the report to be provided directly to the user. The output at this point is the optimized report.

[1394] Step 8:

[1395] The terminal provides an optimized report to the user, for example by displaying the report on the screen or by providing it in a downloadable format. The output at this point is a detailed report provided to the user.

[1396] Creating a business plan

[1397] Step 1:

[1398] The user inputs basic information about the new business into the terminal, such as the business description, target market, and competitive information. At this stage, the input is text data.

[1399] Step 2:

[1400] The device sends the input information to the emotion engine, which recognizes emotions. The emotion data is analyzed using natural language processing technology. The output at this point is the analyzed emotion data.

[1401] Step 3:

[1402] The device sends basic information and emotion data to the server. This data transmission starts processing on the server side. At this point, the input is a set of basic information and emotion data.

[1403] Step 4:

[1404] The server generates a business plan template based on the basic information. This template includes basic items such as market analysis, competitive analysis, and financial plan. The output at this point is a business plan template.

[1405] Step 5:

[1406] The server uses a generative AI model to create a detailed business plan based on the generated template. An example prompt is, "Please create a business plan for a new health food brand." The output at this point is a detailed business plan.

[1407] Step 6:

[1408] The server optimizes the business plan based on the sentiment data, for example, if the user expresses concerns, it creates a plan that specifically includes a risk analysis. The output at this point is an optimized business plan.

[1409] Step 7:

[1410] The server returns the optimized business plan to the terminal. This data transmission prepares the business plan to be provided directly to the user. The output at this point is the optimized business plan.

[1411] Step 8:

[1412] The terminal provides the optimized business plan to the user, for example, by displaying the plan on a screen or by providing it in a downloadable format. The output at this point is a specific business plan provided to the user.

[1413] Creating a marketing strategy

[1414] Step 1:

[1415] The user inputs basic information and marketing goals for the new project into the terminal, including the sales promotion plan, target market, advertising goals, etc. The input at this stage is text data.

[1416] Step 2:

[1417] The device sends the input information to the emotion engine, which recognizes emotions. The emotion data is analyzed using natural language processing technology. The output at this point is the analyzed emotion data.

[1418] Step 3:

[1419] The device sends basic information and emotion data to the server. This data transmission starts processing on the server side. At this point, the input is a set of basic information and emotion data.

[1420] Step 4:

[1421] The server collects historical campaign data and market trends from internal databases and external sources. The output at this point is the collected relevant data.

[1422] Step 5:

[1423] The server uses a generative AI model to create a marketing strategy. An example prompt is "Please create a marketing strategy for a new product launch." The output at this point is a detailed marketing strategy.

[1424] Step 6:

[1425] The server optimizes the marketing strategy based on the emotion data. For example, if the user expresses excitement, it adds a bold strategy. The output at this point is the optimized marketing strategy.

[1426] Step 7:

[1427] The server returns the optimized marketing strategy to the terminal. This data transmission prepares the strategy to be provided directly to the user. The output at this point is the optimized marketing strategy.

[1428] Step 8:

[1429] The terminal provides the optimized marketing strategy to the user, for example by displaying the strategy on a screen or by providing it in a downloadable format. The output at this point is the specific marketing strategy provided to the user.

[1430] Through these steps, the system provides optimal support based on the user's emotions, improving work efficiency.

[1431] (Application example 2)

[1432] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1433] Store managers are required to develop effective business strategies and implement measures within limited resources and time. However, the information gathering and planning required for this is cumbersome, and the results can be disappointing, especially since optimization is not based on the emotions of individual store managers. Therefore, there is a need for a system that can efficiently generate business ideas and optimize them while taking emotions into account.

[1434] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving basic information about a business idea from a user, means for collecting related data from an internal database and external sources, means for generating business ideas using a generation AI based on the collected data, means for providing the generated business idea to the user, and means for analyzing user emotions using an emotion engine and optimizing the generated business idea based on the emotion data. This enables managers of physical stores to quickly develop and implement optimized business ideas and strategies based on emotions.

[1435] 1. A "business idea" is a concept or plan for a new business that a user wants to start.

[1436] 2. "Basic information" refers to the basic data required to develop a business idea, as well as information about users' interests, target markets, and existing challenges.

[1437] 3. "Internal Database" means the collection of data stored within the System.

[1438] 4. "External Source" means a source of data collected from outside the System.

[1439] 5. "Emotion Engine" refers to a system component that analyzes user input data and recognizes their emotional state.

[1440] 6. "Generative AI" refers to artificial intelligence that uses large amounts of data to generate new content or ideas based on specific prompts.

[1441] 7. "Optimization" is the process of adjusting something to best suit a particular purpose or condition.

[1442] 8. "Market Data" means data such as statistics, consumer trends, and competitive analysis relating to a particular market.

[1443] 9. A "business plan template" is a basic business plan template for building a new business.

[1444] To implement this invention, it is important to build a system that combines generative AI and an emotion engine, allowing store managers to efficiently generate business ideas and provide plans optimized based on emotions.

[1445] System Configuration

[1446] The system consists of a terminal operated by the user, a server that processes data, and a generative AI and emotion engine for generating and optimizing business ideas.

[1447] Program Overview

[1448] 1. The terminal receives basic information about the business idea from the user.

[1449] 2. The terminal sends the received basic information to the server.

[1450] 3. Based on the received basic information, the server collects relevant data from its internal database and external sources.

[1451] 4. The server uses an emotion engine to analyze emotions from the user's basic information input.

[1452] 5. The server uses generative AI to generate business ideas based on the collected data and analyzed emotional data.

[1453] 6. The server optimizes the generated business ideas based on the emotion data.

[1454] 7. The server sends the optimized business idea to the terminal and provides it to the user.

[1455] Hardware and Software Use

[1456] This system uses the user's smartphone as the terminal. To process data and perform sentiment analysis, a server runs on a cloud platform such as Amazon Web Services (AWS). The generative AI uses the OpenAI API, and modules such as the "sentiment_analysis_module" for the sentiment engine and the "database_connector" for database connection are used.

[1457] Data processing and calculation

[1458] Basic information entered on the device is sent to the server as text data. The server then uses an emotion engine to perform sentiment analysis of the text data and recognize positive, negative, and neutral emotional states. Data collected from internal databases and external sources is normalized and aggregated in a database management system (DBMS). The generative AI generates prompt responses based on the data and further optimizes them based on the emotional data.

[1459] Examples of concrete examples and prompts

[1460] For example, if a user is looking for new business ideas for "summer sales promotions," they input basic information from their device. The server analyzes this information with an emotion engine, and if it determines that the user is expressing positive emotions, it uses generative AI to generate novel ideas such as "beach party-themed sales events."

[1461] An example of a prompt is:

[1462] Generate new business ideas for "Summer Sale Promotion" when users are feeling positive.

[1463] This allows store owners to quickly obtain business ideas that are optimized based on emotions, allowing them to plan and implement more effective strategies.

[1464] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1465] Step 1:

[1466] The user uses a terminal to input basic information about their business idea, including their interests, areas of interest, target market, and existing challenges. This input data is then passed on to the next step.

[1467] Step 2:

[1468] The device sends the basic information entered in step 1 to the server. The data is passed to the server in text format, and data analysis is performed based on this.

[1469] Step 3:

[1470] The server sends the received basic information to the emotion engine, which analyzes the user's emotions. The emotion engine analyzes the text data and outputs a positive, negative, or neutral emotional state. The analysis results are used in the next step.

[1471] Step 4:

[1472] The server collects relevant data from internal databases and external sources based on the basic information and sentiment analysis results. The collected data includes market trends and competitive information, and this data is normalized and aggregated in a database management system (DBMS). This processed data is used in the next step.

[1473] Step 5:

[1474] The server calls the generation AI based on the collected data and the results of sentiment analysis to generate new business ideas. Specific prompts are provided to the generation AI, and an example of a prompt is "Generate a new business idea for a 'summer sales promotion' when the user is feeling positive." The generation AI outputs new ideas based on this.

[1475] Step 6:

[1476] The server optimizes the generated business ideas based on the emotional data. For example, if the user shows positive emotions, it will adjust the idea to be more innovative. This optimized business idea is sent to the next step.

[1477] Step 7:

[1478] The server sends the optimized business idea to the terminal, which displays it to the user. The user can check the optimized business idea and use it to plan and execute a specific business strategy.

[1479] Through the above processing steps, brick-and-mortar store managers can efficiently generate business ideas and obtain optimized plans based on emotions.

[1480] 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.

[1481] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1482] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1483] [Fourth embodiment]

[1484] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1485] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1486] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1487] 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.

[1488] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1489] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1490] 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.

[1491] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1492] 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.

[1493] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1494] 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.

[1495] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1496] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1497] This invention provides a system that utilizes generative AI to improve the operational efficiency of startup companies. This system enables users to efficiently generate business ideas, conduct market research, create business plans, and develop marketing strategies.

[1498] Specifically, the system works as follows:

[1499] Brainstorming business ideas

[1500] The user enters basic information about their business idea into the device, including areas of interest, target market, and existing challenges. The device then sends this information to the server, which collects relevant data from internal databases and external sources. Generative AI is then used to generate a business idea, which is then provided to the user by the server via the device. For example, if a user requests "new ideas for sustainable products," the server will suggest specific ideas such as "a fashion brand made from recycled materials."

[1501] Market Research

[1502] The user inputs information about the specific market they wish to research into their device. This information includes the target market, region, and time range. The device then sends this information to the server, which collects relevant market data from internal databases and external sources. The collected data is analyzed by the server and sent to the device in the form of a report, which is then displayed to the user. For example, if a user wants to research "demand for e-books in the Japanese market," the server will aggregate statistical data, consumer trends, and competitive analysis and provide it as a report.

[1503] Creating a business plan

[1504] The user enters basic information about their new business into the device. The device then sends this information to the server, which then uses it to generate a business plan template. A detailed business plan is created using generative AI and provided to the user by the server via the device. For example, if a user enters detailed information about "launching a new health food brand," the server will create a business plan that includes market analysis, target market, competitive analysis, and financial plan.

[1505] Creating a marketing strategy

[1506] The user enters basic information about a new project and its marketing goals into the device. The device then sends the information to the server, which analyzes past campaign data and market trends. An optimal marketing strategy is created using generative AI and provided to the user by the server via the device. For example, if the user requests a "marketing strategy for a new product launch," the server will propose a plan that includes a social media strategy, advertising campaign, and PR activities.

[1507] This system allows startups to efficiently utilize their limited resources and time, enabling them to rapidly expand their business. The system, which utilizes generative AI, supports the growth of companies by quickly responding to user needs and providing high-quality output.

[1508] The processing flow will be explained below.

[1509] Specific steps for brainstorming business ideas

[1510] Step 1:

[1511] The user enters basic information about their business idea (area of ​​interest, target market, existing challenges, etc.) into the terminal.

[1512] Step 2:

[1513] The terminal sends the entered basic information to the server.

[1514] Step 3:

[1515] The server collects relevant data from internal databases and external sources (Internet, statistical data, etc.).

[1516] Step 4:

[1517] Multiple business ideas are generated using generative AI based on the relevant data collected by the server.

[1518] Step 5:

[1519] The server transmits the generated business idea to the terminal.

[1520] Step 6:

[1521] The user checks the provided business idea on the terminal.

[1522] Specific steps in market research

[1523] Step 1:

[1524] The user inputs information about a specific market (market name, target area, time range, etc.) into the terminal.

[1525] Step 2:

[1526] The terminal sends the request information to the server.

[1527] Step 3:

[1528] The server collects relevant market data from internal databases and external sources (statistical data, research reports, etc.).

[1529] Step 4:

[1530] The server analyzes the collected market data.

[1531] Step 5:

[1532] The server compiles the analysis results into a report.

[1533] Step 6:

[1534] The server sends the generated report to the device.

[1535] Step 7:

[1536] The user checks the report on the device.

[1537] Specific steps in creating a business plan

[1538] Step 1:

[1539] The user enters basic information about the new business (business details, target market, competitive information, etc.) into the terminal.

[1540] Step 2:

[1541] The terminal sends the entered basic information to the server.

[1542] Step 3:

[1543] The server generates a business plan template based on the received information.

[1544] Step 4:

[1545] The server uses generated AI to create a detailed business plan (market analysis, target market, competitive analysis, financial plan, etc.).

[1546] Step 5:

[1547] The server transmits the generated business plan to the terminal.

[1548] Step 6:

[1549] The user checks the detailed business plan on the device.

[1550] Specific process steps for creating a marketing strategy

[1551] Step 1:

[1552] The user enters basic information and marketing goals for the new project into the terminal.

[1553] Step 2:

[1554] The terminal sends the entered basic information to the server.

[1555] Step 3:

[1556] The server collects and analyzes past campaign data and market trends from internal databases and external sources.

[1557] Step 4:

[1558] The server uses generative AI to create the optimal marketing strategy.

[1559] Step 5:

[1560] The server transmits the generated marketing strategy to the terminal.

[1561] Step 6:

[1562] The user checks the marketing strategy on the device.

[1563] Specific steps for fundraising

[1564] Step 1:

[1565] The user inputs their fundraising request (amount of funds needed, outline of business plan, etc.) into the terminal.

[1566] Step 2:

[1567] The terminal transmits the input request to the server.

[1568] Step 3:

[1569] The server collects and analyzes investor information and past fundraising cases from internal databases and external sources.

[1570] Step 4:

[1571] Based on the analysis results, the server generates a list of fundraising methods and investors suitable for the user.

[1572] Step 5:

[1573] The server sends the generated fundraising methods and investor list to the terminal.

[1574] Step 6:

[1575] The user checks fundraising methods and investor list on the terminal.

[1576] Example 1

[1577] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1578] Traditional business processes in startups consume a lot of time and resources and lack efficiency. In particular, key tasks such as brainstorming business ideas, market research, creating business plans, and formulating marketing strategies require a great deal of effort, making it difficult to rapidly develop a business. Furthermore, these processes rely on experience and expertise, which is a major barrier faced by startups. To solve these challenges, a system utilizing generative AI is needed.

[1579] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1580] In this invention, the server includes means for receiving basic information about a business idea from a user, means for collecting related data from an internal database and external sources, means for generating business ideas using a generative AI model based on the collected data, and means for providing the generated business ideas to the user, thereby enabling the user to quickly obtain high-quality business ideas.

[1581] The server also includes means for receiving information about a particular market from a user, means for collecting market data from an internal database and external sources, and means for analyzing the collected data and providing it in the form of a report, thereby enabling the user to quickly gain in-depth insight into the market.

[1582] Furthermore, the server includes means for receiving basic information about a new business from a user, means for generating a business plan template based on the received information, and means for generating a detailed business plan using a generative AI model and providing the detailed business plan to the user, thereby enabling startup companies to create detailed business plans while saving time and resources.

[1583] Finally, the server includes means for receiving basic information and marketing goals for a new project from a user, means for analyzing past campaign data and market trends, and means for generating a marketing strategy using a generative AI model and providing it to the user, thereby enabling the user to quickly formulate and implement an effective marketing strategy.

[1584] "User" means any person who uses the System to generate business ideas, market research, business plans, or marketing strategies.

[1585] "Basic information about business ideas" refers to the basic information required to generate business ideas, such as the user's areas of interest, target market, and existing challenges.

[1586] "Database" refers to an information resource that stores and manages relevant data for generating business ideas, market research, business plans, and marketing strategies.

[1587] "External sources" refer to data providers or information sources that exist outside the system, such as public information on the Internet or APIs.

[1588] A "generative AI model" refers to an artificial intelligence algorithm that generates new ideas, strategies, reports, etc. based on given prompts.

[1589] "Prompt" refers to the instructions a generative AI model uses to generate new ideas and data.

[1590] "Report format" refers to the document format in which collected and analyzed data is provided to the user.

[1591] A "business plan template" refers to a template or format that makes creating a business plan more efficient.

[1592] "Marketing objectives" refer to the specific goals to be achieved regarding promotional activities and market development for a new project.

[1593] "Historical Campaign Data" means data containing details of or results from previously conducted marketing or promotional activities.

[1594] "Market trends" refers to data that includes current trends and future predictions for a particular market.

[1595] The present invention relates to a system that utilizes generative AI to enable users to efficiently generate business ideas, conduct market research, create business plans, and develop marketing strategies. Specific embodiments of this system are described below.

[1596] Brainstorming business ideas

[1597] The user enters basic information about their business idea into the device. The entered information is sent to the server via a REST API. The server collects relevant data from an internal database (e.g., an RDBMS) and external sources (e.g., APIs on the Internet). Specific examples include data collection using Amazon Aurora and Google News API. Based on the collected data, the server inputs a prompt to a generative AI model (e.g., GPT-4) saying, "Please propose new ideas for sustainable products." The server then sends the generated ideas (e.g., "A fashion brand made from recycled materials") to the device for the user to confirm.

[1598] Market Research

[1599] The user inputs the market information they wish to research into their device. This includes the target market, region, and time range. The input information is sent to the server via a REST API. The server calls external data sources such as the Statista API to collect e-book market data. Based on the collected data, the server inputs a prompt to the generation AI: "Please create a detailed report on e-book demand in the Japanese market." The server then sends the generated report to the device, where the user can review it.

[1600] Creating a business plan

[1601] The user enters basic information about a new business into the device. The entered information is sent to the server via a REST API. The server generates a business plan template based on the received information and inputs it into the generative AI model. For example, a user enters detailed information about "launching a new health food brand" and inputs the prompt "Please create a business plan for the health food brand" into the generative AI. The server then sends a detailed business plan, including the target market, competitive analysis, and financial plan, to the device for the user to review.

[1602] Creating a marketing strategy

[1603] The user enters basic information and marketing goals for a new project into the device. The entered information is sent to the server via a REST API. The server collects and analyzes past campaign data and market trends. To do this, it uses the AdEspresso API, among others. Based on the collected data, the server inputs a prompt to the generation AI: "Please propose the optimal marketing strategy for the new product launch." The server then sends the generated marketing strategy (e.g., social media strategy, advertising campaign, PR activities) to the device, where the user can confirm it.

[1604] This system allows startups to efficiently utilize their limited resources and time, enabling them to rapidly expand their business. By utilizing generative AI, they can quickly respond to user needs and provide high-quality output.

[1605] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1606] Brainstorming business ideas

[1607] Step 1:

[1608] The user enters basic information about their business idea into the device, such as areas of interest, target market, existing challenges, etc. The entered information is saved in JSON format on the device.

[1609] Step 2:

[1610] The device sends the input information to the server via the REST API. At this time, the device sends JSON format data to the server using an HTTP POST request.

[1611] Step 3:

[1612] The server receives the information you enter and collects relevant data from internal databases (e.g., RDBMS) and external sources (e.g., Google News API), which are then stored on the server in a structured data format.

[1613] Step 4:

[1614] Based on the data collected by the server, a prompt sentence is input to the generative AI model (e.g., GPT-4). Specifically, the prompt sentence is input as "Please propose new ideas for sustainable products."

[1615] Step 5:

[1616] The server receives business ideas (e.g., "a fashion brand made from recycled materials") obtained from the generative AI model and organizes the data in JSON format.

[1617] Step 6:

[1618] The server sends the generated business idea to the terminal, where the generated idea is sent as an HTTP response.

[1619] Step 7:

[1620] The user checks the generated business idea on the device's display screen, and the device displays the received data in UI elements.

[1621] Market Research

[1622] Step 1:

[1623] The user inputs the market information they wish to research (e.g., target market, region, time range) into the terminal. The input information is saved in JSON format on the terminal.

[1624] Step 2:

[1625] The device sends the entered information to the server via the REST API. The device sends JSON format data to the server via an HTTP POST request.

[1626] Step 3:

[1627] Based on the information received, the server collects relevant market data from external data sources such as the Statista API, and stores the collected data in a structured data format on the server.

[1628] Step 4:

[1629] The server analyzes the collected data and inputs a prompt to the generation AI: "Please create a detailed report on the demand for e-books in the Japanese market."

[1630] Step 5:

[1631] The server receives the generated report and organizes the data in JSON format.

[1632] Step 6:

[1633] The server sends the generated report to the terminal as an HTTP response.

[1634] Step 7:

[1635] The user checks the generated report on the device's display screen, and the device displays the received data in UI elements.

[1636] Creating a business plan

[1637] Step 1:

[1638] The user enters basic information about their new business into the device, including the business concept, target market, and competitors. The information is then saved in JSON format on the device.

[1639] Step 2:

[1640] The device sends the entered information to the server via the REST API. The device sends JSON format data to the server via an HTTP POST request.

[1641] Step 3:

[1642] The server generates a business plan template based on the received information and stores the generated template on the server.

[1643] Step 4:

[1644] Based on the generated template, the server inputs the prompt statement "Please create a business plan for a health food brand" into the generative AI model.

[1645] Step 5:

[1646] The server receives the results from the generative AI model and adds details to the business plan, including target markets, competitive analysis, and financial plans.

[1647] Step 6:

[1648] The server organizes the generated business plan in JSON format and sends it to the terminal. At this time, the generated business plan is sent to the terminal as an HTTP response.

[1649] Step 7:

[1650] The user checks the generated business plan on the device's display screen, and the device displays the received data in UI elements.

[1651] Creating a marketing strategy

[1652] Step 1:

[1653] The user enters basic information about the new project and marketing goals into the device, such as the product name, target audience, budget range, etc. The entered information is saved in JSON format on the device.

[1654] Step 2:

[1655] The device sends the entered information to the server via the REST API. The device sends JSON format data to the server via an HTTP POST request.

[1656] Step 3:

[1657] Based on the information received, the server collects and analyzes past campaign data and market trends. For this purpose, it uses external data sources such as the AdEspresso API. The collected data is stored on the server.

[1658] Step 4:

[1659] Based on the data collected and analyzed by the server, the generative AI model is given a prompt: "Please suggest the optimal marketing strategy for the launch of a new product."

[1660] Step 5:

[1661] The server receives the results from the generative AI model and designs a detailed marketing strategy, including social media strategies, advertising campaigns, and PR activities.

[1662] Step 6:

[1663] The server organizes the generated marketing strategy in JSON format and sends it to the terminal. At this time, the generated strategy is sent to the terminal as an HTTP response.

[1664] Step 7:

[1665] The user checks the generated marketing strategy on the device's display screen, and the device displays the received data in UI elements.

[1666] (Application example 1)

[1667] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1668] For startups, it is extremely important to develop business ideas and marketing strategies while efficiently utilizing limited resources and time. However, with previous systems, users needed a great deal of effort and specialized knowledge to plan and create effective advertising campaigns. Furthermore, existing methods made it difficult to collect and analyze market information in real time and quickly generate advertising campaign plans. This led to delays in business development and the risk of losing competitiveness.

[1669] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1670] In this invention, the server includes means for receiving basic information about a business idea from a user, means for collecting related data from an internal database and external sources, means for generating business ideas using a generation AI based on the collected data, means for providing the generated business ideas to the user, and means for generating an advertising campaign plan based on advertising campaign requirements entered by the user. This allows users to efficiently obtain market information and quickly develop optimal advertising strategies. This allows startup companies to make the most of their limited resources and develop competitive businesses.

[1671] "User" means an individual or organization that uses a particular system or service.

[1672] A "business idea" is a concept or plan for a new business, product, or service.

[1673] An "internal database" is a database that accumulates data managed within a company.

[1674] "External sources" refer to data or information sources that can be obtained from outside.

[1675] "Relevant data" refers to information or numerical data that is relevant to a particular topic or purpose.

[1676] "Generative AI" refers to systems or models that use artificial intelligence technology to generate new ideas and information.

[1677] An "advertising campaign" is a series of advertising activities designed to promote a particular product or service.

[1678] A "means" is a method or device used to achieve a particular purpose.

[1679] A "server" is a computer that provides data and services over a network.

[1680] "Requirements" are the conditions or criteria necessary to carry out a particular task or project.

[1681] "Data collection" is the process of gathering specific information or data.

[1682] "Market information" refers to data such as market conditions, trends, and competitive information.

[1683] An "advertising strategy" is a plan or method for successfully running a particular advertising campaign.

[1684] This invention is a system that allows users to freely generate business ideas and advertising campaigns and quickly and effectively realize them. This system consists of a server, a terminal, and a generative AI model. The following explains the details of each component and how they interact with each other.

[1685] Data input from the user

[1686] Users input basic information about their business idea and advertising campaign through a device such as a smartphone. For example, users input the requirements for their advertising campaign (purpose, market, target audience, format, period, budget). For example,

[1687] Advertising campaign requirements:

[1688] Purpose: Increase awareness

[1689] Market: Japanese market

[1690] Target Audience: Young people (18-25 years old)

[1691] Format: Social Media Ad

[1692] Duration: 3 months

[1693] Budget: 5 million yen

[1694] Data submission and collection

[1695] The device sends user input data to a server, which then collects relevant data from an internal database and external sources. This process utilizes natural language processing (NLP) and machine learning algorithms. Specific technologies include accessing external data sources via APIs to obtain the latest market information and trend data.

[1696] Idea generation and campaign proposals using generative AI

[1697] The server uses generative AI models based on the collected data to generate business ideas and elements of advertising campaigns. The generated ideas and strategies are then returned to the device and provided to the user.

[1698] For example, a generative AI model might work like this:

[1699] Business idea generation: Based on the basic information entered by the user, the server generates specific ideas such as "a fashion brand made from recycled materials."

[1700] Advertising campaign generation: The server generates a campaign plan (keyword selection, ad copy, image and video themes, distribution method, etc.) based on the advertising requirements entered by the user.

[1701] Report Generation and Simulation

[1702] The advertising campaign plan created by the generative AI is simulated to show expected results, and the results are provided to the user as a report. This simulation is performed by analyzing past campaign data and market trends.

[1703] Specific examples

[1704] If a user wants a "marketing strategy for a new product launch," they can send the following prompt to the generative AI model:

[1705] New product launch marketing strategy:

[1706] Target market: North American market

[1707] Target audience: IT engineers aged 25-35

[1708] Primary goal: 1,000 sales in the first month

[1709] Budget: 10 million yen

[1710] Based on this input, the generative AI will suggest optimal marketing strategies (social media strategies, advertising campaigns, PR activities, etc.).

[1711] This allows users to quickly and effectively develop business ideas and advertising strategies with minimal expertise or effort, helping startups maximize their limited resources and increase their competitiveness.

[1712] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1713] Step 1:

[1714] The user inputs the requirements for the advertising campaign. The user inputs basic information such as the advertising objective, market, target audience, format, period, budget, etc. in text format via a device such as a smartphone. This input data is used in the next processing step.

[1715] Step 2:

[1716] The device sends the input data to the server. The advertising campaign requirements entered by the user are recorded on the device and transmitted to the server using a secure communication protocol (e.g. HTTPS). This data forms the basis for collecting related data on the server.

[1717] Step 3:

[1718] The server collects relevant data from internal databases and external sources. The server uses NLP and web scraping techniques to gather the necessary information from internal databases (e.g., past advertising campaign data) and external sources (e.g., market research reports and public data). This data is used as training material for the generative AI model.

[1719] Step 4:

[1720] The server analyzes the collected data and generates an advertising campaign plan using a generative AI model. The server inputs the preprocessed data into a generative AI model (e.g., OpenAI's GPT series) to generate each element of the advertising campaign (keywords, ad copy, image theme, distribution method, etc.) based on the user's requirements and market insights. This generated plan is the output presented to the user.

[1721] Step 5:

[1722] The server sends the generated advertising campaign plan to the device. The advertising campaign plan created by the generative AI model is returned to the user's device, again using a secure communication protocol. The device receives this data and displays it through a user interface.

[1723] Step 6:

[1724] The user checks the generated advertising campaign plan. The user checks the advertising campaign plan displayed on the terminal screen and makes corrections or feedback as necessary. This feedback is sent back to the server for further optimization.

[1725] Step 7:

[1726] The server simulates the advertising campaign plan and generates the results in a report. The server simulates the effectiveness of the generated advertising campaign plan based on past data and trends, and summarizes the results in a report. This report is provided to the user and is useful for making final campaign decisions.

[1727] Step 8:

[1728] The server sends the final report to the terminal. The generated simulation report is then sent to the user's terminal again using a secure communication protocol, and the user can review this report and proceed with preparations for the actual advertising campaign.

[1729] These steps provide a system that allows users to efficiently plan and execute advertising campaigns without requiring specialized knowledge.

[1730] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1731] This invention provides a system that combines generative AI and an emotion engine to improve the operational efficiency of startup companies. This system enables users to efficiently generate business ideas, conduct market research, create business plans, and develop marketing strategies, and provides optimized results by taking user emotions into account.

[1732] Specifically, the system works as follows:

[1733] Brainstorming business ideas

[1734] The user enters basic information about their business idea (areas of interest, target market, existing challenges, etc.) into the device. At this time, the emotion engine analyzes the user's input and recognizes emotions. The device then sends the basic information and emotion data to the server, which collects related data from an internal database and external sources. Generative AI is used to generate business ideas, and the server provides optimized business ideas based on the emotion data to the user via the device. For example, if a user requests "new ideas for sustainable products," the server will suggest specific ideas such as "a fashion brand made from recycled materials," but if the user is expressing positive emotions, it will suggest more innovative ideas.

[1735] Market Research

[1736] The user inputs information about a specific market (such as the market name, target region, and time range) into the device. The emotion engine then analyzes the user's input and recognizes emotions. The device then sends the request information and emotion data to the server, which then collects relevant market data from internal databases and external sources. The collected data is analyzed by the server and sent to the device in the form of a report optimized based on the emotion data, which is then displayed to the user. For example, if a user wants to research "demand for e-books in the Japanese market," the server aggregates statistical data, consumer trends, and competitive analysis, and provides a particularly detailed analysis if the user expresses concerns.

[1737] Creating a business plan

[1738] The user enters basic information about their new business (business details, target market, competitive information, etc.) into the device. At this time, an emotion engine analyzes the user's input and recognizes emotions. The device then sends the basic information and emotional data to the server, which then generates a business plan template based on that information. A detailed business plan is created using generative AI, and the server provides the plan to the user via the device, adjusted based on the emotional data. For example, if a user enters detailed information about "launching a new health food brand," the server will create a business plan that includes market analysis, target market, competitive analysis, and financial plan, and will also include a risk analysis if the user expresses any concerns.

[1739] Creating a marketing strategy

[1740] The user enters basic information and marketing goals for a new project into the device. The emotion engine analyzes the user's input and recognizes emotions. The device then sends the basic information and emotion data to the server, which collects and analyzes past campaign data and market trends from internal databases and external sources. An optimal marketing strategy is created using generative AI, and the strategy, adjusted based on the emotion data, is provided to the user from the server via the device. For example, if the user requests a "marketing strategy for a new product launch," the server will propose plans for social media strategies, advertising campaigns, PR activities, and more, including bolder strategies if the user expresses excitement.

[1741] This system allows startups to efficiently utilize limited resources and time, and rapidly expand their business by receiving more personalized support based on emotions.The system, which utilizes generative AI and an emotion engine, supports the growth of companies by quickly responding to users' needs and emotions and providing high-quality output.

[1742] The processing flow will be explained below.

[1743] Specific steps for brainstorming business ideas

[1744] Step 1:

[1745] The user inputs basic information about their business idea (areas of interest, target market, existing challenges, etc.) into the device, and the emotion engine analyzes the user's input and recognizes their emotions.

[1746] Step 2:

[1747] The device transmits basic information and recognized emotion data to the server.

[1748] Step 3:

[1749] The server collects relevant data from internal databases and external sources (Internet, statistical data, etc.).

[1750] Step 4:

[1751] Generate multiple business ideas using generative AI based on relevant data collected by the server.

[1752] Step 5:

[1753] The server takes into account the user's emotional data to optimize the generated business ideas, for example, highlighting more innovative ideas if the user shows positive emotions.

[1754] Step 6:

[1755] The server sends the optimized business idea to the terminal.

[1756] Step 7:

[1757] The system checks the business ideas provided by the user on the device, and if the user responds positively, it will also suggest additional ideas.

[1758] Specific steps in market research

[1759] Step 1:

[1760] The user inputs information about a specific market (market name, target area, time range, etc.) into the terminal, and the emotion engine analyzes the user's input and recognizes emotions.

[1761] Step 2:

[1762] The device sends the request information and emotion data to the server.

[1763] Step 3:

[1764] The server collects relevant market data from internal databases and external sources (statistical data, research reports, etc.).

[1765] Step 4:

[1766] The server analyzes the collected market data.

[1767] Step 5:

[1768] The server takes into account the sentiment data and compiles the analysis results into a report, for example, including a detailed risk analysis if the user expresses anxiety.

[1769] Step 6:

[1770] The server sends the generated report to the device.

[1771] Step 7:

[1772] The user reviews the report on their device, and if they express anxiety, it includes specific suggestions for action.

[1773] Specific steps in creating a business plan

[1774] Step 1:

[1775] The user inputs basic information about their new business (business details, target market, competitive information, etc.) into the terminal. At this time, the emotion engine analyzes the user's input and recognizes their emotions.

[1776] Step 2:

[1777] The device sends the input basic information and emotion data to the server.

[1778] Step 3:

[1779] The server generates a business plan template based on the received information.

[1780] Step 4:

[1781] The server uses generative AI to create a detailed business plan and adjusts it based on the user's sentiment data, for example detailing a risk management plan if the user expresses concerns.

[1782] Step 5:

[1783] The server sends the adjusted business plan to the terminal.

[1784] Step 6:

[1785] Users review the detailed business plan on their devices and provide feedback on any areas of particular interest or concern.

[1786] Specific process steps for creating a marketing strategy

[1787] Step 1:

[1788] The user inputs basic information about the new project and its marketing goals into the device, and the emotion engine analyzes the user's input and recognizes their emotions.

[1789] Step 2:

[1790] The device sends the input basic information and emotion data to the server.

[1791] Step 3:

[1792] The server collects and analyzes past campaign data and market trends from internal databases and external sources.

[1793] Step 4:

[1794] The server uses generative AI to create optimal marketing strategies and adjusts them by taking into account sentiment data, for example, adopting a more aggressive strategy if users express excitement.

[1795] Step 5:

[1796] The server transmits the adjusted marketing strategy to the terminal.

[1797] Step 6:

[1798] Users can view marketing strategies on their devices and receive detailed recommendations for strategies that interest them.

[1799] Specific steps for fundraising

[1800] Step 1:

[1801] The user inputs their fundraising request (such as the amount of funds needed and an outline of their business plan) into the terminal. At this time, the emotion engine analyzes the user's input and recognizes their emotion.

[1802] Step 2:

[1803] The terminal transmits the input request and emotion data to the server.

[1804] Step 3:

[1805] The server collects and analyzes investor information and past fundraising cases from internal databases and external sources.

[1806] Step 4:

[1807] The server takes emotional data into account to generate a list of investors and fundraising methods suited to the user. For example, if the user shows signs of nervousness, it will recommend investors with relatively low risk.

[1808] Step 5:

[1809] The server sends the generated fundraising methods and investor list to the terminal.

[1810] Step 6:

[1811] Users can check fundraising methods and investor lists on their device, and if they're feeling nervous, they can also receive specific negotiation advice.

[1812] Example 2

[1813] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1814] Startups need to operate efficiently within limited resources and time constraints, but conventional systems have struggled to provide optimal support that takes user emotions into account. In particular, there has been no technology that provides results that reflect user emotions when generating business ideas, conducting market research, creating business plans, or formulating marketing strategies. Therefore, there is a need for personalized support based on user emotions to improve the quality of user decision-making.

[1815] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for receiving basic information from a user, means for analyzing the received input and recognizing emotions, means for transmitting the analysis results and related data to the server, means for collecting related data from an internal database and external sources, means for processing the collected data using a generative AI model, means for optimizing the generated results based on emotion data, and means for providing the optimized results to the user. This makes it possible to create optimal business ideas, market research, business plans, and marketing strategies based on user emotions.

[1816] A "user" is an entity that uses this system to develop business ideas, market research, business plans, or marketing strategies.

[1817] "Basic information" refers to input data about a business provided by a user, including business details, target market, competitive information, and the like.

[1818] "Emotion data" is data that indicates the user's emotional state, analyzed by the emotion engine based on the user's input.

[1819] A "terminal" is a hardware or software device through which a user interacts with the system.

[1820] The "server" is the central device that executes various processes in this system and collects, analyzes, generates, and optimizes data.

[1821] "Generative AI model" refers to an artificial intelligence model that automatically generates business ideas, market research reports, business plans, or marketing strategies based on user requests.

[1822] "Internal Database" means a collection of information stored within the server that the system uses to gather relevant data needed.

[1823] "External Source" means an external information source, other than the internal database, that the system connects to to gather relevant data.

[1824] "Optimization" refers to the process of adjusting a generated business idea, report, business plan, or marketing strategy based on user sentiment data to make it more effective.

[1825] "Analysis" refers to the process of processing received user input data to recognize its content and sentiment.

[1826] A "report" is output data in document format that organizes and presents the results of market research, etc.

[1827] This invention provides a system that combines a generative AI model and an emotion engine to improve the operational efficiency of startup companies. This system takes user emotions into account and provides optimized results in generating business ideas, conducting market research, creating business plans, and formulating marketing strategies.

[1828] System configuration

[1829] The system consists of a device used by the user, a server that analyzes and generates data, and an internal database and external sources. Basic business information provided by the user is received by the device, and its content and emotional data are analyzed. The analyzed data is sent to the server, which collects related data from the internal database and external sources. The collected data is processed by the server, and the required output is generated using a generative AI model. This output is optimized based on the user's emotional data and provided to the user via the device.

[1830] Brainstorming business ideas

[1831] When a user enters basic information about their business idea into the device, the emotion engine analyzes the input and recognizes emotions. The basic information along with the emotion data is sent to the server, which collects relevant data from its internal database and external sources. The server uses a generative AI model to generate business ideas and provides them to the user via the device, optimized based on the emotion data.

[1832] For example, if a user requests "new ideas for sustainable products," specific suggestions such as "fashion brands that use recycled materials" may be given. An example of a prompt for the generative AI model is "Please generate new business ideas for sustainable products."

[1833] Market Research

[1834] When a user inputs information about a specific market into the terminal, the emotion engine analyzes the input and recognizes emotions. The request information along with the emotion data is sent to the server, which collects relevant market data from internal databases and external sources. The server analyzes the collected data and generates an optimized report based on the emotion data, which is then provided to the user via the terminal.

[1835] For example, if a user wants to research "demand for e-books in the Japanese market," a report containing statistical data, consumer trends, and competitive analysis will be generated. An example of a prompt for the generative AI model is, "Please research demand for e-books in the Japanese market and create a detailed report."

[1836] Creating a business plan

[1837] When a user enters basic information about a new business into the device, the emotion engine analyzes the input and recognizes emotions. The basic information along with the emotion data is sent to the server, which then generates a basic business plan based on a template. A generative AI model is then used to create a detailed business plan, which is then adjusted based on the emotion data and provided to the user via the device.

[1838] For example, if a user enters details about "launching a new health food brand," a business plan will be created that includes market analysis, financial planning, and competitive analysis. An example prompt for the generative AI model is, "Please create a business plan for a new health food brand."

[1839] Creating a marketing strategy

[1840] When a user enters basic information about a new project and marketing goals into their device, the emotion engine analyzes the input and recognizes emotions. The basic information along with the emotion data is sent to a server, which then collects and analyzes past campaign data and market trends from internal databases and external sources. An optimal marketing strategy is created using a generative AI model, and the strategy, adjusted based on the emotion data, is provided to the user via their device.

[1841] For example, if a user requests a "marketing strategy for a new product launch," plans for a social media strategy, advertising campaign, and PR activities will be suggested. An example of a prompt for the generative AI model is, "Please create a marketing strategy for a new product launch."

[1842] This system allows startups to utilize limited resources and time and rapidly expand their business by receiving optimal support based on user emotions. Utilizing a generative AI model and emotion engine, the system responds quickly to user needs and emotions, providing high-quality output and supporting business growth.

[1843] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1844] Brainstorming business ideas

[1845] Step 1:

[1846] The user inputs basic information about their business idea into the device, such as areas of interest, target market, existing challenges, etc. The input at this stage is text data.

[1847] Step 2:

[1848] The device sends the input information to an emotion engine to recognize emotions. For example, it uses natural language processing technology to analyze text data and extract emotions such as positive and negative. The output at this point is analyzed emotion data.

[1849] Step 3:

[1850] The device sends basic information and emotion data to the server. This data transmission allows the server to start the necessary processing. At this point, the input is a set of basic information and emotion data.

[1851] Step 4:

[1852] The server collects relevant data from internal databases and external sources, for example, market data and trend information relevant to the business, and consolidates this data. The output at this point is the collected relevant data.

[1853] Step 5:

[1854] The server uses a generative AI model to generate business ideas based on the collected data. Specifically, it gives the AI ​​model a prompt to start the idea generation process. An example of a prompt is, "Generate a new business idea for a sustainable product." The output at this point is the generated business idea.

[1855] Step 6:

[1856] The server optimizes the generated business ideas based on the sentiment data. For example, if the sentiment is positive, it adds novel ideas, and if it is negative, it generates ideas that minimize risk. The output at this point is an optimized business idea.

[1857] Step 7:

[1858] The server returns the optimized business idea to the terminal. This data transmission prepares the idea to be presented directly to the user. The output at this point is the optimized business idea.

[1859] Step 8:

[1860] The terminal provides the optimized business idea to the user, for example, by displaying the business idea on a screen or by providing it in a downloadable format, and the output at this point is the specific business idea provided to the user.

[1861] Market Research

[1862] Step 1:

[1863] The user inputs information about a specific market into the terminal. Specifically, the user inputs information such as the market name, target area, time range, etc. The input at this point is text data.

[1864] Step 2:

[1865] The device sends the input information to an emotion engine for emotion recognition. Emotions are extracted from text data using natural language processing techniques. The output at this point is analyzed emotion data.

[1866] Step 3:

[1867] The device sends request information and emotion data to the server. This data transmission starts processing on the server side. The input at this point is a set of request information and emotion data.

[1868] Step 4:

[1869] The server collects market-related data from internal databases and external sources, such as market statistics and consumer trend information, and aggregates them. The output at this point is market-related data.

[1870] Step 5:

[1871] The server analyzes the collected data and uses generative AI models to create a detailed report. The output at this point is a report containing the analysis results.

[1872] Step 6:

[1873] The server optimizes the report based on the emotion data, for example if the user indicates anxiety it will create a report with a particularly detailed analysis. The output at this point is the optimized report.

[1874] Step 7:

[1875] The server returns the optimized report to the terminal. This data transmission prepares the report to be provided directly to the user. The output at this point is the optimized report.

[1876] Step 8:

[1877] The terminal provides an optimized report to the user, for example by displaying the report on the screen or by providing it in a downloadable format. The output at this point is a detailed report provided to the user.

[1878] Creating a business plan

[1879] Step 1:

[1880] The user inputs basic information about the new business into the terminal, such as the business description, target market, and competitive information. At this stage, the input is text data.

[1881] Step 2:

[1882] The device sends the input information to the emotion engine, which recognizes emotions. The emotion data is analyzed using natural language processing technology. The output at this point is the analyzed emotion data.

[1883] Step 3:

[1884] The device sends basic information and emotion data to the server. This data transmission starts processing on the server side. At this point, the input is a set of basic information and emotion data.

[1885] Step 4:

[1886] The server generates a business plan template based on the basic information. This template includes basic items such as market analysis, competitive analysis, and financial plan. The output at this point is a business plan template.

[1887] Step 5:

[1888] The server uses a generative AI model to create a detailed business plan based on the generated template. An example prompt is, "Please create a business plan for a new health food brand." The output at this point is a detailed business plan.

[1889] Step 6:

[1890] The server optimizes the business plan based on the sentiment data, for example, if the user expresses concerns, it creates a plan that specifically includes a risk analysis. The output at this point is an optimized business plan.

[1891] Step 7:

[1892] The server returns the optimized business plan to the terminal. This data transmission prepares the business plan to be provided directly to the user. The output at this point is the optimized business plan.

[1893] Step 8:

[1894] The terminal provides the optimized business plan to the user, for example, by displaying the plan on a screen or by providing it in a downloadable format. The output at this point is a specific business plan provided to the user.

[1895] Creating a marketing strategy

[1896] Step 1:

[1897] The user inputs basic information and marketing goals for the new project into the terminal, including the sales promotion plan, target market, advertising goals, etc. The input at this stage is text data.

[1898] Step 2:

[1899] The device sends the input information to the emotion engine, which recognizes emotions. The emotion data is analyzed using natural language processing technology. The output at this point is the analyzed emotion data.

[1900] Step 3:

[1901] The device sends basic information and emotion data to the server. This data transmission starts processing on the server side. At this point, the input is a set of basic information and emotion data.

[1902] Step 4:

[1903] The server collects historical campaign data and market trends from internal databases and external sources. The output at this point is the collected relevant data.

[1904] Step 5:

[1905] The server uses a generative AI model to create a marketing strategy. An example prompt is "Please create a marketing strategy for a new product launch." The output at this point is a detailed marketing strategy.

[1906] Step 6:

[1907] The server optimizes the marketing strategy based on the emotion data. For example, if the user expresses excitement, it adds a bold strategy. The output at this point is the optimized marketing strategy.

[1908] Step 7:

[1909] The server returns the optimized marketing strategy to the terminal. This data transmission prepares the strategy to be provided directly to the user. The output at this point is the optimized marketing strategy.

[1910] Step 8:

[1911] The terminal provides the optimized marketing strategy to the user, for example by displaying the strategy on a screen or by providing it in a downloadable format. The output at this point is the specific marketing strategy provided to the user.

[1912] Through these steps, the system provides optimal support based on the user's emotions, improving work efficiency.

[1913] (Application example 2)

[1914] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1915] Store managers are required to develop effective business strategies and implement measures within limited resources and time. However, the information gathering and planning required for this is cumbersome, and the results can be disappointing, especially since optimization is not based on the emotions of individual store managers. Therefore, there is a need for a system that can efficiently generate business ideas and optimize them while taking emotions into account.

[1916] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving basic information about a business idea from a user, means for collecting related data from an internal database and external sources, means for generating business ideas using a generation AI based on the collected data, means for providing the generated business idea to the user, and means for analyzing user emotions using an emotion engine and optimizing the generated business idea based on the emotion data. This enables managers of physical stores to quickly develop and implement optimized business ideas and strategies based on emotions.

[1917] 1. A "business idea" is a concept or plan for a new business that a user wants to start.

[1918] 2. "Basic information" refers to the basic data required to develop a business idea, as well as information about users' interests, target markets, and existing challenges.

[1919] 3. "Internal Database" means the collection of data stored within the System.

[1920] 4. "External Source" means a source of data collected from outside the System.

[1921] 5. "Emotion Engine" refers to a system component that analyzes user input data and recognizes their emotional state.

[1922] 6. "Generative AI" refers to artificial intelligence that uses large amounts of data to generate new content or ideas based on specific prompts.

[1923] 7. "Optimization" is the process of adjusting something to best suit a particular purpose or condition.

[1924] 8. "Market Data" means data such as statistics, consumer trends, and competitive analysis relating to a particular market.

[1925] 9. A "business plan template" is a basic business plan template for building a new business.

[1926] To implement this invention, it is important to build a system that combines generative AI and an emotion engine, allowing store managers to efficiently generate business ideas and provide plans optimized based on emotions.

[1927] System Configuration

[1928] The system consists of a terminal operated by the user, a server that processes data, and a generative AI and emotion engine for generating and optimizing business ideas.

[1929] Program Overview

[1930] 1. The terminal receives basic information about the business idea from the user.

[1931] 2. The terminal sends the received basic information to the server.

[1932] 3. Based on the received basic information, the server collects relevant data from its internal database and external sources.

[1933] 4. The server uses an emotion engine to analyze emotions from the user's basic information input.

[1934] 5. The server uses generative AI to generate business ideas based on the collected data and analyzed emotional data.

[1935] 6. The server optimizes the generated business ideas based on the emotion data.

[1936] 7. The server sends the optimized business idea to the terminal and provides it to the user.

[1937] Hardware and Software Use

[1938] This system uses the user's smartphone as the terminal. To process data and perform sentiment analysis, a server runs on a cloud platform such as Amazon Web Services (AWS). The generative AI uses the OpenAI API, and modules such as the "sentiment_analysis_module" for the sentiment engine and the "database_connector" for database connection are used.

[1939] Data processing and calculation

[1940] Basic information entered on the device is sent to the server as text data. The server then uses an emotion engine to perform sentiment analysis of the text data and recognize positive, negative, and neutral emotional states. Data collected from internal databases and external sources is normalized and aggregated in a database management system (DBMS). The generative AI generates prompt responses based on the data and further optimizes them based on the emotional data.

[1941] Examples of concrete examples and prompts

[1942] For example, if a user is looking for new business ideas for "summer sales promotions," they input basic information from their device. The server analyzes this information with an emotion engine, and if it determines that the user is expressing positive emotions, it uses generative AI to generate novel ideas such as "beach party-themed sales events."

[1943] An example of a prompt is:

[1944] Generate new business ideas for "Summer Sale Promotion" when users are feeling positive.

[1945] This allows store owners to quickly obtain business ideas that are optimized based on emotions, allowing them to plan and implement more effective strategies.

[1946] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1947] Step 1:

[1948] The user uses a terminal to input basic information about their business idea, including their interests, areas of interest, target market, and existing challenges. This input data is then passed on to the next step.

[1949] Step 2:

[1950] The device sends the basic information entered in step 1 to the server. The data is passed to the server in text format, and data analysis is performed based on this.

[1951] Step 3:

[1952] The server sends the received basic information to the emotion engine, which analyzes the user's emotions. The emotion engine analyzes the text data and outputs a positive, negative, or neutral emotional state. The analysis results are used in the next step.

[1953] Step 4:

[1954] The server collects relevant data from internal databases and external sources based on the basic information and sentiment analysis results. The collected data includes market trends and competitive information, and this data is normalized and aggregated in a database management system (DBMS). This processed data is used in the next step.

[1955] Step 5:

[1956] The server calls the generation AI based on the collected data and the results of sentiment analysis to generate new business ideas. Specific prompts are provided to the generation AI, and an example of a prompt is "Generate a new business idea for a 'summer sales promotion' when the user is feeling positive." The generation AI outputs new ideas based on this.

[1957] Step 6:

[1958] The server optimizes the generated business ideas based on the emotional data. For example, if the user shows positive emotions, it will adjust the idea to be more innovative. This optimized business idea is sent to the next step.

[1959] Step 7:

[1960] The server sends the optimized business idea to the terminal, which displays it to the user. The user can check the optimized business idea and use it to plan and execute a specific business strategy.

[1961] Through the above processing steps, brick-and-mortar store managers can efficiently generate business ideas and obtain optimized plans based on emotions.

[1962] 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.

[1963] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1964] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1965] 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.

[1966] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1967] 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.

[1968] 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).

[1969] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1970] 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."

[1971] 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.

[1972] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1973] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1974] 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.

[1975] 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.

[1976] 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.

[1977] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1978] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1979] 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.

[1980] 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.

[1981] The above-described description and illustrations are a detailed explanation of the parts related to...

Claims

1. a means for receiving basic information regarding a business idea from a user; means of collecting relevant data from internal databases and external sources; A means of generating business ideas using AI based on collected data, A means for providing the generated business ideas to a user; A system including:

2. means for receiving information about a particular market from a user; a means of collecting market data from internal databases and external sources; A means of analyzing the collected data and providing it in the form of a report; The system of claim 1 , comprising:

3. a means for receiving basic information about new businesses from users; a means for generating a business plan template based on the received information; means for generating and providing a detailed business plan to a user; The system of claim 1 , comprising:

4. A means for receiving basic project information from users; A means to analyze past campaign data and market trends, A means for generating an optimal marketing strategy and providing it to a user; The system of claim 1 , comprising:

Images