system

Abstract

Provide a system. A means for inputting a market research request from a user terminal; means for collecting data about a designated market from the Internet; A means of organizing the collected data into a uniform format; A means of extracting important keywords and topics using natural language processing technology, A means of conducting a PEST analysis based on the extracted data; A method for conducting 5 Forces analysis based on the extracted data, and A means to generate market understanding reports based on the results of PEST analysis and 5 Forces analysis; The system includes means for transmitting reports to a user terminal.

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] In the early stages of a new business, market research is an important process that requires time and effort. However, collecting and analyzing large amounts of data can be difficult for beginners, students, and companies considering entering a new market. Traditional market research methods require specialized knowledge and require efficient data analysis. Therefore, there is a need for a method that efficiently supports market research and deepens user understanding. [Means for solving the problem]

[0005] The present invention provides a system including: means for inputting a market research request from a user terminal; means for collecting data on a specified market from the Internet; means for organizing the collected data into a unified format; means for extracting important keywords and topics using natural language processing technology; means for performing a PEST analysis based on the extracted data; means for performing a 5 Forces analysis based on the extracted data; means for generating a market understanding report based on the results of the PEST analysis and the 5 Forces analysis; and means for transmitting the report to the user terminal. This system allows users to efficiently deepen their understanding of the market and conduct advanced market research even without specialized knowledge.

[0006] "User terminal" means a device through which a user accesses and inputs data to the system.

[0007] A "market research request" is a request entered by a user to obtain market information.

[0008] The "means for collecting data" is a function for automatically searching and acquiring data on a specified market from the Internet.

[0009] A "uniform format" is a standard for converting collected data into a consistent format.

[0010] "Natural language processing technology" is a technology that allows computers to understand and process human language.

[0011] "Means for extracting keywords and topics" is the function of identifying and extracting important information from data.

[0012] "PEST analysis" is a method of analyzing a market from four perspectives: politics, economics, society, and technology.

[0013] "Five Forces Analysis" is a method of analyzing a market based on five factors: intensity of competition, threat of new entrants, threat of substitutes, bargaining power of suppliers, and bargaining power of buyers.

[0014] A "Market Understanding Report" is a report generated by integrating the results of PEST analysis and 5 Forces analysis.

[0015] The "means for sending a report to a user terminal" is a function for delivering the generated market understanding report to the user's device. [Brief explanation of the drawings]

[0016] [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

[0017] 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.

[0018] First, the terms used in the following description will be explained.

[0019] 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).

[0020] 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.

[0021] 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.

[0022] 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.

[0023] 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."

[0024] [First embodiment]

[0025] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0026] 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.

[0027] 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).

[0028] 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.

[0029] 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.

[0030] 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.

[0031] 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.

[0032] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0033] 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.

[0034] 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.

[0035] 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.

[0036] 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."

[0037] The present invention relates to a system that efficiently supports market research. When a user inputs a market request, the system collects and analyzes related data from the Internet, generates a market understanding report based on PEST analysis and 5 Forces analysis, and provides it to the user.

[0038] System Program

[0039] 1. User Interface

[0040] How it works: The terminal provides an interface where users can enter market research requests, allowing them to specify specific markets and types of analysis.

[0041] Example: A user enters a request to "conduct a PEST analysis and 5 Forces analysis of the AI ​​market."

[0042] 2. Processing the Request

[0043] Operation: The terminal sends a request entered by the user to the server, which includes keywords and instructions for analysis.

[0044] Example: A user request is sent to the server, and the keywords "AI market", "PEST analysis", and "5 Forces analysis" arrive at the server.

[0045] 3. Data Collection

[0046] How it works: The server collects data related to a specified market from the internet, including open data, industry reports, news articles, academic papers, etc.

[0047] Example: A server searches and collects the latest news articles and technical reports related to the AI ​​market.

[0048] 4. Data format organization

[0049] How it works: The server organizes the collected data into a consistent format (e.g., JSON) so that the data is stored in a unified form before analysis.

[0050] Example: Data in various formats such as text, PDF, CSV, etc. is converted to JSON format.

[0051] 5. Data analysis and keyword extraction

[0052] How it works: The server uses natural language processing techniques to extract important keywords and topics from the organized data.

[0053] Example: Keywords such as "technology trends," "regulatory changes," and "market growth rate" are extracted.

[0054] 6. Conduct a PEST analysis

[0055] How it works: The server performs a PEST analysis based on the extracted data, which analyzes the market from political, economic, social, and technological perspectives.

[0056] Example: Sarver assesses the latest technological trends and regulatory impacts in the AI ​​market and categorizes them into their respective categories.

[0057] 7. Conducting a Five Forces Analysis

[0058] How it works: The server performs a 5 Forces analysis on the same extracted data, assessing the intensity of competition, the threat of new entrants, the threat of substitutes, the bargaining power of suppliers, and the bargaining power of buyers.

[0059] Example: The server analyzes key competitors in the AI ​​market and assesses the threat of new entrants.

[0060] 8. Generate Reports

[0061] How it works: The server generates a market understanding report based on the results of the PEST and 5 Forces analyses. The report contains specific information and assessments that allow users to gain a deeper understanding of the market.

[0062] Example: The server generates a comprehensive report summarizing "AI market growth opportunities and challenges," "analysis of key players," and "impact of technology trends."

[0063] 9. Report Distribution

[0064] How it works: The server generates a report and sends it to the user's device. The report is provided in PDF format or as a web page.

[0065] Example: Users can view reports generated on their devices and get detailed market analysis.

[0066] In this way, the present system efficiently supports market research and provides users with the ability to perform advanced market analysis even without specialized knowledge.

[0067] The processing flow will be explained below.

[0068] Step 1: The user uses their device to enter a research request for a specific market, for example, "I would like a PEST analysis and 5 Forces analysis of the AI ​​market."

[0069] Step 2: The terminal sends the request entered by the user to the server, which includes the market to be analyzed and the type of analysis required.

[0070] Step 3: Based on the received request, the server collects data related to the specified market, searching and retrieving open data, industry reports, news articles, academic papers, etc. from the Internet.

[0071] Step 4: The server converts the acquired data into a unified format, for example, organizing data in different formats such as text, PDF, CSV, etc. into JSON format.

[0072] Step 5: The server applies natural language processing (NLP) techniques to the organized data to extract important keywords and topics, such as technology trends, regulatory changes, and market growth rates.

[0073] Step 6: The server performs a PEST analysis based on the extracted data, including analysis of political, economic, social, and technological factors, such as assessing the impact of emerging technological trends and regulations on the AI ​​market.

[0074] Step 7: The server performs a 5 Forces analysis based on the extracted data, including the intensity of competition, the threat of new entrants, the threat of substitutes, the bargaining power of suppliers, and the bargaining power of buyers. For example, it analyzes major competitors in the AI ​​market and evaluates the threat of new entrants.

[0075] Step 8: The server generates a market understanding report based on the results of the PEST analysis and 5 Forces analysis. The report contains specific information and assessments that allow users to gain a deeper understanding of the market. For example, the report includes "AI market growth opportunities and challenges," "analysis of key players," and "impact of technological trends."

[0076] Step 9: The server sends the generated report to the user's device, which can be provided in PDF or web page format.

[0077] Step 10: The terminal displays the received report to the user. The user can view the report generated on the terminal and check the details of the market analysis.

[0078] Example 1

[0079] 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."

[0080] The market research process requires the collection, organization, and analysis of a wide variety of data, which requires a great deal of time and specialized knowledge. When conducting PEST analysis or 5 Forces analysis, the challenge is to quickly and accurately extract relevant information from a wide range of data sources. Many existing market research tools struggle to efficiently complete this process, forcing users to use multiple tools in combination.

[0081] 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.

[0082] In this invention, the server includes means for inputting a market research request from a user terminal, means for collecting data on a specified market from the Internet, means for organizing the collected data into a unified format, means for extracting important keywords and topics using natural language processing technology, means for analyzing the market from political, economic, social, and technological perspectives based on the extracted data, means for analyzing the market structure and competitive environment based on the extracted data, means for generating a market understanding report based on the analysis results, and means for transmitting the report to the user terminal. This enables users to quickly and efficiently perform advanced market analysis even without specialized knowledge.

[0083] "User Terminal" means the electronic device used by a User to access the System and enter market research requests.

[0084] A "Market Research Request" is a request entered into the System by a User specifying a particular market or type of analysis.

[0085] The "Internet" is a global network used to collect information.

[0086] "Data" refers to information about the market, collected from news articles, industry reports, academic papers, etc.

[0087] "Format" refers to the format or structure that unifies data and provides a basis for consistent analysis.

[0088] "Natural language processing technology" is a technology that allows computers to understand and analyze human language, and is used to extract keywords and topics.

[0089] "Keywords" refer to important words or phrases that are the subject of market research.

[0090] "Topics" refer to major themes or topics related to the subject of market research.

[0091] "PEST analysis" is an analytical method that evaluates a market from political, economic, social, and technological perspectives.

[0092] "Five Forces Analysis" is an analytical method for evaluating market structure and the competitive environment, assessing the intensity of competition, the threat of new entrants, the threat of substitutes, the bargaining power of suppliers, and the bargaining power of buyers.

[0093] A "Market Understanding Report" is a document created based on the results of PEST analysis and 5 Forces analysis, which allows users to gain a deeper understanding of the market.

[0094] A "server" is a computer system that performs processes such as data collection, organization, analysis, and report generation.

[0095] "Send" refers to the act of transferring the generated report to a user terminal.

[0096] This invention relates to a system that efficiently supports market research. In this system, when a user inputs a market request through a terminal, a server collects and analyzes related data from the Internet, generates a market understanding report based on PEST analysis and 5 Forces analysis, and provides it to the user.

[0097] The system is configured as follows: The user terminal has a user interface for inputting requests. The user uses this interface to specify a specific market and type of analysis. For example, a request can be made to "conduct a PEST analysis and 5 Forces analysis of the AI ​​market."

[0098] The device sends a request from the user to the server. The request includes keywords and instructions necessary for analysis. The server then collects data related to the specified market from the Internet. This collection uses a wide range of data sources, including open data, industry reports, news articles, and academic papers. Specifically, it uses Python's "BeautifulSoup" and "Google (registered trademark) News API" to collect information from the Internet.

[0099] The collected data is organized on the server in a consistent format (e.g., JSON format). This streamlines preprocessing for analysis and stores the data in a unified format. Python libraries such as "pandas" and "PyPDF2" are used to organize the data.

[0100] The server uses natural language processing technology (using NLTK and SpaCy) to extract important keywords and topics from the organized data, such as "technology trends," "regulatory changes," and "market growth rates."

[0101] The server then performs a PEST analysis based on the extracted data. The PEST analysis evaluates the market from political, economic, social, and technological perspectives. Specifically, it evaluates the impact of the latest technological trends and regulations on the AI ​​market and classifies them into categories.

[0102] Similarly, the server performs a 5 Forces analysis, which evaluates the intensity of competition, threat of new entrants, threat of substitutes, bargaining power of suppliers, and bargaining power of buyers, including a detailed analysis of key competitors and a detailed assessment of the threat of new entrants.

[0103] Finally, the server generates a market understanding report based on the results of the PEST and 5 Forces analyses. This report contains specific information and assessments that allow users to gain a deeper understanding of the market. The report can also include graphical elements using Python's Jupyter Notebook and Matplotlib.

[0104] The generated report is sent from the server to the user's device, and is available in PDF or web page format, which the user can access via email or a download link.

[0105] Here is an example prompt:

[0106] "Please conduct a PEST analysis and 5 Forces analysis of the AI ​​market."

[0107] This system enables users to perform sophisticated market analysis quickly and efficiently, even without specialized knowledge.

[0108] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0109] Step 1:

[0110] User Interface Display

[0111] What it does: The terminal displays an interface that allows the user to enter a market research request.

[0112] Input: A web page a user visits or a mobile app launch.

[0113] Output: A display of an input interface that includes text boxes and drop-down menus.

[0114] What it does: When a user launches the app, the home screen displays the message "Enter your market research request." The request input field becomes active.

[0115] Step 2:

[0116] Submitting a Request

[0117] Operation: The terminal sends the input request to the server.

[0118] Input: The request the user types in the text field.

[0119] Output: The request data in JSON format is sent to the server.

[0120] Specific operation: When the user presses the "Submit" button, a request to "perform a PEST analysis and 5 Forces analysis of the AI ​​market" is sent to the server in JSON format. For example, {"request":"AI market", "analysis":["PEST", "5 Forces"]}.

[0121] Step 3:

[0122] Data collection

[0123] Operation: The server collects data related to a specified market from the Internet.

[0124] Input: Request data in JSON format.

[0125] Output: Raw market data collected (news articles, reports, papers, etc.).

[0126] What it does: The server uses the Google News API and PubMed API to search for the latest articles and academic papers on the AI ​​market, retrieves the results, and uses Python's "BeautifulSoup" to perform web scraping and collect relevant data.

[0127] Step 4:

[0128] Data formatting

[0129] How it works: The server organizes the collected data into a unified format (e.g., JSON format).

[0130] Input: Data in various formats (HTML, PDF, CSV, etc.).

[0131] Output: Data in consistent JSON format.

[0132] What it does: Uses Python's "pandas" and "PyPDF2" to convert collected data into a consistent format, for example extracting technical reports in PDF format into text and formatting them into JSON fields.

[0133] Step 5:

[0134] Keyword extraction

[0135] How it works: The server uses natural language processing techniques to extract important keywords and topics from the organized data.

[0136] Input: Organized data in JSON format.

[0137] Output: A dataset containing important keywords and topics.

[0138] Specific operation: The server performs text analysis using NLTK and SpaCy to extract keywords such as "technology trends," "regulatory changes," and "market growth rate."

[0139] Step 6:

[0140] Performing a PEST Analysis

[0141] Operation: The server performs a PEST analysis based on the extracted data.

[0142] Input: A dataset containing keywords or topics.

[0143] Output: Analysis results evaluated from political, economic, social and technological perspectives.

[0144] What it does: The server evaluates political regulations, economic trends, social influences, and technological advancements in the AI ​​market and categorizes and describes them.

[0145] Step 7:

[0146] 5. Performing Forces Analysis

[0147] How it works: The server performs a 5 Forces analysis on the extracted data.

[0148] Input: A dataset containing keywords or topics.

[0149] Output: Analysis assessing the intensity of competition, threat of new entrants, threat of substitutes, bargaining power of suppliers, and bargaining power of buyers.

[0150] What it does: The server analyzes data on key competitors to assess competitiveness and threats of new entrants. For example, it performs a detailed assessment of the impact of key competitor X on the market.

[0151] Step 8:

[0152] Generate reports

[0153] How it works: The server generates a market understanding report based on the results of the PEST analysis and the 5 Forces analysis.

[0154] Input: Results of PEST analysis and 5 Forces analysis.

[0155] Output: Market understanding report.

[0156] What it does: Uses Python's Jupyter Notebook and Matplotlib to generate text and graphical reports, including detailed PDF reports with PEST and 5 Forces charts.

[0157] Step 9:

[0158] Report distribution

[0159] How it works: The server generates a report and sends it to the user's device.

[0160] Input: Market Understanding Report.

[0161] Output: Report delivered to user terminal.

[0162] What happens: The report will be attached to your email in PDF format, or you will be provided with a download link. For example, open the email on your device and you will be able to download the "AI Market Analysis Report" as a PDF.

[0163] (Application example 1)

[0164] 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."

[0165] Market research is important in the advertising industry for formulating effective marketing strategies. However, traditional market research methods are time-consuming, labor-intensive, and require significant resource expenditures. Furthermore, it is difficult to maintain consistency in data collection, organization, and analysis, which can lead to problems with the accuracy and reliability of the resulting reports. Given this background, there is a growing need for systems that support market research efficiently and effectively.

[0166] 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.

[0167] In this invention, the server includes means for inputting a market research request from a user terminal, means for collecting data on a specified market from the Internet, means for organizing the collected data into a unified format, means for extracting important keywords and topics using natural language processing technology, means for performing a PEST analysis based on the extracted data, means for performing a 5 Forces analysis based on the extracted data, means for generating a market understanding report based on the results of the PEST analysis and the 5 Forces analysis, means for sending the generated report to the user terminal in PDF or web page format, means for supporting the generation of a market research report in the advertising industry using the analysis results, and means for guiding user input using prompt sentences. This allows for efficient and effective support of market research in the advertising industry, enabling users to perform advanced market analysis even without specialized knowledge.

[0168] "Market Research Request" means instructions entered by a User requesting the collection or analysis of information about a particular market or type of analysis.

[0169] A "user terminal" is a device, such as a smartphone or computer, that a user uses to connect to the Internet and input and receive information.

[0170] "Data collection means" refers to the function of the server to search and acquire data related to a specified market from the Internet.

[0171] "Means of organizing into a unified format" refers to the function of converting collected data into a unified format, such as JSON format, and saving it.

[0172] "Natural language processing technology" refers to the technology that uses computers to analyze, understand, and generate human language.

[0173] "Means for extracting keywords and topics" refers to the function of extracting important words and topics from text data using natural language processing technology.

[0174] "PEST analysis" is a method of analyzing a market from four perspectives: political, economic, social, and technological.

[0175] "Five Forces Analysis" is an analytical method for evaluating a market based on five factors: intensity of competition (competition among existing companies), threat of new entrants, threat of substitutes, bargaining power of suppliers, and bargaining power of buyers.

[0176] A "Market Understanding Report" is a detailed and comprehensive report on a specific market that compiles the results of a PEST analysis and a 5 Forces analysis.

[0177] "Means for sending to user terminal in PDF or web page format" refers to the functionality for providing the generated report to the user as a PDF file or web page.

[0178] "Means for supporting the generation of market research reports in the advertising industry" refers to a function for creating detailed market analysis reports for the purpose of formulating effective marketing strategies in the advertising industry.

[0179] "Means for guiding user input using prompts" refers to a function that provides specific instructions and examples to guide users in properly entering their market research requests.

[0180] This invention relates to a system in which a user inputs a research request for a specific market, a server collects and analyzes the necessary data from the Internet, and generates and provides a market understanding report based on PEST analysis and 5 Forces analysis. This system is specialized for the advertising industry, and it efficiently conducts market research and supports the formulation of marketing strategies.

[0181] The system for implementing this invention includes the following main functions: a user terminal, a server, natural language processing technology (NLP), and data collection and analysis means.

[0182] Hardware and Software

[0183] Hardware: User devices such as smartphones and computers where users input information, and servers that collect and analyze data.

[0184] Software: Server-side processing is done using Python and Flask, data scraping is done using Beautiful Soup and Selenium, and NLP is done using SpaCy or NLTK.

[0185] Details of data processing and calculation

[0186] 1. User Interface:

[0187] The user terminal provides a form for entering a research request. The form is constructed using HTML / CSS / JavaScript. The user enters details about a specific market and analysis format, and the information is received by the Flask server.

[0188] Example: A user fills out a form and asks for a PEST analysis and 5 Forces analysis of the smartphone advertising market.

[0189] 2. Processing the request:

[0190] The information entered into the form is sent to the server via the Flask server, which starts collecting data related to the specified market based on the request.

[0191] Example: A user request for "Smartphone Advertising Market", "PEST Analysis", and "5 Forces Analysis" is sent to the server.

[0192] 3. Data Collection:

[0193] The server collects the necessary data from the Internet using a scraping tool such as Beautiful Soup or Selenium, and the collected data may be provided in various formats (text, PDF, HTML, etc.).

[0194] Example: A server searches for the latest industry reports and news articles to gather data about the smartphone advertising market.

[0195] 4. Data formatting:

[0196] The server converts the collected data into a unified format (JSON), which makes subsequent analysis easier.

[0197] Example: Data in various formats (e.g. text, PDF, HTML) is organized into JSON format.

[0198] 5. Data analysis and keyword extraction:

[0199] Using natural language processing techniques (SpaCy or NLTK), the server extracts important keywords and topics from the data.

[0200] Example: The server extracts keywords such as "market size," "growth rate," "major competitors," and "consumer trends."

[0201] 6. PEST Analysis and Five Forces Analysis:

[0202] Based on the extracted data, the server performs a PEST analysis and a 5 Forces analysis, evaluating the market from each perspective (political, economic, social, technological and competitive, new entrants, threat of substitutes, and bargaining power of suppliers and buyers).

[0203] Example: The server analyzes the current state of the market and future trends from various perspectives.

[0204] 7. Report Generation and Delivery:

[0205] Based on the analysis results, the server generates a detailed market understanding report and provides it to the user in PDF or web page format, including a prompt function to guide the user to input appropriate requests.

[0206] Example: A report will be generated that includes "Current Status and Future Outlook of the Smartphone Advertising Market," "Analysis of Major Players," and "Technical Challenges and Trends."

[0207] Example prompt: "Please enter the market you want to analyze and select the type of analysis (PEST, 5 Forces). E.g., 'Smartphone advertising market, PEST and 5 Forces analysis.'"

[0208] In this way, the system can efficiently and effectively support market research in the advertising industry, enabling users to perform advanced market analysis without having specialized knowledge.

[0209] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0210] Step 1:

[0211] A user inputs a market research request from their device. A specific request is information about a specific market and analysis format. For example, a user might input, "I would like a PEST analysis and 5 Forces analysis of the smartphone advertising market." This input is received as a form in a user interface built with HTML / CSS / JavaScript.

[0212] Step 2:

[0213] Once the user has completed the input, the user device sends the input request to the Flask server. The specific operation of this step is to encode the form contents into JSON format and send it as an HTTP POST request to the server. The server receives this request and extracts keywords and instructions to start parsing it.

[0214] Step 3:

[0215] Based on the received request, the server collects data about the specified market from the Internet. For example, the server uses Beautiful Soup or Selenium to scrape the web for relevant open data, industry reports, news articles, etc. The input for this step is the request keywords, and the output is the collected raw data.

[0216] Step 4:

[0217] The server organizes the collected data into a unified format. In this step, data from various formats (text, PDF, HTML, etc.) is converted into a unified JSON format. Specifically, the server uses a PDF parsing library or parses text and HTML and combines them into a consistent format. The input is raw data, and the output is organized JSON data.

[0218] Step 5:

[0219] The server uses natural language processing (NLP) techniques to extract important keywords and topics from the unified data. Specifically, it uses SpaCy or NLTK to extract specific words and phrases within the data. The input is organized JSON data, and the output is a list of extracted keywords.

[0220] Step 6:

[0221] The server performs a PEST analysis based on the extracted keywords. Specifically, it categorizes the information in the data into political, economic, social, and technological categories and evaluates each category. The input is a list of keywords, and the output is the results of the PEST analysis.

[0222] Step 7:

[0223] The server then performs a 5 Forces analysis based on the extracted keywords. In this step, it evaluates the intensity of competition, the threat of new entrants, the threat of substitutes, and the bargaining power of suppliers and buyers. The input is a list of keywords, and the output is the results of the 5 Forces analysis.

[0224] Step 8:

[0225] The server generates a market understanding report based on the results of the PEST analysis and the 5 Forces analysis. Its specific operation is to integrate the results of each analysis and create a report in a format that is easy for users to understand. The input is the results of both analyses, and the output is the market understanding report.

[0226] Step 9:

[0227] The generated report is sent to the user's terminal in PDF or web page format. The server generates the PDF using a document generation tool (such as FPDF) and converts it to HTML when providing it in web format. The input is the market understanding report, and the output is a PDF or web page format report to the user.

[0228] Step 10:

[0229] The server provides a means to guide user input using prompts. Specifically, when a user enters a market research request, the server displays appropriate prompts (e.g., "Please enter the market you want to analyze and select the type of analysis (PEST, 5 Forces). Eg, 'Smartphone advertising market, PEST and 5 Forces analysis.'") to improve the accuracy of user input. The input is the market and analysis type specified by the user, and the output is the optimal request input situation.

[0230] 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.

[0231] The present invention relates to a system that efficiently supports market research, and is combined with an emotion engine that recognizes user emotions. When a user inputs a market request, the system collects and analyzes related data from the Internet, generates a market understanding report based on PEST analysis and 5 Forces analysis, and provides it to the user. Furthermore, by using an emotion engine that recognizes user emotions, the content and format of the report can be customized based on the user's emotional state.

[0232] System Program

[0233] 1. User Interface

[0234] How it works: The terminal provides an interface where users can enter market research requests, allowing them to specify specific markets and types of analysis.

[0235] Example: A user enters a request to "conduct a PEST analysis and 5 Forces analysis of the AI ​​market."

[0236] 2. Processing the Request

[0237] Operation: The terminal sends a request entered by the user to the server, which includes keywords and instructions for analysis.

[0238] Example: A user request is sent to the server, and the keywords "AI market", "PEST analysis", and "5 Forces analysis" arrive at the server.

[0239] 3. Emotion Recognition Implementation

[0240] How it works: The server sends the user's input request to the emotion engine, which analyzes the user's emotion. The emotion engine analyzes the input text data and evaluates the user's emotional state (e.g., interest, tension, satisfaction, etc.).

[0241] Example: A user's input text is analyzed by an emotion engine to identify emotional states such as "excited," "anxious," or "indifferent."

[0242] 4. Data Collection

[0243] How it works: The server collects data related to a specified market from the internet, including open data, industry reports, news articles, academic papers, etc.

[0244] Example: A server searches and collects the latest news articles and technical reports related to the AI ​​market.

[0245] 5. Data format organization

[0246] How it works: The server converts the data it receives into a unified format, for example, organizing data in different formats (text, PDF, CSV, etc.) into JSON format.

[0247] Example: Data in various formats such as text, PDF, CSV, etc. is converted to JSON format.

[0248] 6. Data analysis and keyword extraction

[0249] How it works: The server applies natural language processing (NLP) techniques to the organized data to extract important keywords and topics.

[0250] Example: Keywords such as "technology trends," "regulatory changes," and "market growth rate" are extracted.

[0251] 7. Conduct a PEST analysis

[0252] How it works: The server performs a PEST analysis based on the extracted data, including analysis of Politics, Economics, Society, and Technology factors.

[0253] Example: Sarver assesses the latest technological trends and regulatory impacts in the AI ​​market and categorizes them into their respective categories.

[0254] 8. Conducting a Five Forces Analysis

[0255] How it works: The server performs a 5 Forces analysis based on the same extracted data, including the intensity of competition, the threat of new entrants, the threat of substitutes, the bargaining power of suppliers, and the bargaining power of buyers.

[0256] Example: The server analyzes key competitors in the AI ​​market and assesses the threat of new entrants.

[0257] 9. Generate Reports

[0258] How it works: The server generates a market understanding report based on the results of the PEST and 5 Forces analyses. The report contains specific information and assessments that allow users to gain a deeper understanding of the market. Furthermore, the report content is customized based on the analysis results of the sentiment engine.

[0259] Example: The server generates a comprehensive report summarizing "AI market growth opportunities and challenges," "analysis of key players," "impact of technology trends," etc. If the user is excited, the report will highlight the positive aspects.

[0260] 10. Report Distribution

[0261] How it works: The server generates a report and sends it to the user's device. The report is provided in PDF format or as a web page.

[0262] Example: Users can view reports generated on their devices, which provide detailed market analysis and reflect their sentiment.

[0263] In this way, the system can efficiently support market research and further improve user experience by providing customized reports according to user sentiment.

[0264] The processing flow will be explained below.

[0265] Step 1:

[0266] Users use their devices to enter research requests for specific markets, such as "I'd like a PEST and 5 Forces analysis of the AI ​​market."

[0267] Step 2:

[0268] The terminal sends the request entered by the user to the server, which includes the market to be analyzed and the type of analysis required.

[0269] Step 3:

[0270] Based on the received request, the server sends the user's input to the emotion engine, which analyzes the user's emotion. The emotion engine analyzes the input text data and evaluates the user's emotional state (e.g., interest level, tension level, satisfaction level, etc.).

[0271] Step 4:

[0272] The server receives the user's emotional data sent from the emotion engine, identifying their emotional state, such as "excited," "anxious," or "indifferent."

[0273] Step 5:

[0274] The server collects data related to the specified market from the internet, including open data, industry reports, news articles, academic papers, etc.

[0275] Step 6:

[0276] The server converts the acquired data into a unified format, for example, organizing data in different formats such as text, PDF, and CSV into JSON format.

[0277] Step 7:

[0278] The server applies natural language processing (NLP) technology to the organized data to extract important keywords and topics, such as "technology trends," "regulatory changes," and "market growth rates."

[0279] Step 8:

[0280] The server then performs a PEST analysis based on the extracted data, including analysis of political, economic, social, and technological factors, such as assessing the impact of emerging technological trends and regulations on the AI ​​market.

[0281] Step 9:

[0282] The server also performs a 5 Forces analysis based on the extracted data, including the intensity of competition, the threat of new entrants, the threat of substitutes, the bargaining power of suppliers, and the bargaining power of buyers. For example, it analyzes major competitors in the AI ​​market and evaluates the threat of new entrants.

[0283] Step 10:

[0284] The server generates a market understanding report based on the results of the PEST and 5 Forces analyses. The report contains specific information and assessments that allow users to gain a deeper understanding of the market. Furthermore, the report content is customized based on the analysis results of the emotion engine. For example, if the user is excited, a report that emphasizes positive aspects will be generated.

[0285] Step 11:

[0286] The server then sends the generated report to the user's device, where it is available in PDF or web page format.

[0287] Step 12:

[0288] The terminal displays the received report to the user, who can then view the report generated by the terminal to check the detailed market analysis. The report also reflects the user's sentiment.

[0289] Example 2

[0290] 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."

[0291] Traditional market research systems have limited user experience because they are unable to customize reports to fit the user's needs and emotional state. Furthermore, data collection and analysis are manual, making the research process inefficient and time-consuming. To solve this issue, a system is needed that automates the market research process by providing customized reports that take user emotions into account.

[0292] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for sending a user request to an emotion engine and analyzing the user's emotions, means for collecting data on the specified market from the Internet, and means for organizing the collected data into a unified format. This makes it possible to provide a market understanding report customized based on the user's emotional state, thereby making the market research process more efficient and faster.

[0293] "User Terminal" means a device operated by a User and used to enter market research requests and receive generated reports.

[0294] "Market Research Request" means an instruction or request entered by a User to request the collection and analysis of information about a particular market.

[0295] An "emotion engine" refers to an algorithm or system that analyzes a user's input text and assesses the user's emotional state.

[0296] The "Internet" is an information and communications network that interconnects computers and networks around the world and is a medium for obtaining data from public sources.

[0297] "Data" refers to information collected from the internet, including open market data, industry reports, news articles, academic papers, etc.

[0298] "Format" refers to the format or structure in which data is stored, and indicates the standards for unifying data of different formats.

[0299] "Natural language processing technology" is a technology that enables computers to understand, interpret, and generate human language, and is used to extract important keywords and topics.

[0300] "Keywords" refer to important words or phrases related to the market research subject and are extracted during the data analysis process.

[0301] "Topics" refer to the major themes or topics extracted from the data.

[0302] "PEST analysis" refers to a method of market analysis that takes into account political, economic, social, and technological factors.

[0303] "Five Forces Analysis" refers to a market analysis method that evaluates the intensity of competition, the threat of new entrants, the threat of substitutes, the bargaining power of suppliers, and the bargaining power of buyers.

[0304] A "Market Understanding Report" is a report that details the current state and future trends of a market based on collected and analyzed data.

[0305] "Customization" refers to adjusting the content and format of a report based on the user's emotional state and needs.

[0306] "Server" refers to a central processing unit or system that receives requests from user devices and performs data collection, analysis, and report generation.

[0307] The present invention relates to a system that efficiently supports market research, particularly by incorporating an emotion engine that recognizes user emotions. When a user inputs a market request, the system collects and analyzes related data from the Internet, generates a market understanding report based on PEST analysis and 5 Forces analysis, and provides it to the user. Furthermore, by using an emotion engine that recognizes user emotions, the content and format of the report can be customized based on the user's emotional state. This improves the user experience and streamlines the market research process.

[0308] This system consists of a server and a user terminal. The user terminal provides an interface for users to input market research requests. This interface includes text input fields and selection menus. For example, a user can input a request such as "I would like you to conduct a PEST analysis and 5 Forces analysis of the AI ​​market."

[0309] When a user inputs a market research request, the device sends the request to the server. The request includes keywords and instructions for analysis. The server then sends the received request to the emotion engine, which analyzes the user's emotions. The emotion engine analyzes the input text data and evaluates the user's emotional state (e.g., interest, tension, satisfaction, etc.).

[0310] The server then collects data related to the specified market from the internet, including open data, industry reports, news articles, academic papers, etc. Because the collected data often exists in different formats, the server converts this data into a unified format, specifically converting formats such as text, PDF, and CSV into JSON.

[0311] The collected data is analyzed using natural language processing (NLP) technology to extract important keywords and topics, such as "technology trends," "regulatory changes," and "market growth rates." Based on these keywords, the server performs PEST and 5 Forces analyses.

[0312] A PEST analysis involves analyzing the market from political, economic, social, and technological perspectives. For example, it evaluates the impact of the latest technological trends and regulations on the AI ​​market and categorizes them into their respective categories. Similarly, a 5 Forces analysis evaluates the intensity of competition, the threat of new entrants, the threat of substitutes, the bargaining power of suppliers, and the bargaining power of buyers. Specifically, it analyzes major competitors in the AI ​​market and evaluates the threat of new entrants.

[0313] The server generates a market understanding report based on these analysis results. The report contains specific information and evaluations that allow users to gain a deeper understanding of the market. The report content is also customized based on the analysis results of the emotion engine. For example, if the user is excited, a report that emphasizes the positive aspects will be generated.

[0314] Finally, the server will send the generated report to the user's device, which will be available in PDF format or web page format, allowing users to view detailed market analysis and get customized information based on their own sentiment.

[0315] Examples of prompts to input to a generative AI model include:

[0316] "I would like you to conduct a PEST analysis and 5 Forces analysis of the AI ​​market."

[0317] In this way, the system can efficiently support market research and improve user experience by providing customized reports according to user sentiment.

[0318] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0319] Step 1:

[0320] The user enters a market research request, specifying a specific market and type of analysis through a user interface displayed on the terminal. As input, the user provides a prompt such as "I would like you to conduct a PEST analysis and 5 Forces analysis of the AI ​​market." As output, the user's request is obtained from the terminal.

[0321] Step 2:

[0322] The terminal sends the market research request entered by the user to the server. The input includes the user's request data (e.g., "AI market," "PEST analysis," "5 Forces analysis"), and the output includes an HTTP POST request to the server that includes the request data.

[0323] Step 3:

[0324] The server sends the received request data to the emotion engine to analyze the user's emotions. Using the request data as input, the emotion engine analyzes the text data to evaluate the user's emotional state (e.g., interest, tension, satisfaction, etc.). As output, JSON data containing the analysis results is sent back to the server.

[0325] Step 4:

[0326] The server collects data related to a specified market from the internet. Keywords such as "AI market" and "technology trends" are used as input. Specifically, data is collected through web scraping and API usage. The acquired data is then saved on the server as output.

[0327] Step 5:

[0328] The server organizes the collected data into a unified format. Data in various formats (text, PDF, CSV, etc.) is used as input. Specifically, it converts the data into JSON format using Python libraries (e.g., PyPDF2, pandas). Data in a unified format is obtained as output.

[0329] Step 6:

[0330] The server applies natural language processing (NLP) techniques to the organized data to extract important keywords and topics. Data in a standardized format is used as input. Specifically, analysis is performed using an NLP library (e.g., spaCy, NLTK). Key keywords such as "technology trends," "regulatory changes," and "market growth rates" are extracted as output.

[0331] Step 7:

[0332] The server performs a PEST analysis based on the extracted keywords. The extracted keywords are used as input. Specifically, these keywords are classified into political, economic, social, and technological categories, and an evaluation is performed for each category. The output is a detailed analysis of each category.

[0333] Step 8:

[0334] The server then performs a 5 Forces analysis based on the extracted keywords. The extracted keywords are used as input. Specifically, it evaluates the intensity of market competition, the threat of new entrants, the threat of substitutes, the bargaining power of suppliers, and the bargaining power of buyers. The output is the analysis results for each element of the 5 Forces.

[0335] Step 9:

[0336] The server generates a market understanding report based on the results of the PEST and 5 Forces analyses. The results of both analyses and the analysis of the user's emotional state are used as input. Specifically, the server compiles the report in HTML or PDF format and customizes the report content based on the results of the emotion engine. The server outputs the completed market understanding report.

[0337] Step 10:

[0338] The server sends the generated market understanding report to the user's device. The completed report data is used as input. Specifically, the server sends the report via an HTTP response so that the user can view it on their device. The output is a report that the user can view.

[0339] (Application example 2)

[0340] 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."

[0341] Conventional market research systems often provide uniform reports without considering the user's emotional state. This resulted in a lack of information tailored to the user's needs and emotions, resulting in a lack of improvement in the user experience. Furthermore, it was difficult to efficiently utilize the results of market research, preventing the improvement of user satisfaction.

[0342] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0343] In this invention, the server includes means for inputting a market research request from a user terminal, means for collecting data on a specified market from the Internet, means for organizing the collected data into a unified format, means for extracting important keywords and topics using natural language processing technology, means for performing a PEST analysis based on the extracted data, means for performing a 5 Forces analysis based on the extracted data, means for generating a market understanding report based on the results of the PEST analysis and the 5 Forces analysis, means for recognizing the emotional state of the user, means for customizing the content and format of the report based on the emotional state of the user, and means for sending the report to the user terminal. This makes it possible to generate a market understanding report customized in line with the user's emotions, improving the user experience.

[0344] "User Terminal" means the device through which a User enters market research requests and receives generated reports.

[0345] A "market research request" is information entered by a user to specify the market they wish to research and the type of analysis they wish to perform.

[0346] The "means for collecting data relating to a designated market from the Internet" is a function for automatically obtaining data relating to a designated market from the Internet.

[0347] "Means for organizing collected data into a unified format" refers to a function for converting and organizing acquired data into a consistent format.

[0348] "Natural language processing technology" is a technology for analyzing human language and extracting specific information.

[0349] "Means of extracting important keywords and topics" is a function that finds key words and themes needed for analysis from market data.

[0350] "PEST analysis" is a method of analyzing the market environment from four perspectives: politics, economics, society, and technology.

[0351] The "5 Forces Analysis" is a method for assessing the intensity of competition in a market, the threat of new entrants, the threat of substitutes, the bargaining power of suppliers, and the bargaining power of buyers.

[0352] A "Market Understanding Report" is a report that shows the current state and forecast of the market, generated based on PEST analysis and 5 Forces analysis.

[0353] "Means for recognizing the user's emotional state" refers to a function that analyzes the user's emotional state from their input and behavior.

[0354] "Means for customizing the content and format of a report based on the user's emotional state" is a function that adjusts the content and presentation of a report according to the user's emotions.

[0355] The "means for sending a report to a user terminal" is a function for sending the generated market understanding report to a user device.

[0356] This invention is a market research system that is composed of a user terminal, a server, and an emotion engine. A specific embodiment of this system is described below.

[0357] System configuration

[0358] 1. User Device:

[0359] Market research request input method: An input device (e.g., a smartphone or PC interface) through which a user requests market research.

[0360] Report receiving means: Has the function of receiving and displaying market understanding reports sent from the server.

[0361] 2. Server:

[0362] Data collection method: A function that automatically collects data about a specified market from the Internet. For example, using an API to obtain relevant data.

[0363] Data reduction: A function to convert and reduce collected data into a unified format. Convert data in different formats (text, PDF, CSV, etc.) into JSON format.

[0364] Natural language processing technology: Technology that uses software libraries such as TextBlob to extract important keywords and topics from collected data.

[0365] PEST analysis and 5 Forces analysis: A function that evaluates the market to deepen understanding based on the analysis results. For example, it evaluates growth opportunities and the intensity of competition in the AI ​​market.

[0366] Report generation tool: A function that generates a market understanding report that integrates the results of PEST analysis and 5 Forces analysis based on the analysis results.

[0367] Emotion recognition: Analyzes the user's input and recognizes their emotional state. Uses an emotion analysis engine such as TextBlob.

[0368] Report customization: Ability to tailor and customize report content and format based on perceived sentiment.

[0369] Report sending method: A function for sending generated reports to the user's terminal.

[0370] Specific processing flow

[0371] When a user inputs a market research request into their device, the request is first analyzed using emotion recognition means to identify the user's emotional state (e.g., positive, negative, neutral). The server then collects relevant data from the Internet and organizes it into a unified format. The organized data is then analyzed using natural language processing techniques to extract important keywords and topics.

[0372] The extracted data is then used for PEST and 5 Forces analysis, and the analysis results are compiled into a market understanding report, which is customized based on the user's emotional state. Finally, the customized report is sent to the user's device for viewing.

[0373] Specific examples of hardware or software to be used

[0374] Sentiment Analysis Engine: TextBlob or similar natural language processing library

[0375] Data collection: Public APIs and web crawlers

[0376] Data format conversion: JSON library

[0377] Analysis technology: Natural Language Processing (e.g., NLTK)

[0378] Specific examples

[0379] An example of a prompt is:

[0380] "Please conduct a PEST analysis and 5 Forces analysis of the AI ​​market."

[0381] "Provide the latest trends and competitive analysis in the automotive industry"

[0382] With this invention, users receive personalized, emotionally relevant market understanding reports, enabling them to make more informed decisions.

[0383] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0384] Step 1:

[0385] Enter a market research request from the user's device.

[0386] The user uses a smartphone or PC interface to input information specifying a particular market and type of analysis, which then inputs the user's request into the terminal.

[0387] Step 2:

[0388] The input request is sent to the server.

[0389] The user terminal sends the input request to the server, which includes instructions on the market to be researched and the type of analysis.

[0390] Step 3:

[0391] An emotion recognizer analyzes the request and recognizes the user's emotional state.

[0392] The server uses an emotion engine to analyze the input request text and identify the user's emotional state (positive, negative, neutral, etc.), resulting in the emotion analysis result.

[0393] Step 4:

[0394] Collect data about a specified market from the internet.

[0395] The server retrieves data about the specified market from the internet using APIs and web crawlers, and stores the retrieved data as raw data.

[0396] Step 5:

[0397] Organize the collected data into a unified format.

[0398] The server converts and organizes data from different formats (text, PDF, CSV, etc.) into a unified format (such as JSON), thereby maintaining data consistency.

[0399] Step 6:

[0400] Natural language processing technology is used to extract important keywords and topics.

[0401] The server uses natural language processing libraries such as TextBlob to extract important keywords and topics from the data, providing key insights and trends.

[0402] Step 7:

[0403] A PEST analysis is performed based on the extracted data.

[0404] The server then analyzes the Politics, Economics, Society, and Technology elements based on the extracted keywords and topics, generating the PEST analysis results.

[0405] Step 8:

[0406] A 5 Forces analysis will be performed based on the extracted data.

[0407] The server applies the 5 Forces analysis to evaluate the intensity of competition, the threat of new entrants, the threat of substitutes, the bargaining power of suppliers, and the bargaining power of buyers, thereby generating the 5 Forces analysis results.

[0408] Step 9:

[0409] Generate market understanding reports based on the results of PEST analysis and 5 Forces analysis.

[0410] The server integrates the results of PEST and 5 Forces analysis to create a comprehensive market understanding report, the content and format of which are customized based on the user's emotional state as previously analyzed.

[0411] Step 10:

[0412] Send the generated report to the user's device.

[0413] The server generates a customized market understanding report in PDF format, web page format, etc., and sends it to the user's device, where the user can view the report.

[0414] Prompt Sentence Examples

[0415] "Please conduct a PEST analysis and 5 Forces analysis of the AI ​​market."

[0416] "Provide the latest trends and competitive analysis in the automotive industry"

[0417] In this way, users receive emotionally relevant and customized market understanding reports, leading to more accurate and useful information.

[0418] 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.

[0419] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (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.

[0420] 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.

[0421] [Second embodiment]

[0422] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0423] 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.

[0424] 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).

[0425] 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.

[0426] 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.

[0427] 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).

[0428] 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. 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.

[0429] 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.

[0430] 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.

[0431] 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.

[0432] 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.

[0433] 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."

[0434] The present invention relates to a system that efficiently supports market research. When a user inputs a market request, the system collects and analyzes related data from the Internet, generates a market understanding report based on PEST analysis and 5 Forces analysis, and provides it to the user.

[0435] System Program

[0436] 1. User Interface

[0437] How it works: The terminal provides an interface where users can enter market research requests, allowing them to specify specific markets and types of analysis.

[0438] Example: A user enters a request to "conduct a PEST analysis and 5 Forces analysis of the AI ​​market."

[0439] 2. Processing the Request

[0440] Operation: The terminal sends a request entered by the user to the server, which includes keywords and instructions for analysis.

[0441] Example: A user request is sent to the server, and the keywords "AI market", "PEST analysis", and "5 Forces analysis" arrive at the server.

[0442] 3. Data Collection

[0443] How it works: The server collects data related to a specified market from the internet, including open data, industry reports, news articles, academic papers, etc.

[0444] Example: A server searches and collects the latest news articles and technical reports related to the AI ​​market.

[0445] 4. Data format organization

[0446] How it works: The server organizes the collected data into a consistent format (e.g., JSON) so that the data is stored in a unified form before analysis.

[0447] Example: Data in various formats such as text, PDF, CSV, etc. is converted to JSON format.

[0448] 5. Data analysis and keyword extraction

[0449] How it works: The server uses natural language processing techniques to extract important keywords and topics from the organized data.

[0450] Example: Keywords such as "technology trends," "regulatory changes," and "market growth rate" are extracted.

[0451] 6. Conduct a PEST analysis

[0452] How it works: The server performs a PEST analysis based on the extracted data, which analyzes the market from political, economic, social, and technological perspectives.

[0453] Example: Sarver assesses the latest technological trends and regulatory impacts in the AI ​​market and categorizes them into their respective categories.

[0454] 7. Conducting a Five Forces Analysis

[0455] How it works: The server performs a 5 Forces analysis on the same extracted data, assessing the intensity of competition, the threat of new entrants, the threat of substitutes, the bargaining power of suppliers, and the bargaining power of buyers.

[0456] Example: The server analyzes key competitors in the AI ​​market and assesses the threat of new entrants.

[0457] 8. Generate Reports

[0458] How it works: The server generates a market understanding report based on the results of the PEST and 5 Forces analyses. The report contains specific information and assessments that allow users to gain a deeper understanding of the market.

[0459] Example: The server generates a comprehensive report summarizing "AI market growth opportunities and challenges," "analysis of key players," and "impact of technology trends."

[0460] 9. Report Distribution

[0461] How it works: The server generates a report and sends it to the user's device. The report is provided in PDF format or as a web page.

[0462] Example: Users can view reports generated on their devices and get detailed market analysis.

[0463] In this way, the present system efficiently supports market research and provides users with the ability to perform advanced market analysis even without specialized knowledge.

[0464] The processing flow will be explained below.

[0465] Step 1: The user uses their device to enter a research request for a specific market, for example, "I would like a PEST analysis and 5 Forces analysis of the AI ​​market."

[0466] Step 2: The terminal sends the request entered by the user to the server, which includes the market to be analyzed and the type of analysis required.

[0467] Step 3: Based on the received request, the server collects data related to the specified market, searching and retrieving open data, industry reports, news articles, academic papers, etc. from the Internet.

[0468] Step 4: The server converts the acquired data into a unified format, for example, organizing data in different formats such as text, PDF, CSV, etc. into JSON format.

[0469] Step 5: The server applies natural language processing (NLP) techniques to the organized data to extract important keywords and topics, such as technology trends, regulatory changes, and market growth rates.

[0470] Step 6: The server performs a PEST analysis based on the extracted data, including analysis of political, economic, social, and technological factors, such as assessing the impact of emerging technological trends and regulations on the AI ​​market.

[0471] Step 7: The server performs a 5 Forces analysis based on the extracted data, including the intensity of competition, the threat of new entrants, the threat of substitutes, the bargaining power of suppliers, and the bargaining power of buyers. For example, it analyzes major competitors in the AI ​​market and evaluates the threat of new entrants.

[0472] Step 8: The server generates a market understanding report based on the results of the PEST analysis and 5 Forces analysis. The report contains specific information and assessments that allow users to gain a deeper understanding of the market. For example, the report includes "AI market growth opportunities and challenges," "analysis of key players," and "impact of technological trends."

[0473] Step 9: The server sends the generated report to the user's device, which can be provided in PDF or web page format.

[0474] Step 10: The terminal displays the received report to the user. The user can view the report generated on the terminal and check the details of the market analysis.

[0475] Example 1

[0476] 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."

[0477] The market research process requires the collection, organization, and analysis of a wide variety of data, which requires a great deal of time and specialized knowledge. When conducting PEST analysis or 5 Forces analysis, the challenge is to quickly and accurately extract relevant information from a wide range of data sources. Many existing market research tools struggle to efficiently complete this process, forcing users to use multiple tools in combination.

[0478] 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.

[0479] In this invention, the server includes means for inputting a market research request from a user terminal, means for collecting data on a specified market from the Internet, means for organizing the collected data into a unified format, means for extracting important keywords and topics using natural language processing technology, means for analyzing the market from political, economic, social, and technological perspectives based on the extracted data, means for analyzing the market structure and competitive environment based on the extracted data, means for generating a market understanding report based on the analysis results, and means for transmitting the report to the user terminal. This enables users to quickly and efficiently perform advanced market analysis even without specialized knowledge.

[0480] "User Terminal" means the electronic device used by a User to access the System and enter market research requests.

[0481] A "Market Research Request" is a request entered into the System by a User specifying a particular market or type of analysis.

[0482] The "Internet" is a global network used to collect information.

[0483] "Data" refers to information about the market, collected from news articles, industry reports, academic papers, etc.

[0484] "Format" refers to the format or structure that unifies data and provides a basis for consistent analysis.

[0485] "Natural language processing technology" is a technology that allows computers to understand and analyze human language, and is used to extract keywords and topics.

[0486] "Keywords" refer to important words or phrases that are the subject of market research.

[0487] "Topics" refer to major themes or topics related to the subject of market research.

[0488] "PEST analysis" is an analytical method that evaluates a market from political, economic, social, and technological perspectives.

[0489] "Five Forces Analysis" is an analytical method for evaluating market structure and the competitive environment, assessing the intensity of competition, the threat of new entrants, the threat of substitutes, the bargaining power of suppliers, and the bargaining power of buyers.

[0490] A "Market Understanding Report" is a document created based on the results of PEST analysis and 5 Forces analysis, which allows users to gain a deeper understanding of the market.

[0491] A "server" is a computer system that performs processes such as data collection, organization, analysis, and report generation.

[0492] "Send" refers to the act of transferring the generated report to a user terminal.

[0493] This invention relates to a system that efficiently supports market research. In this system, when a user inputs a market request through a terminal, a server collects and analyzes related data from the Internet, generates a market understanding report based on PEST analysis and 5 Forces analysis, and provides it to the user.

[0494] The system is configured as follows: The user terminal has a user interface for inputting requests. The user uses this interface to specify a specific market and type of analysis. For example, a request can be made to "conduct a PEST analysis and 5 Forces analysis of the AI ​​market."

[0495] The device sends a request from the user to the server. The request includes keywords and instructions necessary for analysis. The server then collects data related to the specified market from the Internet. This collection uses a wide range of data sources, including open data, industry reports, news articles, and academic papers. Specifically, it uses Python's "BeautifulSoup" and "Google News API" to collect information from the Internet.

[0496] The collected data is organized on the server in a consistent format (e.g., JSON format). This streamlines preprocessing for analysis and stores the data in a unified format. Python libraries such as "pandas" and "PyPDF2" are used to organize the data.

[0497] The server uses natural language processing technology (using NLTK and SpaCy) to extract important keywords and topics from the organized data, such as "technology trends," "regulatory changes," and "market growth rates."

[0498] The server then performs a PEST analysis based on the extracted data. The PEST analysis evaluates the market from political, economic, social, and technological perspectives. Specifically, it evaluates the impact of the latest technological trends and regulations on the AI ​​market and classifies them into categories.

[0499] Similarly, the server performs a 5 Forces analysis, which evaluates the intensity of competition, threat of new entrants, threat of substitutes, bargaining power of suppliers, and bargaining power of buyers, including a detailed analysis of key competitors and a detailed assessment of the threat of new entrants.

[0500] Finally, the server generates a market understanding report based on the results of the PEST and 5 Forces analyses. This report contains specific information and assessments that allow users to gain a deeper understanding of the market. The report can also include graphical elements using Python's Jupyter Notebook and Matplotlib.

[0501] The generated report is sent from the server to the user's device, and is available in PDF or web page format, which the user can access via email or a download link.

[0502] Here is an example prompt:

[0503] "Please conduct a PEST analysis and 5 Forces analysis of the AI ​​market."

[0504] This system enables users to perform sophisticated market analysis quickly and efficiently, even without specialized knowledge.

[0505] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0506] Step 1:

[0507] User Interface Display

[0508] What it does: The terminal displays an interface that allows the user to enter a market research request.

[0509] Input: A web page a user visits or a mobile app launch.

[0510] Output: A display of an input interface that includes text boxes and drop-down menus.

[0511] What it does: When a user launches the app, the home screen displays the message "Enter your market research request." The request input field becomes active.

[0512] Step 2:

[0513] Submitting a Request

[0514] Operation: The terminal sends the input request to the server.

[0515] Input: The request the user types in the text field.

[0516] Output: The request data in JSON format is sent to the server.

[0517] Specific operation: When the user presses the "Submit" button, a request to "perform a PEST analysis and 5 Forces analysis of the AI ​​market" is sent to the server in JSON format. For example, {"request":"AI market", "analysis":["PEST", "5 Forces"]}.

[0518] Step 3:

[0519] Data collection

[0520] Operation: The server collects data related to a specified market from the Internet.

[0521] Input: Request data in JSON format.

[0522] Output: Raw market data collected (news articles, reports, papers, etc.).

[0523] What it does: The server uses the Google News API and PubMed API to search for the latest articles and academic papers on the AI ​​market, retrieves the results, and uses Python's "BeautifulSoup" to perform web scraping and collect relevant data.

[0524] Step 4:

[0525] Data formatting

[0526] How it works: The server organizes the collected data into a unified format (e.g., JSON format).

[0527] Input: Data in various formats (HTML, PDF, CSV, etc.).

[0528] Output: Data in consistent JSON format.

[0529] What it does: Uses Python's "pandas" and "PyPDF2" to convert collected data into a consistent format, for example extracting technical reports in PDF format into text and formatting them into JSON fields.

[0530] Step 5:

[0531] Keyword extraction

[0532] How it works: The server uses natural language processing techniques to extract important keywords and topics from the organized data.

[0533] Input: Organized data in JSON format.

[0534] Output: A dataset containing important keywords and topics.

[0535] Specific operation: The server performs text analysis using NLTK and SpaCy to extract keywords such as "technology trends," "regulatory changes," and "market growth rate."

[0536] Step 6:

[0537] Performing a PEST Analysis

[0538] Operation: The server performs a PEST analysis based on the extracted data.

[0539] Input: A dataset containing keywords or topics.

[0540] Output: Analysis results evaluated from political, economic, social and technological perspectives.

[0541] What it does: The server evaluates political regulations, economic trends, social influences, and technological advancements in the AI ​​market and categorizes and describes them.

[0542] Step 7:

[0543] 5. Performing Forces Analysis

[0544] How it works: The server performs a 5 Forces analysis on the extracted data.

[0545] Input: A dataset containing keywords or topics.

[0546] Output: Analysis assessing the intensity of competition, threat of new entrants, threat of substitutes, bargaining power of suppliers, and bargaining power of buyers.

[0547] What it does: The server analyzes data on key competitors to assess competitiveness and threats of new entrants. For example, it performs a detailed assessment of the impact of key competitor X on the market.

[0548] Step 8:

[0549] Generate reports

[0550] How it works: The server generates a market understanding report based on the results of the PEST analysis and the 5 Forces analysis.

[0551] Input: Results of PEST analysis and 5 Forces analysis.

[0552] Output: Market understanding report.

[0553] What it does: Uses Python's Jupyter Notebook and Matplotlib to generate text and graphical reports, including detailed PDF reports with PEST and 5 Forces charts.

[0554] Step 9:

[0555] Report distribution

[0556] How it works: The server generates a report and sends it to the user's device.

[0557] Input: Market Understanding Report.

[0558] Output: Report delivered to user terminal.

[0559] What happens: The report will be attached to your email in PDF format, or you will be provided with a download link. For example, open the email on your device and you will be able to download the "AI Market Analysis Report" as a PDF.

[0560] (Application example 1)

[0561] 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."

[0562] Market research is important in the advertising industry for formulating effective marketing strategies. However, traditional market research methods are time-consuming, labor-intensive, and require significant resource expenditures. Furthermore, it is difficult to maintain consistency in data collection, organization, and analysis, which can lead to problems with the accuracy and reliability of the resulting reports. Given this background, there is a growing need for systems that support market research efficiently and effectively.

[0563] 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.

[0564] In this invention, the server includes means for inputting a market research request from a user terminal, means for collecting data on a specified market from the Internet, means for organizing the collected data into a unified format, means for extracting important keywords and topics using natural language processing technology, means for performing a PEST analysis based on the extracted data, means for performing a 5 Forces analysis based on the extracted data, means for generating a market understanding report based on the results of the PEST analysis and the 5 Forces analysis, means for sending the generated report to the user terminal in PDF or web page format, means for supporting the generation of a market research report in the advertising industry using the analysis results, and means for guiding user input using prompt sentences. This allows for efficient and effective support of market research in the advertising industry, enabling users to perform advanced market analysis even without specialized knowledge.

[0565] "Market Research Request" means instructions entered by a User requesting the collection or analysis of information about a particular market or type of analysis.

[0566] A "user terminal" is a device, such as a smartphone or computer, that a user uses to connect to the Internet and input and receive information.

[0567] "Data collection means" refers to the function of the server to search and acquire data related to a specified market from the Internet.

[0568] "Means of organizing into a unified format" refers to the function of converting collected data into a unified format, such as JSON format, and saving it.

[0569] "Natural language processing technology" refers to the technology that uses computers to analyze, understand, and generate human language.

[0570] "Means for extracting keywords and topics" refers to the function of extracting important words and topics from text data using natural language processing technology.

[0571] "PEST analysis" is a method of analyzing a market from four perspectives: political, economic, social, and technological.

[0572] "Five Forces Analysis" is an analytical method for evaluating a market based on five factors: intensity of competition (competition among existing companies), threat of new entrants, threat of substitutes, bargaining power of suppliers, and bargaining power of buyers.

[0573] A "Market Understanding Report" is a detailed and comprehensive report on a specific market that compiles the results of a PEST analysis and a 5 Forces analysis.

[0574] "Means for sending to user terminal in PDF or web page format" refers to the functionality for providing the generated report to the user as a PDF file or web page.

[0575] "Means for supporting the generation of market research reports in the advertising industry" refers to a function for creating detailed market analysis reports for the purpose of formulating effective marketing strategies in the advertising industry.

[0576] "Means for guiding user input using prompts" refers to a function that provides specific instructions and examples to guide users in properly entering their market research requests.

[0577] This invention relates to a system in which a user inputs a research request for a specific market, a server collects and analyzes the necessary data from the Internet, and generates and provides a market understanding report based on PEST analysis and 5 Forces analysis. This system is specialized for the advertising industry, and it efficiently conducts market research and supports the formulation of marketing strategies.

[0578] The system for implementing this invention includes the following main functions: a user terminal, a server, natural language processing technology (NLP), and data collection and analysis means.

[0579] Hardware and Software

[0580] Hardware: User devices such as smartphones and computers where users input information, and servers that collect and analyze data.

[0581] Software: Server-side processing is done using Python and Flask, data scraping is done using Beautiful Soup and Selenium, and NLP is done using SpaCy or NLTK.

[0582] Details of data processing and calculation

[0583] 1. User Interface:

[0584] The user terminal provides a form for entering a research request. The form is built using HTML / CSS / JavaScript. The user enters details about a specific market and analysis format, and the information is received by the Flask server.

[0585] Example: A user fills out a form and asks for a PEST analysis and 5 Forces analysis of the smartphone advertising market.

[0586] 2. Processing the request:

[0587] The information entered into the form is sent to the server via the Flask server, which starts collecting data related to the specified market based on the request.

[0588] Example: A user request for "Smartphone Advertising Market", "PEST Analysis", and "5 Forces Analysis" is sent to the server.

[0589] 3. Data Collection:

[0590] The server collects the necessary data from the Internet using a scraping tool such as Beautiful Soup or Selenium, and the collected data may be provided in various formats (text, PDF, HTML, etc.).

[0591] Example: A server searches for the latest industry reports and news articles to gather data about the smartphone advertising market.

[0592] 4. Data formatting:

[0593] The server converts the collected data into a unified format (JSON), which makes subsequent analysis easier.

[0594] Example: Data in various formats (e.g. text, PDF, HTML) is organized into JSON format.

[0595] 5. Data analysis and keyword extraction:

[0596] Using natural language processing techniques (SpaCy or NLTK), the server extracts important keywords and topics from the data.

[0597] Example: The server extracts keywords such as "market size," "growth rate," "major competitors," and "consumer trends."

[0598] 6. PEST Analysis and Five Forces Analysis:

[0599] Based on the extracted data, the server performs a PEST analysis and a 5 Forces analysis, evaluating the market from each perspective (political, economic, social, technological and competitive, new entrants, threat of substitutes, and bargaining power of suppliers and buyers).

[0600] Example: The server analyzes the current state of the market and future trends from various perspectives.

[0601] 7. Report Generation and Delivery:

[0602] Based on the analysis results, the server generates a detailed market understanding report and provides it to the user in PDF or web page format, including a prompt function to guide the user to input appropriate requests.

[0603] Example: A report will be generated that includes "Current Status and Future Outlook of the Smartphone Advertising Market," "Analysis of Major Players," and "Technical Challenges and Trends."

[0604] Example prompt: "Please enter the market you want to analyze and select the type of analysis (PEST, 5 Forces). E.g., 'Smartphone advertising market, PEST and 5 Forces analysis.'"

[0605] In this way, the system can efficiently and effectively support market research in the advertising industry, enabling users to perform advanced market analysis without having specialized knowledge.

[0606] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0607] Step 1:

[0608] A user inputs a market research request from their device. A specific request is information about a specific market and analysis format. For example, a user might input, "I would like a PEST analysis and 5 Forces analysis of the smartphone advertising market." This input is received as a form in a user interface built with HTML / CSS / JavaScript.

[0609] Step 2:

[0610] Once the user has completed the input, the user device sends the input request to the Flask server. The specific operation of this step is to encode the form contents into JSON format and send it as an HTTP POST request to the server. The server receives this request and extracts keywords and instructions to start parsing it.

[0611] Step 3:

[0612] Based on the received request, the server collects data about the specified market from the Internet. For example, the server uses Beautiful Soup or Selenium to scrape the web for relevant open data, industry reports, news articles, etc. The input for this step is the request keywords, and the output is the collected raw data.

[0613] Step 4:

[0614] The server organizes the collected data into a unified format. In this step, data from various formats (text, PDF, HTML, etc.) is converted into a unified JSON format. Specifically, the server uses a PDF parsing library or parses text and HTML and combines them into a consistent format. The input is raw data, and the output is organized JSON data.

[0615] Step 5:

[0616] The server uses natural language processing (NLP) techniques to extract important keywords and topics from the unified data. Specifically, it uses SpaCy or NLTK to extract specific words and phrases within the data. The input is organized JSON data, and the output is a list of extracted keywords.

[0617] Step 6:

[0618] The server performs a PEST analysis based on the extracted keywords. Specifically, it categorizes the information in the data into political, economic, social, and technological categories and evaluates each category. The input is a list of keywords, and the output is the results of the PEST analysis.

[0619] Step 7:

[0620] The server then performs a 5 Forces analysis based on the extracted keywords. In this step, it evaluates the intensity of competition, the threat of new entrants, the threat of substitutes, and the bargaining power of suppliers and buyers. The input is a list of keywords, and the output is the results of the 5 Forces analysis.

[0621] Step 8:

[0622] The server generates a market understanding report based on the results of the PEST analysis and the 5 Forces analysis. Its specific operation is to integrate the results of each analysis and create a report in a format that is easy for users to understand. The input is the results of both analyses, and the output is the market understanding report.

[0623] Step 9:

[0624] The generated report is sent to the user's terminal in PDF or web page format. The server generates the PDF using a document generation tool (such as FPDF) and converts it to HTML when providing it in web format. The input is the market understanding report, and the output is a PDF or web page format report to the user.

[0625] Step 10:

[0626] The server provides a means to guide user input using prompts. Specifically, when a user enters a market research request, the server displays appropriate prompts (e.g., "Please enter the market you want to analyze and select the type of analysis (PEST, 5 Forces). Eg, 'Smartphone advertising market, PEST and 5 Forces analysis.'") to improve the accuracy of user input. The input is the market and analysis type specified by the user, and the output is the optimal request input situation.

[0627] 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.

[0628] The present invention relates to a system that efficiently supports market research, and is combined with an emotion engine that recognizes user emotions. When a user inputs a market request, the system collects and analyzes related data from the Internet, generates a market understanding report based on PEST analysis and 5 Forces analysis, and provides it to the user. Furthermore, by using an emotion engine that recognizes user emotions, the content and format of the report can be customized based on the user's emotional state.

[0629] System Program

[0630] 1. User Interface

[0631] How it works: The terminal provides an interface where users can enter market research requests, allowing them to specify specific markets and types of analysis.

[0632] Example: A user enters a request to "conduct a PEST analysis and 5 Forces analysis of the AI ​​market."

[0633] 2. Processing the Request

[0634] Operation: The terminal sends a request entered by the user to the server, which includes keywords and instructions for analysis.

[0635] Example: A user request is sent to the server, and the keywords "AI market", "PEST analysis", and "5 Forces analysis" arrive at the server.

[0636] 3. Emotion Recognition Implementation

[0637] How it works: The server sends the user's input request to the emotion engine, which analyzes the user's emotion. The emotion engine analyzes the input text data and evaluates the user's emotional state (e.g., interest, tension, satisfaction, etc.).

[0638] Example: A user's input text is analyzed by an emotion engine to identify emotional states such as "excited," "anxious," or "indifferent."

[0639] 4. Data Collection

[0640] How it works: The server collects data related to a specified market from the internet, including open data, industry reports, news articles, academic papers, etc.

[0641] Example: A server searches and collects the latest news articles and technical reports related to the AI ​​market.

[0642] 5. Data format organization

[0643] How it works: The server converts the data it receives into a unified format, for example, organizing data in different formats (text, PDF, CSV, etc.) into JSON format.

[0644] Example: Data in various formats such as text, PDF, CSV, etc. is converted to JSON format.

[0645] 6. Data analysis and keyword extraction

[0646] How it works: The server applies natural language processing (NLP) techniques to the organized data to extract important keywords and topics.

[0647] Example: Keywords such as "technology trends," "regulatory changes," and "market growth rate" are extracted.

[0648] 7. Conduct a PEST analysis

[0649] How it works: The server performs a PEST analysis based on the extracted data, including analysis of Politics, Economics, Society, and Technology factors.

[0650] Example: Sarver assesses the latest technological trends and regulatory impacts in the AI ​​market and categorizes them into their respective categories.

[0651] 8. Conducting a Five Forces Analysis

[0652] How it works: The server performs a 5 Forces analysis based on the same extracted data, including the intensity of competition, the threat of new entrants, the threat of substitutes, the bargaining power of suppliers, and the bargaining power of buyers.

[0653] Example: The server analyzes key competitors in the AI ​​market and assesses the threat of new entrants.

[0654] 9. Generate Reports

[0655] How it works: The server generates a market understanding report based on the results of the PEST and 5 Forces analyses. The report contains specific information and assessments that allow users to gain a deeper understanding of the market. Furthermore, the report content is customized based on the analysis results of the sentiment engine.

[0656] Example: The server generates a comprehensive report summarizing "AI market growth opportunities and challenges," "analysis of key players," "impact of technology trends," etc. If the user is excited, the report will highlight the positive aspects.

[0657] 10. Report Distribution

[0658] How it works: The server generates a report and sends it to the user's device. The report is provided in PDF format or as a web page.

[0659] Example: Users can view reports generated on their devices, which provide detailed market analysis and reflect their sentiment.

[0660] In this way, the system can efficiently support market research and further improve user experience by providing customized reports according to user sentiment.

[0661] The processing flow will be explained below.

[0662] Step 1:

[0663] Users use their devices to enter research requests for specific markets, such as "I'd like a PEST and 5 Forces analysis of the AI ​​market."

[0664] Step 2:

[0665] The terminal sends the request entered by the user to the server, which includes the market to be analyzed and the type of analysis required.

[0666] Step 3:

[0667] Based on the received request, the server sends the user's input to the emotion engine, which analyzes the user's emotion. The emotion engine analyzes the input text data and evaluates the user's emotional state (e.g., interest level, tension level, satisfaction level, etc.).

[0668] Step 4:

[0669] The server receives the user's emotional data sent from the emotion engine, identifying their emotional state, such as "excited," "anxious," or "indifferent."

[0670] Step 5:

[0671] The server collects data related to the specified market from the internet, including open data, industry reports, news articles, academic papers, etc.

[0672] Step 6:

[0673] The server converts the acquired data into a unified format, for example, organizing data in different formats such as text, PDF, and CSV into JSON format.

[0674] Step 7:

[0675] The server applies natural language processing (NLP) technology to the organized data to extract important keywords and topics, such as "technology trends," "regulatory changes," and "market growth rates."

[0676] Step 8:

[0677] The server then performs a PEST analysis based on the extracted data, including analysis of political, economic, social, and technological factors, such as assessing the impact of emerging technological trends and regulations on the AI ​​market.

[0678] Step 9:

[0679] The server also performs a 5 Forces analysis based on the extracted data, including the intensity of competition, the threat of new entrants, the threat of substitutes, the bargaining power of suppliers, and the bargaining power of buyers. For example, it analyzes major competitors in the AI ​​market and evaluates the threat of new entrants.

[0680] Step 10:

[0681] The server generates a market understanding report based on the results of the PEST and 5 Forces analyses. The report contains specific information and assessments that allow users to gain a deeper understanding of the market. Furthermore, the report content is customized based on the analysis results of the emotion engine. For example, if the user is excited, a report that emphasizes positive aspects will be generated.

[0682] Step 11:

[0683] The server then sends the generated report to the user's device, where it is available in PDF or web page format.

[0684] Step 12:

[0685] The terminal displays the received report to the user, who can then view the report generated by the terminal to check the detailed market analysis. The report also reflects the user's sentiment.

[0686] Example 2

[0687] 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."

[0688] Traditional market research systems have limited user experience because they are unable to customize reports to fit the user's needs and emotional state. Furthermore, data collection and analysis are manual, making the research process inefficient and time-consuming. To solve this issue, a system is needed that automates the market research process by providing customized reports that take user emotions into account.

[0689] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for sending a user request to an emotion engine and analyzing the user's emotions, means for collecting data on the specified market from the Internet, and means for organizing the collected data into a unified format. This makes it possible to provide a market understanding report customized based on the user's emotional state, thereby making the market research process more efficient and faster.

[0690] "User Terminal" means a device operated by a User and used to enter market research requests and receive generated reports.

[0691] "Market Research Request" means an instruction or request entered by a User to request the collection and analysis of information about a particular market.

[0692] An "emotion engine" refers to an algorithm or system that analyzes a user's input text and assesses the user's emotional state.

[0693] The "Internet" is an information and communications network that interconnects computers and networks around the world and is a medium for obtaining data from public sources.

[0694] "Data" refers to information collected from the internet, including open market data, industry reports, news articles, academic papers, etc.

[0695] "Format" refers to the format or structure in which data is stored, and indicates the standards for unifying data of different formats.

[0696] "Natural language processing technology" is a technology that enables computers to understand, interpret, and generate human language, and is used to extract important keywords and topics.

[0697] "Keywords" refer to important words or phrases related to the market research subject and are extracted during the data analysis process.

[0698] "Topics" refer to the major themes or topics extracted from the data.

[0699] "PEST analysis" refers to a method of market analysis that takes into account political, economic, social, and technological factors.

[0700] "Five Forces Analysis" refers to a market analysis method that evaluates the intensity of competition, the threat of new entrants, the threat of substitutes, the bargaining power of suppliers, and the bargaining power of buyers.

[0701] A "Market Understanding Report" is a report that details the current state and future trends of a market based on collected and analyzed data.

[0702] "Customization" refers to adjusting the content and format of a report based on the user's emotional state and needs.

[0703] "Server" refers to a central processing unit or system that receives requests from user devices and performs data collection, analysis, and report generation.

[0704] The present invention relates to a system that efficiently supports market research, particularly by incorporating an emotion engine that recognizes user emotions. When a user inputs a market request, the system collects and analyzes related data from the Internet, generates a market understanding report based on PEST analysis and 5 Forces analysis, and provides it to the user. Furthermore, by using an emotion engine that recognizes user emotions, the content and format of the report can be customized based on the user's emotional state. This improves the user experience and streamlines the market research process.

[0705] This system consists of a server and a user terminal. The user terminal provides an interface for users to input market research requests. This interface includes text input fields and selection menus. For example, a user can input a request such as "I would like you to conduct a PEST analysis and 5 Forces analysis of the AI ​​market."

[0706] When a user inputs a market research request, the device sends the request to the server. The request includes keywords and instructions for analysis. The server then sends the received request to the emotion engine, which analyzes the user's emotions. The emotion engine analyzes the input text data and evaluates the user's emotional state (e.g., interest, tension, satisfaction, etc.).

[0707] The server then collects data related to the specified market from the internet, including open data, industry reports, news articles, academic papers, etc. Because the collected data often exists in different formats, the server converts this data into a unified format, specifically converting formats such as text, PDF, and CSV into JSON.

[0708] The collected data is analyzed using natural language processing (NLP) technology to extract important keywords and topics, such as "technology trends," "regulatory changes," and "market growth rates." Based on these keywords, the server performs PEST and 5 Forces analyses.

[0709] A PEST analysis involves analyzing the market from political, economic, social, and technological perspectives. For example, it evaluates the impact of the latest technological trends and regulations on the AI ​​market and categorizes them into their respective categories. Similarly, a 5 Forces analysis evaluates the intensity of competition, the threat of new entrants, the threat of substitutes, the bargaining power of suppliers, and the bargaining power of buyers. Specifically, it analyzes major competitors in the AI ​​market and evaluates the threat of new entrants.

[0710] The server generates a market understanding report based on these analysis results. The report contains specific information and evaluations that allow users to gain a deeper understanding of the market. The report content is also customized based on the analysis results of the emotion engine. For example, if the user is excited, a report that emphasizes the positive aspects will be generated.

[0711] Finally, the server will send the generated report to the user's device, which will be available in PDF format or web page format, allowing users to view detailed market analysis and get customized information based on their own sentiment.

[0712] Examples of prompts to input to a generative AI model include:

[0713] "I would like you to conduct a PEST analysis and 5 Forces analysis of the AI ​​market."

[0714] In this way, the system can efficiently support market research and improve user experience by providing customized reports according to user sentiment.

[0715] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0716] Step 1:

[0717] The user enters a market research request, specifying a specific market and type of analysis through a user interface displayed on the terminal. As input, the user provides a prompt such as "I would like you to conduct a PEST analysis and 5 Forces analysis of the AI ​​market." As output, the user's request is obtained from the terminal.

[0718] Step 2:

[0719] The terminal sends the market research request entered by the user to the server. The input includes the user's request data (e.g., "AI market," "PEST analysis," "5 Forces analysis"), and the output includes an HTTP POST request to the server that includes the request data.

[0720] Step 3:

[0721] The server sends the received request data to the emotion engine to analyze the user's emotions. Using the request data as input, the emotion engine analyzes the text data to evaluate the user's emotional state (e.g., interest, tension, satisfaction, etc.). As output, JSON data containing the analysis results is sent back to the server.

[0722] Step 4:

[0723] The server collects data related to a specified market from the internet. Keywords such as "AI market" and "technology trends" are used as input. Specifically, data is collected through web scraping and API usage. The acquired data is then saved on the server as output.

[0724] Step 5:

[0725] The server organizes the collected data into a unified format. Data in various formats (text, PDF, CSV, etc.) is used as input. Specifically, it converts the data into JSON format using Python libraries (e.g., PyPDF2, pandas). Data in a unified format is obtained as output.

[0726] Step 6:

[0727] The server applies natural language processing (NLP) techniques to the organized data to extract important keywords and topics. Data in a standardized format is used as input. Specifically, analysis is performed using an NLP library (e.g., spaCy, NLTK). Key keywords such as "technology trends," "regulatory changes," and "market growth rates" are extracted as output.

[0728] Step 7:

[0729] The server performs a PEST analysis based on the extracted keywords. The extracted keywords are used as input. Specifically, these keywords are classified into political, economic, social, and technological categories, and an evaluation is performed for each category. The output is a detailed analysis of each category.

[0730] Step 8:

[0731] The server then performs a 5 Forces analysis based on the extracted keywords. The extracted keywords are used as input. Specifically, it evaluates the intensity of market competition, the threat of new entrants, the threat of substitutes, the bargaining power of suppliers, and the bargaining power of buyers. The output is the analysis results for each element of the 5 Forces.

[0732] Step 9:

[0733] The server generates a market understanding report based on the results of the PEST and 5 Forces analyses. The results of both analyses and the analysis of the user's emotional state are used as input. Specifically, the server compiles the report in HTML or PDF format and customizes the report content based on the results of the emotion engine. The server outputs the completed market understanding report.

[0734] Step 10:

[0735] The server sends the generated market understanding report to the user's device. The completed report data is used as input. Specifically, the server sends the report via an HTTP response so that the user can view it on their device. The output is a report that the user can view.

[0736] (Application example 2)

[0737] 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."

[0738] Conventional market research systems often provide uniform reports without considering the user's emotional state. This resulted in a lack of information tailored to the user's needs and emotions, resulting in a lack of improvement in the user experience. Furthermore, it was difficult to efficiently utilize the results of market research, preventing the improvement of user satisfaction.

[0739] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0740] In this invention, the server includes means for inputting a market research request from a user terminal, means for collecting data on a specified market from the Internet, means for organizing the collected data into a unified format, means for extracting important keywords and topics using natural language processing technology, means for performing a PEST analysis based on the extracted data, means for performing a 5 Forces analysis based on the extracted data, means for generating a market understanding report based on the results of the PEST analysis and the 5 Forces analysis, means for recognizing the emotional state of the user, means for customizing the content and format of the report based on the emotional state of the user, and means for sending the report to the user terminal. This makes it possible to generate a market understanding report customized in line with the user's emotions, improving the user experience.

[0741] "User Terminal" means the device through which a User enters market research requests and receives generated reports.

[0742] A "market research request" is information entered by a user to specify the market they wish to research and the type of analysis they wish to perform.

[0743] The "means for collecting data relating to a designated market from the Internet" is a function for automatically obtaining data relating to a designated market from the Internet.

[0744] "Means for organizing collected data into a unified format" refers to a function for converting and organizing acquired data into a consistent format.

[0745] "Natural language processing technology" is a technology for analyzing human language and extracting specific information.

[0746] "Means of extracting important keywords and topics" is a function that finds key words and themes needed for analysis from market data.

[0747] "PEST analysis" is a method of analyzing the market environment from four perspectives: politics, economics, society, and technology.

[0748] The "5 Forces Analysis" is a method for assessing the intensity of competition in a market, the threat of new entrants, the threat of substitutes, the bargaining power of suppliers, and the bargaining power of buyers.

[0749] A "Market Understanding Report" is a report that shows the current state and forecast of the market, generated based on PEST analysis and 5 Forces analysis.

[0750] "Means for recognizing the user's emotional state" refers to a function that analyzes the user's emotional state from their input and behavior.

[0751] "Means for customizing the content and format of a report based on the user's emotional state" is a function that adjusts the content and presentation of a report according to the user's emotions.

[0752] The "means for sending a report to a user terminal" is a function for sending the generated market understanding report to a user device.

[0753] This invention is a market research system that is composed of a user terminal, a server, and an emotion engine. A specific embodiment of this system is described below.

[0754] System configuration

[0755] 1. User Device:

[0756] Market research request input method: An input device (e.g., a smartphone or PC interface) through which a user requests market research.

[0757] Report receiving means: Has the function of receiving and displaying market understanding reports sent from the server.

[0758] 2. Server:

[0759] Data collection method: A function that automatically collects data about a specified market from the Internet. For example, using an API to obtain relevant data.

[0760] Data reduction: A function to convert and reduce collected data into a unified format. Convert data in different formats (text, PDF, CSV, etc.) into JSON format.

[0761] Natural language processing technology: Technology that uses software libraries such as TextBlob to extract important keywords and topics from collected data.

[0762] PEST analysis and 5 Forces analysis: A function that evaluates the market to deepen understanding based on the analysis results. For example, it evaluates growth opportunities and the intensity of competition in the AI ​​market.

[0763] Report generation tool: A function that generates a market understanding report that integrates the results of PEST analysis and 5 Forces analysis based on the analysis results.

[0764] Emotion recognition: Analyzes the user's input and recognizes their emotional state. Uses an emotion analysis engine such as TextBlob.

[0765] Report customization: Ability to tailor and customize report content and format based on perceived sentiment.

[0766] Report sending method: A function for sending generated reports to the user's terminal.

[0767] Specific processing flow

[0768] When a user inputs a market research request into their device, the request is first analyzed using emotion recognition means to identify the user's emotional state (e.g., positive, negative, neutral). The server then collects relevant data from the Internet and organizes it into a unified format. The organized data is then analyzed using natural language processing techniques to extract important keywords and topics.

[0769] The extracted data is then used for PEST and 5 Forces analysis, and the analysis results are compiled into a market understanding report, which is customized based on the user's emotional state. Finally, the customized report is sent to the user's device for viewing.

[0770] Specific examples of hardware or software to be used

[0771] Sentiment Analysis Engine: TextBlob or similar natural language processing library

[0772] Data collection: Public APIs and web crawlers

[0773] Data format conversion: JSON library

[0774] Analysis technology: Natural Language Processing (e.g., NLTK)

[0775] Specific examples

[0776] An example of a prompt is:

[0777] "Please conduct a PEST analysis and 5 Forces analysis of the AI ​​market."

[0778] "Provide the latest trends and competitive analysis in the automotive industry"

[0779] With this invention, users receive personalized, emotionally relevant market understanding reports, enabling them to make more informed decisions.

[0780] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0781] Step 1:

[0782] Enter a market research request from the user's device.

[0783] The user uses a smartphone or PC interface to input information specifying a particular market and type of analysis, which then inputs the user's request into the terminal.

[0784] Step 2:

[0785] The input request is sent to the server.

[0786] The user terminal sends the input request to the server, which includes instructions on the market to be researched and the type of analysis.

[0787] Step 3:

[0788] An emotion recognizer analyzes the request and recognizes the user's emotional state.

[0789] The server uses an emotion engine to analyze the input request text and identify the user's emotional state (positive, negative, neutral, etc.), resulting in the emotion analysis result.

[0790] Step 4:

[0791] Collect data about a specified market from the internet.

[0792] The server retrieves data about the specified market from the internet using APIs and web crawlers, and stores the retrieved data as raw data.

[0793] Step 5:

[0794] Organize the collected data into a unified format.

[0795] The server converts and organizes data from different formats (text, PDF, CSV, etc.) into a unified format (such as JSON), thereby maintaining data consistency.

[0796] Step 6:

[0797] Natural language processing technology is used to extract important keywords and topics.

[0798] The server uses natural language processing libraries such as TextBlob to extract important keywords and topics from the data, providing key insights and trends.

[0799] Step 7:

[0800] A PEST analysis is performed based on the extracted data.

[0801] The server then analyzes the Politics, Economics, Society, and Technology elements based on the extracted keywords and topics, generating the PEST analysis results.

[0802] Step 8:

[0803] A 5 Forces analysis will be performed based on the extracted data.

[0804] The server applies the 5 Forces analysis to evaluate the intensity of competition, the threat of new entrants, the threat of substitutes, the bargaining power of suppliers, and the bargaining power of buyers, thereby generating the 5 Forces analysis results.

[0805] Step 9:

[0806] Generate market understanding reports based on the results of PEST analysis and 5 Forces analysis.

[0807] The server integrates the results of PEST and 5 Forces analysis to create a comprehensive market understanding report, the content and format of which are customized based on the user's emotional state as previously analyzed.

[0808] Step 10:

[0809] Send the generated report to the user's device.

[0810] The server generates a customized market understanding report in PDF format, web page format, etc., and sends it to the user's device, where the user can view the report.

[0811] Prompt Sentence Examples

[0812] "Please conduct a PEST analysis and 5 Forces analysis of the AI ​​market."

[0813] "Provide the latest trends and competitive analysis in the automotive industry"

[0814] In this way, users receive emotionally relevant and customized market understanding reports, leading to more accurate and useful information.

[0815] 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.

[0816] 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.

[0817] 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.

[0818] [Third embodiment]

[0819] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0820] 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.

[0821] 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).

[0822] 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.

[0823] 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.

[0824] 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).

[0825] 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. 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.

[0826] 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.

[0827] 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.

[0828] 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.

[0829] 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.

[0830] 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."

[0831] The present invention relates to a system that efficiently supports market research. When a user inputs a market request, the system collects and analyzes related data from the Internet, generates a market understanding report based on PEST analysis and 5 Forces analysis, and provides it to the user.

[0832] System Program

[0833] 1. User Interface

[0834] How it works: The terminal provides an interface where users can enter market research requests, allowing them to specify specific markets and types of analysis.

[0835] Example: A user enters a request to "conduct a PEST analysis and 5 Forces analysis of the AI ​​market."

[0836] 2. Processing the Request

[0837] Operation: The terminal sends a request entered by the user to the server, which includes keywords and instructions for analysis.

[0838] Example: A user request is sent to the server, and the keywords "AI market", "PEST analysis", and "5 Forces analysis" arrive at the server.

[0839] 3. Data Collection

[0840] How it works: The server collects data related to a specified market from the internet, including open data, industry reports, news articles, academic papers, etc.

[0841] Example: A server searches and collects the latest news articles and technical reports related to the AI ​​market.

[0842] 4. Data format organization

[0843] How it works: The server organizes the collected data into a consistent format (e.g., JSON) so that the data is stored in a unified form before analysis.

[0844] Example: Data in various formats such as text, PDF, CSV, etc. is converted to JSON format.

[0845] 5. Data analysis and keyword extraction

[0846] How it works: The server uses natural language processing techniques to extract important keywords and topics from the organized data.

[0847] Example: Keywords such as "technology trends," "regulatory changes," and "market growth rate" are extracted.

[0848] 6. Conduct a PEST analysis

[0849] How it works: The server performs a PEST analysis based on the extracted data, which analyzes the market from political, economic, social, and technological perspectives.

[0850] Example: Sarver assesses the latest technological trends and regulatory impacts in the AI ​​market and categorizes them into their respective categories.

[0851] 7. Conducting a Five Forces Analysis

[0852] How it works: The server performs a 5 Forces analysis on the same extracted data, assessing the intensity of competition, the threat of new entrants, the threat of substitutes, the bargaining power of suppliers, and the bargaining power of buyers.

[0853] Example: The server analyzes key competitors in the AI ​​market and assesses the threat of new entrants.

[0854] 8. Generate Reports

[0855] How it works: The server generates a market understanding report based on the results of the PEST and 5 Forces analyses. The report contains specific information and assessments that allow users to gain a deeper understanding of the market.

[0856] Example: The server generates a comprehensive report summarizing "AI market growth opportunities and challenges," "analysis of key players," and "impact of technology trends."

[0857] 9. Report Distribution

[0858] How it works: The server generates a report and sends it to the user's device. The report is provided in PDF format or as a web page.

[0859] Example: Users can view reports generated on their devices and get detailed market analysis.

[0860] In this way, the present system efficiently supports market research and provides users with the ability to perform advanced market analysis even without specialized knowledge.

[0861] The processing flow will be explained below.

[0862] Step 1: The user uses their device to enter a research request for a specific market, for example, "I would like a PEST analysis and 5 Forces analysis of the AI ​​market."

[0863] Step 2: The terminal sends the request entered by the user to the server, which includes the market to be analyzed and the type of analysis required.

[0864] Step 3: Based on the received request, the server collects data related to the specified market, searching and retrieving open data, industry reports, news articles, academic papers, etc. from the Internet.

[0865] Step 4: The server converts the acquired data into a unified format, for example, organizing data in different formats such as text, PDF, CSV, etc. into JSON format.

[0866] Step 5: The server applies natural language processing (NLP) techniques to the organized data to extract important keywords and topics, such as technology trends, regulatory changes, and market growth rates.

[0867] Step 6: The server performs a PEST analysis based on the extracted data, including analysis of political, economic, social, and technological factors, such as assessing the impact of emerging technological trends and regulations on the AI ​​market.

[0868] Step 7: The server performs a 5 Forces analysis based on the extracted data, including the intensity of competition, the threat of new entrants, the threat of substitutes, the bargaining power of suppliers, and the bargaining power of buyers. For example, it analyzes major competitors in the AI ​​market and evaluates the threat of new entrants.

[0869] Step 8: The server generates a market understanding report based on the results of the PEST analysis and 5 Forces analysis. The report contains specific information and assessments that allow users to gain a deeper understanding of the market. For example, the report includes "AI market growth opportunities and challenges," "analysis of key players," and "impact of technological trends."

[0870] Step 9: The server sends the generated report to the user's device, which can be provided in PDF or web page format.

[0871] Step 10: The terminal displays the received report to the user. The user can view the report generated on the terminal and check the details of the market analysis.

[0872] Example 1

[0873] 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."

[0874] The market research process requires the collection, organization, and analysis of a wide variety of data, which requires a great deal of time and specialized knowledge. When conducting PEST analysis or 5 Forces analysis, the challenge is to quickly and accurately extract relevant information from a wide range of data sources. Many existing market research tools struggle to efficiently complete this process, forcing users to use multiple tools in combination.

[0875] 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.

[0876] In this invention, the server includes means for inputting a market research request from a user terminal, means for collecting data on a specified market from the Internet, means for organizing the collected data into a unified format, means for extracting important keywords and topics using natural language processing technology, means for analyzing the market from political, economic, social, and technological perspectives based on the extracted data, means for analyzing the market structure and competitive environment based on the extracted data, means for generating a market understanding report based on the analysis results, and means for transmitting the report to the user terminal. This enables users to quickly and efficiently perform advanced market analysis even without specialized knowledge.

[0877] "User Terminal" means the electronic device used by a User to access the System and enter market research requests.

[0878] A "Market Research Request" is a request entered into the System by a User specifying a particular market or type of analysis.

[0879] The "Internet" is a global network used to collect information.

[0880] "Data" refers to information about the market, collected from news articles, industry reports, academic papers, etc.

[0881] "Format" refers to the format or structure that unifies data and provides a basis for consistent analysis.

[0882] "Natural language processing technology" is a technology that allows computers to understand and analyze human language, and is used to extract keywords and topics.

[0883] "Keywords" refer to important words or phrases that are the subject of market research.

[0884] "Topics" refer to major themes or topics related to the subject of market research.

[0885] "PEST analysis" is an analytical method that evaluates a market from political, economic, social, and technological perspectives.

[0886] "Five Forces Analysis" is an analytical method for evaluating market structure and the competitive environment, assessing the intensity of competition, the threat of new entrants, the threat of substitutes, the bargaining power of suppliers, and the bargaining power of buyers.

[0887] A "Market Understanding Report" is a document created based on the results of PEST analysis and 5 Forces analysis, which allows users to gain a deeper understanding of the market.

[0888] A "server" is a computer system that performs processes such as data collection, organization, analysis, and report generation.

[0889] "Send" refers to the act of transferring the generated report to a user terminal.

[0890] This invention relates to a system that efficiently supports market research. In this system, when a user inputs a market request through a terminal, a server collects and analyzes related data from the Internet, generates a market understanding report based on PEST analysis and 5 Forces analysis, and provides it to the user.

[0891] The system is configured as follows: The user terminal has a user interface for inputting requests. The user uses this interface to specify a specific market and type of analysis. For example, a request can be made to "conduct a PEST analysis and 5 Forces analysis of the AI ​​market."

[0892] The device sends a request from the user to the server. The request includes keywords and instructions necessary for analysis. The server then collects data related to the specified market from the Internet. This collection uses a wide range of data sources, including open data, industry reports, news articles, and academic papers. Specifically, it uses Python's "BeautifulSoup" and "Google News API" to collect information from the Internet.

[0893] The collected data is organized on the server in a consistent format (e.g., JSON format). This streamlines preprocessing for analysis and stores the data in a unified format. Python libraries such as "pandas" and "PyPDF2" are used to organize the data.

[0894] The server uses natural language processing technology (using NLTK and SpaCy) to extract important keywords and topics from the organized data, such as "technology trends," "regulatory changes," and "market growth rates."

[0895] The server then performs a PEST analysis based on the extracted data. The PEST analysis evaluates the market from political, economic, social, and technological perspectives. Specifically, it evaluates the impact of the latest technological trends and regulations on the AI ​​market and classifies them into categories.

[0896] Similarly, the server performs a 5 Forces analysis, which evaluates the intensity of competition, threat of new entrants, threat of substitutes, bargaining power of suppliers, and bargaining power of buyers, including a detailed analysis of key competitors and a detailed assessment of the threat of new entrants.

[0897] Finally, the server generates a market understanding report based on the results of the PEST and 5 Forces analyses. This report contains specific information and assessments that allow users to gain a deeper understanding of the market. The report can also include graphical elements using Python's Jupyter Notebook and Matplotlib.

[0898] The generated report is sent from the server to the user's device, and is available in PDF or web page format, which the user can access via email or a download link.

[0899] Here is an example prompt:

[0900] "Please conduct a PEST analysis and 5 Forces analysis of the AI ​​market."

[0901] This system enables users to perform sophisticated market analysis quickly and efficiently, even without specialized knowledge.

[0902] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0903] Step 1:

[0904] User Interface Display

[0905] What it does: The terminal displays an interface that allows the user to enter a market research request.

[0906] Input: A web page a user visits or a mobile app launch.

[0907] Output: A display of an input interface that includes text boxes and drop-down menus.

[0908] What it does: When a user launches the app, the home screen displays the message "Enter your market research request." The request input field becomes active.

[0909] Step 2:

[0910] Submitting a Request

[0911] Operation: The terminal sends the input request to the server.

[0912] Input: The request the user types in the text field.

[0913] Output: The request data in JSON format is sent to the server.

[0914] Specific operation: When the user presses the "Submit" button, a request to "perform a PEST analysis and 5 Forces analysis of the AI ​​market" is sent to the server in JSON format. For example, {"request":"AI market", "analysis":["PEST", "5 Forces"]}.

[0915] Step 3:

[0916] Data collection

[0917] Operation: The server collects data related to a specified market from the Internet.

[0918] Input: Request data in JSON format.

[0919] Output: Raw market data collected (news articles, reports, papers, etc.).

[0920] What it does: The server uses the Google News API and PubMed API to search for the latest articles and academic papers on the AI ​​market, retrieves the results, and uses Python's "BeautifulSoup" to perform web scraping and collect relevant data.

[0921] Step 4:

[0922] Data formatting

[0923] How it works: The server organizes the collected data into a unified format (e.g., JSON format).

[0924] Input: Data in various formats (HTML, PDF, CSV, etc.).

[0925] Output: Data in consistent JSON format.

[0926] What it does: Uses Python's "pandas" and "PyPDF2" to convert collected data into a consistent format, for example extracting technical reports in PDF format into text and formatting them into JSON fields.

[0927] Step 5:

[0928] Keyword extraction

[0929] How it works: The server uses natural language processing techniques to extract important keywords and topics from the organized data.

[0930] Input: Organized data in JSON format.

[0931] Output: A dataset containing important keywords and topics.

[0932] Specific operation: The server performs text analysis using NLTK and SpaCy to extract keywords such as "technology trends," "regulatory changes," and "market growth rate."

[0933] Step 6:

[0934] Performing a PEST Analysis

[0935] Operation: The server performs a PEST analysis based on the extracted data.

[0936] Input: A dataset containing keywords or topics.

[0937] Output: Analysis results evaluated from political, economic, social and technological perspectives.

[0938] What it does: The server evaluates political regulations, economic trends, social influences, and technological advancements in the AI ​​market and categorizes and describes them.

[0939] Step 7:

[0940] 5. Performing Forces Analysis

[0941] How it works: The server performs a 5 Forces analysis on the extracted data.

[0942] Input: A dataset containing keywords or topics.

[0943] Output: Analysis assessing the intensity of competition, threat of new entrants, threat of substitutes, bargaining power of suppliers, and bargaining power of buyers.

[0944] What it does: The server analyzes data on key competitors to assess competitiveness and threats of new entrants. For example, it performs a detailed assessment of the impact of key competitor X on the market.

[0945] Step 8:

[0946] Generate reports

[0947] How it works: The server generates a market understanding report based on the results of the PEST analysis and the 5 Forces analysis.

[0948] Input: Results of PEST analysis and 5 Forces analysis.

[0949] Output: Market understanding report.

[0950] What it does: Uses Python's Jupyter Notebook and Matplotlib to generate text and graphical reports, including detailed PDF reports with PEST and 5 Forces charts.

[0951] Step 9:

[0952] Report distribution

[0953] How it works: The server generates a report and sends it to the user's device.

[0954] Input: Market Understanding Report.

[0955] Output: Report delivered to user terminal.

[0956] What happens: The report will be attached to your email in PDF format, or you will be provided with a download link. For example, open the email on your device and you will be able to download the "AI Market Analysis Report" as a PDF.

[0957] (Application example 1)

[0958] 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."

[0959] Market research is important in the advertising industry for formulating effective marketing strategies. However, traditional market research methods are time-consuming, labor-intensive, and require significant resource expenditures. Furthermore, it is difficult to maintain consistency in data collection, organization, and analysis, which can lead to problems with the accuracy and reliability of the resulting reports. Given this background, there is a growing need for systems that support market research efficiently and effectively.

[0960] 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.

[0961] In this invention, the server includes means for inputting a market research request from a user terminal, means for collecting data on a specified market from the Internet, means for organizing the collected data into a unified format, means for extracting important keywords and topics using natural language processing technology, means for performing a PEST analysis based on the extracted data, means for performing a 5 Forces analysis based on the extracted data, means for generating a market understanding report based on the results of the PEST analysis and the 5 Forces analysis, means for sending the generated report to the user terminal in PDF or web page format, means for supporting the generation of a market research report in the advertising industry using the analysis results, and means for guiding user input using prompt sentences. This allows for efficient and effective support of market research in the advertising industry, enabling users to perform advanced market analysis even without specialized knowledge.

[0962] "Market Research Request" means instructions entered by a User requesting the collection or analysis of information about a particular market or type of analysis.

[0963] A "user terminal" is a device, such as a smartphone or computer, that a user uses to connect to the Internet and input and receive information.

[0964] "Data collection means" refers to the function of the server to search and acquire data related to a specified market from the Internet.

[0965] "Means of organizing into a unified format" refers to the function of converting collected data into a unified format, such as JSON format, and saving it.

[0966] "Natural language processing technology" refers to the technology that uses computers to analyze, understand, and generate human language.

[0967] "Means for extracting keywords and topics" refers to the function of extracting important words and topics from text data using natural language processing technology.

[0968] "PEST analysis" is a method of analyzing a market from four perspectives: political, economic, social, and technological.

[0969] "Five Forces Analysis" is an analytical method for evaluating a market based on five factors: intensity of competition (competition among existing companies), threat of new entrants, threat of substitutes, bargaining power of suppliers, and bargaining power of buyers.

[0970] A "Market Understanding Report" is a detailed and comprehensive report on a specific market that compiles the results of a PEST analysis and a 5 Forces analysis.

[0971] "Means for sending to user terminal in PDF or web page format" refers to the functionality for providing the generated report to the user as a PDF file or web page.

[0972] "Means for supporting the generation of market research reports in the advertising industry" refers to a function for creating detailed market analysis reports for the purpose of formulating effective marketing strategies in the advertising industry.

[0973] "Means for guiding user input using prompts" refers to a function that provides specific instructions and examples to guide users in properly entering their market research requests.

[0974] This invention relates to a system in which a user inputs a research request for a specific market, a server collects and analyzes the necessary data from the Internet, and generates and provides a market understanding report based on PEST analysis and 5 Forces analysis. This system is specialized for the advertising industry, and it efficiently conducts market research and supports the formulation of marketing strategies.

[0975] The system for implementing this invention includes the following main functions: a user terminal, a server, natural language processing technology (NLP), and data collection and analysis means.

[0976] Hardware and Software

[0977] Hardware: User devices such as smartphones and computers where users input information, and servers that collect and analyze data.

[0978] Software: Server-side processing is done using Python and Flask, data scraping is done using Beautiful Soup and Selenium, and NLP is done using SpaCy or NLTK.

[0979] Details of data processing and calculation

[0980] 1. User Interface:

[0981] The user terminal provides a form for entering a research request. The form is built using HTML / CSS / JavaScript. The user enters details about a specific market and analysis format, and the information is received by the Flask server.

[0982] Example: A user fills out a form and asks for a PEST analysis and 5 Forces analysis of the smartphone advertising market.

[0983] 2. Processing the request:

[0984] The information entered into the form is sent to the server via the Flask server, which starts collecting data related to the specified market based on the request.

[0985] Example: A user request for "Smartphone Advertising Market", "PEST Analysis", and "5 Forces Analysis" is sent to the server.

[0986] 3. Data Collection:

[0987] The server collects the necessary data from the Internet using a scraping tool such as Beautiful Soup or Selenium, and the collected data may be provided in various formats (text, PDF, HTML, etc.).

[0988] Example: A server searches for the latest industry reports and news articles to gather data about the smartphone advertising market.

[0989] 4. Data formatting:

[0990] The server converts the collected data into a unified format (JSON), which makes subsequent analysis easier.

[0991] Example: Data in various formats (e.g. text, PDF, HTML) is organized into JSON format.

[0992] 5. Data analysis and keyword extraction:

[0993] Using natural language processing techniques (SpaCy or NLTK), the server extracts important keywords and topics from the data.

[0994] Example: The server extracts keywords such as "market size," "growth rate," "major competitors," and "consumer trends."

[0995] 6. PEST Analysis and Five Forces Analysis:

[0996] Based on the extracted data, the server performs a PEST analysis and a 5 Forces analysis, evaluating the market from each perspective (political, economic, social, technological and competitive, new entrants, threat of substitutes, and bargaining power of suppliers and buyers).

[0997] Example: The server analyzes the current state of the market and future trends from various perspectives.

[0998] 7. Report Generation and Delivery:

[0999] Based on the analysis results, the server generates a detailed market understanding report and provides it to the user in PDF or web page format, including a prompt function to guide the user to input appropriate requests.

[1000] Example: A report will be generated that includes "Current Status and Future Outlook of the Smartphone Advertising Market," "Analysis of Major Players," and "Technical Challenges and Trends."

[1001] Example prompt: "Please enter the market you want to analyze and select the type of analysis (PEST, 5 Forces). E.g., 'Smartphone advertising market, PEST and 5 Forces analysis.'"

[1002] In this way, the system can efficiently and effectively support market research in the advertising industry, enabling users to perform advanced market analysis without having specialized knowledge.

[1003] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1004] Step 1:

[1005] A user inputs a market research request from their device. A specific request is information about a specific market and analysis format. For example, a user might input, "I would like a PEST analysis and 5 Forces analysis of the smartphone advertising market." This input is received as a form in a user interface built with HTML / CSS / JavaScript.

[1006] Step 2:

[1007] Once the user has completed the input, the user device sends the input request to the Flask server. The specific operation of this step is to encode the form contents into JSON format and send it as an HTTP POST request to the server. The server receives this request and extracts keywords and instructions to start parsing it.

[1008] Step 3:

[1009] Based on the received request, the server collects data about the specified market from the Internet. For example, the server uses Beautiful Soup or Selenium to scrape the web for relevant open data, industry reports, news articles, etc. The input for this step is the request keywords, and the output is the collected raw data.

[1010] Step 4:

[1011] The server organizes the collected data into a unified format. In this step, data from various formats (text, PDF, HTML, etc.) is converted into a unified JSON format. Specifically, the server uses a PDF parsing library or parses text and HTML and combines them into a consistent format. The input is raw data, and the output is organized JSON data.

[1012] Step 5:

[1013] The server uses natural language processing (NLP) techniques to extract important keywords and topics from the unified data. Specifically, it uses SpaCy or NLTK to extract specific words and phrases within the data. The input is organized JSON data, and the output is a list of extracted keywords.

[1014] Step 6:

[1015] The server performs a PEST analysis based on the extracted keywords. Specifically, it categorizes the information in the data into political, economic, social, and technological categories and evaluates each category. The input is a list of keywords, and the output is the results of the PEST analysis.

[1016] Step 7:

[1017] The server then performs a 5 Forces analysis based on the extracted keywords. In this step, it evaluates the intensity of competition, the threat of new entrants, the threat of substitutes, and the bargaining power of suppliers and buyers. The input is a list of keywords, and the output is the results of the 5 Forces analysis.

[1018] Step 8:

[1019] The server generates a market understanding report based on the results of the PEST analysis and the 5 Forces analysis. Its specific operation is to integrate the results of each analysis and create a report in a format that is easy for users to understand. The input is the results of both analyses, and the output is the market understanding report.

[1020] Step 9:

[1021] The generated report is sent to the user's terminal in PDF or web page format. The server generates the PDF using a document generation tool (such as FPDF) and converts it to HTML when providing it in web format. The input is the market understanding report, and the output is a PDF or web page format report to the user.

[1022] Step 10:

[1023] The server provides a means to guide user input using prompts. Specifically, when a user enters a market research request, the server displays appropriate prompts (e.g., "Please enter the market you want to analyze and select the type of analysis (PEST, 5 Forces). Eg, 'Smartphone advertising market, PEST and 5 Forces analysis.'") to improve the accuracy of user input. The input is the market and analysis type specified by the user, and the output is the optimal request input situation.

[1024] 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.

[1025] The present invention relates to a system that efficiently supports market research, and is combined with an emotion engine that recognizes user emotions. When a user inputs a market request, the system collects and analyzes related data from the Internet, generates a market understanding report based on PEST analysis and 5 Forces analysis, and provides it to the user. Furthermore, by using an emotion engine that recognizes user emotions, the content and format of the report can be customized based on the user's emotional state.

[1026] System Program

[1027] 1. User Interface

[1028] How it works: The terminal provides an interface where users can enter market research requests, allowing them to specify specific markets and types of analysis.

[1029] Example: A user enters a request to "conduct a PEST analysis and 5 Forces analysis of the AI ​​market."

[1030] 2. Processing the Request

[1031] Operation: The terminal sends a request entered by the user to the server, which includes keywords and instructions for analysis.

[1032] Example: A user request is sent to the server, and the keywords "AI market", "PEST analysis", and "5 Forces analysis" arrive at the server.

[1033] 3. Emotion Recognition Implementation

[1034] How it works: The server sends the user's input request to the emotion engine, which analyzes the user's emotion. The emotion engine analyzes the input text data and evaluates the user's emotional state (e.g., interest, tension, satisfaction, etc.).

[1035] Example: A user's input text is analyzed by an emotion engine to identify emotional states such as "excited," "anxious," or "indifferent."

[1036] 4. Data Collection

[1037] How it works: The server collects data related to a specified market from the internet, including open data, industry reports, news articles, academic papers, etc.

[1038] Example: A server searches and collects the latest news articles and technical reports related to the AI ​​market.

[1039] 5. Data format organization

[1040] How it works: The server converts the data it receives into a unified format, for example, organizing data in different formats (text, PDF, CSV, etc.) into JSON format.

[1041] Example: Data in various formats such as text, PDF, CSV, etc. is converted to JSON format.

[1042] 6. Data analysis and keyword extraction

[1043] How it works: The server applies natural language processing (NLP) techniques to the organized data to extract important keywords and topics.

[1044] Example: Keywords such as "technology trends," "regulatory changes," and "market growth rate" are extracted.

[1045] 7. Conduct a PEST analysis

[1046] How it works: The server performs a PEST analysis based on the extracted data, including analysis of Politics, Economics, Society, and Technology factors.

[1047] Example: Sarver assesses the latest technological trends and regulatory impacts in the AI ​​market and categorizes them into their respective categories.

[1048] 8. Conducting a Five Forces Analysis

[1049] How it works: The server performs a 5 Forces analysis based on the same extracted data, including the intensity of competition, the threat of new entrants, the threat of substitutes, the bargaining power of suppliers, and the bargaining power of buyers.

[1050] Example: The server analyzes key competitors in the AI ​​market and assesses the threat of new entrants.

[1051] 9. Generate Reports

[1052] How it works: The server generates a market understanding report based on the results of the PEST and 5 Forces analyses. The report contains specific information and assessments that allow users to gain a deeper understanding of the market. Furthermore, the report content is customized based on the analysis results of the sentiment engine.

[1053] Example: The server generates a comprehensive report summarizing "AI market growth opportunities and challenges," "analysis of key players," "impact of technology trends," etc. If the user is excited, the report will highlight the positive aspects.

[1054] 10. Report Distribution

[1055] How it works: The server generates a report and sends it to the user's device. The report is provided in PDF format or as a web page.

[1056] Example: Users can view reports generated on their devices, which provide detailed market analysis and reflect their sentiment.

[1057] In this way, the system can efficiently support market research and further improve user experience by providing customized reports according to user sentiment.

[1058] The processing flow will be explained below.

[1059] Step 1:

[1060] Users use their devices to enter research requests for specific markets, such as "I'd like a PEST and 5 Forces analysis of the AI ​​market."

[1061] Step 2:

[1062] The terminal sends the request entered by the user to the server, which includes the market to be analyzed and the type of analysis required.

[1063] Step 3:

[1064] Based on the received request, the server sends the user's input to the emotion engine, which analyzes the user's emotion. The emotion engine analyzes the input text data and evaluates the user's emotional state (e.g., interest level, tension level, satisfaction level, etc.).

[1065] Step 4:

[1066] The server receives the user's emotional data sent from the emotion engine, identifying their emotional state, such as "excited," "anxious," or "indifferent."

[1067] Step 5:

[1068] The server collects data related to the specified market from the internet, including open data, industry reports, news articles, academic papers, etc.

[1069] Step 6:

[1070] The server converts the acquired data into a unified format, for example, organizing data in different formats such as text, PDF, and CSV into JSON format.

[1071] Step 7:

[1072] The server applies natural language processing (NLP) technology to the organized data to extract important keywords and topics, such as "technology trends," "regulatory changes," and "market growth rates."

[1073] Step 8:

[1074] The server then performs a PEST analysis based on the extracted data, including analysis of political, economic, social, and technological factors, such as assessing the impact of emerging technological trends and regulations on the AI ​​market.

[1075] Step 9:

[1076] The server also performs a 5 Forces analysis based on the extracted data, including the intensity of competition, the threat of new entrants, the threat of substitutes, the bargaining power of suppliers, and the bargaining power of buyers. For example, it analyzes major competitors in the AI ​​market and evaluates the threat of new entrants.

[1077] Step 10:

[1078] The server generates a market understanding report based on the results of the PEST and 5 Forces analyses. The report contains specific information and assessments that allow users to gain a deeper understanding of the market. Furthermore, the report content is customized based on the analysis results of the emotion engine. For example, if the user is excited, a report that emphasizes positive aspects will be generated.

[1079] Step 11:

[1080] The server then sends the generated report to the user's device, where it is available in PDF or web page format.

[1081] Step 12:

[1082] The terminal displays the received report to the user, who can then view the report generated by the terminal to check the detailed market analysis. The report also reflects the user's sentiment.

[1083] Example 2

[1084] 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."

[1085] Traditional market research systems have limited user experience because they are unable to customize reports to fit the user's needs and emotional state. Furthermore, data collection and analysis are manual, making the research process inefficient and time-consuming. To solve this issue, a system is needed that automates the market research process by providing customized reports that take user emotions into account.

[1086] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for sending a user request to an emotion engine and analyzing the user's emotions, means for collecting data on the specified market from the Internet, and means for organizing the collected data into a unified format. This makes it possible to provide a market understanding report customized based on the user's emotional state, thereby making the market research process more efficient and faster.

[1087] "User Terminal" means a device operated by a User and used to enter market research requests and receive generated reports.

[1088] "Market Research Request" means an instruction or request entered by a User to request the collection and analysis of information about a particular market.

[1089] An "emotion engine" refers to an algorithm or system that analyzes a user's input text and assesses the user's emotional state.

[1090] The "Internet" is an information and communications network that interconnects computers and networks around the world and is a medium for obtaining data from public sources.

[1091] "Data" refers to information collected from the internet, including open market data, industry reports, news articles, academic papers, etc.

[1092] "Format" refers to the format or structure in which data is stored, and indicates the standards for unifying data of different formats.

[1093] "Natural language processing technology" is a technology that enables computers to understand, interpret, and generate human language, and is used to extract important keywords and topics.

[1094] "Keywords" refer to important words or phrases related to the market research subject and are extracted during the data analysis process.

[1095] "Topics" refer to the major themes or topics extracted from the data.

[1096] "PEST analysis" refers to a method of market analysis that takes into account political, economic, social, and technological factors.

[1097] "Five Forces Analysis" refers to a market analysis method that evaluates the intensity of competition, the threat of new entrants, the threat of substitutes, the bargaining power of suppliers, and the bargaining power of buyers.

[1098] A "Market Understanding Report" is a report that details the current state and future trends of a market based on collected and analyzed data.

[1099] "Customization" refers to adjusting the content and format of a report based on the user's emotional state and needs.

[1100] "Server" refers to a central processing unit or system that receives requests from user devices and performs data collection, analysis, and report generation.

[1101] The present invention relates to a system that efficiently supports market research, particularly by incorporating an emotion engine that recognizes user emotions. When a user inputs a market request, the system collects and analyzes related data from the Internet, generates a market understanding report based on PEST analysis and 5 Forces analysis, and provides it to the user. Furthermore, by using an emotion engine that recognizes user emotions, the content and format of the report can be customized based on the user's emotional state. This improves the user experience and streamlines the market research process.

[1102] This system consists of a server and a user terminal. The user terminal provides an interface for users to input market research requests. This interface includes text input fields and selection menus. For example, a user can input a request such as "I would like you to conduct a PEST analysis and 5 Forces analysis of the AI ​​market."

[1103] When a user inputs a market research request, the device sends the request to the server. The request includes keywords and instructions for analysis. The server then sends the received request to the emotion engine, which analyzes the user's emotions. The emotion engine analyzes the input text data and evaluates the user's emotional state (e.g., interest, tension, satisfaction, etc.).

[1104] The server then collects data related to the specified market from the internet, including open data, industry reports, news articles, academic papers, etc. Because the collected data often exists in different formats, the server converts this data into a unified format, specifically converting formats such as text, PDF, and CSV into JSON.

[1105] The collected data is analyzed using natural language processing (NLP) technology to extract important keywords and topics, such as "technology trends," "regulatory changes," and "market growth rates." Based on these keywords, the server performs PEST and 5 Forces analyses.

[1106] A PEST analysis involves analyzing the market from political, economic, social, and technological perspectives. For example, it evaluates the impact of the latest technological trends and regulations on the AI ​​market and categorizes them into their respective categories. Similarly, a 5 Forces analysis evaluates the intensity of competition, the threat of new entrants, the threat of substitutes, the bargaining power of suppliers, and the bargaining power of buyers. Specifically, it analyzes major competitors in the AI ​​market and evaluates the threat of new entrants.

[1107] The server generates a market understanding report based on these analysis results. The report contains specific information and evaluations that allow users to gain a deeper understanding of the market. The report content is also customized based on the analysis results of the emotion engine. For example, if the user is excited, a report that emphasizes the positive aspects will be generated.

[1108] Finally, the server will send the generated report to the user's device, which will be available in PDF format or web page format, allowing users to view detailed market analysis and get customized information based on their own sentiment.

[1109] Examples of prompts to input to a generative AI model include:

[1110] "I would like you to conduct a PEST analysis and 5 Forces analysis of the AI ​​market."

[1111] In this way, the system can efficiently support market research and improve user experience by providing customized reports according to user sentiment.

[1112] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1113] Step 1:

[1114] The user enters a market research request, specifying a specific market and type of analysis through a user interface displayed on the terminal. As input, the user provides a prompt such as "I would like you to conduct a PEST analysis and 5 Forces analysis of the AI ​​market." As output, the user's request is obtained from the terminal.

[1115] Step 2:

[1116] The terminal sends the market research request entered by the user to the server. The input includes the user's request data (e.g., "AI market," "PEST analysis," "5 Forces analysis"), and the output includes an HTTP POST request to the server that includes the request data.

[1117] Step 3:

[1118] The server sends the received request data to the emotion engine to analyze the user's emotions. Using the request data as input, the emotion engine analyzes the text data to evaluate the user's emotional state (e.g., interest, tension, satisfaction, etc.). As output, JSON data containing the analysis results is sent back to the server.

[1119] Step 4:

[1120] The server collects data related to a specified market from the internet. Keywords such as "AI market" and "technology trends" are used as input. Specifically, data is collected through web scraping and API usage. The acquired data is then saved on the server as output.

[1121] Step 5:

[1122] The server organizes the collected data into a unified format. Data in various formats (text, PDF, CSV, etc.) is used as input. Specifically, it converts the data into JSON format using Python libraries (e.g., PyPDF2, pandas). Data in a unified format is obtained as output.

[1123] Step 6:

[1124] The server applies natural language processing (NLP) techniques to the organized data to extract important keywords and topics. Data in a standardized format is used as input. Specifically, analysis is performed using an NLP library (e.g., spaCy, NLTK). Key keywords such as "technology trends," "regulatory changes," and "market growth rates" are extracted as output.

[1125] Step 7:

[1126] The server performs a PEST analysis based on the extracted keywords. The extracted keywords are used as input. Specifically, these keywords are classified into political, economic, social, and technological categories, and an evaluation is performed for each category. The output is a detailed analysis of each category.

[1127] Step 8:

[1128] The server then performs a 5 Forces analysis based on the extracted keywords. The extracted keywords are used as input. Specifically, it evaluates the intensity of market competition, the threat of new entrants, the threat of substitutes, the bargaining power of suppliers, and the bargaining power of buyers. The output is the analysis results for each element of the 5 Forces.

[1129] Step 9:

[1130] The server generates a market understanding report based on the results of the PEST and 5 Forces analyses. The results of both analyses and the analysis of the user's emotional state are used as input. Specifically, the server compiles the report in HTML or PDF format and customizes the report content based on the results of the emotion engine. The server outputs the completed market understanding report.

[1131] Step 10:

[1132] The server sends the generated market understanding report to the user's device. The completed report data is used as input. Specifically, the server sends the report via an HTTP response so that the user can view it on their device. The output is a report that the user can view.

[1133] (Application example 2)

[1134] 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."

[1135] Conventional market research systems often provide uniform reports without considering the user's emotional state. This resulted in a lack of information tailored to the user's needs and emotions, resulting in a lack of improvement in the user experience. Furthermore, it was difficult to efficiently utilize the results of market research, preventing the improvement of user satisfaction.

[1136] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1137] In this invention, the server includes means for inputting a market research request from a user terminal, means for collecting data on a specified market from the Internet, means for organizing the collected data into a unified format, means for extracting important keywords and topics using natural language processing technology, means for performing a PEST analysis based on the extracted data, means for performing a 5 Forces analysis based on the extracted data, means for generating a market understanding report based on the results of the PEST analysis and the 5 Forces analysis, means for recognizing the emotional state of the user, means for customizing the content and format of the report based on the emotional state of the user, and means for sending the report to the user terminal. This makes it possible to generate a market understanding report customized in line with the user's emotions, improving the user experience.

[1138] "User Terminal" means the device through which a User enters market research requests and receives generated reports.

[1139] A "market research request" is information entered by a user to specify the market they wish to research and the type of analysis they wish to perform.

[1140] The "means for collecting data relating to a designated market from the Internet" is a function for automatically obtaining data relating to a designated market from the Internet.

[1141] "Means for organizing collected data into a unified format" refers to a function for converting and organizing acquired data into a consistent format.

[1142] "Natural language processing technology" is a technology for analyzing human language and extracting specific information.

[1143] "Means of extracting important keywords and topics" is a function that finds key words and themes needed for analysis from market data.

[1144] "PEST analysis" is a method of analyzing the market environment from four perspectives: politics, economics, society, and technology.

[1145] The "5 Forces Analysis" is a method for assessing the intensity of competition in a market, the threat of new entrants, the threat of substitutes, the bargaining power of suppliers, and the bargaining power of buyers.

[1146] A "Market Understanding Report" is a report that shows the current state and forecast of the market, generated based on PEST analysis and 5 Forces analysis.

[1147] "Means for recognizing the user's emotional state" refers to a function that analyzes the user's emotional state from their input and behavior.

[1148] "Means for customizing the content and format of a report based on the user's emotional state" is a function that adjusts the content and presentation of a report according to the user's emotions.

[1149] The "means for sending a report to a user terminal" is a function for sending the generated market understanding report to a user device.

[1150] This invention is a market research system that is composed of a user terminal, a server, and an emotion engine. A specific embodiment of this system is described below.

[1151] System configuration

[1152] 1. User Device:

[1153] Market research request input method: An input device (e.g., a smartphone or PC interface) through which a user requests market research.

[1154] Report receiving means: Has the function of receiving and displaying market understanding reports sent from the server.

[1155] 2. Server:

[1156] Data collection method: A function that automatically collects data about a specified market from the Internet. For example, using an API to obtain relevant data.

[1157] Data reduction: A function to convert and reduce collected data into a unified format. Convert data in different formats (text, PDF, CSV, etc.) into JSON format.

[1158] Natural language processing technology: Technology that uses software libraries such as TextBlob to extract important keywords and topics from collected data.

[1159] PEST analysis and 5 Forces analysis: A function that evaluates the market to deepen understanding based on the analysis results. For example, it evaluates growth opportunities and the intensity of competition in the AI ​​market.

[1160] Report generation tool: A function that generates a market understanding report that integrates the results of PEST analysis and 5 Forces analysis based on the analysis results.

[1161] Emotion recognition: Analyzes the user's input and recognizes their emotional state. Uses an emotion analysis engine such as TextBlob.

[1162] Report customization: Ability to tailor and customize report content and format based on perceived sentiment.

[1163] Report sending method: A function for sending generated reports to the user's terminal.

[1164] Specific processing flow

[1165] When a user inputs a market research request into their device, the request is first analyzed using emotion recognition means to identify the user's emotional state (e.g., positive, negative, neutral). The server then collects relevant data from the Internet and organizes it into a unified format. The organized data is then analyzed using natural language processing techniques to extract important keywords and topics.

[1166] The extracted data is then used for PEST and 5 Forces analysis, and the analysis results are compiled into a market understanding report, which is customized based on the user's emotional state. Finally, the customized report is sent to the user's device for viewing.

[1167] Specific examples of hardware or software to be used

[1168] Sentiment Analysis Engine: TextBlob or similar natural language processing library

[1169] Data collection: Public APIs and web crawlers

[1170] Data format conversion: JSON library

[1171] Analysis technology: Natural Language Processing (e.g., NLTK)

[1172] Specific examples

[1173] An example of a prompt is:

[1174] "Please conduct a PEST analysis and 5 Forces analysis of the AI ​​market."

[1175] "Provide the latest trends and competitive analysis in the automotive industry"

[1176] With this invention, users receive personalized, emotionally relevant market understanding reports, enabling them to make more informed decisions.

[1177] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1178] Step 1:

[1179] Enter a market research request from the user's device.

[1180] The user uses a smartphone or PC interface to input information specifying a particular market and type of analysis, which then inputs the user's request into the terminal.

[1181] Step 2:

[1182] The input request is sent to the server.

[1183] The user terminal sends the input request to the server, which includes instructions on the market to be researched and the type of analysis.

[1184] Step 3:

[1185] An emotion recognizer analyzes the request and recognizes the user's emotional state.

[1186] The server uses an emotion engine to analyze the input request text and identify the user's emotional state (positive, negative, neutral, etc.), resulting in the emotion analysis result.

[1187] Step 4:

[1188] Collect data about a specified market from the internet.

[1189] The server retrieves data about the specified market from the internet using APIs and web crawlers, and stores the retrieved data as raw data.

[1190] Step 5:

[1191] Organize the collected data into a unified format.

[1192] The server converts and organizes data from different formats (text, PDF, CSV, etc.) into a unified format (such as JSON), thereby maintaining data consistency.

[1193] Step 6:

[1194] Natural language processing technology is used to extract important keywords and topics.

[1195] The server uses natural language processing libraries such as TextBlob to extract important keywords and topics from the data, providing key insights and trends.

[1196] Step 7:

[1197] A PEST analysis is performed based on the extracted data.

[1198] The server then analyzes the Politics, Economics, Society, and Technology elements based on the extracted keywords and topics, generating the PEST analysis results.

[1199] Step 8:

[1200] A 5 Forces analysis will be performed based on the extracted data.

[1201] The server applies the 5 Forces analysis to evaluate the intensity of competition, the threat of new entrants, the threat of substitutes, the bargaining power of suppliers, and the bargaining power of buyers, thereby generating the 5 Forces analysis results.

[1202] Step 9:

[1203] Generate market understanding reports based on the results of PEST analysis and 5 Forces analysis.

[1204] The server integrates the results of PEST and 5 Forces analysis to create a comprehensive market understanding report, the content and format of which are customized based on the user's emotional state as previously analyzed.

[1205] Step 10:

[1206] Send the generated report to the user's device.

[1207] The server generates a customized market understanding report in PDF format, web page format, etc., and sends it to the user's device, where the user can view the report.

[1208] Prompt Sentence Examples

[1209] "Please conduct a PEST analysis and 5 Forces analysis of the AI ​​market."

[1210] "Provide the latest trends and competitive analysis in the automotive industry"

[1211] In this way, users receive emotionally relevant and customized market understanding reports, leading to more accurate and useful information.

[1212] 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.

[1213] 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.

[1214] 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.

[1215] [Fourth embodiment]

[1216] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1217] 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.

[1218] 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).

[1219] 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.

[1220] 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.

[1221] 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).

[1222] 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. 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.

[1223] 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.

[1224] 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.

[1225] 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.

[1226] 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.

[1227] 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.

[1228] 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."

[1229] The present invention relates to a system that efficiently supports market research. When a user inputs a market request, the system collects and analyzes related data from the Internet, generates a market understanding report based on PEST analysis and 5 Forces analysis, and provides it to the user.

[1230] System Program

[1231] 1. User Interface

[1232] How it works: The terminal provides an interface where users can enter market research requests, allowing them to specify specific markets and types of analysis.

[1233] Example: A user enters a request to "conduct a PEST analysis and 5 Forces analysis of the AI ​​market."

[1234] 2. Processing the Request

[1235] Operation: The terminal sends a request entered by the user to the server, which includes keywords and instructions for analysis.

[1236] Example: A user request is sent to the server, and the keywords "AI market", "PEST analysis", and "5 Forces analysis" arrive at the server.

[1237] 3. Data Collection

[1238] How it works: The server collects data related to a specified market from the internet, including open data, industry reports, news articles, academic papers, etc.

[1239] Example: A server searches and collects the latest news articles and technical reports related to the AI ​​market.

[1240] 4. Data format organization

[1241] How it works: The server organizes the collected data into a consistent format (e.g., JSON) so that the data is stored in a unified form before analysis.

[1242] Example: Data in various formats such as text, PDF, CSV, etc. is converted to JSON format.

[1243] 5. Data analysis and keyword extraction

[1244] How it works: The server uses natural language processing techniques to extract important keywords and topics from the organized data.

[1245] Example: Keywords such as "technology trends," "regulatory changes," and "market growth rate" are extracted.

[1246] 6. Conduct a PEST analysis

[1247] How it works: The server performs a PEST analysis based on the extracted data, which analyzes the market from political, economic, social, and technological perspectives.

[1248] Example: Sarver assesses the latest technological trends and regulatory impacts in the AI ​​market and categorizes them into their respective categories.

[1249] 7. Conducting a Five Forces Analysis

[1250] How it works: The server performs a 5 Forces analysis on the same extracted data, assessing the intensity of competition, the threat of new entrants, the threat of substitutes, the bargaining power of suppliers, and the bargaining power of buyers.

[1251] Example: The server analyzes key competitors in the AI ​​market and assesses the threat of new entrants.

[1252] 8. Generate Reports

[1253] How it works: The server generates a market understanding report based on the results of the PEST and 5 Forces analyses. The report contains specific information and assessments that allow users to gain a deeper understanding of the market.

[1254] Example: The server generates a comprehensive report summarizing "AI market growth opportunities and challenges," "analysis of key players," and "impact of technology trends."

[1255] 9. Report Distribution

[1256] How it works: The server generates a report and sends it to the user's device. The report is provided in PDF format or as a web page.

[1257] Example: Users can view reports generated on their devices and get detailed market analysis.

[1258] In this way, the present system efficiently supports market research and provides users with the ability to perform advanced market analysis even without specialized knowledge.

[1259] The processing flow will be explained below.

[1260] Step 1: The user uses their device to enter a research request for a specific market, for example, "I would like a PEST analysis and 5 Forces analysis of the AI ​​market."

[1261] Step 2: The terminal sends the request entered by the user to the server, which includes the market to be analyzed and the type of analysis required.

[1262] Step 3: Based on the received request, the server collects data related to the specified market, searching and retrieving open data, industry reports, news articles, academic papers, etc. from the Internet.

[1263] Step 4: The server converts the acquired data into a unified format, for example, organizing data in different formats such as text, PDF, CSV, etc. into JSON format.

[1264] Step 5: The server applies natural language processing (NLP) techniques to the organized data to extract important keywords and topics, such as technology trends, regulatory changes, and market growth rates.

[1265] Step 6: The server performs a PEST analysis based on the extracted data, including analysis of political, economic, social, and technological factors, such as assessing the impact of emerging technological trends and regulations on the AI ​​market.

[1266] Step 7: The server performs a 5 Forces analysis based on the extracted data, including the intensity of competition, the threat of new entrants, the threat of substitutes, the bargaining power of suppliers, and the bargaining power of buyers. For example, it analyzes major competitors in the AI ​​market and evaluates the threat of new entrants.

[1267] Step 8: The server generates a market understanding report based on the results of the PEST analysis and 5 Forces analysis. The report contains specific information and assessments that allow users to gain a deeper understanding of the market. For example, the report includes "AI market growth opportunities and challenges," "analysis of key players," and "impact of technological trends."

[1268] Step 9: The server sends the generated report to the user's device, which can be provided in PDF or web page format.

[1269] Step 10: The terminal displays the received report to the user. The user can view the report generated on the terminal and check the details of the market analysis.

[1270] Example 1

[1271] 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."

[1272] The market research process requires the collection, organization, and analysis of a wide variety of data, which requires a great deal of time and specialized knowledge. When conducting PEST analysis or 5 Forces analysis, the challenge is to quickly and accurately extract relevant information from a wide range of data sources. Many existing market research tools struggle to efficiently complete this process, forcing users to use multiple tools in combination.

[1273] 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.

[1274] In this invention, the server includes means for inputting a market research request from a user terminal, means for collecting data on a specified market from the Internet, means for organizing the collected data into a unified format, means for extracting important keywords and topics using natural language processing technology, means for analyzing the market from political, economic, social, and technological perspectives based on the extracted data, means for analyzing the market structure and competitive environment based on the extracted data, means for generating a market understanding report based on the analysis results, and means for transmitting the report to the user terminal. This enables users to quickly and efficiently perform advanced market analysis even without specialized knowledge.

[1275] "User Terminal" means the electronic device used by a User to access the System and enter market research requests.

[1276] A "Market Research Request" is a request entered into the System by a User specifying a particular market or type of analysis.

[1277] The "Internet" is a global network used to collect information.

[1278] "Data" refers to information about the market, collected from news articles, industry reports, academic papers, etc.

[1279] "Format" refers to the format or structure that unifies data and provides a basis for consistent analysis.

[1280] "Natural language processing technology" is a technology that allows computers to understand and analyze human language, and is used to extract keywords and topics.

[1281] "Keywords" refer to important words or phrases that are the subject of market research.

[1282] "Topics" refer to major themes or topics related to the subject of market research.

[1283] "PEST analysis" is an analytical method that evaluates a market from political, economic, social, and technological perspectives.

[1284] "Five Forces Analysis" is an analytical method for evaluating market structure and the competitive environment, assessing the intensity of competition, the threat of new entrants, the threat of substitutes, the bargaining power of suppliers, and the bargaining power of buyers.

[1285] A "Market Understanding Report" is a document created based on the results of PEST analysis and 5 Forces analysis, which allows users to gain a deeper understanding of the market.

[1286] A "server" is a computer system that performs processes such as data collection, organization, analysis, and report generation.

[1287] "Send" refers to the act of transferring the generated report to a user terminal.

[1288] This invention relates to a system that efficiently supports market research. In this system, when a user inputs a market request through a terminal, a server collects and analyzes related data from the Internet, generates a market understanding report based on PEST analysis and 5 Forces analysis, and provides it to the user.

[1289] The system is configured as follows: The user terminal has a user interface for inputting requests. The user uses this interface to specify a specific market and type of analysis. For example, a request can be made to "conduct a PEST analysis and 5 Forces analysis of the AI ​​market."

[1290] The device sends a request from the user to the server. The request includes keywords and instructions necessary for analysis. The server then collects data related to the specified market from the Internet. This collection uses a wide range of data sources, including open data, industry reports, news articles, and academic papers. Specifically, it uses Python's "BeautifulSoup" and "Google News API" to collect information from the Internet.

[1291] The collected data is organized on the server in a consistent format (e.g., JSON format). This streamlines preprocessing for analysis and stores the data in a unified format. Python libraries such as "pandas" and "PyPDF2" are used to organize the data.

[1292] The server uses natural language processing technology (using NLTK and SpaCy) to extract important keywords and topics from the organized data, such as "technology trends," "regulatory changes," and "market growth rates."

[1293] The server then performs a PEST analysis based on the extracted data. The PEST analysis evaluates the market from political, economic, social, and technological perspectives. Specifically, it evaluates the impact of the latest technological trends and regulations on the AI ​​market and classifies them into categories.

[1294] Similarly, the server performs a 5 Forces analysis, which evaluates the intensity of competition, threat of new entrants, threat of substitutes, bargaining power of suppliers, and bargaining power of buyers, including a detailed analysis of key competitors and a detailed assessment of the threat of new entrants.

[1295] Finally, the server generates a market understanding report based on the results of the PEST and 5 Forces analyses. This report contains specific information and assessments that allow users to gain a deeper understanding of the market. The report can also include graphical elements using Python's Jupyter Notebook and Matplotlib.

[1296] The generated report is sent from the server to the user's device, and is available in PDF or web page format, which the user can access via email or a download link.

[1297] Here is an example prompt:

[1298] "Please conduct a PEST analysis and 5 Forces analysis of the AI ​​market."

[1299] This system enables users to perform sophisticated market analysis quickly and efficiently, even without specialized knowledge.

[1300] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1301] Step 1:

[1302] User Interface Display

[1303] What it does: The terminal displays an interface that allows the user to enter a market research request.

[1304] Input: A web page a user visits or a mobile app launch.

[1305] Output: A display of an input interface that includes text boxes and drop-down menus.

[1306] What it does: When a user launches the app, the home screen displays the message "Enter your market research request." The request input field becomes active.

[1307] Step 2:

[1308] Submitting a Request

[1309] Operation: The terminal sends the input request to the server.

[1310] Input: The request the user types in the text field.

[1311] Output: The request data in JSON format is sent to the server.

[1312] Specific operation: When the user presses the "Submit" button, a request to "perform a PEST analysis and 5 Forces analysis of the AI ​​market" is sent to the server in JSON format. For example, {"request":"AI market", "analysis":["PEST", "5 Forces"]}.

[1313] Step 3:

[1314] Data collection

[1315] Operation: The server collects data related to a specified market from the Internet.

[1316] Input: Request data in JSON format.

[1317] Output: Raw market data collected (news articles, reports, papers, etc.).

[1318] What it does: The server uses the Google News API and PubMed API to search for the latest articles and academic papers on the AI ​​market, retrieves the results, and uses Python's "BeautifulSoup" to perform web scraping and collect relevant data.

[1319] Step 4:

[1320] Data formatting

[1321] How it works: The server organizes the collected data into a unified format (e.g., JSON format).

[1322] Input: Data in various formats (HTML, PDF, CSV, etc.).

[1323] Output: Data in consistent JSON format.

[1324] What it does: Uses Python's "pandas" and "PyPDF2" to convert collected data into a consistent format, for example extracting technical reports in PDF format into text and formatting them into JSON fields.

[1325] Step 5:

[1326] Keyword extraction

[1327] How it works: The server uses natural language processing techniques to extract important keywords and topics from the organized data.

[1328] Input: Organized data in JSON format.

[1329] Output: A dataset containing important keywords and topics.

[1330] Specific operation: The server performs text analysis using NLTK and SpaCy to extract keywords such as "technology trends," "regulatory changes," and "market growth rate."

[1331] Step 6:

[1332] Performing a PEST Analysis

[1333] Operation: The server performs a PEST analysis based on the extracted data.

[1334] Input: A dataset containing keywords or topics.

[1335] Output: Analysis results evaluated from political, economic, social and technological perspectives.

[1336] What it does: The server evaluates political regulations, economic trends, social influences, and technological advancements in the AI ​​market and categorizes and describes them.

[1337] Step 7:

[1338] 5. Performing Forces Analysis

[1339] How it works: The server performs a 5 Forces analysis on the extracted data.

[1340] Input: A dataset containing keywords or topics.

[1341] Output: Analysis assessing the intensity of competition, threat of new entrants, threat of substitutes, bargaining power of suppliers, and bargaining power of buyers.

[1342] What it does: The server analyzes data on key competitors to assess competitiveness and threats of new entrants. For example, it performs a detailed assessment of the impact of key competitor X on the market.

[1343] Step 8:

[1344] Generate reports

[1345] How it works: The server generates a market understanding report based on the results of the PEST analysis and the 5 Forces analysis.

[1346] Input: Results of PEST analysis and 5 Forces analysis.

[1347] Output: Market understanding report.

[1348] What it does: Uses Python's Jupyter Notebook and Matplotlib to generate text and graphical reports, including detailed PDF reports with PEST and 5 Forces charts.

[1349] Step 9:

[1350] Report distribution

[1351] How it works: The server generates a report and sends it to the user's device.

[1352] Input: Market Understanding Report.

[1353] Output: Report delivered to user terminal.

[1354] What happens: The report will be attached to your email in PDF format, or you will be provided with a download link. For example, open the email on your device and you will be able to download the "AI Market Analysis Report" as a PDF.

[1355] (Application example 1)

[1356] 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."

[1357] Market research is important in the advertising industry for formulating effective marketing strategies. However, traditional market research methods are time-consuming, labor-intensive, and require significant resource expenditures. Furthermore, it is difficult to maintain consistency in data collection, organization, and analysis, which can lead to problems with the accuracy and reliability of the resulting reports. Given this background, there is a growing need for systems that support market research efficiently and effectively.

[1358] 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.

[1359] In this invention, the server includes means for inputting a market research request from a user terminal, means for collecting data on a specified market from the Internet, means for organizing the collected data into a unified format, means for extracting important keywords and topics using natural language processing technology, means for performing a PEST analysis based on the extracted data, means for performing a 5 Forces analysis based on the extracted data, means for generating a market understanding report based on the results of the PEST analysis and the 5 Forces analysis, means for sending the generated report to the user terminal in PDF or web page format, means for supporting the generation of a market research report in the advertising industry using the analysis results, and means for guiding user input using prompt sentences. This allows for efficient and effective support of market research in the advertising industry, enabling users to perform advanced market analysis even without specialized knowledge.

[1360] "Market Research Request" means instructions entered by a User requesting the collection or analysis of information about a particular market or type of analysis.

[1361] A "user terminal" is a device, such as a smartphone or computer, that a user uses to connect to the Internet and input and receive information.

[1362] "Data collection means" refers to the function of the server to search and acquire data related to a specified market from the Internet.

[1363] "Means of organizing into a unified format" refers to the function of converting collected data into a unified format, such as JSON format, and saving it.

[1364] "Natural language processing technology" refers to the technology that uses computers to analyze, understand, and generate human language.

[1365] "Means for extracting keywords and topics" refers to the function of extracting important words and topics from text data using natural language processing technology.

[1366] "PEST analysis" is a method of analyzing a market from four perspectives: political, economic, social, and technological.

[1367] "Five Forces Analysis" is an analytical method for evaluating a market based on five factors: intensity of competition (competition among existing companies), threat of new entrants, threat of substitutes, bargaining power of suppliers, and bargaining power of buyers.

[1368] A "Market Understanding Report" is a detailed and comprehensive report on a specific market that compiles the results of a PEST analysis and a 5 Forces analysis.

[1369] "Means for sending to user terminal in PDF or web page format" refers to the functionality for providing the generated report to the user as a PDF file or web page.

[1370] "Means for supporting the generation of market research reports in the advertising industry" refers to a function for creating detailed market analysis reports for the purpose of formulating effective marketing strategies in the advertising industry.

[1371] "Means for guiding user input using prompts" refers to a function that provides specific instructions and examples to guide users in properly entering their market research requests.

[1372] This invention relates to a system in which a user inputs a research request for a specific market, a server collects and analyzes the necessary data from the Internet, and generates and provides a market understanding report based on PEST analysis and 5 Forces analysis. This system is specialized for the advertising industry, and it efficiently conducts market research and supports the formulation of marketing strategies.

[1373] The system for implementing this invention includes the following main functions: a user terminal, a server, natural language processing technology (NLP), and data collection and analysis means.

[1374] Hardware and Software

[1375] Hardware: User devices such as smartphones and computers where users input information, and servers that collect and analyze data.

[1376] Software: Server-side processing is done using Python and Flask, data scraping is done using Beautiful Soup and Selenium, and NLP is done using SpaCy or NLTK.

[1377] Details of data processing and calculation

[1378] 1. User Interface:

[1379] The user terminal provides a form for entering a research request. The form is built using HTML / CSS / JavaScript. The user enters details about a specific market and analysis format, and the information is received by the Flask server.

[1380] Example: A user fills out a form and asks for a PEST analysis and 5 Forces analysis of the smartphone advertising market.

[1381] 2. Processing the request:

[1382] The information entered into the form is sent to the server via the Flask server, which starts collecting data related to the specified market based on the request.

[1383] Example: A user request for "Smartphone Advertising Market", "PEST Analysis", and "5 Forces Analysis" is sent to the server.

[1384] 3. Data Collection:

[1385] The server collects the necessary data from the Internet using a scraping tool such as Beautiful Soup or Selenium, and the collected data may be provided in various formats (text, PDF, HTML, etc.).

[1386] Example: A server searches for the latest industry reports and news articles to gather data about the smartphone advertising market.

[1387] 4. Data formatting:

[1388] The server converts the collected data into a unified format (JSON), which makes subsequent analysis easier.

[1389] Example: Data in various formats (e.g. text, PDF, HTML) is organized into JSON format.

[1390] 5. Data analysis and keyword extraction:

[1391] Using natural language processing techniques (SpaCy or NLTK), the server extracts important keywords and topics from the data.

[1392] Example: The server extracts keywords such as "market size," "growth rate," "major competitors," and "consumer trends."

[1393] 6. PEST Analysis and Five Forces Analysis:

[1394] Based on the extracted data, the server performs a PEST analysis and a 5 Forces analysis, evaluating the market from each perspective (political, economic, social, technological and competitive, new entrants, threat of substitutes, and bargaining power of suppliers and buyers).

[1395] Example: The server analyzes the current state of the market and future trends from various perspectives.

[1396] 7. Report Generation and Delivery:

[1397] Based on the analysis results, the server generates a detailed market understanding report and provides it to the user in PDF or web page format, including a prompt function to guide the user to input appropriate requests.

[1398] Example: A report will be generated that includes "Current Status and Future Outlook of the Smartphone Advertising Market," "Analysis of Major Players," and "Technical Challenges and Trends."

[1399] Example prompt: "Please enter the market you want to analyze and select the type of analysis (PEST, 5 Forces). E.g., 'Smartphone advertising market, PEST and 5 Forces analysis.'"

[1400] In this way, the system can efficiently and effectively support market research in the advertising industry, enabling users to perform advanced market analysis without having specialized knowledge.

[1401] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1402] Step 1:

[1403] A user inputs a market research request from their device. A specific request is information about a specific market and analysis format. For example, a user might input, "I would like a PEST analysis and 5 Forces analysis of the smartphone advertising market." This input is received as a form in a user interface built with HTML / CSS / JavaScript.

[1404] Step 2:

[1405] Once the user has completed the input, the user device sends the input request to the Flask server. The specific operation of this step is to encode the form contents into JSON format and send it as an HTTP POST request to the server. The server receives this request and extracts keywords and instructions to start parsing it.

[1406] Step 3:

[1407] Based on the received request, the server collects data about the specified market from the Internet. For example, the server uses Beautiful Soup or Selenium to scrape the web for relevant open data, industry reports, news articles, etc. The input for this step is the request keywords, and the output is the collected raw data.

[1408] Step 4:

[1409] The server organizes the collected data into a unified format. In this step, data from various formats (text, PDF, HTML, etc.) is converted into a unified JSON format. Specifically, the server uses a PDF parsing library or parses text and HTML and combines them into a consistent format. The input is raw data, and the output is organized JSON data.

[1410] Step 5:

[1411] The server uses natural language processing (NLP) techniques to extract important keywords and topics from the unified data. Specifically, it uses SpaCy or NLTK to extract specific words and phrases within the data. The input is organized JSON data, and the output is a list of extracted keywords.

[1412] Step 6:

[1413] The server performs a PEST analysis based on the extracted keywords. Specifically, it categorizes the information in the data into political, economic, social, and technological categories and evaluates each category. The input is a list of keywords, and the output is the results of the PEST analysis.

[1414] Step 7:

[1415] The server then performs a 5 Forces analysis based on the extracted keywords. In this step, it evaluates the intensity of competition, the threat of new entrants, the threat of substitutes, and the bargaining power of suppliers and buyers. The input is a list of keywords, and the output is the results of the 5 Forces analysis.

[1416] Step 8:

[1417] The server generates a market understanding report based on the results of the PEST analysis and the 5 Forces analysis. Its specific operation is to integrate the results of each analysis and create a report in a format that is easy for users to understand. The input is the results of both analyses, and the output is the market understanding report.

[1418] Step 9:

[1419] The generated report is sent to the user's terminal in PDF or web page format. The server generates the PDF using a document generation tool (such as FPDF) and converts it to HTML when providing it in web format. The input is the market understanding report, and the output is a PDF or web page format report to the user.

[1420] Step 10:

[1421] The server provides a means to guide user input using prompts. Specifically, when a user enters a market research request, the server displays appropriate prompts (e.g., "Please enter the market you want to analyze and select the type of analysis (PEST, 5 Forces). Eg, 'Smartphone advertising market, PEST and 5 Forces analysis.'") to improve the accuracy of user input. The input is the market and analysis type specified by the user, and the output is the optimal request input situation.

[1422] 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.

[1423] The present invention relates to a system that efficiently supports market research, and is combined with an emotion engine that recognizes user emotions. When a user inputs a market request, the system collects and analyzes related data from the Internet, generates a market understanding report based on PEST analysis and 5 Forces analysis, and provides it to the user. Furthermore, by using an emotion engine that recognizes user emotions, the content and format of the report can be customized based on the user's emotional state.

[1424] System Program

[1425] 1. User Interface

[1426] How it works: The terminal provides an interface where users can enter market research requests, allowing them to specify specific markets and types of analysis.

[1427] Example: A user enters a request to "conduct a PEST analysis and 5 Forces analysis of the AI ​​market."

[1428] 2. Processing the Request

[1429] Operation: The terminal sends a request entered by the user to the server, which includes keywords and instructions for analysis.

[1430] Example: A user request is sent to the server, and the keywords "AI market", "PEST analysis", and "5 Forces analysis" arrive at the server.

[1431] 3. Emotion Recognition Implementation

[1432] How it works: The server sends the user's input request to the emotion engine, which analyzes the user's emotion. The emotion engine analyzes the input text data and evaluates the user's emotional state (e.g., interest, tension, satisfaction, etc.).

[1433] Example: A user's input text is analyzed by an emotion engine to identify emotional states such as "excited," "anxious," or "indifferent."

[1434] 4. Data Collection

[1435] How it works: The server collects data related to a specified market from the internet, including open data, industry reports, news articles, academic papers, etc.

[1436] Example: A server searches and collects the latest news articles and technical reports related to the AI ​​market.

[1437] 5. Data format organization

[1438] How it works: The server converts the data it receives into a unified format, for example, organizing data in different formats (text, PDF, CSV, etc.) into JSON format.

[1439] Example: Data in various formats such as text, PDF, CSV, etc. is converted to JSON format.

[1440] 6. Data analysis and keyword extraction

[1441] How it works: The server applies natural language processing (NLP) techniques to the organized data to extract important keywords and topics.

[1442] Example: Keywords such as "technology trends," "regulatory changes," and "market growth rate" are extracted.

[1443] 7. Conduct a PEST analysis

[1444] How it works: The server performs a PEST analysis based on the extracted data, including analysis of Politics, Economics, Society, and Technology factors.

[1445] Example: Sarver assesses the latest technological trends and regulatory impacts in the AI ​​market and categorizes them into their respective categories.

[1446] 8. Conducting a Five Forces Analysis

[1447] How it works: The server performs a 5 Forces analysis based on the same extracted data, including the intensity of competition, the threat of new entrants, the threat of substitutes, the bargaining power of suppliers, and the bargaining power of buyers.

[1448] Example: The server analyzes key competitors in the AI ​​market and assesses the threat of new entrants.

[1449] 9. Generate Reports

[1450] How it works: The server generates a market understanding report based on the results of the PEST and 5 Forces analyses. The report contains specific information and assessments that allow users to gain a deeper understanding of the market. Furthermore, the report content is customized based on the analysis results of the sentiment engine.

[1451] Example: The server generates a comprehensive report summarizing "AI market growth opportunities and challenges," "analysis of key players," "impact of technology trends," etc. If the user is excited, the report will highlight the positive aspects.

[1452] 10. Report Distribution

[1453] How it works: The server generates a report and sends it to the user's device. The report is provided in PDF format or as a web page.

[1454] Example: Users can view reports generated on their devices, which provide detailed market analysis and reflect their sentiment.

[1455] In this way, the system can efficiently support market research and further improve user experience by providing customized reports according to user sentiment.

[1456] The processing flow will be explained below.

[1457] Step 1:

[1458] Users use their devices to enter research requests for specific markets, such as "I'd like a PEST and 5 Forces analysis of the AI ​​market."

[1459] Step 2:

[1460] The terminal sends the request entered by the user to the server, which includes the market to be analyzed and the type of analysis required.

[1461] Step 3:

[1462] Based on the received request, the server sends the user's input to the emotion engine, which analyzes the user's emotion. The emotion engine analyzes the input text data and evaluates the user's emotional state (e.g., interest level, tension level, satisfaction level, etc.).

[1463] Step 4:

[1464] The server receives the user's emotional data sent from the emotion engine, identifying their emotional state, such as "excited," "anxious," or "indifferent."

[1465] Step 5:

[1466] The server collects data related to the specified market from the internet, including open data, industry reports, news articles, academic papers, etc.

[1467] Step 6:

[1468] The server converts the acquired data into a unified format, for example, organizing data in different formats such as text, PDF, and CSV into JSON format.

[1469] Step 7:

[1470] The server applies natural language processing (NLP) technology to the organized data to extract important keywords and topics, such as "technology trends," "regulatory changes," and "market growth rates."

[1471] Step 8:

[1472] The server then performs a PEST analysis based on the extracted data, including analysis of political, economic, social, and technological factors, such as assessing the impact of emerging technological trends and regulations on the AI ​​market.

[1473] Step 9:

[1474] The server also performs a 5 Forces analysis based on the extracted data, including the intensity of competition, the threat of new entrants, the threat of substitutes, the bargaining power of suppliers, and the bargaining power of buyers. For example, it analyzes major competitors in the AI ​​market and evaluates the threat of new entrants.

[1475] Step 10:

[1476] The server generates a market understanding report based on the results of the PEST and 5 Forces analyses. The report contains specific information and assessments that allow users to gain a deeper understanding of the market. Furthermore, the report content is customized based on the analysis results of the emotion engine. For example, if the user is excited, a report that emphasizes positive aspects will be generated.

[1477] Step 11:

[1478] The server then sends the generated report to the user's device, where it is available in PDF or web page format.

[1479] Step 12:

[1480] The terminal displays the received report to the user, who can then view the report generated by the terminal to check the detailed market analysis. The report also reflects the user's sentiment.

[1481] Example 2

[1482] 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."

[1483] Traditional market research systems have limited user experience because they are unable to customize reports to fit the user's needs and emotional state. Furthermore, data collection and analysis are manual, making the research process inefficient and time-consuming. To solve this issue, a system is needed that automates the market research process by providing customized reports that take user emotions into account.

[1484] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for sending a user request to an emotion engine and analyzing the user's emotions, means for collecting data on the specified market from the Internet, and means for organizing the collected data into a unified format. This makes it possible to provide a market understanding report customized based on the user's emotional state, thereby making the market research process more efficient and faster.

[1485] "User Terminal" means a device operated by a User and used to enter market research requests and receive generated reports.

[1486] "Market Research Request" means an instruction or request entered by a User to request the collection and analysis of information about a particular market.

[1487] An "emotion engine" refers to an algorithm or system that analyzes a user's input text and assesses the user's emotional state.

[1488] The "Internet" is an information and communications network that interconnects computers and networks around the world and is a medium for obtaining data from public sources.

[1489] "Data" refers to information collected from the internet, including open market data, industry reports, news articles, academic papers, etc.

[1490] "Format" refers to the format or structure in which data is stored, and indicates the standards for unifying data of different formats.

[1491] "Natural language processing technology" is a technology that enables computers to understand, interpret, and generate human language, and is used to extract important keywords and topics.

[1492] "Keywords" refer to important words or phrases related to the market research subject and are extracted during the data analysis process.

[1493] "Topics" refer to the major themes or topics extracted from the data.

[1494] "PEST analysis" refers to a method of market analysis that takes into account political, economic, social, and technological factors.

[1495] "Five Forces Analysis" refers to a market analysis method that evaluates the intensity of competition, the threat of new entrants, the threat of substitutes, the bargaining power of suppliers, and the bargaining power of buyers.

[1496] A "Market Understanding Report" is a report that details the current state and future trends of a market based on collected and analyzed data.

[1497] "Customization" refers to adjusting the content and format of a report based on the user's emotional state and needs.

[1498] "Server" refers to a central processing unit or system that receives requests from user devices and performs data collection, analysis, and report generation.

[1499] The present invention relates to a system that efficiently supports market research, particularly by incorporating an emotion engine that recognizes user emotions. When a user inputs a market request, the system collects and analyzes related data from the Internet, generates a market understanding report based on PEST analysis and 5 Forces analysis, and provides it to the user. Furthermore, by using an emotion engine that recognizes user emotions, the content and format of the report can be customized based on the user's emotional state. This improves the user experience and streamlines the market research process.

[1500] This system consists of a server and a user terminal. The user terminal provides an interface for users to input market research requests. This interface includes text input fields and selection menus. For example, a user can input a request such as "I would like you to conduct a PEST analysis and 5 Forces analysis of the AI ​​market."

[1501] When a user inputs a market research request, the device sends the request to the server. The request includes keywords and instructions for analysis. The server then sends the received request to the emotion engine, which analyzes the user's emotions. The emotion engine analyzes the input text data and evaluates the user's emotional state (e.g., interest, tension, satisfaction, etc.).

[1502] The server then collects data related to the specified market from the internet, including open data, industry reports, news articles, academic papers, etc. Because the collected data often exists in different formats, the server converts this data into a unified format, specifically converting formats such as text, PDF, and CSV into JSON.

[1503] The collected data is analyzed using natural language processing (NLP) technology to extract important keywords and topics, such as "technology trends," "regulatory changes," and "market growth rates." Based on these keywords, the server performs PEST and 5 Forces analyses.

[1504] A PEST analysis involves analyzing the market from political, economic, social, and technological perspectives. For example, it evaluates the impact of the latest technological trends and regulations on the AI ​​market and categorizes them into their respective categories. Similarly, a 5 Forces analysis evaluates the intensity of competition, the threat of new entrants, the threat of substitutes, the bargaining power of suppliers, and the bargaining power of buyers. Specifically, it analyzes major competitors in the AI ​​market and evaluates the threat of new entrants.

[1505] The server generates a market understanding report based on these analysis results. The report contains specific information and evaluations that allow users to gain a deeper understanding of the market. The report content is also customized based on the analysis results of the emotion engine. For example, if the user is excited, a report that emphasizes the positive aspects will be generated.

[1506] Finally, the server will send the generated report to the user's device, which will be available in PDF format or web page format, allowing users to view detailed market analysis and get customized information based on their own sentiment.

[1507] Examples of prompts to input to a generative AI model include:

[1508] "I would like you to conduct a PEST analysis and 5 Forces analysis of the AI ​​market."

[1509] In this way, the system can efficiently support market research and improve user experience by providing customized reports according to user sentiment.

[1510] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1511] Step 1:

[1512] The user enters a market research request, specifying a specific market and type of analysis through a user interface displayed on the terminal. As input, the user provides a prompt such as "I would like you to conduct a PEST analysis and 5 Forces analysis of the AI ​​market." As output, the user's request is obtained from the terminal.

[1513] Step 2:

[1514] The terminal sends the market research request entered by the user to the server. The input includes the user's request data (e.g., "AI market," "PEST analysis," "5 Forces analysis"), and the output includes an HTTP POST request to the server that includes the request data.

[1515] Step 3:

[1516] The server sends the received request data to the emotion engine to analyze the user's emotions. Using the request data as input, the emotion engine analyzes the text data to evaluate the user's emotional state (e.g., interest, tension, satisfaction, etc.). As output, JSON data containing the analysis results is sent back to the server.

[1517] Step 4:

[1518] The server collects data related to a specified market from the internet. Keywords such as "AI market" and "technology trends" are used as input. Specifically, data is collected through web scraping and API usage. The acquired data is then saved on the server as output.

[1519] Step 5:

[1520] The server organizes the collected data into a unified format. Data in various formats (text, PDF, CSV, etc.) is used as input. Specifically, it converts the data into JSON format using Python libraries (e.g., PyPDF2, pandas). Data in a unified format is obtained as output.

[1521] Step 6:

[1522] The server applies natural language processing (NLP) techniques to the organized data to extract important keywords and topics. Data in a standardized format is used as input. Specifically, analysis is performed using an NLP library (e.g., spaCy, NLTK). Key keywords such as "technology trends," "regulatory changes," and "market growth rates" are extracted as output.

[1523] Step 7:

[1524] The server performs a PEST analysis based on the extracted keywords. The extracted keywords are used as input. Specifically, these keywords are classified into political, economic, social, and technological categories, and an evaluation is performed for each category. The output is a detailed analysis of each category.

[1525] Step 8:

[1526] The server then performs a 5 Forces analysis based on the extracted keywords. The extracted keywords are used as input. Specifically, it evaluates the intensity of market competition, the threat of new entrants, the threat of substitutes, the bargaining power of suppliers, and the bargaining power of buyers. The output is the analysis results for each element of the 5 Forces.

[1527] Step 9:

[1528] The server generates a market understanding report based on the results of the PEST and 5 Forces analyses. The results of both analyses and the analysis of the user's emotional state are used as input. Specifically, the server compiles the report in HTML or PDF format and customizes the report content based on the results of the emotion engine. The server outputs the completed market understanding report.

[1529] Step 10:

[1530] The server sends the generated market understanding report to the user's device. The completed report data is used as input. Specifically, the server sends the report via an HTTP response so that the user can view it on their device. The output is a report that the user can view.

[1531] (Application example 2)

[1532] 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."

[1533] Conventional market research systems often provide uniform reports without considering the user's emotional state. This resulted in a lack of information tailored to the user's needs and emotions, resulting in a lack of improvement in the user experience. Furthermore, it was difficult to efficiently utilize the results of market research, preventing the improvement of user satisfaction.

[1534] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1535] In this invention, the server includes means for inputting a market research request from a user terminal, means for collecting data on a specified market from the Internet, means for organizing the collected data into a unified format, means for extracting important keywords and topics using natural language processing technology, means for performing a PEST analysis based on the extracted data, means for performing a 5 Forces analysis based on the extracted data, means for generating a market understanding report based on the results of the PEST analysis and the 5 Forces analysis, means for recognizing the emotional state of the user, means for customizing the content and format of the report based on the emotional state of the user, and means for sending the report to the user terminal. This makes it possible to generate a market understanding report customized in line with the user's emotions, improving the user experience.

[1536] "User Terminal" means the device through which a User enters market research requests and receives generated reports.

[1537] A "market research request" is information entered by a user to specify the market they wish to research and the type of analysis they wish to perform.

[1538] The "means for collecting data relating to a designated market from the Internet" is a function for automatically obtaining data relating to a designated market from the Internet.

[1539] "Means for organizing collected data into a unified format" refers to a function for converting and organizing acquired data into a consistent format.

[1540] "Natural language processing technology" is a technology for analyzing human language and extracting specific information.

[1541] "Means of extracting important keywords and topics" is a function that finds key words and themes needed for analysis from market data.

[1542] "PEST analysis" is a method of analyzing the market environment from four perspectives: politics, economics, society, and technology.

[1543] The "5 Forces Analysis" is a method for assessing the intensity of competition in a market, the threat of new entrants, the threat of substitutes, the bargaining power of suppliers, and the bargaining power of buyers.

[1544] A "Market Understanding Report" is a report that shows the current state and forecast of the market, generated based on PEST analysis and 5 Forces analysis.

[1545] "Means for recognizing the user's emotional state" refers to a function that analyzes the user's emotional state from their input and behavior.

[1546] "Means for customizing the content and format of a report based on the user's emotional state" is a function that adjusts the content and presentation of a report according to the user's emotions.

[1547] The "means for sending a report to a user terminal" is a function for sending the generated market understanding report to a user device.

[1548] This invention is a market research system that is composed of a user terminal, a server, and an emotion engine. A specific embodiment of this system is described below.

[1549] System configuration

[1550] 1. User Device:

[1551] Market research request input method: An input device (e.g., a smartphone or PC interface) through which a user requests market research.

[1552] Report receiving means: Has the function of receiving and displaying market understanding reports sent from the server.

[1553] 2. Server:

[1554] Data collection method: A function that automatically collects data about a specified market from the Internet. For example, using an API to obtain relevant data.

[1555] Data reduction: A function to convert and reduce collected data into a unified format. Convert data in different formats (text, PDF, CSV, etc.) into JSON format.

[1556] Natural language processing technology: Technology that uses software libraries such as TextBlob to extract important keywords and topics from collected data.

[1557] PEST analysis and 5 Forces analysis: A function that evaluates the market to deepen understanding based on the analysis results. For example, it evaluates growth opportunities and the intensity of competition in the AI ​​market.

[1558] Report generation tool: A function that generates a market understanding report that integrates the results of PEST analysis and 5 Forces analysis based on the analysis results.

[1559] Emotion recognition: Analyzes the user's input and recognizes their emotional state. Uses an emotion analysis engine such as TextBlob.

[1560] Report customization: Ability to tailor and customize report content and format based on perceived sentiment.

[1561] Report sending method: A function for sending generated reports to the user's terminal.

[1562] Specific processing flow

[1563] When a user inputs a market research request into their device, the request is first analyzed using emotion recognition means to identify the user's emotional state (e.g., positive, negative, neutral). The server then collects relevant data from the Internet and organizes it into a unified format. The organized data is then analyzed using natural language processing techniques to extract important keywords and topics.

[1564] The extracted data is then used for PEST and 5 Forces analysis, and the analysis results are compiled into a market understanding report, which is customized based on the user's emotional state. Finally, the customized report is sent to the user's device for viewing.

[1565] Specific examples of hardware or software to be used

[1566] Sentiment Analysis Engine: TextBlob or similar natural language processing library

[1567] Data collection: Public APIs and web crawlers

[1568] Data format conversion: JSON library

[1569] Analysis technology: Natural Language Processing (e.g., NLTK)

[1570] Specific examples

[1571] An example of a prompt is:

[1572] "Please conduct a PEST analysis and 5 Forces analysis of the AI ​​market."

[1573] "Provide the latest trends and competitive analysis in the automotive industry"

[1574] With this invention, users receive personalized, emotionally relevant market understanding reports, enabling them to make more informed decisions.

[1575] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1576] Step 1:

[1577] Enter a market research request from the user's device.

[1578] The user uses a smartphone or PC interface to input information specifying a particular market and type of analysis, which then inputs the user's request into the terminal.

[1579] Step 2:

[1580] The input request is sent to the server.

[1581] The user terminal sends the input request to the server, which includes instructions on the market to be researched and the type of analysis.

[1582] Step 3:

[1583] An emotion recognizer analyzes the request and recognizes the user's emotional state.

[1584] The server uses an emotion engine to analyze the input request text and identify the user's emotional state (positive, negative, neutral, etc.), resulting in the emotion analysis result.

[1585] Step 4:

[1586] Collect data about a specified market from the internet.

[1587] The server retrieves data about the specified market from the internet using APIs and web crawlers, and stores the retrieved data as raw data.

[1588] Step 5:

[1589] Organize the collected data into a unified format.

[1590] The server converts and organizes data from different formats (text, PDF, CSV, etc.) into a unified format (such as JSON), thereby maintaining data consistency.

[1591] Step 6:

[1592] Natural language processing technology is used to extract important keywords and topics.

[1593] The server uses natural language processing libraries such as TextBlob to extract important keywords and topics from the data, providing key insights and trends.

[1594] Step 7:

[1595] A PEST analysis is performed based on the extracted data.

[1596] The server then analyzes the Politics, Economics, Society, and Technology elements based on the extracted keywords and topics, generating the PEST analysis results.

[1597] Step 8:

[1598] A 5 Forces analysis will be performed based on the extracted data.

[1599] The server applies the 5 Forces analysis to evaluate the intensity of competition, the threat of new entrants, the threat of substitutes, the bargaining power of suppliers, and the bargaining power of buyers, thereby generating the 5 Forces analysis results.

[1600] Step 9:

[1601] Generate market understanding reports based on the results of PEST analysis and 5 Forces analysis.

[1602] The server integrates the results of PEST and 5 Forces analysis to create a comprehensive market understanding report, the content and format of which are customized based on the user's emotional state as previously analyzed.

[1603] Step 10:

[1604] Send the generated report to the user's device.

[1605] The server generates a customized market understanding report in PDF format, web page format, etc., and sends it to the user's device, where the user can view the report.

[1606] Prompt Sentence Examples

[1607] "Please conduct a PEST analysis and 5 Forces analysis of the AI ​​market."

[1608] "Provide the latest trends and competitive analysis in the automotive industry"

[1609] In this way, users receive emotionally relevant and customized market understanding reports, leading to more accurate and useful information.

[1610] 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.

[1611] 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.

[1612] 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.

[1613] 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.

[1614] 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.

[1615] 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.

[1616] 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).

[1617] 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.

[1618] 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."

[1619] 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.

[1620] 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).

[1621] 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.

[1622] 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.

[1623] 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.

[1624] 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.

[1625] 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.

[1626] 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.

[1627] 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.

[1628] 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.

[1629] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1630] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1631] The following is further disclosed regarding the above embodiment.

[1632] (Claim 1)

[1633] a means for inputting market research requests from a user terminal;

[1634] means for collecting data about a designated market from the Internet;

[1635] A means of organizing the collected data into a uniform format;

[1636] A means of extracting important keywords and topics using natural language processing technology,

[1637] A means of conducting a PEST analysis based on the extracted data;

[1638] A method for conducting 5 Forces analysis based on the extracted data, and

[1639] A means to generate market understanding reports based on the results of PEST analysis and 5 Forces analysis;

[1640] The system includes means for transmitting reports to a user terminal.

[1641] (Claim 2)

[1642] The system according to claim 1, which collects data on a specified market from the Internet based on a request input from a user terminal, organizes the data, performs PEST analysis and 5 Forces analysis, and generates a market understanding report based on the analysis results.

[1643] (Claim 3)

[1644] 2. The system of claim 1, wherein natural language processing techniques are used to extract important keywords and topics from collected market data.

[1645] "Example 1"

[1646] (Claim 1)

[1647] a means for inputting market research requests from a user terminal;

[1648] means for collecting data about a designated market from the Internet;

[1649] A means of organizing the collected data into a uniform format;

[1650] A means of extracting important keywords and topics using natural language processing technology,

[1651] A means of analyzing the market from political, economic, social and technological perspectives based on the extracted data;

[1652] A means of analyzing the market structure and competitive environment based on the extracted data;

[1653] a means for generating a market understanding report based on the analysis results;

[1654] The system includes means for transmitting reports to a user terminal.

[1655] (Claim 2)

[1656] The system described in claim 1 collects data on a specified market from the Internet based on a request input from a user terminal, organizes the data, and performs an analysis to evaluate the market from political, economic, social, and technological perspectives, as well as an analysis to evaluate the market structure and competitive environment, and generates a market understanding report based on the analysis results.

[1657] (Claim 3)

[1658] 2. The system of claim 1, wherein natural language processing techniques are used to extract important keywords and topics from collected market data.

[1659] "Application Example 1"

[1660] (Claim 1)

[1661] a means for inputting market research requests from a user terminal;

[1662] means for collecting data about a designated market from the Internet;

[1663] A means of organizing the collected data into a uniform format;

[1664] A means of extracting important keywords and topics using natural language processing technology,

[1665] A means of conducting a PEST analysis based on the extracted data;

[1666] A method for conducting 5 Forces analysis based on the extracted data, and

[1667] A means to generate market understanding reports based on the results of PEST analysis and 5 Forces analysis;

[1668] A means for sending the generated report to the user's device in PDF or web page format;

[1669] a means for using the analysis results to assist in generating market research reports in the advertising industry;

[1670] means for guiding user input using prompt sentences;

[1671] A system including:

[1672] (Claim 2)

[1673] The system of claim 1 collects data on a specified market from the Internet based on a request input from a user terminal, organizes the data to perform PEST analysis and 5 Forces analysis, generates a market understanding report based on the analysis results, and uses prompt sentences to guide the user's input.

[1674] (Claim 3)

[1675] 2. The system of claim 1, which uses natural language processing technology to extract important keywords and topics from collected market data and assists in generating market research reports in the advertising industry.

[1676] "Example 2: Combining Emotion Engines"

[1677] (Claim 1)

[1678] a means for inputting market research requests from a user terminal;

[1679] means for transmitting user requests to an emotion engine and analyzing the user's emotions;

[1680] means for collecting data about a designated market from the Internet;

[1681] A means of organizing the collected data into a uniform format;

[1682] A means of extracting important keywords and topics using natural language processing technology,

[1683] A means of conducting a PEST analysis based on the extracted data;

[1684] A method for conducting 5 Forces analysis based on the extracted data, and

[1685] Generate market understanding reports based on the results of PEST analysis and 5 Forces analysis, and customize them based on the user's emotional state.

[1686] The system includes means for transmitting reports to a user terminal.

[1687] (Claim 2)

[1688] The system according to claim 1, which collects data on a specified market from the Internet based on a request input from a user terminal, organizes the data to perform PEST analysis and 5 Forces analysis, generates a market understanding report based on the analysis results, and customizes it based on the user's emotional state.

[1689] (Claim 3)

[1690] 2. The system of claim 1, wherein natural language processing techniques are used to extract important keywords and topics from collected market data.

[1691] "Application example 2 when combining emotion engines"

[1692] (Claim 1)

[1693] a means for inputting market research requests from a user terminal;

[1694] means for collecting data about a designated market from the Internet;

[1695] A means of organizing the collected data into a uniform format;

[1696] A means of extracting important keywords and topics using natural language processing technology,

[1697] A means of conducting a PEST analysis based on the extracted data;

[1698] A method for conducting 5 Forces analysis based on the extracted data, and

[1699] A means to generate market understanding reports based on the results of PEST analysis and 5 Forces analysis;

[1700] a means for recognizing the emotional state of a user;

[1701] A means to customize the content and format of reports based on the user's emotional state;

[1702] The system includes means for transmitting reports to a user terminal.

[1703] (Claim 2)

[1704] The system according to claim 1, which collects data on a specified market from the Internet based on a request input from a user terminal, organizes the data, performs PEST analysis and 5 Forces analysis, and generates a market understanding report based on the analysis results.

[1705] (Claim 3)

[1706] 2. The system of claim 1, wherein natural language processing techniques are used to extract important keywords and topics from collected market data. [Explanation of symbols]

[1707] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. a means for inputting market research requests from a user terminal; means for collecting data about a designated market from the Internet; A means of organizing the collected data into a uniform format; A means of extracting important keywords and topics using natural language processing technology, A means of conducting a PEST analysis based on the extracted data; A method for conducting 5 Forces analysis based on the extracted data, and A means to generate market understanding reports based on the results of PEST analysis and 5 Forces analysis; The system includes means for transmitting reports to a user terminal.

2. The system of claim 1 collects data on a specified market from the Internet based on a request input from a user terminal, organizes the data, performs PEST analysis and 5 Forces analysis, and generates a market understanding report based on the analysis results.

3. 10. The system of claim 1, wherein natural language processing techniques are used to extract important keywords and topics from the collected market data.

Images