System

Abstract

To provide a system.SOLUTION: The system includes: means of collecting user information including the price of products which a user has already purchased; means of proposing the price of a new product that the user is considering purchasing based on the user information; means of analyzing the emotion of the user with respect to the price of the proposed product; and means of proposing while dynamically changing the price of the product based on the analyzed emotion of the user.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] In the B2B world, there is a lack of efficient ways for companies to check the prices of products they have already introduced or to propose prices for new products they are considering introducing. [Means for solving the problem]

[0005] We have developed a system that allows customers to input the size of their company, the purpose of use, and the prices of products that have already been introduced, and provides a means to display a list of prices for products currently being used based on this information, as well as a means to propose prices for products that are being considered for new introduction.In particular, the proposal method uses generation AI to propose product prices, and this system can be used as a tool for in-house use in B2B companies. [Brief explanation of the drawings]

[0006] [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. 2 is a sequence diagram showing a flow of processing in the data processing system according to the first embodiment of the first form example. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1 of Embodiment 1. [Figure 13] FIG. 10 is a sequence diagram showing a processing flow of a data processing system in a second embodiment of the second form example. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 of Embodiment Example 2. [Figure 15] FIG. 10 is a sequence diagram showing the flow of processing in a data processing system according to a third embodiment of the third embodiment. [Figure 16]FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 3 of Embodiment 3. [Figure 17] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in the first embodiment of the first form example when an emotion engine is combined. [Figure 18] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1 of Form Example 1 when an emotion engine is combined. [Figure 19] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in the second embodiment of the second form example when an emotion engine is combined. [Figure 20] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 of Form Example 2 when an emotion engine is combined. [Figure 21] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in the third embodiment of the third form example when an emotion engine is combined. [Figure 22] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 3 of Form Example 3 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0007] 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.

[0008] First, the terms used in the following description will be explained.

[0009] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, the processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), or a TPU (TENSOR PROCESSING UNIT (registered trademark)).

[0010] 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.

[0011] 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.

[0012] 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.

[0013] 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."

[0014] [First embodiment]

[0015] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0016] 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.

[0017] 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).

[0018] 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.

[0019] 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.

[0020] 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.

[0021] 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.

[0022] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0023] 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.

[0024] 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.

[0025] 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.

[0026] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[0027] "Example 1"

[0028] The system of the present invention is equipped with a means for inputting the customer's company size, intended use, and prices of products already in use. Specifically, this information can be input through a user interface. It also has a means for displaying a list of prices of products currently in use based on this information. This allows users to check the price information of their company's products at a glance.

[0029] "Example 2"

[0030] Furthermore, the system of the present invention includes a means for proposing prices for new products that are being considered for introduction. This means uses a generation AI to propose prices for the products. Specifically, the AI ​​calculates an appropriate price for the new product based on the price information of existing products and information entered by the user, and proposes it to the user.

[0031] "Example 3"

[0032] The system of the present invention can be used as a tool for in-company use in B2B. A specific example of its use is when a company is considering introducing a new product and is deciding on the price, the system is used to propose an appropriate price, and the price is then decided based on the results.

[0033] The processing flow of each embodiment will be described below.

[0034] "Example 1"

[0035] Step 1: The user enters their company size, intended use, and the prices of products already in use through the system's user interface.

[0036] Step 2: The system will display a list of the prices of the products currently being used based on the information entered. This list is organized so that users can check the pricing information of their company's products at a glance.

[0037] "Example 2"

[0038] Step 1: The user enters information about the new product they are considering introducing into the system. Step 2: The system's generation AI calculates the appropriate price for the new product based on the price information of existing products and the information entered by the user.

[0039] Step 3: The AI ​​generator proposes the calculated price to the user, who can then decide the price of the product based on this proposal.

[0040] "Example 3"

[0041] Step 1: Companies use this system when determining the price of new products they are considering introducing.

[0042] Step 2: The company enters the necessary information into the system and receives a price proposal from the generative AI.

[0043] Step 3: The company determines the price of the product based on the price proposals received.

[0044] Example 1

[0045] Next, a description will be given of Example 1 of Form 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."

[0046] With conventional systems, it was difficult for companies to check the pricing information of their own products at a glance, and there was a lack of means to appropriately propose prices for new products that companies were considering introducing. As a result, companies were unable to efficiently manage and compare pricing information for products, making it difficult to select the most suitable products.

[0047] 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.

[0048] In this invention, the server includes means for inputting the size of the customer's company, its intended use, and the prices of products already introduced, means for displaying a list of prices of products currently being used based on this information, means for saving the input data in a database, means for searching and filtering product price information from the database, means for generating a list of filtered product price information, means for displaying the generated price information, and means for proposing prices for products being considered for new introduction. This allows companies to check the price information of their own products at a glance, and further enables them to receive appropriate price proposals for products being considered for new introduction.

[0049] "Company size" is an indicator that shows the size of a company, such as the number of employees and sales.

[0050] "Usage" refers to the purpose for which a company uses a particular product or service.

[0051] "Merchandise" is a general term for goods and services that a company purchases or uses.

[0052] "Price" refers to the amount of money paid for goods or services.

[0053] "User interface" refers to the means, such as a screen or input form, through which a user interacts with a system.

[0054] A "database" is a system for efficiently storing, searching, and managing data.

[0055] "Filtering" refers to the process of selecting data based on specific conditions.

[0056] A "generative AI model" refers to an algorithm or system that uses artificial intelligence to analyze data and generate new information or suggestions.

[0057] A "prompt" refers to an instruction or question to be input into a generative AI model.

[0058] "Business-to-business transactions" refer to transactions in which companies buy and sell goods and services.

[0059] MODE FOR CARRYING OUT THE INVENTION

[0060] This invention is a system that allows companies to check the pricing information of their own products at a glance and receive appropriate pricing suggestions for products they are considering introducing. The system provides a user interface for users to input information about the company's size, intended use, and the prices of products already introduced. The system also has the ability to save the input data in a database, search and filter product pricing information from the database, and display it in a list format.

[0061] Hardware and software used

[0062] Device: PC, smartphone, or other device

[0063] Server: A server that processes data and manages the database

[0064] Database management system: MySQL (registered trademark), PostgreSQL, etc.

[0065] User Interface: Interface accessible through a web browser

[0066] Generative AI model: An artificial intelligence algorithm for suggesting product prices

[0067] Program processing

[0068] Users access the system's user interface using a terminal. They input information such as the size of their company, the purpose of use, and the prices of products they have already introduced. This input data is then sent from the terminal to the server.

[0069] The server analyzes the received data and stores it in a database management system (e.g., MySQL). The server searches for product price information stored in the database and filters it based on the information entered by the user. The filtered product price information is generated in list format and sent back to the terminal.

[0070] The terminal displays the received price information on the user interface, allowing users to check the price information of their company's products at a glance.The system also has a function that uses a generative AI model to suggest prices for new products that are being considered for introduction.

[0071] Specific examples

[0072] As a concrete example, consider a case where a user is a small or medium-sized enterprise and uses IT services. The user inputs the prices of "cloud storage" and "project management tools" as products that have already been introduced.

[0073] Example prompt sentence:

[0074] Company size: Small business

[0075] Usage: IT services

[0076] Prices of already introduced products:

[0077] Cloud storage: 5000 yen / month

[0078] Project management tool: 3000 yen / month

[0079] After entering this prompt, the system will use this information to display a list of prices for the products you are currently using. For example, the following results will be displayed:

[0080] Prices for the products currently in use:

[0081] Cloud storage: 5000 yen / month

[0082] Project management tool: 3000 yen / month

[0083] Furthermore, the generative AI model is used to suggest prices for new products that users are considering introducing, allowing them to easily check pricing information for their company's products and select the most suitable products.

[0084] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0085] Step 1:

[0086] A user accesses the system's user interface using a terminal. The user opens a web browser and accesses the system's URL, which displays the user interface. The input is the user accessing the system's URL, and the output is the display of the user interface.

[0087] Step 2:

[0088] The user enters the size of the company, the purpose of use, and the price of the products that have already been introduced. The user enters the size of the company (e.g., small and medium-sized enterprise), the purpose of use (e.g., IT services), and the price of the products that have already been introduced (e.g., cloud storage: 5,000 yen / month, project management tool: 3,000 yen / month) into the input form on the displayed user interface. The input is the data that the user entered into the input form, and the output is the preparation of the input data for transmission.

[0089] Step 3:

[0090] The terminal sends the data entered by the user to the server. The terminal sends the data entered by the user to the server as an HTTP request. At this time, the data is sent in an appropriate format such as JSON. The input is the data entered by the user, and the output is the data sent to the server.

[0091] Step 4:

[0092] The server saves the received data in a database. The server analyzes the received data and saves it in a database management system (e.g. MySQL). When saving, it inserts the data into the appropriate table. The input is the data sent from the terminal, and the output is data saved in the database.

[0093] Step 5:

[0094] The server searches the database for product price information and filters it. The server searches for product price information stored in the database. The search results are filtered based on the company size and purpose of use entered by the user. For example, extract only price information for products related to IT services for small and medium-sized enterprises. The input is data stored in the database, and the output is filtered price information.

[0095] Step 6:

[0096] The server generates the price information of the filtered products in a list format. The server formats the price information of the filtered products in a list format. At this time, the data is generated in HTML or JSON format. The input is the filtered price information, and the output is the price information in a list format.

[0097] Step 7:

[0098] The server sends the generated price information to the terminal. The server sends the generated price information to the terminal as an HTTP response. The data is sent in a format that is easy for the user to understand. The input is price information in list format, and the output is data sent to the terminal.

[0099] Step 8:

[0100] The terminal displays the received price information on the user interface. The terminal displays the received price information on the user interface. The user can check the displayed list and understand the price information of their company's products at a glance. The input is the price information sent from the server, and the output is the display on the user interface.

[0101] (Application example 1)

[0102] Next, a description will be given of Application Example 1 of Embodiment 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."

[0103] With conventional systems, it was difficult for companies to easily check the pricing information of their own products, make price comparisons, and make price adjustments. Furthermore, there was a lack of means to compare prices with market price data and make appropriate price adjustments, making it impossible for companies to set prices in line with market trends. For this reason, effective price management is needed to maintain a company's competitive edge.

[0104] 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.

[0105] In this invention, the server includes means for inputting the size of the customer's company, the purpose of use, and the prices of already introduced products, means for displaying a list of prices of currently used products based on this information, means for proposing prices for products being considered for new introduction, means for comparing with market price data and proposing price adjustments, and means for displaying the price comparison results. This allows companies to easily check price information for their own products and make price comparisons and price adjustments.

[0106] "Company size" is an indicator that shows the size of a company, number of employees, sales, etc.

[0107] "Usage" refers to the use of a particular purpose or method of use.

[0108] "Merchandise" is a general term for the products and services that a company handles.

[0109] "Price list display" is a function that displays the prices of the currently used products in a list format based on the input information.

[0110] A "price proposal" is the act of presenting the price of a new product that is being considered for introduction.

[0111] "Market Price Data" refers to price information for a commodity in a particular market.

[0112] "Price adjustment proposal" is the act of proposing appropriate price changes by comparing with market price data.

[0113] "Price comparison results" show the results of comparing the price of the product currently being used with market price data.

[0114] "Generative AI" is a system that uses artificial intelligence technology to generate data and make analysis and suggestions.

[0115] A system for implementing this invention includes a server, a user terminal, and a generative AI model. The server receives information entered by the user about the company size, intended use, and pricing of products already introduced, and displays a list of prices for currently used products based on this information. The server then compares the prices with market price data, proposes price adjustments, and provides the results to the user.

[0116] The user terminal is a device such as a smartphone or tablet, and provides an interface for users to input information such as company size, usage, and product prices. The data entered by the user is sent to the server, which processes it and generates a price list.

[0117] The generative AI model runs on a server and proposes price adjustments based on data entered by the user and market price data. The generative AI model is implemented using software such as Python (registered trademark), Pandas, and Scikit-learn. Specifically, it compares the product price entered by the user with market price data and performs a regression analysis to propose appropriate price adjustments.

[0118] For example, consider the case where a user inputs the following data:

[0119] Company size: Small business

[0120] Usage: Manufacturing industry

[0121] Item Price: [1000, 2000, 3000]

[0122] Market price data: [1100, 2100, 3100]

[0123] The server receives this data and displays a list of prices for the currently used products. The generative AI model then compares it with market price data to propose price adjustments and provides the results to the user. This allows users to easily check the price information of their company's products, make price comparisons, and make price adjustments.

[0124] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0125] Step 1:

[0126] The user uses a terminal to input the company size, intended use, and the prices of the products already introduced.

[0127] Input: Company size, usage, product price.

[0128] Specific operation: The user enters the company size (e.g., small and medium-sized enterprise), purpose of use (e.g., manufacturing), and product price (e.g., 1,000 yen, 2,000 yen, 3,000 yen) through the interface of a smartphone or tablet.

[0129] Output: The input data is sent to the server.

[0130] Step 2:

[0131] The server processes the data received from the user and displays a list of the prices of the products currently being used.

[0132] Input: Company size, purpose of use, and product price entered by the user.

[0133] Specific operation: The server converts the received data into a data frame and generates a list of product prices.

[0134] Output: A list of product prices is generated and displayed on the user's device.

[0135] Step 3:

[0136] The server retrieves market price data and uses a generative AI model to suggest price adjustments.

[0137] Input: User-entered product price and market price data.

[0138] Specific operation: The server obtains market price data (e.g., 1,100 yen, 2,100 yen, 3,100 yen) and performs regression analysis using a generative AI model (using Python, Pandas, and Scikit-learn).

[0139] Output: A price adjustment proposal is generated.

[0140] Step 4:

[0141] The server transmits the price adjustment proposal results to the user terminal and displays them to the user.

[0142] Input: The proposed price adjustment result.

[0143] Specific operation: The server sends the generated price adjustment proposal results to the user terminal, and the user confirms them on the interface.

[0144] Output: The proposed price adjustment is displayed on the user's terminal.

[0145] Step 5:

[0146] The user adjusts the price of the product based on the price adjustment proposal results.

[0147] Input: The proposed price adjustment result.

[0148] Specific operation: The user adjusts the price of their company's products based on the proposed price adjustment results.

[0149] Output: The adjusted price of the product.

[0150] Example 2

[0151] Next, a description will be given of Example 2 of Form 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."

[0152] Conventional product price proposal systems have difficulty in calculating the appropriate price of new products based on the price information of existing products. Furthermore, they lack a means to effectively utilize the information entered by users to make highly accurate price proposals. This means that companies need time and effort to set prices for new products, potentially resulting in a loss of competitiveness.

[0153] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0154] In this invention, the server includes means for inputting the customer's company size, intended use, and prices of already introduced products, means for displaying a list of prices of currently used products based on this information, means for inputting information on products being considered for new introduction, means for preprocessing price information on existing products and information on products being considered for new introduction, means for inputting the preprocessed data into a generative AI model to calculate an appropriate price, and means for proposing price information obtained from the generative AI model. This enables users to set prices for new products efficiently and accurately.

[0155] "Customer's company size" is information indicating the size of the company, such as the number of employees, sales, and capital.

[0156] "Usage" is information indicating the purpose and situation in which the product will be used.

[0157] "Prices of already introduced products" refers to price information of products currently being used by the company.

[0158] "Information on new products being considered for introduction" refers to information such as the type, features, and target market of the products that a company is considering purchasing.

[0159] "Preprocessing" refers to the processing of data before inputting it into a generative AI model, such as data cleaning, normalization, and feature extraction.

[0160] A "generative AI model" is a model that uses artificial intelligence technology to analyze data and calculate appropriate prices.

[0161] A "price proposal" is the act of presenting price information obtained from a generative AI model to a user.

[0162] "In-house tools" refers to software and systems for internal use by a company.

[0163] This invention relates to a system for proposing prices for commercial products. Specifically, it is a system that uses a generative AI model to calculate an appropriate price for a commercial product that is being considered for new purchase and proposes it to the user.

[0164] System configuration

[0165] This system consists of three main components: a server, a terminal, and a user.

[0166] server

[0167] The server has the following functions:

[0168] 1. Data Collection:

[0169] The server retrieves pricing information for existing products from a database that includes information such as past product prices, sales history, and demand forecasts.

[0170] 2. Data Preprocessing:

[0171] The server preprocesses the acquired price information of existing products and the information entered by the user, specifically by cleaning the data, normalizing it, and extracting features.

[0172] 3. Price Calculation:

[0173] The server inputs the preprocessed data into a generative AI model, such as OpenAI's GPT-4.

[0174] The server inputs the following prompt to the generative AI model:

[0175] "The information about the new product we are considering introducing is as follows: Type: Electronic device, Features: High-performance battery, Target market: Young people. Please propose an appropriate price for this product based on the pricing information of existing products."

[0176] The generative AI model calculates the appropriate price for a new product based on the input information.

[0177] 4. Price Proposal:

[0178] The server proposes price information obtained from the generative AI model to the user.

[0179] Terminal

[0180] The terminal is a device where the user enters information and sees the proposed price. The terminal has the following functions:

[0181] 1. Enter your information:

[0182] The user uses a terminal to input information about the new product they are considering introducing, such as the product type, features, and target market.

[0183] 2. Price Check:

[0184] The user can check the price proposed by the server through the terminal.

[0185] User

[0186] The user is responsible for operating the system and setting the prices of the products. The user performs the following operations:

[0187] 1. Enter your information:

[0188] The user uses the terminal to input information about a new product they are considering introducing. For example, they input information about a "smartphone with a high-performance battery."

[0189] 2. Price Check:

[0190] The user can check the price proposed by the server and make corrections or reevaluations as necessary.

[0191] Specific examples

[0192] For example, if a user is looking to purchase a new smartphone with a high-performance battery, they can input the following prompt into the generative AI model:

[0193] "The information about a new product we are considering introducing is as follows: Type: Smartphone, Features: High-performance battery, Target market: Young people. Please propose an appropriate price for this product based on the pricing information of existing products."

[0194] The generative AI model calculates the appropriate price for a new smartphone based on past price information and information entered by the user. The server then proposes this price information to the user, who can then check the price via their device.

[0195] In this way, users can set prices for new products efficiently and accurately.

[0196] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0197] Step 1: Data collection

[0198] The server retrieves price information for existing products from the database.

[0199] Input: Database connection information, query

[0200] Data processing: Extract information such as past product prices, sales history, and demand forecasts from the database.

[0201] Output: A list of retrieved price information

[0202] Step 2: Enter user information

[0203] The user inputs information about the new product they are considering introducing into the terminal.

[0204] Input: Information on product type, features, target market, etc.

[0205] Data processing: Sending the entered information to the system.

[0206] Output: Product information entered by the user

[0207] Step 3: Data Preprocessing

[0208] The server preprocesses the acquired price information of existing products and the information input by the user.

[0209] Input: Price information of existing products, product information entered by the user

[0210] Data processing: Data cleaning, normalization, and feature extraction, such as imputing missing values ​​and correcting outliers.

[0211] Output: Preprocessed dataset

[0212] Step 4: Price calculation

[0213] The server inputs the preprocessed data into a generative AI model.

[0214] Input: Preprocessed dataset

[0215] Data calculation: Enter a prompt into the generative AI model to calculate an appropriate price.

[0216] Example prompt sentence:

[0217] "The information about a new product we are considering introducing is as follows: Type: Smartphone, Features: High-performance battery, Target market: Young people. Please propose an appropriate price for this product based on the pricing information of existing products."

[0218] Output: Price information obtained from the generative AI model

[0219] Step 5: Price Proposal

[0220] The server proposes price information obtained from the generative AI model to the user.

[0221] Input: Price information obtained from a generative AI model

[0222] Data processing: Convert the proposal into a format that is easy for users to understand.

[0223] Output: Proposed pricing information

[0224] Step 6: Price confirmation

[0225] The user confirms the proposed price through the terminal.

[0226] Input: Proposed pricing information

[0227] Data processing: Display suggested pricing information.

[0228] Output: Price information confirmed by the user

[0229] In this way, users can set prices for new products efficiently and accurately.

[0230] (Application example 2)

[0231] Next, a description will be given of Application Example 2 of Form 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."

[0232] Conventional product price proposal systems have difficulty in proposing appropriate prices for new products based on information such as the price information of existing products, company size, and intended use. Furthermore, the accuracy of price proposals is low, making it impossible to calculate the optimal price for the user. Furthermore, the price proposal process is often done manually, which is time-consuming and labor-intensive.

[0233] The specification processing by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for inputting the customer's company size, intended use, and prices of already introduced products, means for displaying a list of prices of currently used products based on this information, means for proposing prices of products being considered for new introduction, and means for calculating an appropriate price for a new product using a generative AI model and proposing it to the user. This enables the user to quickly and accurately receive an optimal price proposal using the generative AI model based on price information of existing products and the characteristics of the new product.

[0234] "Customer's corporate size" is information that indicates the size and economic scale of a company, such as the number of employees and sales.

[0235] "Usage" is information indicating the purpose and situation in which the product will be used.

[0236] "Prices of already introduced products" refers to price information of products currently being used by the company.

[0237] "Input means" refers to a method or device that allows a user to input the required information into the system.

[0238] The "means for displaying a list of prices of currently used products" refers to a method or device for displaying price information of existing products in a list format.

[0239] The "means for proposing the price of a new product being considered for introduction" refers to a method or device for proposing the price of a new product to users.

[0240] A "generative AI model" is an algorithm or model that uses artificial intelligence to generate data and perform specific tasks.

[0241] "Means for calculating the appropriate price of a new product and proposing it to users" refers to a method or device for calculating the optimal price of a new product using a generative AI model and presenting that price to users.

[0242] A system for carrying out this invention has the following configuration: The server includes means for inputting the size of the customer's company, intended use, and prices of merchandise already introduced, means for displaying a list of prices of merchandise currently being used based on this information, means for proposing prices for merchandise being considered for new introduction, and means for calculating appropriate prices for new merchandise using a generative AI model and proposing the prices to the user.

[0243] Hardware and software used

[0244] Hardware: Smartphones, servers

[0245] Software: Python, OpenAI API, Pandas

[0246] Data processing and calculation

[0247] 1. Data loading: The server loads the price information of existing products from the CSV file. This retrieves the price information of existing products as a data frame.

[0248] 2. User input: The user inputs the name and characteristics of the new product using a smartphone. This information is sent to the server.

[0249] 3. Use of generative AI model: The server uses OpenAI's API to generate an appropriate price for the new product based on the price information of existing products and user-entered information. Specifically, it sends a prompt to the generative AI model, and the AI ​​calculates the price.

[0250] 4. Price Proposal: The generated price is sent from the server to the user's smartphone and displayed to the user.

[0251] Specific examples

[0252] For example, suppose the price information for existing products is stored in a CSV file as shown below.

[0253] Product A, 1000

[0254] Product B, 1500

[0255] Product C, 2000

[0256] If a user enters "Product D" as the name of a new product and "Made of high-quality materials and highly durable" as its features, the server will send the following prompt to the generative AI model.

[0257] Prompt Sentence Examples

[0258] Existing product pricing information: {'Product A': 1000, 'Product B': 1500, 'Product C': 2000}

[0259] New product name: Product D

[0260] Features of the new product: Made from high-quality materials and highly durable

[0261] Please suggest a reasonable price for this new product.

[0262] The generative AI model calculates the appropriate price for the new product based on this prompt and returns the result to the server. The server then sends the result to the user's smartphone and displays it to the user. This allows the user to quickly and accurately find out the appropriate price for the new product.

[0263] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0264] Step 1:

[0265] The server reads the price information of existing products from a CSV file. Specifically, it uses the Pandas library to read the CSV file as a data frame. The input is a CSV file, and the output is the price information of existing products in data frame format.

[0266] Step 2:

[0267] The user uses a smartphone to input the name and characteristics of a new product. The input is the name and characteristics of the new product, and the output is sending this information to the server. Specifically, the user enters the information about the new product into the input form on the smartphone and presses the send button.

[0268] Step 3:

[0269] The server receives the name and characteristics of the new product sent by the user and combines them with the price information of the existing product to generate a prompt. The input is the name and characteristics of the new product and the price information of the existing product, and the output is the generated prompt. Specifically, the prompt is constructed using string manipulation.

[0270] Step 4:

[0271] The server sends the generated prompt text to OpenAI's API and uses the generative AI model to calculate the appropriate price for the new product. The input is the prompt text, and the output is the price information for the new product returned by the generative AI model. Specifically, the server sends the prompt text to the API using an HTTP request and receives a response.

[0272] Step 5:

[0273] The server receives the price information for new products returned from the generative AI model and sends it to the user's smartphone. The input is the price information from the generative AI model, and the output is the price information displayed on the user's smartphone. Specifically, it performs communication processing to send the price information to the user's smartphone.

[0274] Step 6:

[0275] The user checks the price information of a new product displayed on the smartphone. The input is the price information sent from the server, and the output is the price information checked by the user. Specifically, the user views the price information displayed on the smartphone screen.

[0276] Example 3

[0277] Next, a description will be given of a third embodiment of the third embodiment. 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."

[0278] Determining the appropriate price for a new product a company is considering introducing is extremely important for maintaining the company's competitiveness. However, determining an appropriate price by taking into account the product's features, manufacturing costs, and competitor pricing information is a time-consuming and labor-intensive task. Furthermore, the pricing process is prone to subjective judgment, making it difficult to find the optimal price.

[0279] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[0280] In this invention, the server includes a means for a user to input product information, a means for the server to save the input information in a database, a means for the server to send a prompt to the generative AI model, a means for the generative AI model to propose an appropriate price, a means for the server to provide the proposed price to the user, a means for the user to determine a final price, and a means for the server to save the determined price in a database. This enables companies to efficiently and objectively determine an appropriate price for a new product they are considering introducing.

[0281] "Customer's company size" is information indicating the size of the company, such as the number of employees, sales, and capital.

[0282] "Usage" is information that indicates the purpose for which a company will use a product.

[0283] "Already implemented products" refer to products that a company has already purchased and is using.

[0284] "Price input means" refers to the interface or method by which a user inputs product pricing information into the system.

[0285] "Means for displaying prices in a list" refers to an interface or method for displaying entered price information in a list format.

[0286] "Means for suggesting a price" refers to the method or algorithm by which the system calculates an appropriate price and suggests it to the user.

[0287] "Means for users to input product information" refers to the interface or method by which users input product features, costs, competitor pricing information, etc. into the system.

[0288] "Means for the server to save the input information in a database" refers to the method or technology by which the server saves the information input by the user in a database.

[0289] "Means by which the server sends prompt sentences to the generative AI model" refers to the methods and technologies by which the server generates and sends appropriate prompt sentences to the generative AI model.

[0290] "Means by which the generative AI model suggests an appropriate price" refers to the methods and algorithms by which the generative AI model calculates and suggests an appropriate price based on the input prompt.

[0291] "Means by which the server provides the suggested price to the user" refers to the interface or method by which the server displays the suggested price from the generative AI model to the user.

[0292] "Means for users to determine final prices" refers to an interface or method by which a user determines a final price based on the proposed prices and inputs it into the system.

[0293] "Means for the server to store the determined price in a database" refers to a method or technology for the server to store the final price determined by the user in a database.

[0294] "Business-to-business transactions" refer to transactions in which companies buy and sell products or services.

[0295] "Tools for internal use" refers to software and systems for use within a company.

[0296] This invention is a system for determining the appropriate price of a new product that a company is considering introducing. In this system, the user inputs product information, and the server uses a generative AI model based on that information to propose an appropriate price.

[0297] First, a user uses a company's device to input product features (e.g., screen size, battery capacity, camera performance, etc.), manufacturing costs, competitor pricing information, etc. This information is entered through the device's interface.

[0298] The server then receives the information entered by the user and stores it in a database. This database is managed using a database management system such as MySQL. The stored data is divided into fields such as product ID, features, cost, and competitive price.

[0299] The server generates a prompt based on the product information stored in the database. The generated prompt is sent to a generative AI model (e.g., OpenAI's GPT-4). Examples of prompts include:

[0300] Product: Smartphone

[0301] Features: 6.5-inch display, 5000mAh battery, 48MP camera

[0302] Manufacturing cost: $200

[0303] Competitor's Price: $300

[0304] Please suggest a reasonable price.

[0305] The generative AI model analyzes the prompt sent from the server and proposes an appropriate price for the product. This proposed price is calculated based on the generative AI model's algorithm.

[0306] The server receives the proposed price from the generative AI model and provides it to the user, who can then view the proposed price through their device.

[0307] The user decides on the final price based on the price proposal provided by the server. The decided price is sent back to the server and saved in the database. This saved price information can be used for future analysis and reference.

[0308] This system enables a company to efficiently and objectively determine an appropriate price for a new product that the company is considering introducing. The flow of the specification process in the third embodiment will be described with reference to FIG.

[0309] Step 1:

[0310] The user enters product information.

[0311] Users use a company's terminal to input product features (e.g., screen size, battery capacity, camera performance, etc.), manufacturing costs, and competitor pricing information. The input information is sent to the server through the terminal's interface. Input data includes product name, features, costs, and competitor pricing.

[0312] Step 2:

[0313] The server stores the entered information in a database.

[0314] The server receives the product information sent by the user and stores it in a database. The database is managed using a database management system such as MySQL. The stored data includes fields such as product ID, features, cost, and competitive price. The input data is appropriately mapped to each field in the database.

[0315] Step 3:

[0316] The server sends a prompt to the generative AI model.

[0317] The server generates a prompt based on the product information stored in the database. The generated prompt is sent to a generative AI model (e.g., OpenAI's GPT-4). Examples of prompts include:

[0318] Product: Smartphone

[0319] Features: 6.5-inch display, 5000mAh battery, 48MP camera

[0320] Manufacturing cost: $200

[0321] Competitor's Price: $300

[0322] Please suggest a reasonable price.

[0323] The input data is product information obtained from the database, and the output data is the generated prompt sentence.

[0324] Step 4:

[0325] A generative AI model suggests the right price.

[0326] The generative AI model analyzes the prompt sent from the server and proposes an appropriate price for the product. This proposed price is calculated based on the generative AI model's algorithm. The input data is the prompt, and the output data is the proposed price.

[0327] Step 5:

[0328] The server provides the suggested price to the user.

[0329] The server receives the proposed price from the generative AI model and displays it on the user's device. The user can check the proposed price on the device screen. The input data is the proposed price, and the output data is the price information displayed to the user.

[0330] Step 6:

[0331] The user decides the final price.

[0332] The user decides on the final price based on the price proposal provided by the server. The decided price is sent to the server via the terminal. The input data is the proposed price, and the output data is the final decided price.

[0333] Step 7:

[0334] The server stores the determined price in a database.

[0335] The server receives the final price sent by the user and stores it in a database. The stored price information is used for future analysis and reference. The input data is the final determined price, and the output data is the price information stored in the database.

[0336] (Application example 3)

[0337] Next, a description will be given of Application Example 3 of Form Example 3. 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."

[0338] Determining the appropriate price for a new product a company is considering introducing is an important issue in its business strategy. However, traditional methods require a great deal of time and effort to collect and analyze the information necessary for pricing decisions. It is also difficult to evaluate the appropriateness of a price by comparing it with past price data. This can prevent companies from quickly determining an appropriate price, potentially resulting in a loss of competitiveness.

[0339] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 3 is realized by the following means.

[0340] In this invention, the server includes means for inputting the size of the customer's company, intended use, and prices of already introduced products, means for displaying a list of prices of currently used products based on this information, means for proposing prices for products being considered for new introduction, means for proposing an appropriate price using a generative AI model, means for determining prices based on the proposed prices, and means for evaluating the appropriateness of the prices by comparing with past price data. This enables companies to quickly and appropriately determine prices for products being considered for new introduction.

[0341] "Company size" is an indicator that shows the size of a company, such as the number of employees, sales, and capital.

[0342] "Usage" refers to the purpose and situation in which a particular product or service is used.

[0343] "Merchandise" refers to goods or products that a company handles for sale or use.

[0344] "Price" refers to the monetary value assigned to a product or service.

[0345] A "generative AI model" is an algorithm or system that uses artificial intelligence technology to generate new information or suggestions from data.

[0346] A "prompt" is a sentence of instructions or questions that is input to a generative AI model.

[0347] A "price proposal" is the act and result of presenting an appropriate price for a particular product.

[0348] "Pricing" refers to the process of determining the final price based on the proposed price.

[0349] "Price reasonableness" is a criterion for evaluating whether the proposed price is appropriate compared to market and historical data.

[0350] "BtoB" refers to business-to-business transactions, a business model in which companies provide products and services to other companies.

[0351] The system for carrying out the present invention is for appropriately determining the price of a new product that a company is considering introducing. A specific embodiment of this system is described below.

[0352] System Configuration

[0353] The system consists of the following main components:

[0354] 1. Input method: Provides an interface for users to input information such as company size, usage, and prices of products already in use. This can be done using devices such as smartphones or PCs.

[0355] 2. Display method: Based on the information entered, the prices of the products currently being used are displayed in a list. This is also displayed on the screen of a smartphone or computer.

[0356] 3. Proposal method: Propose a price for a new product being considered for introduction. This proposal is made using a generative AI model.

[0357] 4. Pricing method: The final price is determined based on the proposed price.

[0358] 5. Evaluation measures: Evaluate the reasonableness of the proposed price by comparing it with historical price data.

[0359] Program processing

[0360] The server performs the following process.

[0361] 1. Data entry: The user enters the company size, usage, and prices of products already in use. This data is sent to the server via the interface of a smartphone or PC.

[0362] 2. Data display: The server displays a list of prices for the currently used products based on the entered information.

[0363] 3. Price Proposal: The server proposes a price for the new product being considered for introduction using the generative AI model. The generative AI model is implemented using OpenAI's API.

[0364] 4. Price determination: The user determines the final price based on the proposed prices.

[0365] 5. Price Evaluation: The server evaluates the reasonableness of the proposed price by comparing it with historical pricing data.

[0366] Hardware and software used

[0367] Hardware: smartphones, PCs, servers

[0368] Software: Python, OpenAI API

[0369] Specific examples

[0370] For example, if a user inputs "high-performance battery" as a new product they are considering introducing, the following prompt sentence will be sent to the generative AI model.

[0371] Prompt Sentence Examples

[0372] Information on the new product: Product name: High-performance battery, Specifications: 5000mAh, Price range: 3000 yen to 5000 yen

[0373] Please suggest a reasonable price.

[0374] The generative AI model will then suggest an appropriate price based on this prompt and display the results to the user, who can then decide on a final price based on the suggested price and evaluate its appropriateness by comparing it with past price data.

[0375] In this way, companies can quickly and appropriately determine the prices of new products they are considering introducing.

[0376] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[0377] Step 1:

[0378] The user enters the company size, intended use, and the price of the products already introduced.

[0379] Input: Company size, usage, price of already introduced products

[0380] Specific operation: Through the interface of a smartphone or PC, the user inputs the company size (e.g., number of employees, sales), usage (e.g., manufacturing, sales), and price of already introduced products (e.g., price of product A). This data is sent from the device to the server.

[0381] Step 2:

[0382] The server displays a list of prices for the currently used products based on the information entered.

[0383] Input: Company size, usage, price of already introduced products

[0384] Output: Price list of currently used products

[0385] Specific operation: The server processes the received data and displays the prices of the currently used products in a list format. The displayed price list is sent to the user's device and displayed on the screen.

[0386] Step 3:

[0387] The server generates a prompt message to suggest the price of the new product that is being considered for introduction.

[0388] Input: Information about the new product you are considering introducing (e.g. product name, specifications, price range)

[0389] Output: prompt statement

[0390] Specific operation: When a user enters information about a new product they are considering introducing, the server uses that information to generate a prompt to send to the generative AI model. For example, it generates a prompt like this: "Information about the new product: Product name: High-performance battery, Specifications: 5000mAh, Price range: 3000 to 5000 yen. Please suggest an appropriate price."

[0391] Step 4:

[0392] The server uses a generative AI model to suggest an appropriate price.

[0393] Input: prompt statement

[0394] Output: Proposed price

[0395] Specific operation: The server sends the generated prompt to OpenAI's API and receives an appropriate price suggestion from the generative AI model. For example, the generative AI model suggests a price of "4,500 yen."

[0396] Step 5:

[0397] The server will determine the final price based on the proposed price.

[0398] Input: Proposed Price

[0399] Output: Final price

[0400] How it works: The user checks the price suggested by the generative AI model and decides on the final price based on that price. The decided price is sent to the server and recorded.

[0401] Step 6:

[0402] The server evaluates the reasonableness of the proposed price by comparing it with historical pricing data.

[0403] Inputs: Proposed price, historical price data

[0404] Output: Price justification evaluation result

[0405] How it works: The server compares the proposed price with past price data to evaluate its validity. The evaluation result is sent to the user's device and displayed on the screen.

[0406] In this way, companies can quickly and appropriately determine the prices of new products they are considering introducing.

[0407] 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.

[0408] "Example 1"

[0409] As one embodiment of the present invention, a system incorporating an emotion engine is provided. This system inputs the user's company size, intended use, and prices of already implemented products, and based on this information, displays a list of prices for currently used products. It also proposes prices for products that are being considered for new implementation. As a proposal method, it uses a generation AI to propose product prices. This system is a tool for in-company use in B2B.

[0410] "Example 2"

[0411] The emotion engine recognizes the user's emotions and adjusts the price of the product based on those emotions. For example, if the user is feeling stressed, the emotion engine will collect that information and reduce the price of the product to reduce the user's stress.

[0412] "Example 3"

[0413] The emotion engine also optimizes product pricing based on user emotions. For example, if a user is feeling happy, the emotion engine will collect that information and increase the product price to maximize profits.

[0414] The processing flow of each embodiment will be described below.

[0415] "Example 1"

[0416] Step 1: The user enters the company size, intended use, and prices of products already implemented into the system.

[0417] Step 2: The system will display a list of prices for the products you are currently using based on the information you entered.

[0418] Step 3: The system uses AI to suggest prices for new products that are being considered for introduction.

[0419] "Example 2"

[0420] Step 1: The emotion engine recognizes the user's emotion.

[0421] Step 2: The emotion engine adjusts the price of the product based on the emotion it recognizes.

[0422] Step 3: For example, if the user is feeling stressed, the emotion engine will collect that information and reduce the user's stress by lowering the price of the product.

[0423] "Example 3"

[0424] Step 1: The emotion engine recognizes the user's emotion.

[0425] Step 2: The emotion engine optimizes the price suggestions for the product based on the emotions it recognizes.

[0426] Step 3: For example, if the user is feeling happy, the emotion engine will collect that information and maximize profits by increasing the price of the product.

[0427] Example 1

[0428] Next, a description will be given of Example 1 of Form 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."

[0429] With conventional systems, it is difficult for companies to check the pricing information of their own products at a glance, and there is a lack of means to propose appropriate prices for products that they are considering introducing. In addition, in business-to-business transactions, the optimal price proposal based on the size of the company or the purpose of use is not made, making it difficult to efficiently select products.

[0430] 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.

[0431] In this invention, the server includes means for inputting the customer's company size, intended use, and prices of already introduced products, means for displaying a list of prices of currently used products based on this information, means for proposing prices for products being considered for new introduction, means for displaying the generated price information to the user, and means for generating prices for products being considered for new introduction using a generative AI model. This allows companies to check price information for their own products at a glance and receive optimal price proposals based on their company size and intended use.

[0432] "Company size" is an indicator that shows the size of a company, such as the number of employees and sales.

[0433] "Usage" is information indicating the purpose for which a company will use the product.

[0434] "Merchandise" refers to products or services that a company purchases or uses.

[0435] "Price" refers to the monetary value paid for a commodity.

[0436] "Input means" refers to an interface through which a user provides information to a system.

[0437] "Display means" refers to an interface that allows the system to visually present information to the user.

[0438] "Proposal means" refers to a function that allows the system to present the price of a new product to the user.

[0439] A "generative AI model" refers to an algorithm or system that uses artificial intelligence to analyze data and generate new information.

[0440] A "prompt" is text data that is input to a generative AI model and contains instructions for the model to generate output.

[0441] "Business-to-business transactions" refer to commercial transactions conducted between businesses.

[0442] This invention is a system that allows a company to check price information of its own products at a glance and proposes appropriate prices for products that the company is considering introducing. A specific embodiment of this system will be described below.

[0443] The user accesses the system using a device (PC, tablet, smartphone, etc.). The user opens the device's browser and accesses the system's web application. The user enters information into a form that asks for the company size (e.g., small and medium-sized enterprise), purpose of use (e.g., manufacturing), and price of the product already introduced (e.g., 1 million yen), and clicks the "Submit" button.

[0444] The terminal sends the entered information to the server as an HTTP request. Specifically, it sends data using a POST request. The request body includes the company size, purpose of use, and price of existing products.

[0445] The server analyzes the received information and executes an INSERT query to store the information in a database, which stores information such as the company size, usage, and prices of existing products.

[0446] Next, the server queries and obtains the price of the currently used product based on the information stored in the database.The server executes a SELECT query to obtain the price information of the currently used product from the database.

[0447] The server converts the acquired price information into JSON format and sends it to the terminal as an HTTP response. The terminal parses the received JSON data and displays the price information in a list on the user interface. The user can then check the price information on their browser.

[0448] Furthermore, the server uses the generative AI model to generate a price for a new product that is being considered for introduction. A prompt statement is generated for the generative AI model and input into the model. The prompt statement includes information about the company size, intended use, and pricing information for existing products. The generative AI model generates a price for the new product based on the input information.

[0449] The server converts the price information output by the generative AI model into JSON format and sends it to the terminal as an HTTP response. The terminal analyzes the received JSON data and displays the generated price information on the user interface. The user can then check the price of the new product they are considering introducing.

[0450] As a specific example, consider the case where a small or medium-sized enterprise wants to know the price of a new product it is considering introducing. The user enters the company size as "Small or Medium-sized Enterprise," the use as "Manufacturing," and the price of the product already introduced as "1 million yen." Based on this information, the system displays a list of prices for the products currently being used and uses a generative AI model to suggest a price for the new product being considered for introduction.

[0451] Example prompt sentence:

[0452] Company size: Small business

[0453] Usage: Manufacturing industry

[0454] Price of already introduced products: 1 million yen

[0455] By inputting this prompt into the generative AI model, the system will suggest a price for the new product being considered for introduction.

[0456] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0457] Step 1:

[0458] The user opens a browser on their device and accesses the system's web application. They enter information into a form to input the company size, intended use, and price of the product they have already introduced, and click the "Submit" button. The input data is the company size (e.g., small and medium-sized enterprise), intended use (e.g., manufacturing), and price of the existing product (e.g., 1 million yen).

[0459] Step 2:

[0460] The terminal sends the entered information to the server as an HTTP request. Specifically, the data is sent using a POST request. The body of the request includes the company size, intended use, and price of existing products. The input data is the information the user entered into the form, and the output data is the request sent to the server.

[0461] Step 3:

[0462] The server analyzes the received information and executes an INSERT query to save the information in a database. The database stores information such as company size, usage, and prices of existing products. The input data is the information sent from the terminal, and the output data is the information saved in the database.

[0463] Step 4:

[0464] The server queries and retrieves the price of the currently used product based on the information stored in the database. The server executes a SELECT query to retrieve the price information of the currently used product from the database. The input data is the information stored in the database, and the output data is the retrieved price information.

[0465] Step 5:

[0466] The server converts the acquired price information into JSON format and sends it to the terminal as an HTTP response. The input data is the acquired price information, and the output data is a JSON format response.

[0467] Step 6:

[0468] The terminal parses the received JSON data and displays a list of price information in the user interface. The user can check the price information in the browser. The input data is the JSON data received from the server, and the output data is the price information displayed in the user interface.

[0469] Step 7:

[0470] The server uses a generative AI model to generate prices for new products that are being considered for introduction. It generates a prompt statement for the generative AI model and inputs it into the model. The prompt statement includes information about the company size, intended use, and pricing information for existing products. The input data is the prompt statement, and the output data is the generated price information.

[0471] Step 8:

[0472] The server converts the price information output by the generative AI model into JSON format and sends it to the terminal as an HTTP response. The input data is the generated price information, and the output data is a JSON-formatted response.

[0473] Step 9:

[0474] The terminal analyzes the received JSON data and displays the generated price information in the user interface. The user can check the price of the new product they are considering introducing. The input data is the JSON data received from the server, and the output data is the generated price information displayed in the user interface.

[0475] (Application example 1)

[0476] Next, a description will be given of Application Example 1 of Embodiment 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."

[0477] Conventional product price proposal systems have had issues with making appropriate price proposals based on the size of the company and the purpose of use, and not being able to reflect user feedback. Furthermore, there was a lack of a way to check the price information of currently used products at a glance, making efficient price management difficult.

[0478] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. In this invention, the server includes a means for inputting the customer's company size, intended use, and prices of already-used products; a means for displaying a list of prices of currently-used products based on this information; a means for proposing prices for products being considered for new introduction; an emotion engine for analyzing user feedback; and a means for proposing product prices using a generative AI model. This enables appropriate price proposals based on company size and intended use, and also allows price proposals that reflect user feedback. Furthermore, price information for currently-used products can be checked at a glance, enabling efficient price management.

[0479] "Company size" is an indicator that shows the size of a company, such as the number of employees and sales.

[0480] "Use" refers to the method or purpose of using the product for a specific purpose or function.

[0481] "Merchandise" refers to the goods and services that a company sells or uses.

[0482] "Price" means the monetary value paid for the purchase or use of a commodity.

[0483] "Input means" refers to the method or device by which a user provides information to a system.

[0484] "Display means" refers to the method or device by which a system visually presents information to a user.

[0485] "Proposal means" refers to a method or device by which the system presents the user with prices and options for new products.

[0486] An "emotion engine" refers to software or hardware that analyzes user feedback and emotions and adjusts system behavior accordingly.

[0487] A "generative AI model" refers to an algorithm or system that uses artificial intelligence to generate new information or suggestions from data.

[0488] "BtoB" refers to business-to-business transactions, a business model in which companies provide products and services to other companies.

[0489] "Tools for internal use" refers to software and hardware tools used within a company.

[0490] A system for carrying out this invention is configured as follows: The server includes means for inputting the size of the customer's company, intended use, and prices of merchandise already introduced, means for displaying a list of prices of merchandise currently being used based on this information, means for proposing prices for merchandise being considered for new introduction, an emotion engine for analyzing user feedback, and means for proposing merchandise prices using a generative AI model.

[0491] Using a smartphone or PC, users input information such as company size, intended use, current product prices, and user feedback. This information is sent to the server, which receives it. Based on the information received, the server displays a list of the prices of the products currently being used. This information is displayed using a web browser or a dedicated application.

[0492] Next, the server uses an emotion engine to analyze the user's feedback. The emotion engine analyzes the user's feedback and detects positive or negative emotions. For example, the feedback "I'm satisfied with the price" is analyzed as a positive emotion.

[0493] The server then uses a generative AI model to propose a price for the new product. The generative AI model inputs information about the company's size, intended use, and current product price as prompts to generate an appropriate price proposal. Specific examples of prompts include the following:

[0494] Example prompt sentence:

[0495] Company size: Small to medium-sized enterprise, Usage: Online sales, Current prices: Product A: 1,000 yen, Product B: 2,000 yen. Based on this, please propose a price for the new product you are considering introducing.

[0496] The generated price proposal is displayed to the user, allowing them to receive an appropriate price proposal based on their company size and usage. Price proposals can also be made that reflect user feedback, resulting in proposals that are more satisfying.

[0497] The hardware used includes smartphones and PCs, and the software uses Python, a GUI toolkit, and the OpenAI API. Data processing involves converting user input data into prompt statements, and data calculation involves using OpenAI's generative AI model to make price suggestions and an emotion engine to analyze feedback.

[0498] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0499] Step 1:

[0500] Users use their smartphones or PCs to input information such as company size, intended use, current product price, and user feedback. The input information is then sent to the server. Input data includes company size (e.g., small and medium-sized enterprises), intended use (e.g., online sales), current product price (e.g., product A: 1,000 yen, product B: 2,000 yen), and user feedback (e.g., "I'm satisfied with the price").

[0501] Step 2:

[0502] The server displays a list of the prices of the products currently being used based on the information received. Data processing involves formatting the input product price information and displaying it in a visually easy-to-understand format for the user. The output is a list of the current product prices (e.g., product A: 1,000 yen, product B: 2,000 yen). A web browser or dedicated application is used to display the information.

[0503] Step 3:

[0504] The server uses an emotion engine to analyze user feedback. Input data includes user feedback (e.g., "I'm satisfied with the price"). The emotion engine analyzes the feedback and detects positive or negative emotions. Data processing involves text analysis of the feedback, and the output is an emotion analysis result (e.g., positive).

[0505] Step 4:

[0506] The server uses a generative AI model to propose a price for a new product. Input data includes company size, usage, and current product price information. A prompt is generated based on this information and input into the generative AI model. An example of a specific prompt is, "Please suggest a price for the new product we are considering introducing, based on the following: company size: small and medium-sized enterprise, usage: online sales, current prices: product A: 1,000 yen, product B: 2,000 yen." The generative AI model performs data calculations by analyzing the prompt and generating an appropriate price proposal. The output is a price proposal for the new product (e.g., product C: 1,500 yen).

[0507] Step 5:

[0508] The server displays the generated price proposal to the user. This can be done using a web browser or a dedicated application. The output is a price proposal in a format that the user can check (e.g., Product C: 1,500 yen). This allows the user to receive an appropriate price proposal based on the size of their company and the purpose of use.

[0509] Example 2

[0510] Next, a description will be given of Example 2 of Form 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."

[0511] Conventional product price proposal systems did not adjust prices based on user sentiment, which prevented them from fully increasing user satisfaction. Furthermore, they lacked a means to appropriately calculate the price of new products based on the price information of existing products. This sometimes caused stress for users, delaying the decision to introduce new products.

[0512] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0513] In this invention, the server includes: a means for inputting the user's company size, intended use, and prices of already-introduced products; a means for displaying a list of prices of currently-introduced products based on this information; a means for proposing prices for products being considered for new introduction; a means for recognizing the user's emotions and adjusting product prices based on those emotions; and a means for calculating product prices using a generative AI model. This allows for price proposals that take the user's emotions into consideration, thereby increasing user satisfaction. Furthermore, the system can appropriately calculate the price of new products based on price information for existing products, allowing for a rapid decision-making process for introducing new products.

[0514] "Company size" is an indicator that shows the size of a company, such as the number of employees, sales, and capital.

[0515] "Usage" is information indicating the purpose and situation in which the product will be used.

[0516] "Merchandise" refers to products or services that a company sells or uses.

[0517] "Means for inputting prices" refers to the interface or method for users to input price information for products they have already introduced into the system.

[0518] "Means for displaying prices in a list" refers to an interface or method for displaying the price information of the entered merchandise to the user in a list format.

[0519] "Means for proposing prices" refers to a method or system for proposing to users an appropriate price for a new product that is being considered for introduction.

[0520] "Emotion recognition means" refers to methods and techniques for detecting a user's emotional state and adjusting the system's behavior accordingly.

[0521] A "generative AI model" refers to a model that uses artificial intelligence techniques to analyze data and perform specific tasks.

[0522] "Means for calculating price" refers to a method or system for calculating the appropriate price of a product based on collected data.

[0523] This invention relates to a price proposal system for commercial products, and in particular to a system that proposes optimal prices to users using generative AI models and emotion recognition technology.

[0524] Hardware and software used

[0525] Hardware

[0526] Server: Processes data and runs generative AI models.

[0527] Terminal: The device (e.g., PC, smartphone) where the user enters information and checks the results.

[0528] software

[0529] Generative AI models: Use artificial intelligence models such as OpenAI GPT-4.

[0530] Database management system: Use a database such as MySQL to manage pricing information for existing products.

[0531] Emotion Recognition Engine: Software that recognizes user emotions and adjusts prices accordingly.

[0532] Program processing

[0533] server

[0534] The server first collects information entered by the user and pricing information for existing products. This information is stored in a database. Next, the server uses a generative AI model to calculate an appropriate price for the new product being considered for introduction. For example, OpenAI's GPT-4 is used as the generative AI model. The server then proposes the calculated price to the user.

[0535] Terminal

[0536] The terminal is responsible for transmitting information entered by the user to the server, including product characteristics, market conditions, etc. The terminal also displays price proposals received from the server to the user.

[0537] User

[0538] Users input information about the product they are considering introducing through their terminal, including the product's characteristics and market conditions. The user also checks the price suggested by the server and adjusts the price using the emotion engine if necessary.

[0539] Specific examples

[0540] For example, if a user wants to know the price of a new smartphone they are considering purchasing, they input the smartphone's characteristics (e.g., memory capacity, camera performance, battery life, etc.) through their device. The server retrieves pricing information for existing smartphones from a database and calculates an appropriate price using a generative AI model (GPT-4). Furthermore, if the user is feeling stressed, the emotion engine collects that information and reduces the user's stress by lowering the price.

[0541] Prompt Sentence Examples

[0542] "The characteristics of the new product we are considering introducing are as follows. The market situation is currently stable. Please propose an appropriate price for this product based on the pricing information of existing products."

[0543] In this way, it is possible to propose prices that take into account the user's feelings, thereby increasing user satisfaction. In addition, it is possible to appropriately calculate the price of a new product based on the price information of existing products, allowing for a quick decision on introducing the product.

[0544] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0545] Step 1:

[0546] The user uses a terminal to input information about a new product they are considering introducing. Specifically, they input the product's characteristics (e.g., product name, specifications, desired price range, etc.) and market conditions (e.g., balance of supply and demand, competitors' prices, etc.). The input data is information about the product's characteristics and market conditions. This data is saved on the terminal.

[0547] Step 2:

[0548] The terminal sends the information entered by the user to the server. The data sent includes product characteristics information and market situation information. The data is encrypted before transmission to ensure security. The server stores the received data in a database.

[0549] Step 3:

[0550] The server collects pricing information for existing products from a database. The collected data includes past sales data and market trend information. This data, along with product characteristics and market situation information, is input into the generative AI model.

[0551] Step 4:

[0552] The server uses a generative AI model (e.g., OpenAI GPT-4) to calculate an appropriate price for a new product being considered for introduction. Specifically, the following prompt is input into the generative AI model: "The characteristics of the new product being considered for introduction are as follows. The market situation is currently stable. Please propose an appropriate price for this product based on the price information of existing products." The generative AI model then outputs a price proposal based on the input data.

[0553] Step 5:

[0554] The server uses an emotion engine to recognize the user's emotions. The user's emotion data is collected in real time from the device. For example, if the user is feeling stressed, the emotion engine collects that information and reduces the user's stress by lowering the price of the product. The output of the emotion engine is the adjusted price.

[0555] Step 6:

[0556] The server sends the calculated price and the adjustment results from the emotion engine to the terminal. The data sent is the adjusted price information. The data is encrypted again before transmission to ensure security.

[0557] Step 7:

[0558] The user checks the price proposal sent from the server via the terminal. The user considers introducing the product based on the proposed price. The output data is the final price proposal.

[0559] (Application example 2)

[0560] Next, a description will be given of Application Example 2 of Form 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."

[0561] Conventional product price suggestion systems propose prices without considering the user's feelings, which can lead to a decrease in user satisfaction. In addition, price suggestions based on existing product price information and user input information are insufficient, making it difficult to set appropriate prices.

[0562] 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.

[0563] In this invention, the server includes means for inputting the customer's company size, intended use, and prices of already introduced products, means for displaying a list of prices of currently used products based on this information, means for proposing prices of products being considered for new introduction, and means for recognizing the user's emotions and adjusting the prices of products based on those emotions. This makes it possible to propose appropriate prices that take the user's emotions into consideration, thereby improving user satisfaction.

[0564] "Customer's company size" is information that indicates the size of the company, such as the number of employees and sales.

[0565] "Usage" is information indicating the purpose and situation in which the product will be used.

[0566] "Price of already introduced products" refers to price information for products currently being used by the user.

[0567] An "input means" is a method or device for receiving information from a user.

[0568] The "means for displaying a list of prices of merchandise currently being used" refers to a method or device for displaying in list form the prices of merchandise currently being used by the user.

[0569] The "means for proposing a price for a new product being considered for introduction" refers to a method or device for proposing an appropriate price for a new product being considered for introduction by a user.

[0570] "Generative AI" is an artificial intelligence technology that generates new information based on existing data and user input.

[0571] A "means for recognizing a user's emotions" is a method or device for detecting and understanding a user's emotional state.

[0572] A "means for adjusting the price of a product based on emotions" is a method or device for changing the price of a product depending on the emotional state of the user.

[0573] "BtoB" is a term that refers to business-to-business transactions.

[0574] "In-house tools" are tools and software for use within a company.

[0575] A system for implementing the present invention includes a server, a user terminal, and a generative AI model. A specific embodiment of this system will be described below.

[0576] System Configuration

[0577] The server includes the following means:

[0578] 1. A way to input the size of your company, the purpose of use, and the prices of products you have already introduced

[0579] 2. A method to display a list of the prices of the products currently being used based on this information

[0580] 3. A way to propose prices for new products being considered for introduction

[0581] 4. A way to recognize user emotions and adjust product prices based on those emotions

[0582] Program processing

[0583] The server receives information sent from the user's device, uses a generative AI model to propose prices for new products being considered for introduction, and uses an emotion recognition engine to analyze the user's emotions and adjust prices based on those emotions.

[0584] Hardware and software used

[0585] Hardware: Servers, user devices (smartphones, tablets, PCs, etc.)

[0586] Software: OpenAI generative AI model, emotion recognition engine

[0587] Data processing and calculation

[0588] 1. Data entry: Company size, usage, and pricing information for existing products are sent from the user's terminal to the server.

[0589] 2. Price proposal: The server uses the generative AI model to calculate the appropriate price for the new product being considered for introduction.

[0590] 3. Emotion Recognition: The server sends the user's input text to the emotion recognition engine to analyze the user's emotions.

[0591] 4. Price Adjustment: The server adjusts the suggested price based on the emotion information obtained from the emotion recognition engine.

[0592] Specific examples

[0593] For example, if a user enters "I would like to know the price of a new smartphone," the following processing occurs:

[0594] Prompt Sentence Examples

[0595] Existing product price information: [1000, 1500, 2000, 2500]

[0596] User Input: I want to know the price of a new smartphone.

[0597] Please suggest an appropriate price for the newly introduced product.

[0598] The server inputs this prompt into a generative AI model to suggest an appropriate price, then uses an emotion recognition engine to analyze the user's emotions and, for example, discount the suggested price by 10% if the user is feeling stressed.

[0599] In this way, it becomes possible to propose an appropriate price that takes into account the user's feelings, thereby improving user satisfaction.

[0600] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0601] Step 1:

[0602] The user's terminal inputs information about the company's size, intended use, and the price of existing products. This information becomes the basis for proposing prices for products the user is considering introducing. The input information is sent to the server.

[0603] Step 2:

[0604] The server receives information about the company size, intended use, and price of existing products sent from the user's device. Based on the received information, it generates a prompt sentence to input into the generative AI model. An example of a prompt sentence is, "Price information for existing products: [1000, 1500, 2000, 2500] User input: I would like to know the price of a new smartphone. Please suggest an appropriate price for the newly introduced product."

[0605] Step 3:

[0606] The server inputs the generated prompt sentence into the generative AI model to calculate the appropriate price for the new product being considered for introduction. The generative AI model performs data calculations based on the price information of existing products and the information input by the user, and outputs the appropriate price.

[0607] Step 4:

[0608] The server receives the price information output by the generative AI model and sends it to the user's device, at which point the user can confirm the proposed price.

[0609] Step 5:

[0610] The user terminal checks the proposed price and inputs emotional information, such as "I feel the price of the new smartphone is too high." The input emotional information is then sent to the server.

[0611] Step 6:

[0612] The server receives emotion information sent from the user terminal and inputs it into an emotion recognition engine. The emotion recognition engine analyzes the user's emotional state and outputs emotion information. For example, it may determine that the user is feeling "stressed."

[0613] Step 7:

[0614] The server adjusts the proposed price based on the emotional information output from the emotion recognition engine. For example, if the user is feeling stressed, the proposed price is discounted by 10%. The adjusted price information is then sent to the user's device.

[0615] Step 8:

[0616] The user terminal receives the adjusted price information and displays it to the user, who can then confirm the final price and consider purchasing.

[0617] Through the above processing steps, an appropriate price proposal that takes into account the user's feelings is realized.

[0618] Example 3

[0619] Next, a description will be given of a third embodiment of the third embodiment. 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."

[0620] Conventional product pricing systems proposed prices based on the size of the company and the intended use, but did not optimize prices by taking into account the user's feelings. Therefore, there is a need for optimizing price proposals based on the user's feelings. In addition, there was a lack of functionality to store the user's final decision in a database and use it as reference data for future price decisions.

[0621] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[0622] In this invention, the server includes means for collecting user emotion data, means for analyzing the user emotion data using an emotion engine, and means for optimizing the price of merchandise based on the analysis results, thereby enabling optimization of price proposals based on the user's emotions.

[0623] "Company size" is an indicator that shows the size of a company, such as the number of employees, sales, and capital.

[0624] "Usage" refers to the purpose and situation in which a product or service is used.

[0625] "Merchandise" is a general term for goods and services sold or provided by a company.

[0626] "Emotion data" is information about emotions obtained from the user's facial expressions, voice, text, etc.

[0627] An "emotion engine" is software or hardware that analyzes a user's emotion data and identifies the type and intensity of the emotion.

[0628] "Price optimization" is the process of adjusting the price of a product to the most appropriate value based on collected data and analysis results.

[0629] A "generative AI model" is an algorithm or model that uses artificial intelligence techniques to generate data and perform specific tasks.

[0630] A "database" is a system for efficiently storing, managing, and retrieving data.

[0631] "User's final decision" refers to the price that the user selects after reviewing the price proposals presented to them.

[0632] The system of the present invention is a B2B tool used within a company to determine the price of a new product that the company is considering introducing. The system is equipped with an emotion engine and optimizes the price proposal for the product based on the user's emotions.

[0633] Hardware and software used

[0634] Server: A central processing unit for data processing and sentiment analysis.

[0635] Terminal: The device (e.g., PC, tablet, smartphone) where a user enters data and sees the results.

[0636] Emotion engine: Software for analyzing user emotion data (e.g., IBM Watson®, Microsoft® Azure® Emotion API).

[0637] Generative AI model: An artificial intelligence model for generating pricing proposals for products.

[0638] Program processing

[0639] 1. User login and data entry

[0640] The user logs into the system and enters detailed information about the product (e.g., product name, category, desired price range).

[0641] The terminal sends the user's login information to the server for authentication.

[0642] 2. Collecting Emotional Data

[0643] The device collects user input data in real time and also captures facial expressions and voice data.

[0644] The device converts this data into a format for transmission to the emotion engine.

[0645] 3. Emotion analysis

[0646] The server calls the emotion engine's API and sends the user's facial expressions and voice data.

[0647] The emotion engine analyzes the data and identifies the type and intensity of emotion.

[0648] 4. Optimize your price proposals

[0649] The server runs a price optimization algorithm based on the emotion data.

[0650] For example, if the user is feeling "delighted," it will generate a suggestion to increase the price by 10%.

[0651] 5. Submitting a price proposal

[0652] The server sends the generated price proposal to the terminal.

[0653] The terminal displays price proposals in graphs and charts, providing users with a visually easy-to-understand presentation.

[0654] 6. User's final decision and data storage

[0655] The user reviews the proposed price and decides on the final price.

[0656] The terminal transmits the user's final decision to the server.

[0657] The server stores the final decision in a database and uses it as reference data for future pricing decisions.

[0658] Specific examples

[0659] For example, consider a company using this system to determine the price of a new software product. A user logs in to the system and enters details about the software and their desired price range. The emotion engine analyzes the user's input data and identifies the user's feelings of joy. Based on this emotion data, the server makes a proposal to set the software's price higher than usual. The user confirms this proposal and decides on the final price.

[0660] Prompt Sentence Examples

[0661] Examples of prompts to input to a generative AI model include:

[0662] "To determine the price of a new software product, collect user sentiment data and analyze it using an emotion engine. If users are delighted, propose a 10% price increase."

[0663] By using this prompt sentence, the generative AI model executes a process to optimize the price proposal based on the user's emotions. The flow of the identification process in Example 3 will be described with reference to FIG.

[0664] Step 1:

[0665] User Login and Data Entry

[0666] A user logs in to the system using a user ID and password.

[0667] The terminal sends the user's login information to the server for authentication.

[0668] If the authentication is successful, the server displays the dashboard screen to the user.

[0669] The user enters detailed information about the product (e.g., product name, category, desired price range) and clicks the "Submit" button.

[0670] Input: User ID, password, product details

[0671] Output: Authentication results, detailed product information

[0672] Step 2:

[0673] Collecting Emotional Data

[0674] The terminal collects user input data in real time.

[0675] The device also collects facial expressions and voice data as the user types, and prepares this data to send to the emotion engine.

[0676] Input: User input data, facial expression data, voice data

[0677] Output: Formatted data to send to the emotion engine

[0678] Step 3:

[0679] Emotion analysis

[0680] The server calls the emotion engine's API and sends the user's facial expressions and voice data.

[0681] The emotion engine analyzes the data and identifies the type and intensity of emotion.

[0682] The server receives the analysis results and uses them for further processing.

[0683] Input: facial expression data, voice data

[0684] Output: Analysis results of emotion type and intensity

[0685] Step 4:

[0686] Optimizing price proposals

[0687] The server runs a price optimization algorithm based on the emotion data.

[0688] For example, if the user feels "joyed," the server generates a proposal to set the price of the product higher than usual.

[0689] Input: Analysis results of type and intensity of emotion, detailed product information

[0690] Output: Optimized price proposal

[0691] Step 5:

[0692] Presenting a price proposal

[0693] The server sends the generated price proposal to the terminal.

[0694] The terminal displays price proposals in graphs and charts, providing users with a visually easy-to-understand presentation.

[0695] Input: Optimized Price Proposal

[0696] Output: Display of price proposal presented to user

[0697] Step 6:

[0698] User's final decision and data storage

[0699] The user reviews the proposed price and decides on the final price.

[0700] The terminal transmits the user's final decision to the server.

[0701] The server stores the final decision in a database and uses it as reference data for future pricing decisions.

[0702] Input: User's final decision

[0703] Output: Final decision data stored in the database

[0704] (Application example 3)

[0705] Next, a description will be given of Application Example 3 of Form Example 3. 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."

[0706] Conventional product price proposal systems determined prices without considering user emotions, making it difficult to maximize users' purchasing motivation. Furthermore, fixed pricing made it difficult to flexibly respond to market fluctuations and user emotions, making it difficult to maximize profits. This meant that companies needed time and effort to set appropriate prices, preventing them from offering efficient price proposals.

[0707] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 3 is realized by the following means.

[0708] In this invention, the server includes means for inputting the size of the customer's company, its intended use, and the prices of products already introduced, means for displaying a list of prices of products currently being used based on this information, means for proposing prices for products being considered for new introduction, means for analyzing user emotions, and means for dynamically changing product prices based on the analyzed emotions. This enables flexible price proposals based on user emotions, allowing companies to efficiently maximize profits.

[0709] "Company size" is an indicator that shows the size of a company, such as the number of employees, sales, and capital.

[0710] "Use" refers to how the product is used to fulfill a specific purpose or function.

[0711] "Merchandise" refers to goods or services that a company sells or uses.

[0712] "Means for inputting prices" refers to a method or device for inputting price information of merchandise into the system.

[0713] The "means for displaying prices in a list" refers to a method or device for displaying input price information in a list format.

[0714] "Means for proposing a price" refers to a method or device for proposing an appropriate price for a product.

[0715] "Means for analyzing user emotions" refers to a method or device for analyzing emotions from a user's facial expressions, voice, etc.

[0716] "Means for dynamically changing the price of a product based on emotion" refers to a method or device for changing the price of a product in real time based on analyzed emotion information.

[0717] A system for carrying out this invention is configured as follows: The server includes means for inputting the size of the customer's company, intended use, and prices of merchandise already introduced, means for displaying a list of prices of merchandise currently being used based on this information, means for proposing prices for merchandise being considered for new introduction, means for analyzing user emotions, and means for dynamically changing merchandise prices based on the analyzed emotions.

[0718] Hardware and software used

[0719] Hardware: Smartphones, smart glasses, head-mounted displays

[0720] Software: OpenCV, Keras, TENSORFLOW (registered trademark)

[0721] Data processing and calculation

[0722] The server first receives as input the customer's company size, intended use, and prices of products already in use. Based on this information, it displays a list of prices for products currently in use. Next, it uses a generative AI model to propose prices for products that are being considered for new introduction.

[0723] To analyze user emotions, we use cameras and microphones installed on smartphones, smart glasses, and head-mounted displays. We process the video and audio data acquired from these devices using OpenCV to perform face detection and audio analysis. We then use a pre-trained emotion recognition model using Keras and TensorFlow to analyze user emotions in real time.

[0724] Based on the analyzed emotion information, the server dynamically changes the price of the product. For example, if the user expresses "happiness," the price of the product is increased by 10% to maximize profits.

[0725] Specific examples

[0726] When a user wears smart glasses and browses a shopping site, the system analyzes the user's facial expressions to detect the emotion of happiness, and as a result, the system increases the displayed product price by 10%.

[0727] Prompt Sentence Examples

[0728] When a user wears smart glasses and browses a shopping site, the system analyzes the user's facial expressions and detects the emotion of happiness, resulting in the system increasing the displayed product price by 10%.

[0729] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[0730] Step 1:

[0731] The server receives as input the customer's company size, usage, and prices of existing products. The input data includes the company's number of employees, sales, capital, and pricing information for existing products. From this, the server obtains basic information about the company and pricing data for existing products.

[0732] Step 2:

[0733] The server displays a list of prices for currently used products based on the acquired company size, usage, and price information for existing products. It searches the database for price information for the relevant products and generates data for display in list format. This allows users to check the prices of the products they are currently using at a glance.

[0734] Step 3:

[0735] The server uses a generative AI model to propose prices for new products that are being considered for introduction. The server inputs the company size, intended use, and pricing information for existing products into the generative AI model, and outputs the optimal price. This allows users to receive appropriate pricing proposals for new products.

[0736] Step 4:

[0737] The device (smartphone, smart glasses, head-mounted display) captures the user's facial expressions and voice in real time through a camera and microphone. The captured video and audio data is preprocessed using OpenCV to perform face detection and voice analysis. This prepares the data for analyzing the user's emotions.

[0738] Step 5:

[0739] The device inputs the preprocessed data into a pre-trained emotion recognition model using Keras and TensorFlow to analyze the user's emotions in real time. The analysis results are output as the user's emotions (e.g., joy, sadness, surprise), thereby identifying the user's emotional state.

[0740] Step 6:

[0741] The server dynamically changes the price of the product based on the analyzed emotional information. For example, if the user expresses "happiness," the price of the product is increased by 10%. Using the emotional information and existing price information as input data, the server calculates and outputs a new price. This allows for price suggestions that correspond to the user's emotions.

[0742] Step 7:

[0743] The server sends the dynamically updated price information to the terminal and displays it to the user, who can then check the optimized price based on sentiment, allowing the user to obtain the best price information in real time.

[0744] 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.

[0745] 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> ) 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.

[0746] Another example of generative AI is Gemini (registered trademark) (Internet search engine). <url: https: gemini.google.com ?hl="ja">) are mentioned.

[0747] 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.

[0748] [Second embodiment]

[0749] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0750] 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.

[0751] 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).

[0752] 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.

[0753] 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.

[0754] 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).

[0755] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0756] 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.

[0757] 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.

[0758] 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.

[0759] 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.

[0760] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[0761] "Example 1"

[0762] The system of the present invention is equipped with a means for inputting the customer's company size, intended use, and prices of products already in use. Specifically, this information can be input through a user interface. It also has a means for displaying a list of prices of products currently in use based on this information. This allows users to check the price information of their company's products at a glance.

[0763] "Example 2"

[0764] Furthermore, the system of the present invention includes a means for proposing prices for new products that are being considered for introduction. This means uses a generation AI to propose prices for the products. Specifically, the AI ​​calculates an appropriate price for the new product based on the price information of existing products and information entered by the user, and proposes it to the user.

[0765] "Example 3"

[0766] The system of the present invention can be used as a tool for in-company use in B2B. A specific example of its use is when a company is considering introducing a new product and is deciding on the price, the system is used to propose an appropriate price, and the price is then decided based on the results.

[0767] The processing flow of each embodiment will be described below.

[0768] "Example 1"

[0769] Step 1: The user enters their company size, intended use, and the prices of products already in use through the system's user interface.

[0770] Step 2: The system will display a list of the prices of the products currently being used based on the information entered. This list is organized so that users can check the pricing information of their company's products at a glance.

[0771] "Example 2"

[0772] Step 1: The user enters information about the new product they are considering introducing into the system. Step 2: The system's generation AI calculates the appropriate price for the new product based on the price information of existing products and the information entered by the user.

[0773] Step 3: The AI ​​generator proposes the calculated price to the user, who can then decide the price of the product based on this proposal.

[0774] "Example 3"

[0775] Step 1: Companies use this system when determining the price of new products they are considering introducing.

[0776] Step 2: The company enters the necessary information into the system and receives a price proposal from the generative AI.

[0777] Step 3: The company determines the price of the product based on the price proposals received.

[0778] Example 1

[0779] Next, a description will be given of Example 1 of Form 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."

[0780] With conventional systems, it was difficult for companies to check the pricing information of their own products at a glance, and there was a lack of means to appropriately propose prices for new products that companies were considering introducing. As a result, companies were unable to efficiently manage and compare pricing information for products, making it difficult to select the most suitable products.

[0781] 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.

[0782] In this invention, the server includes means for inputting the size of the customer's company, its intended use, and the prices of products already introduced, means for displaying a list of prices of products currently being used based on this information, means for saving the input data in a database, means for searching and filtering product price information from the database, means for generating a list of filtered product price information, means for displaying the generated price information, and means for proposing prices for products being considered for new introduction. This allows companies to check the price information of their own products at a glance, and further enables them to receive appropriate price proposals for products being considered for new introduction.

[0783] "Company size" is an indicator that shows the size of a company, such as the number of employees and sales.

[0784] "Usage" refers to the purpose for which a company uses a particular product or service.

[0785] "Merchandise" is a general term for goods and services that a company purchases or uses.

[0786] "Price" refers to the amount of money paid for goods or services.

[0787] "User interface" refers to the means, such as a screen or input form, through which a user interacts with a system.

[0788] A "database" is a system for efficiently storing, searching, and managing data.

[0789] "Filtering" refers to the process of selecting data based on specific conditions.

[0790] A "generative AI model" refers to an algorithm or system that uses artificial intelligence to analyze data and generate new information or suggestions.

[0791] A "prompt" refers to an instruction or question to be input into a generative AI model.

[0792] "Business-to-business transactions" refer to transactions in which companies buy and sell goods and services.

[0793] MODE FOR CARRYING OUT THE INVENTION

[0794] This invention is a system that allows companies to check the pricing information of their own products at a glance and receive appropriate pricing suggestions for products they are considering introducing. The system provides a user interface for users to input information about the company's size, intended use, and the prices of products already introduced. The system also has the ability to save the input data in a database, search and filter product pricing information from the database, and display it in a list format.

[0795] Hardware and software used

[0796] Device: PC, smartphone, or other device

[0797] Server: A server that processes data and manages the database

[0798] Database management systems: MySQL, PostgreSQL, etc.

[0799] User Interface: Interface accessible through a web browser

[0800] Generative AI model: An artificial intelligence algorithm for suggesting product prices

[0801] Program processing

[0802] Users access the system's user interface using a terminal. They input information such as the size of their company, the purpose of use, and the prices of products they have already introduced. This input data is then sent from the terminal to the server.

[0803] The server analyzes the received data and stores it in a database management system (e.g., MySQL). The server searches for product price information stored in the database and filters it based on the information entered by the user. The filtered product price information is generated in list format and sent back to the terminal.

[0804] The terminal displays the received price information on the user interface, allowing users to check the price information of their company's products at a glance.The system also has a function that uses a generative AI model to suggest prices for new products that are being considered for introduction.

[0805] Specific examples

[0806] As a concrete example, consider a case where a user is a small or medium-sized enterprise and uses IT services. The user inputs the prices of "cloud storage" and "project management tools" as products that have already been introduced.

[0807] Example prompt sentence:

[0808] Company size: Small business

[0809] Usage: IT services

[0810] Prices of already introduced products:

[0811] Cloud storage: 5000 yen / month

[0812] Project management tool: 3000 yen / month

[0813] After entering this prompt, the system will use this information to display a list of prices for the products you are currently using. For example, the following results will be displayed:

[0814] Prices for the products currently in use:

[0815] Cloud storage: 5000 yen / month

[0816] Project management tool: 3000 yen / month

[0817] Furthermore, the generative AI model is used to suggest prices for new products that users are considering introducing, allowing them to easily check pricing information for their company's products and select the most suitable products.

[0818] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0819] Step 1:

[0820] A user accesses the system's user interface using a terminal. The user opens a web browser and accesses the system's URL, which displays the user interface. The input is the user accessing the system's URL, and the output is the display of the user interface.

[0821] Step 2:

[0822] The user enters the size of the company, the purpose of use, and the price of the products that have already been introduced. The user enters the size of the company (e.g., small and medium-sized enterprise), the purpose of use (e.g., IT services), and the price of the products that have already been introduced (e.g., cloud storage: 5,000 yen / month, project management tool: 3,000 yen / month) into the input form on the displayed user interface. The input is the data that the user entered into the input form, and the output is the preparation of the input data for transmission.

[0823] Step 3:

[0824] The terminal sends the data entered by the user to the server. The terminal sends the data entered by the user to the server as an HTTP request. At this time, the data is sent in an appropriate format such as JSON. The input is the data entered by the user, and the output is the data sent to the server.

[0825] Step 4:

[0826] The server saves the received data in a database. The server analyzes the received data and saves it in a database management system (e.g. MySQL). When saving, it inserts the data into the appropriate table. The input is the data sent from the terminal, and the output is data saved in the database.

[0827] Step 5:

[0828] The server searches the database for product price information and filters it. The server searches for product price information stored in the database. The search results are filtered based on the company size and purpose of use entered by the user. For example, extract only price information for products related to IT services for small and medium-sized enterprises. The input is data stored in the database, and the output is filtered price information.

[0829] Step 6:

[0830] The server generates the price information of the filtered products in a list format. The server formats the price information of the filtered products in a list format. At this time, the data is generated in HTML or JSON format. The input is the filtered price information, and the output is the price information in a list format.

[0831] Step 7:

[0832] The server sends the generated price information to the terminal. The server sends the generated price information to the terminal as an HTTP response. The data is sent in a format that is easy for the user to understand. The input is price information in list format, and the output is data sent to the terminal.

[0833] Step 8:

[0834] The terminal displays the received price information on the user interface. The terminal displays the received price information on the user interface. The user can check the displayed list and understand the price information of their company's products at a glance. The input is the price information sent from the server, and the output is the display on the user interface.

[0835] (Application example 1)

[0836] Next, a description will be given of Application Example 1 of Form 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."

[0837] With conventional systems, it was difficult for companies to easily check the pricing information of their own products, make price comparisons, and make price adjustments. Furthermore, there was a lack of means to compare prices with market price data and make appropriate price adjustments, making it impossible for companies to set prices in line with market trends. For this reason, effective price management is needed to maintain a company's competitive edge.

[0838] 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.

[0839] In this invention, the server includes means for inputting the size of the customer's company, the purpose of use, and the prices of already introduced products, means for displaying a list of prices of currently used products based on this information, means for proposing prices for products being considered for new introduction, means for comparing with market price data and proposing price adjustments, and means for displaying the price comparison results. This allows companies to easily check price information for their own products and make price comparisons and price adjustments.

[0840] "Company size" is an indicator that shows the size of a company, number of employees, sales, etc.

[0841] "Usage" refers to the use of a particular purpose or method of use.

[0842] "Merchandise" is a general term for the products and services that a company handles.

[0843] "Price list display" is a function that displays the prices of the currently used products in a list format based on the input information.

[0844] A "price proposal" is the act of presenting the price of a new product that is being considered for introduction.

[0845] "Market Price Data" refers to price information for a commodity in a particular market.

[0846] "Price adjustment proposal" is the act of proposing appropriate price changes by comparing with market price data.

[0847] "Price comparison results" show the results of comparing the price of the product currently being used with market price data.

[0848] "Generative AI" is a system that uses artificial intelligence technology to generate data and make analysis and suggestions.

[0849] A system for implementing this invention includes a server, a user terminal, and a generative AI model. The server receives information entered by the user about the company size, intended use, and pricing of products already introduced, and displays a list of prices for currently used products based on this information. The server then compares the prices with market price data, proposes price adjustments, and provides the results to the user.

[0850] The user terminal is a device such as a smartphone or tablet, and provides an interface for users to input information such as company size, usage, and product prices. The data entered by the user is sent to the server, which processes it and generates a price list.

[0851] The generative AI model runs on a server and proposes price adjustments based on data entered by the user and market price data. The generative AI model is implemented using software such as Python, Pandas, and Scikit-learn. Specifically, it compares the product price entered by the user with market price data and performs a regression analysis to propose appropriate price adjustments.

[0852] For example, consider the case where a user inputs the following data:

[0853] Company size: Small business

[0854] Usage: Manufacturing industry

[0855] Item Price: [1000, 2000, 3000]

[0856] Market price data: [1100, 2100, 3100]

[0857] The server receives this data and displays a list of prices for the currently used products. The generative AI model then compares it with market price data to propose price adjustments and provides the results to the user. This allows users to easily check the price information of their company's products, make price comparisons, and make price adjustments.

[0858] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0859] Step 1:

[0860] The user uses a terminal to input the company size, intended use, and the prices of the products already introduced.

[0861] Input: Company size, usage, product price.

[0862] Specific operation: The user enters the company size (e.g., small and medium-sized enterprise), purpose of use (e.g., manufacturing), and product price (e.g., 1,000 yen, 2,000 yen, 3,000 yen) through the interface of a smartphone or tablet.

[0863] Output: The input data is sent to the server.

[0864] Step 2:

[0865] The server processes the data received from the user and displays a list of the prices of the products currently being used.

[0866] Input: Company size, purpose of use, and product price entered by the user.

[0867] Specific operation: The server converts the received data into a data frame and generates a list of product prices.

[0868] Output: A list of product prices is generated and displayed on the user's device.

[0869] Step 3:

[0870] The server retrieves market price data and uses a generative AI model to suggest price adjustments.

[0871] Input: User-entered product price and market price data.

[0872] Specific operation: The server obtains market price data (e.g., 1,100 yen, 2,100 yen, 3,100 yen) and performs regression analysis using a generative AI model (using Python, Pandas, and Scikit-learn).

[0873] Output: A price adjustment proposal is generated.

[0874] Step 4:

[0875] The server transmits the price adjustment proposal results to the user terminal and displays them to the user.

[0876] Input: The proposed price adjustment result.

[0877] Specific operation: The server sends the generated price adjustment proposal results to the user terminal, and the user confirms them on the interface.

[0878] Output: The proposed price adjustment is displayed on the user's terminal.

[0879] Step 5:

[0880] The user adjusts the price of the product based on the price adjustment proposal results.

[0881] Input: The proposed price adjustment result.

[0882] Specific operation: The user adjusts the price of their company's products based on the proposed price adjustment results.

[0883] Output: The adjusted price of the product.

[0884] Example 2

[0885] Next, a description will be given of Example 2 of Form 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."

[0886] Conventional product price proposal systems have difficulty in calculating the appropriate price of new products based on the price information of existing products. Furthermore, they lack a means to effectively utilize the information entered by users to make highly accurate price proposals. This means that companies need time and effort to set prices for new products, potentially resulting in a loss of competitiveness.

[0887] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0888] In this invention, the server includes means for inputting the customer's company size, intended use, and prices of already introduced products, means for displaying a list of prices of currently used products based on this information, means for inputting information on products being considered for new introduction, means for preprocessing price information on existing products and information on products being considered for new introduction, means for inputting the preprocessed data into a generative AI model to calculate an appropriate price, and means for proposing price information obtained from the generative AI model. This enables users to set prices for new products efficiently and accurately.

[0889] "Customer's company size" is information indicating the size of the company, such as the number of employees, sales, and capital.

[0890] "Usage" is information indicating the purpose and situation in which the product will be used.

[0891] "Prices of already introduced products" refers to price information of products currently being used by the company.

[0892] "Information on new products being considered for introduction" refers to information such as the type, features, and target market of the products that a company is considering purchasing.

[0893] "Preprocessing" refers to the processing of data before inputting it into a generative AI model, such as data cleaning, normalization, and feature extraction.

[0894] A "generative AI model" is a model that uses artificial intelligence technology to analyze data and calculate appropriate prices.

[0895] A "price proposal" is the act of presenting price information obtained from a generative AI model to a user.

[0896] "In-house tools" refers to software and systems for internal use by a company.

[0897] This invention relates to a system for proposing prices for commercial products. Specifically, it is a system that uses a generative AI model to calculate an appropriate price for a commercial product that is being considered for new purchase and proposes it to the user.

[0898] System configuration

[0899] This system consists of three main components: a server, a terminal, and a user.

[0900] server

[0901] The server has the following functions:

[0902] 1. Data Collection:

[0903] The server retrieves pricing information for existing products from a database that includes information such as past product prices, sales history, and demand forecasts.

[0904] 2. Data Preprocessing:

[0905] The server preprocesses the acquired price information of existing products and the information entered by the user, specifically by cleaning the data, normalizing it, and extracting features.

[0906] 3. Price Calculation:

[0907] The server then inputs the preprocessed data into a generative AI model, such as OpenAI's GPT-4.

[0908] The server inputs the following prompt to the generative AI model:

[0909] "The information about the new product we are considering introducing is as follows: Type: Electronic device, Features: High-performance battery, Target market: Young people. Please propose an appropriate price for this product based on the pricing information of existing products."

[0910] The generative AI model calculates the appropriate price for a new product based on the input information.

[0911] 4. Price Proposal:

[0912] The server proposes price information obtained from the generative AI model to the user.

[0913] Terminal

[0914] The terminal is a device where the user enters information and sees the proposed price. The terminal has the following functions:

[0915] 1. Enter your information:

[0916] The user uses a terminal to input information about the new product they are considering introducing, such as the product type, features, and target market.

[0917] 2. Price Check:

[0918] The user can check the price proposed by the server through the terminal.

[0919] User

[0920] The user is responsible for operating the system and setting the prices of the products. The user performs the following operations:

[0921] 1. Enter your information:

[0922] The user uses the terminal to input information about a new product they are considering introducing. For example, they input information about a "smartphone with a high-performance battery."

[0923] 2. Price Check:

[0924] The user can check the price proposed by the server and make corrections or reevaluations as necessary.

[0925] Specific examples

[0926] For example, if a user is looking to purchase a new smartphone with a high-performance battery, they can input the following prompt into the generative AI model:

[0927] "The information about a new product we are considering introducing is as follows: Type: Smartphone, Features: High-performance battery, Target market: Young people. Please propose an appropriate price for this product based on the pricing information of existing products."

[0928] The generative AI model calculates the appropriate price for a new smartphone based on past price information and information entered by the user. The server then proposes this price information to the user, who can then check the price via their device.

[0929] In this way, users can set prices for new products efficiently and accurately.

[0930] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0931] Step 1: Data collection

[0932] The server retrieves price information for existing products from the database.

[0933] Input: Database connection information, query

[0934] Data processing: Extract information such as past product prices, sales history, and demand forecasts from the database.

[0935] Output: A list of retrieved price information

[0936] Step 2: Enter user information

[0937] The user inputs information about the new product they are considering introducing into the terminal.

[0938] Input: Information on product type, features, target market, etc.

[0939] Data processing: Sending the entered information to the system.

[0940] Output: Product information entered by the user

[0941] Step 3: Data Preprocessing

[0942] The server preprocesses the acquired price information of existing products and the information input by the user.

[0943] Input: Price information of existing products, product information entered by the user

[0944] Data processing: Data cleaning, normalization, and feature extraction, such as imputing missing values ​​and correcting outliers.

[0945] Output: Preprocessed dataset

[0946] Step 4: Price calculation

[0947] The server inputs the preprocessed data into a generative AI model.

[0948] Input: Preprocessed dataset

[0949] Data calculation: Enter a prompt into the generative AI model to calculate an appropriate price.

[0950] Example prompt sentence:

[0951] "The information about a new product we are considering introducing is as follows: Type: Smartphone, Features: High-performance battery, Target market: Young people. Please propose an appropriate price for this product based on the pricing information of existing products."

[0952] Output: Price information obtained from the generative AI model

[0953] Step 5: Price Proposal

[0954] The server proposes price information obtained from the generative AI model to the user.

[0955] Input: Price information obtained from a generative AI model

[0956] Data processing: Convert the proposal into a format that is easy for users to understand.

[0957] Output: Proposed pricing information

[0958] Step 6: Price confirmation

[0959] The user confirms the proposed price through the terminal.

[0960] Input: Proposed pricing information

[0961] Data processing: Display suggested pricing information.

[0962] Output: Price information confirmed by the user

[0963] In this way, users can set prices for new products efficiently and accurately.

[0964] (Application example 2)

[0965] Next, a description will be given of Application Example 2 of Form 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."

[0966] Conventional product price proposal systems have difficulty in proposing appropriate prices for new products based on information such as the price information of existing products, company size, and intended use. Furthermore, the accuracy of price proposals is low, making it impossible to calculate the optimal price for the user. Furthermore, the price proposal process is often done manually, which is time-consuming and labor-intensive.

[0967] The specification processing by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for inputting the customer's company size, intended use, and prices of already introduced products, means for displaying a list of prices of currently used products based on this information, means for proposing prices of products being considered for new introduction, and means for calculating an appropriate price for a new product using a generative AI model and proposing it to the user. This enables the user to quickly and accurately receive an optimal price proposal using the generative AI model based on price information of existing products and the characteristics of the new product.

[0968] "Customer's corporate size" is information that indicates the size and economic scale of a company, such as the number of employees and sales.

[0969] "Usage" is information indicating the purpose and situation in which the product will be used.

[0970] "Prices of already introduced products" refers to price information of products currently being used by the company.

[0971] "Input means" refers to a method or device that allows a user to input the required information into the system.

[0972] The "means for displaying a list of prices of currently used products" refers to a method or device for displaying price information of existing products in a list format.

[0973] The "means for proposing the price of a new product being considered for introduction" refers to a method or device for proposing the price of a new product to users.

[0974] A "generative AI model" is an algorithm or model that uses artificial intelligence to generate data and perform specific tasks.

[0975] "Means for calculating the appropriate price of a new product and proposing it to users" refers to a method or device for calculating the optimal price of a new product using a generative AI model and presenting that price to users.

[0976] A system for carrying out this invention has the following configuration: The server includes means for inputting the size of the customer's company, intended use, and prices of merchandise already introduced, means for displaying a list of prices of merchandise currently being used based on this information, means for proposing prices for merchandise being considered for new introduction, and means for calculating appropriate prices for new merchandise using a generative AI model and proposing the prices to the user.

[0977] Hardware and software used

[0978] Hardware: Smartphones, servers

[0979] Software: Python, OpenAI API, Pandas

[0980] Data processing and calculation

[0981] 1. Data loading: The server loads the price information of existing products from the CSV file. This retrieves the price information of existing products as a data frame.

[0982] 2. User input: The user inputs the name and characteristics of the new product using a smartphone. This information is sent to the server.

[0983] 3. Use of generative AI model: The server uses OpenAI's API to generate an appropriate price for the new product based on the price information of existing products and user-entered information. Specifically, it sends a prompt to the generative AI model, and the AI ​​calculates the price.

[0984] 4. Price Proposal: The generated price is sent from the server to the user's smartphone and displayed to the user.

[0985] Specific examples

[0986] For example, suppose the price information for existing products is stored in a CSV file as shown below.

[0987] Product A, 1000

[0988] Product B, 1500

[0989] Product C, 2000

[0990] If a user enters "Product D" as the name of a new product and "Made of high-quality materials and highly durable" as its features, the server will send the following prompt to the generative AI model.

[0991] Prompt Sentence Examples

[0992] Existing product pricing information: {'Product A': 1000, 'Product B': 1500, 'Product C': 2000}

[0993] New product name: Product D

[0994] Features of the new product: Made from high-quality materials and highly durable

[0995] Please suggest a reasonable price for this new product.

[0996] The generative AI model calculates the appropriate price for the new product based on this prompt and returns the result to the server. The server then sends the result to the user's smartphone and displays it to the user. This allows the user to quickly and accurately find out the appropriate price for the new product.

[0997] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0998] Step 1:

[0999] The server reads the price information of existing products from a CSV file. Specifically, it uses the Pandas library to read the CSV file as a data frame. The input is a CSV file, and the output is the price information of existing products in data frame format.

[1000] Step 2:

[1001] The user uses a smartphone to input the name and characteristics of a new product. The input is the name and characteristics of the new product, and the output is sending this information to the server. Specifically, the user enters the information about the new product into the input form on the smartphone and presses the send button.

[1002] Step 3:

[1003] The server receives the name and characteristics of the new product sent by the user and combines them with the price information of the existing product to generate a prompt. The input is the name and characteristics of the new product and the price information of the existing product, and the output is the generated prompt. Specifically, the prompt is constructed using string manipulation.

[1004] Step 4:

[1005] The server sends the generated prompt text to OpenAI's API and uses the generative AI model to calculate the appropriate price for the new product. The input is the prompt text, and the output is the price information for the new product returned by the generative AI model. Specifically, the server sends the prompt text to the API using an HTTP request and receives a response.

[1006] Step 5:

[1007] The server receives the price information for new products returned from the generative AI model and sends it to the user's smartphone. The input is the price information from the generative AI model, and the output is the price information displayed on the user's smartphone. Specifically, it performs communication processing to send the price information to the user's smartphone.

[1008] Step 6:

[1009] The user checks the price information of a new product displayed on the smartphone. The input is the price information sent from the server, and the output is the price information checked by the user. Specifically, the user views the price information displayed on the smartphone screen.

[1010] Example 3

[1011] Next, a description will be given of Example 3 of Form Example 3. 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."

[1012] Determining the appropriate price for a new product a company is considering introducing is extremely important for maintaining the company's competitiveness. However, determining an appropriate price by taking into account the product's features, manufacturing costs, and competitor pricing information is a time-consuming and labor-intensive task. Furthermore, the pricing process is prone to subjective judgment, making it difficult to find the optimal price.

[1013] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[1014] In this invention, the server includes a means for a user to input product information, a means for the server to save the input information in a database, a means for the server to send a prompt to the generative AI model, a means for the generative AI model to propose an appropriate price, a means for the server to provide the proposed price to the user, a means for the user to determine a final price, and a means for the server to save the determined price in a database. This enables companies to efficiently and objectively determine an appropriate price for a new product they are considering introducing.

[1015] "Customer's company size" is information indicating the size of the company, such as the number of employees, sales, and capital.

[1016] "Usage" is information that indicates the purpose for which a company will use a product.

[1017] "Already implemented products" refer to products that a company has already purchased and is using.

[1018] "Price input means" refers to the interface or method by which a user inputs product pricing information into the system.

[1019] "Means for displaying prices in a list" refers to an interface or method for displaying entered price information in a list format.

[1020] "Means for suggesting a price" refers to the method or algorithm by which the system calculates an appropriate price and suggests it to the user.

[1021] "Means for users to input product information" refers to the interface or method by which users input product features, costs, competitor pricing information, etc. into the system.

[1022] "Means for the server to save the input information in a database" refers to the method or technology by which the server saves the information input by the user in a database.

[1023] "Means by which the server sends prompt sentences to the generative AI model" refers to the methods and technologies by which the server generates and sends appropriate prompt sentences to the generative AI model.

[1024] "Means by which the generative AI model suggests an appropriate price" refers to the methods and algorithms by which the generative AI model calculates and suggests an appropriate price based on the input prompt.

[1025] "Means by which the server provides the suggested price to the user" refers to the interface or method by which the server displays the suggested price from the generative AI model to the user.

[1026] "Means for users to determine final prices" refers to an interface or method by which a user determines a final price based on the proposed prices and inputs it into the system.

[1027] "Means for the server to store the determined price in a database" refers to a method or technology for the server to store the final price determined by the user in a database.

[1028] "Business-to-business transactions" refer to transactions in which companies buy and sell products or services.

[1029] "Tools for internal use" refers to software and systems for use within a company.

[1030] This invention is a system for determining the appropriate price of a new product that a company is considering introducing. In this system, the user inputs product information, and the server uses a generative AI model based on that information to propose an appropriate price.

[1031] First, a user uses a company's device to input product features (e.g., screen size, battery capacity, camera performance, etc.), manufacturing costs, competitor pricing information, etc. This information is entered through the device's interface.

[1032] The server then receives the information entered by the user and stores it in a database. This database is managed using a database management system such as MySQL. The stored data is divided into fields such as product ID, features, cost, and competitive price.

[1033] The server generates a prompt based on the product information stored in the database. The generated prompt is sent to a generative AI model (e.g., OpenAI's GPT-4). Examples of prompts include:

[1034] Product: Smartphone

[1035] Features: 6.5-inch display, 5000mAh battery, 48MP camera

[1036] Manufacturing cost: $200

[1037] Competitor's Price: $300

[1038] Please suggest a reasonable price.

[1039] The generative AI model analyzes the prompt sent from the server and proposes an appropriate price for the product. This proposed price is calculated based on the generative AI model's algorithm.

[1040] The server receives the proposed price from the generative AI model and provides it to the user, who can then view the proposed price through their device.

[1041] The user decides on the final price based on the price proposal provided by the server. The decided price is sent back to the server and saved in the database. This saved price information can be used for future analysis and reference.

[1042] This system enables a company to efficiently and objectively determine an appropriate price for a new product that the company is considering introducing. The flow of the specification process in the third embodiment will be described with reference to FIG.

[1043] Step 1:

[1044] The user enters product information.

[1045] Users use a company's terminal to input product features (e.g., screen size, battery capacity, camera performance, etc.), manufacturing costs, and competitor pricing information. The input information is sent to the server through the terminal's interface. Input data includes product name, features, costs, and competitor pricing.

[1046] Step 2:

[1047] The server stores the entered information in a database.

[1048] The server receives the product information sent by the user and stores it in a database. The database is managed using a database management system such as MySQL. The stored data includes fields such as product ID, features, cost, and competitive price. The input data is appropriately mapped to each field in the database.

[1049] Step 3:

[1050] The server sends a prompt to the generative AI model.

[1051] The server generates a prompt based on the product information stored in the database. The generated prompt is sent to a generative AI model (e.g., OpenAI's GPT-4). Examples of prompts include:

[1052] Product: Smartphone

[1053] Features: 6.5-inch display, 5000mAh battery, 48MP camera

[1054] Manufacturing cost: $200

[1055] Competitor's Price: $300

[1056] Please suggest a reasonable price.

[1057] The input data is product information obtained from the database, and the output data is the generated prompt sentence.

[1058] Step 4:

[1059] A generative AI model suggests the right price.

[1060] The generative AI model analyzes the prompt sent from the server and proposes an appropriate price for the product. This proposed price is calculated based on the generative AI model's algorithm. The input data is the prompt, and the output data is the proposed price.

[1061] Step 5:

[1062] The server provides the suggested price to the user.

[1063] The server receives the proposed price from the generative AI model and displays it on the user's device. The user can check the proposed price on the device screen. The input data is the proposed price, and the output data is the price information displayed to the user.

[1064] Step 6:

[1065] The user decides the final price.

[1066] The user decides on the final price based on the price proposal provided by the server. The decided price is sent to the server via the terminal. The input data is the proposed price, and the output data is the final decided price.

[1067] Step 7:

[1068] The server stores the determined price in a database.

[1069] The server receives the final price sent by the user and stores it in a database. The stored price information is used for future analysis and reference. The input data is the final determined price, and the output data is the price information stored in the database.

[1070] (Application example 3)

[1071] Next, a description will be given of Application Example 3 of Form Example 3. 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."

[1072] Determining the appropriate price for a new product a company is considering introducing is an important issue in its business strategy. However, traditional methods require a great deal of time and effort to collect and analyze the information necessary for pricing decisions. It is also difficult to evaluate the appropriateness of a price by comparing it with past price data. This can prevent companies from quickly determining an appropriate price, potentially resulting in a loss of competitiveness.

[1073] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 3 is realized by the following means.

[1074] In this invention, the server includes means for inputting the size of the customer's company, intended use, and prices of already introduced products, means for displaying a list of prices of currently used products based on this information, means for proposing prices for products being considered for new introduction, means for proposing an appropriate price using a generative AI model, means for determining prices based on the proposed prices, and means for evaluating the appropriateness of the prices by comparing with past price data. This enables companies to quickly and appropriately determine prices for products being considered for new introduction.

[1075] "Company size" is an indicator that shows the size of a company, such as the number of employees, sales, and capital.

[1076] "Usage" refers to the purpose and situation in which a particular product or service is used.

[1077] "Merchandise" refers to goods or products that a company handles for sale or use.

[1078] "Price" refers to the monetary value assigned to a product or service.

[1079] A "generative AI model" is an algorithm or system that uses artificial intelligence technology to generate new information or suggestions from data.

[1080] A "prompt" is a sentence of instructions or questions that is input to a generative AI model.

[1081] A "price proposal" is the act and result of presenting an appropriate price for a particular product.

[1082] "Pricing" refers to the process of determining the final price based on the proposed price.

[1083] "Price reasonableness" is a criterion for evaluating whether the proposed price is appropriate compared to market and historical data.

[1084] "BtoB" refers to business-to-business transactions, a business model in which companies provide products and services to other companies.

[1085] The system for carrying out the present invention is for appropriately determining the price of a new product that a company is considering introducing. A specific embodiment of this system is described below.

[1086] System Configuration

[1087] The system consists of the following main components:

[1088] 1. Input method: Provides an interface for users to input information such as company size, usage, and prices of products already in use. This can be done using devices such as smartphones or PCs.

[1089] 2. Display method: Based on the information entered, the prices of the products currently being used are displayed in a list. This is also displayed on the screen of a smartphone or computer.

[1090] 3. Proposal method: Propose a price for a new product being considered for introduction. This proposal is made using a generative AI model.

[1091] 4. Pricing method: The final price is determined based on the proposed price.

[1092] 5. Evaluation measures: Evaluate the reasonableness of the proposed price by comparing it with historical price data.

[1093] Program processing

[1094] The server performs the following process.

[1095] 1. Data entry: The user enters the company size, usage, and prices of products already in use. This data is sent to the server via the interface of a smartphone or PC.

[1096] 2. Data display: The server displays a list of prices for the currently used products based on the entered information.

[1097] 3. Price Proposal: The server proposes a price for the new product being considered for introduction using the generative AI model. The generative AI model is implemented using OpenAI's API.

[1098] 4. Price determination: The user determines the final price based on the proposed prices.

[1099] 5. Price Evaluation: The server evaluates the reasonableness of the proposed price by comparing it with historical pricing data.

[1100] Hardware and software used

[1101] Hardware: smartphones, PCs, servers

[1102] Software: Python, OpenAI API

[1103] Specific examples

[1104] For example, if a user inputs "high-performance battery" as a new product they are considering introducing, the following prompt sentence will be sent to the generative AI model.

[1105] Prompt Sentence Examples

[1106] Information on the new product: Product name: High-performance battery, Specifications: 5000mAh, Price range: 3000 yen to 5000 yen

[1107] Please suggest a reasonable price.

[1108] The generative AI model will then suggest an appropriate price based on this prompt and display the results to the user, who can then decide on a final price based on the suggested price and evaluate its appropriateness by comparing it with past price data.

[1109] In this way, companies can quickly and appropriately determine the prices of new products they are considering introducing.

[1110] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[1111] Step 1:

[1112] The user enters the company size, intended use, and the price of the products already introduced.

[1113] Input: Company size, usage, price of already introduced products

[1114] Specific operation: Through the interface of a smartphone or PC, the user inputs the company size (e.g., number of employees, sales), usage (e.g., manufacturing, sales), and price of already introduced products (e.g., price of product A). This data is sent from the device to the server.

[1115] Step 2:

[1116] The server displays a list of prices for the currently used products based on the information entered.

[1117] Input: Company size, usage, price of already introduced products

[1118] Output: Price list of currently used products

[1119] Specific operation: The server processes the received data and displays the prices of the currently used products in a list format. The displayed price list is sent to the user's device and displayed on the screen.

[1120] Step 3:

[1121] The server generates a prompt message to suggest the price of the new product that is being considered for introduction.

[1122] Input: Information about the new product you are considering introducing (e.g. product name, specifications, price range)

[1123] Output: prompt statement

[1124] Specific operation: When a user enters information about a new product they are considering introducing, the server uses that information to generate a prompt to send to the generative AI model. For example, it generates a prompt like this: "Information about the new product: Product name: High-performance battery, Specifications: 5000mAh, Price range: 3000 to 5000 yen. Please suggest an appropriate price."

[1125] Step 4:

[1126] The server uses a generative AI model to suggest an appropriate price.

[1127] Input: prompt statement

[1128] Output: Proposed price

[1129] Specific operation: The server sends the generated prompt to OpenAI's API and receives an appropriate price suggestion from the generative AI model. For example, the generative AI model suggests a price of "4,500 yen."

[1130] Step 5:

[1131] The server will determine the final price based on the proposed price.

[1132] Input: Proposed Price

[1133] Output: Final price

[1134] How it works: The user checks the price suggested by the generative AI model and decides on the final price based on that price. The decided price is sent to the server and recorded.

[1135] Step 6:

[1136] The server evaluates the reasonableness of the proposed price by comparing it with historical pricing data.

[1137] Inputs: Proposed price, historical price data

[1138] Output: Price justification evaluation result

[1139] How it works: The server compares the proposed price with past price data to evaluate its validity. The evaluation result is sent to the user's device and displayed on the screen.

[1140] In this way, companies can quickly and appropriately determine the prices of new products they are considering introducing.

[1141] 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.

[1142] "Example 1"

[1143] As one embodiment of the present invention, a system incorporating an emotion engine is provided. This system inputs the user's company size, intended use, and prices of already implemented products, and based on this information, displays a list of prices for currently used products. It also proposes prices for products that are being considered for new implementation. As a proposal method, it uses a generation AI to propose product prices. This system is a tool for in-company use in B2B.

[1144] "Example 2"

[1145] The emotion engine recognizes the user's emotions and adjusts the price of the product based on those emotions. For example, if the user is feeling stressed, the emotion engine will collect that information and reduce the price of the product to reduce the user's stress.

[1146] "Example 3"

[1147] The emotion engine also optimizes product pricing based on user emotions. For example, if a user is feeling happy, the emotion engine will collect that information and increase the product price to maximize profits.

[1148] The processing flow of each embodiment will be described below.

[1149] "Example 1"

[1150] Step 1: The user enters the company size, intended use, and prices of products already implemented into the system.

[1151] Step 2: The system will display a list of prices for the products you are currently using based on the information you entered.

[1152] Step 3: The system uses AI to suggest prices for new products that are being considered for introduction.

[1153] "Example 2"

[1154] Step 1: The emotion engine recognizes the user's emotion.

[1155] Step 2: The emotion engine adjusts the price of the product based on the emotion it recognizes.

[1156] Step 3: For example, if the user is feeling stressed, the emotion engine will collect that information and reduce the user's stress by lowering the price of the product.

[1157] "Example 3"

[1158] Step 1: The emotion engine recognizes the user's emotion.

[1159] Step 2: The emotion engine optimizes the price suggestions for the product based on the emotions it recognizes.

[1160] Step 3: For example, if the user is feeling happy, the emotion engine will collect that information and maximize profits by increasing the price of the product.

[1161] Example 1

[1162] Next, a description will be given of Example 1 of Form 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."

[1163] With conventional systems, it is difficult for companies to check the pricing information of their own products at a glance, and there is a lack of means to propose appropriate prices for products that they are considering introducing. In addition, in business-to-business transactions, the optimal price proposal based on the size of the company or the purpose of use is not made, making it difficult to efficiently select products.

[1164] 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.

[1165] In this invention, the server includes means for inputting the customer's company size, intended use, and prices of already introduced products, means for displaying a list of prices of currently used products based on this information, means for proposing prices for products being considered for new introduction, means for displaying the generated price information to the user, and means for generating prices for products being considered for new introduction using a generative AI model. This allows companies to check price information for their own products at a glance and receive optimal price proposals based on their company size and intended use.

[1166] "Company size" is an indicator that shows the size of a company, such as the number of employees and sales.

[1167] "Usage" is information indicating the purpose for which a company will use the product.

[1168] "Merchandise" refers to products or services that a company purchases or uses.

[1169] "Price" refers to the monetary value paid for a commodity.

[1170] "Input means" refers to an interface through which a user provides information to a system.

[1171] "Display means" refers to an interface that allows the system to visually present information to the user.

[1172] "Proposal means" refers to a function that allows the system to present the price of a new product to the user.

[1173] A "generative AI model" refers to an algorithm or system that uses artificial intelligence to analyze data and generate new information.

[1174] A "prompt" is text data that is input to a generative AI model and contains instructions for the model to generate output.

[1175] "Business-to-business transactions" refer to commercial transactions conducted between businesses.

[1176] This invention is a system that allows a company to check price information of its own products at a glance and proposes appropriate prices for products that the company is considering introducing. A specific embodiment of this system will be described below.

[1177] The user accesses the system using a device (PC, tablet, smartphone, etc.). The user opens the device's browser and accesses the system's web application. The user enters information into a form that asks for the company size (e.g., small and medium-sized enterprise), purpose of use (e.g., manufacturing), and price of the product already introduced (e.g., 1 million yen), and clicks the "Submit" button.

[1178] The terminal sends the entered information to the server as an HTTP request. Specifically, it sends data using a POST request. The request body includes the company size, purpose of use, and price of existing products.

[1179] The server analyzes the received information and executes an INSERT query to store the information in a database, which stores information such as the company size, usage, and prices of existing products.

[1180] Next, the server queries and obtains the price of the currently used product based on the information stored in the database.The server executes a SELECT query to obtain the price information of the currently used product from the database.

[1181] The server converts the acquired price information into JSON format and sends it to the terminal as an HTTP response. The terminal parses the received JSON data and displays the price information in a list on the user interface. The user can then check the price information on their browser.

[1182] Furthermore, the server uses the generative AI model to generate a price for a new product that is being considered for introduction. A prompt statement is generated for the generative AI model and input into the model. The prompt statement includes information about the company size, intended use, and pricing information for existing products. The generative AI model generates a price for the new product based on the input information.

[1183] The server converts the price information output by the generative AI model into JSON format and sends it to the terminal as an HTTP response. The terminal analyzes the received JSON data and displays the generated price information on the user interface. The user can then check the price of the new product they are considering introducing.

[1184] As a specific example, consider the case where a small or medium-sized enterprise wants to know the price of a new product it is considering introducing. The user enters the company size as "Small or Medium-sized Enterprise," the use as "Manufacturing," and the price of the product already introduced as "1 million yen." Based on this information, the system displays a list of prices for the products currently being used and uses a generative AI model to suggest a price for the new product being considered for introduction.

[1185] Example prompt sentence:

[1186] Company size: Small business

[1187] Usage: Manufacturing industry

[1188] Price of already introduced products: 1 million yen

[1189] By inputting this prompt into the generative AI model, the system will suggest a price for the new product being considered for introduction.

[1190] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1191] Step 1:

[1192] The user opens a browser on their device and accesses the system's web application. They enter information into a form to input the company size, intended use, and price of the product they have already introduced, and click the "Submit" button. The input data is the company size (e.g., small and medium-sized enterprise), intended use (e.g., manufacturing), and price of the existing product (e.g., 1 million yen).

[1193] Step 2:

[1194] The terminal sends the entered information to the server as an HTTP request. Specifically, the data is sent using a POST request. The body of the request includes the company size, intended use, and price of existing products. The input data is the information the user entered into the form, and the output data is the request sent to the server.

[1195] Step 3:

[1196] The server analyzes the received information and executes an INSERT query to save the information in a database. The database stores information such as company size, usage, and prices of existing products. The input data is the information sent from the terminal, and the output data is the information saved in the database.

[1197] Step 4:

[1198] The server queries and retrieves the price of the currently used product based on the information stored in the database. The server executes a SELECT query to retrieve the price information of the currently used product from the database. The input data is the information stored in the database, and the output data is the retrieved price information.

[1199] Step 5:

[1200] The server converts the acquired price information into JSON format and sends it to the terminal as an HTTP response. The input data is the acquired price information, and the output data is a JSON format response.

[1201] Step 6:

[1202] The terminal parses the received JSON data and displays a list of price information in the user interface. The user can check the price information in the browser. The input data is the JSON data received from the server, and the output data is the price information displayed in the user interface.

[1203] Step 7:

[1204] The server uses a generative AI model to generate prices for new products that are being considered for introduction. It generates a prompt statement for the generative AI model and inputs it into the model. The prompt statement includes information about the company size, intended use, and pricing information for existing products. The input data is the prompt statement, and the output data is the generated price information.

[1205] Step 8:

[1206] The server converts the price information output by the generative AI model into JSON format and sends it to the terminal as an HTTP response. The input data is the generated price information, and the output data is a JSON-formatted response.

[1207] Step 9:

[1208] The terminal analyzes the received JSON data and displays the generated price information in the user interface. The user can check the price of the new product they are considering introducing. The input data is the JSON data received from the server, and the output data is the generated price information displayed in the user interface.

[1209] (Application example 1)

[1210] Next, a description will be given of Application Example 1 of Form 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."

[1211] Conventional product price proposal systems have had issues with making appropriate price proposals based on the size of the company and the purpose of use, and not being able to reflect user feedback. Furthermore, there was a lack of a way to check the price information of currently used products at a glance, making efficient price management difficult.

[1212] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. In this invention, the server includes a means for inputting the customer's company size, intended use, and prices of already-used products; a means for displaying a list of prices of currently-used products based on this information; a means for proposing prices for products being considered for new introduction; an emotion engine for analyzing user feedback; and a means for proposing product prices using a generative AI model. This enables appropriate price proposals based on company size and intended use, and also allows price proposals that reflect user feedback. Furthermore, price information for currently-used products can be checked at a glance, enabling efficient price management.

[1213] "Company size" is an indicator that shows the size of a company, such as the number of employees and sales.

[1214] "Use" refers to the method or purpose of using the product for a specific purpose or function.

[1215] "Merchandise" refers to the goods and services that a company sells or uses.

[1216] "Price" means the monetary value paid for the purchase or use of a commodity.

[1217] "Input means" refers to the method or device by which a user provides information to a system.

[1218] "Display means" refers to the method or device by which a system visually presents information to a user.

[1219] "Proposal means" refers to a method or device by which the system presents the user with prices and options for new products.

[1220] An "emotion engine" refers to software or hardware that analyzes user feedback and emotions and adjusts system behavior accordingly.

[1221] A "generative AI model" refers to an algorithm or system that uses artificial intelligence to generate new information or suggestions from data.

[1222] "BtoB" refers to business-to-business transactions, a business model in which companies provide products and services to other companies.

[1223] "Tools for internal use" refers to software and hardware tools used within a company.

[1224] A system for carrying out this invention is configured as follows: The server includes means for inputting the size of the customer's company, intended use, and prices of merchandise already introduced, means for displaying a list of prices of merchandise currently being used based on this information, means for proposing prices for merchandise being considered for new introduction, an emotion engine for analyzing user feedback, and means for proposing merchandise prices using a generative AI model.

[1225] Using a smartphone or PC, users input information such as company size, intended use, current product prices, and user feedback. This information is sent to the server, which receives it. Based on the information received, the server displays a list of the prices of the products currently being used. This information is displayed using a web browser or a dedicated application.

[1226] Next, the server uses an emotion engine to analyze the user's feedback. The emotion engine analyzes the user's feedback and detects positive or negative emotions. For example, the feedback "I'm satisfied with the price" is analyzed as a positive emotion.

[1227] The server then uses a generative AI model to propose a price for the new product. The generative AI model inputs information about the company's size, intended use, and current product price as prompts to generate an appropriate price proposal. Specific examples of prompts include the following:

[1228] Example prompt sentence:

[1229] Company size: Small to medium-sized enterprise, Usage: Online sales, Current prices: Product A: 1,000 yen, Product B: 2,000 yen. Based on this, please propose a price for the new product you are considering introducing.

[1230] The generated price proposal is displayed to the user, allowing them to receive an appropriate price proposal based on their company size and usage. Price proposals can also be made that reflect user feedback, resulting in proposals that are more satisfying.

[1231] The hardware used includes smartphones and PCs, and the software uses Python, a GUI toolkit, and the OpenAI API. Data processing involves converting user input data into prompt statements, and data calculation involves using OpenAI's generative AI model to make price suggestions and an emotion engine to analyze feedback.

[1232] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1233] Step 1:

[1234] Users use their smartphones or PCs to input information such as company size, intended use, current product price, and user feedback. The input information is then sent to the server. Input data includes company size (e.g., small and medium-sized enterprises), intended use (e.g., online sales), current product price (e.g., product A: 1,000 yen, product B: 2,000 yen), and user feedback (e.g., "I'm satisfied with the price").

[1235] Step 2:

[1236] The server displays a list of the prices of the products currently being used based on the information received. Data processing involves formatting the input product price information and displaying it in a visually easy-to-understand format for the user. The output is a list of the current product prices (e.g., product A: 1,000 yen, product B: 2,000 yen). A web browser or dedicated application is used to display the information.

[1237] Step 3:

[1238] The server uses an emotion engine to analyze user feedback. Input data includes user feedback (e.g., "I'm satisfied with the price"). The emotion engine analyzes the feedback and detects positive or negative emotions. Data processing involves text analysis of the feedback, and the output is an emotion analysis result (e.g., positive).

[1239] Step 4:

[1240] The server uses a generative AI model to propose a price for a new product. Input data includes company size, usage, and current product price information. A prompt is generated based on this information and input into the generative AI model. An example of a specific prompt is, "Please suggest a price for the new product we are considering introducing, based on the following: company size: small and medium-sized enterprise, usage: online sales, current prices: product A: 1,000 yen, product B: 2,000 yen." The generative AI model performs data calculations by analyzing the prompt and generating an appropriate price proposal. The output is a price proposal for the new product (e.g., product C: 1,500 yen).

[1241] Step 5:

[1242] The server displays the generated price proposal to the user. This can be done using a web browser or a dedicated application. The output is a price proposal in a format that the user can check (e.g., Product C: 1,500 yen). This allows the user to receive an appropriate price proposal based on the size of their company and the purpose of use.

[1243] Example 2

[1244] Next, a description will be given of Example 2 of Form 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."

[1245] Conventional product price proposal systems did not adjust prices based on user sentiment, which prevented them from fully increasing user satisfaction. Furthermore, they lacked a means to appropriately calculate the price of new products based on the price information of existing products. This sometimes caused stress for users, delaying the decision to introduce new products.

[1246] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1247] In this invention, the server includes: a means for inputting the user's company size, intended use, and prices of already-introduced products; a means for displaying a list of prices of currently-introduced products based on this information; a means for proposing prices for products being considered for new introduction; a means for recognizing the user's emotions and adjusting product prices based on those emotions; and a means for calculating product prices using a generative AI model. This allows for price proposals that take the user's emotions into consideration, thereby increasing user satisfaction. Furthermore, the system can appropriately calculate the price of new products based on price information for existing products, allowing for a rapid decision-making process for introducing new products.

[1248] "Company size" is an indicator that shows the size of a company, such as the number of employees, sales, and capital.

[1249] "Usage" is information indicating the purpose and situation in which the product will be used.

[1250] "Merchandise" refers to products or services that a company sells or uses.

[1251] "Means for inputting prices" refers to the interface or method for users to input price information for products they have already introduced into the system.

[1252] "Means for displaying prices in a list" refers to an interface or method for displaying the price information of the entered merchandise to the user in a list format.

[1253] "Means for proposing prices" refers to a method or system for proposing to users an appropriate price for a new product that is being considered for introduction.

[1254] "Emotion recognition means" refers to methods and techniques for detecting a user's emotional state and adjusting the system's behavior accordingly.

[1255] A "generative AI model" refers to a model that uses artificial intelligence techniques to analyze data and perform specific tasks.

[1256] "Means for calculating price" refers to a method or system for calculating the appropriate price of a product based on collected data.

[1257] This invention relates to a price proposal system for commercial products, and in particular to a system that proposes optimal prices to users using generative AI models and emotion recognition technology.

[1258] Hardware and software used

[1259] Hardware

[1260] Server: Processes data and runs generative AI models.

[1261] Terminal: The device (e.g., PC, smartphone) where the user enters information and checks the results.

[1262] software

[1263] Generative AI models: Use artificial intelligence models such as OpenAI GPT-4.

[1264] Database management system: Use a database such as MySQL to manage pricing information for existing products.

[1265] Emotion Recognition Engine: Software that recognizes user emotions and adjusts prices accordingly.

[1266] Program processing

[1267] server

[1268] The server first collects information entered by the user and pricing information for existing products. This information is stored in a database. Next, the server uses a generative AI model to calculate an appropriate price for the new product being considered for introduction. For example, OpenAI's GPT-4 is used as the generative AI model. The server then proposes the calculated price to the user.

[1269] Terminal

[1270] The terminal is responsible for transmitting information entered by the user to the server, including product characteristics, market conditions, etc. The terminal also displays price proposals received from the server to the user.

[1271] User

[1272] Users input information about the product they are considering introducing through their terminal, including the product's characteristics and market conditions. The user also checks the price suggested by the server and adjusts the price using the emotion engine if necessary.

[1273] Specific examples

[1274] For example, if a user wants to know the price of a new smartphone they are considering purchasing, they input the smartphone's characteristics (e.g., memory capacity, camera performance, battery life, etc.) through their device. The server retrieves pricing information for existing smartphones from a database and calculates an appropriate price using a generative AI model (GPT-4). Furthermore, if the user is feeling stressed, the emotion engine collects that information and reduces the user's stress by lowering the price.

[1275] Prompt Sentence Examples

[1276] "The characteristics of the new product we are considering introducing are as follows. The market situation is currently stable. Please propose an appropriate price for this product based on the pricing information of existing products."

[1277] In this way, it is possible to propose prices that take into account the user's feelings, thereby increasing user satisfaction. In addition, it is possible to appropriately calculate the price of a new product based on the price information of existing products, allowing for a quick decision on introducing the product.

[1278] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1279] Step 1:

[1280] The user uses a terminal to input information about a new product they are considering introducing. Specifically, they input the product's characteristics (e.g., product name, specifications, desired price range, etc.) and market conditions (e.g., balance of supply and demand, competitors' prices, etc.). The input data is information about the product's characteristics and market conditions. This data is saved on the terminal.

[1281] Step 2:

[1282] The terminal sends the information entered by the user to the server. The data sent includes product characteristics information and market situation information. The data is encrypted before transmission to ensure security. The server stores the received data in a database.

[1283] Step 3:

[1284] The server collects pricing information for existing products from a database. The collected data includes past sales data and market trend information. This data, along with product characteristics and market situation information, is input into the generative AI model.

[1285] Step 4:

[1286] The server uses a generative AI model (e.g., OpenAI GPT-4) to calculate an appropriate price for a new product being considered for introduction. Specifically, the following prompt is input into the generative AI model: "The characteristics of the new product being considered for introduction are as follows. The market situation is currently stable. Please propose an appropriate price for this product based on the price information of existing products." The generative AI model then outputs a price proposal based on the input data.

[1287] Step 5:

[1288] The server uses an emotion engine to recognize the user's emotions. The user's emotion data is collected in real time from the device. For example, if the user is feeling stressed, the emotion engine collects that information and reduces the user's stress by lowering the price of the product. The output of the emotion engine is the adjusted price.

[1289] Step 6:

[1290] The server sends the calculated price and the adjustment results from the emotion engine to the terminal. The data sent is the adjusted price information. The data is encrypted again before transmission to ensure security.

[1291] Step 7:

[1292] The user checks the price proposal sent from the server via the terminal. The user considers introducing the product based on the proposed price. The output data is the final price proposal.

[1293] (Application example 2)

[1294] Next, a description will be given of Application Example 2 of Form 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."

[1295] Conventional product price suggestion systems propose prices without considering the user's feelings, which can lead to a decrease in user satisfaction. In addition, price suggestions based on existing product price information and user input information are insufficient, making it difficult to set appropriate prices.

[1296] 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.

[1297] In this invention, the server includes means for inputting the customer's company size, intended use, and prices of already introduced products, means for displaying a list of prices of currently used products based on this information, means for proposing prices of products being considered for new introduction, and means for recognizing the user's emotions and adjusting the prices of products based on those emotions. This makes it possible to propose appropriate prices that take the user's emotions into consideration, thereby improving user satisfaction.

[1298] "Customer's company size" is information that indicates the size of the company, such as the number of employees and sales.

[1299] "Usage" is information indicating the purpose and situation in which the product will be used.

[1300] "Price of already introduced products" refers to price information for products currently being used by the user.

[1301] An "input means" is a method or device for receiving information from a user.

[1302] The "means for displaying a list of prices of merchandise currently being used" refers to a method or device for displaying in list form the prices of merchandise currently being used by the user.

[1303] The "means for proposing a price for a new product being considered for introduction" refers to a method or device for proposing an appropriate price for a new product being considered for introduction by a user.

[1304] "Generative AI" is an artificial intelligence technology that generates new information based on existing data and user input.

[1305] A "means for recognizing a user's emotions" is a method or device for detecting and understanding a user's emotional state.

[1306] A "means for adjusting the price of a product based on emotions" is a method or device for changing the price of a product depending on the emotional state of the user.

[1307] "BtoB" is a term that refers to business-to-business transactions.

[1308] "In-house tools" are tools and software for use within a company.

[1309] A system for implementing the present invention includes a server, a user terminal, and a generative AI model. A specific embodiment of this system will be described below.

[1310] System Configuration

[1311] The server includes the following means:

[1312] 1. A way to input the size of your company, the purpose of use, and the prices of products you have already introduced

[1313] 2. A method to display a list of the prices of the products currently being used based on this information

[1314] 3. A way to propose prices for new products being considered for introduction

[1315] 4. A way to recognize user emotions and adjust product prices based on those emotions

[1316] Program processing

[1317] The server receives information sent from the user's device, uses a generative AI model to propose prices for new products being considered for introduction, and uses an emotion recognition engine to analyze the user's emotions and adjust prices based on those emotions.

[1318] Hardware and software used

[1319] Hardware: Servers, user devices (smartphones, tablets, PCs, etc.)

[1320] Software: OpenAI generative AI model, emotion recognition engine

[1321] Data processing and calculation

[1322] 1. Data entry: Company size, usage, and pricing information for existing products are sent from the user's terminal to the server.

[1323] 2. Price proposal: The server uses the generative AI model to calculate the appropriate price for the new product being considered for introduction.

[1324] 3. Emotion Recognition: The server sends the user's input text to the emotion recognition engine to analyze the user's emotions.

[1325] 4. Price Adjustment: The server adjusts the suggested price based on the emotion information obtained from the emotion recognition engine.

[1326] Specific examples

[1327] For example, if a user enters "I would like to know the price of a new smartphone," the following processing occurs:

[1328] Prompt Sentence Examples

[1329] Existing product price information: [1000, 1500, 2000, 2500]

[1330] User Input: I want to know the price of a new smartphone.

[1331] Please suggest an appropriate price for the newly introduced product.

[1332] The server inputs this prompt into a generative AI model to suggest an appropriate price, then uses an emotion recognition engine to analyze the user's emotions and, for example, discount the suggested price by 10% if the user is feeling stressed.

[1333] In this way, it becomes possible to propose an appropriate price that takes into account the user's feelings, thereby improving user satisfaction.

[1334] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1335] Step 1:

[1336] The user's terminal inputs information about the company's size, intended use, and the price of existing products. This information becomes the basis for proposing prices for products the user is considering introducing. The input information is sent to the server.

[1337] Step 2:

[1338] The server receives information about the company size, intended use, and price of existing products sent from the user's device. Based on the received information, it generates a prompt sentence to input into the generative AI model. An example of a prompt sentence is, "Price information for existing products: [1000, 1500, 2000, 2500] User input: I would like to know the price of a new smartphone. Please suggest an appropriate price for the newly introduced product."

[1339] Step 3:

[1340] The server inputs the generated prompt sentence into the generative AI model to calculate the appropriate price for the new product being considered for introduction. The generative AI model performs data calculations based on the price information of existing products and the information input by the user, and outputs the appropriate price.

[1341] Step 4:

[1342] The server receives the price information output by the generative AI model and sends it to the user's device, at which point the user can confirm the proposed price.

[1343] Step 5:

[1344] The user terminal checks the proposed price and inputs emotional information, such as "I feel the price of the new smartphone is too high." The input emotional information is then sent to the server.

[1345] Step 6:

[1346] The server receives emotion information sent from the user terminal and inputs it into an emotion recognition engine. The emotion recognition engine analyzes the user's emotional state and outputs emotion information. For example, it may determine that the user is feeling "stressed."

[1347] Step 7:

[1348] The server adjusts the proposed price based on the emotional information output from the emotion recognition engine. For example, if the user is feeling stressed, the proposed price is discounted by 10%. The adjusted price information is then sent to the user's device.

[1349] Step 8:

[1350] The user terminal receives the adjusted price information and displays it to the user, who can then confirm the final price and consider purchasing.

[1351] Through the above processing steps, an appropriate price proposal that takes into account the user's feelings is realized.

[1352] Example 3

[1353] Next, a description will be given of Example 3 of Form Example 3. 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."

[1354] Conventional product pricing systems proposed prices based on the size of the company and the intended use, but did not optimize prices by taking into account the user's feelings. Therefore, there is a need for optimizing price proposals based on the user's feelings. In addition, there was a lack of functionality to store the user's final decision in a database and use it as reference data for future price decisions.

[1355] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[1356] In this invention, the server includes means for collecting user emotion data, means for analyzing the user emotion data using an emotion engine, and means for optimizing the price of merchandise based on the analysis results, thereby enabling optimization of price proposals based on the user's emotions.

[1357] "Company size" is an indicator that shows the size of a company, such as the number of employees, sales, and capital.

[1358] "Usage" refers to the purpose and situation in which a product or service is used.

[1359] "Merchandise" is a general term for goods and services sold or provided by a company.

[1360] "Emotion data" is information about emotions obtained from the user's facial expressions, voice, text, etc.

[1361] An "emotion engine" is software or hardware that analyzes a user's emotion data and identifies the type and intensity of the emotion.

[1362] "Price optimization" is the process of adjusting the price of a product to the most appropriate value based on collected data and analysis results.

[1363] A "generative AI model" is an algorithm or model that uses artificial intelligence techniques to generate data and perform specific tasks.

[1364] A "database" is a system for efficiently storing, managing, and retrieving data.

[1365] "User's final decision" refers to the price that the user selects after reviewing the price proposals presented to them.

[1366] The system of the present invention is a B2B tool used within a company to determine the price of a new product that the company is considering introducing. The system is equipped with an emotion engine and optimizes the price proposal for the product based on the user's emotions.

[1367] Hardware and software used

[1368] Server: A central processing unit for data processing and sentiment analysis.

[1369] Terminal: The device (e.g., PC, tablet, smartphone) where a user enters data and sees the results.

[1370] Emotion engine: Software for analyzing user emotion data (e.g., IBM Watson, Microsoft Azure Emotion API).

[1371] Generative AI model: An artificial intelligence model for generating pricing proposals for products.

[1372] Program processing

[1373] 1. User login and data entry

[1374] The user logs into the system and enters detailed information about the product (e.g., product name, category, desired price range).

[1375] The terminal sends the user's login information to the server for authentication.

[1376] 2. Collecting Emotional Data

[1377] The device collects user input data in real time and also captures facial expressions and voice data.

[1378] The device converts this data into a format for transmission to the emotion engine.

[1379] 3. Emotion analysis

[1380] The server calls the emotion engine's API and sends the user's facial expressions and voice data.

[1381] The emotion engine analyzes the data and identifies the type and intensity of emotion.

[1382] 4. Optimize your price proposals

[1383] The server runs a price optimization algorithm based on the emotion data.

[1384] For example, if the user is feeling "delighted," it will generate a suggestion to increase the price by 10%.

[1385] 5. Submitting a price proposal

[1386] The server sends the generated price proposal to the terminal.

[1387] The terminal displays price proposals in graphs and charts, providing users with a visually easy-to-understand presentation.

[1388] 6. User's final decision and data storage

[1389] The user reviews the proposed price and decides on the final price.

[1390] The terminal transmits the user's final decision to the server.

[1391] The server stores the final decision in a database and uses it as reference data for future pricing decisions.

[1392] Specific examples

[1393] For example, consider a company using this system to determine the price of a new software product. A user logs in to the system and enters details about the software and their desired price range. The emotion engine analyzes the user's input data and identifies the user's feelings of joy. Based on this emotion data, the server makes a proposal to set the software's price higher than usual. The user confirms this proposal and decides on the final price.

[1394] Prompt Sentence Examples

[1395] Examples of prompts to input to a generative AI model include:

[1396] "To determine the price of a new software product, collect user sentiment data and analyze it using an emotion engine. If users are delighted, propose a 10% price increase."

[1397] By using this prompt sentence, the generative AI model executes a process to optimize the price proposal based on the user's emotions. The flow of the identification process in Example 3 will be described with reference to FIG.

[1398] Step 1:

[1399] User Login and Data Entry

[1400] A user logs in to the system using a user ID and password.

[1401] The terminal sends the user's login information to the server for authentication.

[1402] If the authentication is successful, the server displays the dashboard screen to the user.

[1403] The user enters detailed information about the product (e.g., product name, category, desired price range) and clicks the "Submit" button.

[1404] Input: User ID, password, product details

[1405] Output: Authentication results, detailed product information

[1406] Step 2:

[1407] Collecting Emotional Data

[1408] The terminal collects user input data in real time.

[1409] The device also collects facial expressions and voice data as the user types, and prepares this data to send to the emotion engine.

[1410] Input: User input data, facial expression data, voice data

[1411] Output: Formatted data to send to the emotion engine

[1412] Step 3:

[1413] Emotion analysis

[1414] The server calls the emotion engine's API and sends the user's facial expressions and voice data.

[1415] The emotion engine analyzes the data and identifies the type and intensity of emotion.

[1416] The server receives the analysis results and uses them for further processing.

[1417] Input: facial expression data, voice data

[1418] Output: Analysis results of emotion type and intensity

[1419] Step 4:

[1420] Optimizing price proposals

[1421] The server runs a price optimization algorithm based on the emotion data.

[1422] For example, if the user feels "joyed," the server generates a proposal to set the price of the product higher than usual.

[1423] Input: Analysis results of type and intensity of emotion, detailed product information

[1424] Output: Optimized price proposal

[1425] Step 5:

[1426] Presenting a price proposal

[1427] The server sends the generated price proposal to the terminal.

[1428] The terminal displays price proposals in graphs and charts, providing users with a visually easy-to-understand presentation.

[1429] Input: Optimized Price Proposal

[1430] Output: Display of price proposal presented to user

[1431] Step 6:

[1432] User's final decision and data storage

[1433] The user reviews the proposed price and decides on the final price.

[1434] The terminal transmits the user's final decision to the server.

[1435] The server stores the final decision in a database and uses it as reference data for future pricing decisions.

[1436] Input: User's final decision

[1437] Output: Final decision data stored in the database

[1438] (Application example 3)

[1439] Next, a description will be given of Application Example 3 of Form Example 3. 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."

[1440] Conventional product price proposal systems determined prices without considering user emotions, making it difficult to maximize users' purchasing motivation. Furthermore, fixed pricing made it difficult to flexibly respond to market fluctuations and user emotions, making it difficult to maximize profits. This meant that companies needed time and effort to set appropriate prices, preventing them from offering efficient price proposals.

[1441] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 3 is realized by the following means.

[1442] In this invention, the server includes means for inputting the size of the customer's company, its intended use, and the prices of products already introduced, means for displaying a list of prices of products currently being used based on this information, means for proposing prices for products being considered for new introduction, means for analyzing user emotions, and means for dynamically changing product prices based on the analyzed emotions. This enables flexible price proposals based on user emotions, allowing companies to efficiently maximize profits.

[1443] "Company size" is an indicator that shows the size of a company, such as the number of employees, sales, and capital.

[1444] "Use" refers to how the product is used to fulfill a specific purpose or function.

[1445] "Merchandise" refers to goods or services that a company sells or uses.

[1446] "Means for inputting prices" refers to a method or device for inputting price information of merchandise into the system.

[1447] The "means for displaying prices in a list" refers to a method or device for displaying input price information in a list format.

[1448] "Means for proposing a price" refers to a method or device for proposing an appropriate price for a product.

[1449] "Means for analyzing user emotions" refers to a method or device for analyzing emotions from a user's facial expressions, voice, etc.

[1450] "Means for dynamically changing the price of a product based on emotion" refers to a method or device for changing the price of a product in real time based on analyzed emotion information.

[1451] A system for carrying out this invention is configured as follows: The server includes means for inputting the size of the customer's company, intended use, and prices of merchandise already introduced, means for displaying a list of prices of merchandise currently being used based on this information, means for proposing prices for merchandise being considered for new introduction, means for analyzing user emotions, and means for dynamically changing merchandise prices based on the analyzed emotions.

[1452] Hardware and software used

[1453] Hardware: Smartphones, smart glasses, head-mounted displays

[1454] Software: OpenCV, Keras, TensorFlow

[1455] Data processing and calculation

[1456] The server first receives as input the customer's company size, intended use, and prices of products already in use. Based on this information, it displays a list of prices for products currently in use. Next, it uses a generative AI model to propose prices for products that are being considered for new introduction.

[1457] To analyze user emotions, we use cameras and microphones installed on smartphones, smart glasses, and head-mounted displays. We process the video and audio data acquired from these devices using OpenCV to perform face detection and audio analysis. We then use a pre-trained emotion recognition model using Keras and TensorFlow to analyze user emotions in real time.

[1458] Based on the analyzed emotion information, the server dynamically changes the price of the product. For example, if the user expresses "happiness," the price of the product is increased by 10% to maximize profits.

[1459] Specific examples

[1460] When a user wears smart glasses and browses a shopping site, the system analyzes the user's facial expressions to detect the emotion of happiness, and as a result, the system increases the displayed product price by 10%.

[1461] Prompt Sentence Examples

[1462] When a user wears smart glasses and browses a shopping site, the system analyzes the user's facial expressions and detects the emotion of happiness, resulting in the system increasing the displayed product price by 10%.

[1463] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[1464] Step 1:

[1465] The server receives as input the customer's company size, usage, and prices of existing products. The input data includes the company's number of employees, sales, capital, and pricing information for existing products. From this, the server obtains basic information about the company and pricing data for existing products.

[1466] Step 2:

[1467] The server displays a list of prices for currently used products based on the acquired company size, usage, and price information for existing products. It searches the database for price information for the relevant products and generates data for display in list format. This allows users to check the prices of the products they are currently using at a glance.

[1468] Step 3:

[1469] The server uses a generative AI model to propose prices for new products that are being considered for introduction. The server inputs the company size, intended use, and pricing information for existing products into the generative AI model, and outputs the optimal price. This allows users to receive appropriate pricing proposals for new products.

[1470] Step 4:

[1471] The device (smartphone, smart glasses, head-mounted display) captures the user's facial expressions and voice in real time through a camera and microphone. The captured video and audio data is preprocessed using OpenCV to perform face detection and voice analysis. This prepares the data for analyzing the user's emotions.

[1472] Step 5:

[1473] The device inputs the preprocessed data into a pre-trained emotion recognition model using Keras and TensorFlow to analyze the user's emotions in real time. The analysis results are output as the user's emotions (e.g., joy, sadness, surprise), thereby identifying the user's emotional state.

[1474] Step 6:

[1475] The server dynamically changes the price of the product based on the analyzed emotional information. For example, if the user expresses "happiness," the price of the product is increased by 10%. Using the emotional information and existing price information as input data, the server calculates and outputs a new price. This allows for price suggestions that correspond to the user's emotions.

[1476] Step 7:

[1477] The server sends the dynamically updated price information to the terminal and displays it to the user, who can then check the optimized price based on sentiment, allowing the user to obtain the best price information in real time.

[1478] 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.

[1479] 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> ) 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.

[1480] Another example of generative AI is Gemini (internet search engine). <url: https: gemini.google.com ?hl="ja">) are mentioned.

[1481] 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.

[1482] [Third embodiment]

[1483] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1484] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[1485] 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).

[1486] 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.

[1487] 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.

[1488] 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).

[1489] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1490] 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.

[1491] 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.

[1492] 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.

[1493] 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.

[1494] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[1495] "Example 1"

[1496] The system of the present invention is equipped with a means for inputting the customer's company size, intended use, and prices of products already in use. Specifically, this information can be input through a user interface. It also has a means for displaying a list of prices of products currently in use based on this information. This allows users to check the price information of their company's products at a glance.

[1497] "Example 2"

[1498] Furthermore, the system of the present invention includes a means for proposing prices for new products that are being considered for introduction. This means uses a generation AI to propose prices for the products. Specifically, the AI ​​calculates an appropriate price for the new product based on the price information of existing products and information entered by the user, and proposes it to the user.

[1499] "Example 3"

[1500] The system of the present invention can be used as a tool for in-company use in B2B. A specific example of its use is when a company is considering introducing a new product and is deciding on the price, the system is used to propose an appropriate price, and the price is then decided based on the results.

[1501] The processing flow of each embodiment will be described below.

[1502] "Example 1"

[1503] Step 1: The user enters their company size, intended use, and the prices of products already in use through the system's user interface.

[1504] Step 2: The system will display a list of the prices of the products currently being used based on the information entered. This list is organized so that users can check the pricing information of their company's products at a glance.

[1505] "Example 2"

[1506] Step 1: The user enters information about the new product they are considering introducing into the system. Step 2: The system's generation AI calculates the appropriate price for the new product based on the price information of existing products and the information entered by the user.

[1507] Step 3: The AI ​​generator proposes the calculated price to the user, who can then decide the price of the product based on this proposal.

[1508] "Example 3"

[1509] Step 1: Companies use this system when determining the price of new products they are considering introducing.

[1510] Step 2: The company enters the necessary information into the system and receives a price proposal from the generative AI.

[1511] Step 3: The company determines the price of the product based on the price proposals received.

[1512] Example 1

[1513] Next, a description will be given of Example 1 of Form 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."

[1514] With conventional systems, it was difficult for companies to check the pricing information of their own products at a glance, and there was a lack of means to appropriately propose prices for new products that companies were considering introducing. As a result, companies were unable to efficiently manage and compare pricing information for products, making it difficult to select the most suitable products.

[1515] 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.

[1516] In this invention, the server includes means for inputting the size of the customer's company, its intended use, and the prices of products already introduced, means for displaying a list of prices of products currently being used based on this information, means for saving the input data in a database, means for searching and filtering product price information from the database, means for generating a list of filtered product price information, means for displaying the generated price information, and means for proposing prices for products being considered for new introduction. This allows companies to check the price information of their own products at a glance, and further enables them to receive appropriate price proposals for products being considered for new introduction.

[1517] "Company size" is an indicator that shows the size of a company, such as the number of employees and sales.

[1518] "Usage" refers to the purpose for which a company uses a particular product or service.

[1519] "Merchandise" is a general term for goods and services that a company purchases or uses.

[1520] "Price" refers to the amount of money paid for goods or services.

[1521] "User interface" refers to the means, such as a screen or input form, through which a user interacts with a system.

[1522] A "database" is a system for efficiently storing, searching, and managing data.

[1523] "Filtering" refers to the process of selecting data based on specific conditions.

[1524] A "generative AI model" refers to an algorithm or system that uses artificial intelligence to analyze data and generate new information or suggestions.

[1525] A "prompt" refers to an instruction or question to be input into a generative AI model.

[1526] "Business-to-business transactions" refer to transactions in which companies buy and sell goods and services.

[1527] MODE FOR CARRYING OUT THE INVENTION

[1528] This invention is a system that allows companies to check the pricing information of their own products at a glance and receive appropriate pricing suggestions for products they are considering introducing. The system provides a user interface for users to input information about the company's size, intended use, and the prices of products already introduced. The system also has the ability to save the input data in a database, search and filter product pricing information from the database, and display it in a list format.

[1529] Hardware and software used

[1530] Device: PC, smartphone, or other device

[1531] Server: A server that processes data and manages the database

[1532] Database management systems: MySQL, PostgreSQL, etc.

[1533] User Interface: Interface accessible through a web browser

[1534] Generative AI model: An artificial intelligence algorithm for suggesting product prices

[1535] Program processing

[1536] Users access the system's user interface using a terminal. They input information such as the size of their company, the purpose of use, and the prices of products they have already introduced. This input data is then sent from the terminal to the server.

[1537] The server analyzes the received data and stores it in a database management system (e.g., MySQL). The server searches for product price information stored in the database and filters it based on the information entered by the user. The filtered product price information is generated in list format and sent back to the terminal.

[1538] The terminal displays the received price information on the user interface, allowing users to check the price information of their company's products at a glance.The system also has a function that uses a generative AI model to suggest prices for new products that are being considered for introduction.

[1539] Specific examples

[1540] As a concrete example, consider a case where a user is a small or medium-sized enterprise and uses IT services. The user inputs the prices of "cloud storage" and "project management tools" as products that have already been introduced.

[1541] Example prompt sentence:

[1542] Company size: Small business

[1543] Usage: IT services

[1544] Prices of already introduced products:

[1545] Cloud storage: 5000 yen / month

[1546] Project management tool: 3000 yen / month

[1547] After entering this prompt, the system will use this information to display a list of prices for the products you are currently using. For example, the following results will be displayed:

[1548] Prices for the products currently in use:

[1549] Cloud storage: 5000 yen / month

[1550] Project management tool: 3000 yen / month

[1551] Furthermore, the generative AI model is used to suggest prices for new products that users are considering introducing, allowing them to easily check pricing information for their company's products and select the most suitable products.

[1552] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1553] Step 1:

[1554] A user accesses the system's user interface using a terminal. The user opens a web browser and accesses the system's URL, which displays the user interface. The input is the user accessing the system's URL, and the output is the display of the user interface.

[1555] Step 2:

[1556] The user enters the size of the company, the purpose of use, and the price of the products that have already been introduced. The user enters the size of the company (e.g., small and medium-sized enterprise), the purpose of use (e.g., IT services), and the price of the products that have already been introduced (e.g., cloud storage: 5,000 yen / month, project management tool: 3,000 yen / month) into the input form on the displayed user interface. The input is the data that the user entered into the input form, and the output is the preparation of the input data for transmission.

[1557] Step 3:

[1558] The terminal sends the data entered by the user to the server. The terminal sends the data entered by the user to the server as an HTTP request. At this time, the data is sent in an appropriate format such as JSON. The input is the data entered by the user, and the output is the data sent to the server.

[1559] Step 4:

[1560] The server saves the received data in a database. The server analyzes the received data and saves it in a database management system (e.g. MySQL). When saving, it inserts the data into the appropriate table. The input is the data sent from the terminal, and the output is data saved in the database.

[1561] Step 5:

[1562] The server searches the database for product price information and filters it. The server searches for product price information stored in the database. The search results are filtered based on the company size and purpose of use entered by the user. For example, extract only price information for products related to IT services for small and medium-sized enterprises. The input is data stored in the database, and the output is filtered price information.

[1563] Step 6:

[1564] The server generates the price information of the filtered products in a list format. The server formats the price information of the filtered products in a list format. At this time, the data is generated in HTML or JSON format. The input is the filtered price information, and the output is the price information in a list format.

[1565] Step 7:

[1566] The server sends the generated price information to the terminal. The server sends the generated price information to the terminal as an HTTP response. The data is sent in a format that is easy for the user to understand. The input is price information in list format, and the output is data sent to the terminal.

[1567] Step 8:

[1568] The terminal displays the received price information on the user interface. The terminal displays the received price information on the user interface. The user can check the displayed list and understand the price information of their company's products at a glance. The input is the price information sent from the server, and the output is the display on the user interface.

[1569] (Application example 1)

[1570] Next, a description will be given of Application Example 1 of Form 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."

[1571] With conventional systems, it was difficult for companies to easily check the pricing information of their own products, make price comparisons, and make price adjustments. Furthermore, there was a lack of means to compare prices with market price data and make appropriate price adjustments, making it impossible for companies to set prices in line with market trends. For this reason, effective price management is needed to maintain a company's competitive edge.

[1572] 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.

[1573] In this invention, the server includes means for inputting the size of the customer's company, the purpose of use, and the prices of already introduced products, means for displaying a list of prices of currently used products based on this information, means for proposing prices for products being considered for new introduction, means for comparing with market price data and proposing price adjustments, and means for displaying the price comparison results. This allows companies to easily check price information for their own products and make price comparisons and price adjustments.

[1574] "Company size" is an indicator that shows the size of a company, number of employees, sales, etc.

[1575] "Usage" refers to the use of a particular purpose or method of use.

[1576] "Merchandise" is a general term for the products and services that a company handles.

[1577] "Price list display" is a function that displays the prices of the currently used products in a list format based on the input information.

[1578] A "price proposal" is the act of presenting the price of a new product that is being considered for introduction.

[1579] "Market Price Data" refers to price information for a commodity in a particular market.

[1580] "Price adjustment proposal" is the act of proposing appropriate price changes by comparing with market price data.

[1581] "Price comparison results" show the results of comparing the price of the product currently being used with market price data.

[1582] "Generative AI" is a system that uses artificial intelligence technology to generate data and make analysis and suggestions.

[1583] A system for implementing this invention includes a server, a user terminal, and a generative AI model. The server receives information entered by the user about the company size, intended use, and pricing of products already introduced, and displays a list of prices for currently used products based on this information. The server then compares the prices with market price data, proposes price adjustments, and provides the results to the user.

[1584] The user terminal is a device such as a smartphone or tablet, and provides an interface for users to input information such as company size, usage, and product prices. The data entered by the user is sent to the server, which processes it and generates a price list.

[1585] The generative AI model runs on a server and proposes price adjustments based on data entered by the user and market price data. The generative AI model is implemented using software such as Python, Pandas, and Scikit-learn. Specifically, it compares the product price entered by the user with market price data and performs a regression analysis to propose appropriate price adjustments.

[1586] For example, consider the case where a user inputs the following data:

[1587] Company size: Small business

[1588] Usage: Manufacturing industry

[1589] Item Price: [1000, 2000, 3000]

[1590] Market price data: [1100, 2100, 3100]

[1591] The server receives this data and displays a list of prices for the currently used products. The generative AI model then compares it with market price data to propose price adjustments and provides the results to the user. This allows users to easily check the price information of their company's products, make price comparisons, and make price adjustments.

[1592] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1593] Step 1:

[1594] The user uses a terminal to input the company size, intended use, and the prices of the products already introduced.

[1595] Input: Company size, usage, product price.

[1596] Specific operation: The user enters the company size (e.g., small and medium-sized enterprise), purpose of use (e.g., manufacturing), and product price (e.g., 1,000 yen, 2,000 yen, 3,000 yen) through the interface of a smartphone or tablet.

[1597] Output: The input data is sent to the server.

[1598] Step 2:

[1599] The server processes the data received from the user and displays a list of the prices of the products currently being used.

[1600] Input: Company size, purpose of use, and product price entered by the user.

[1601] Specific operation: The server converts the received data into a data frame and generates a list of product prices.

[1602] Output: A list of product prices is generated and displayed on the user's device.

[1603] Step 3:

[1604] The server retrieves market price data and uses a generative AI model to suggest price adjustments.

[1605] Input: User-entered product price and market price data.

[1606] Specific operation: The server obtains market price data (e.g., 1,100 yen, 2,100 yen, 3,100 yen) and performs regression analysis using a generative AI model (using Python, Pandas, and Scikit-learn).

[1607] Output: A price adjustment proposal is generated.

[1608] Step 4:

[1609] The server transmits the price adjustment proposal results to the user terminal and displays them to the user.

[1610] Input: The proposed price adjustment result.

[1611] Specific operation: The server sends the generated price adjustment proposal results to the user terminal, and the user confirms them on the interface.

[1612] Output: The proposed price adjustment is displayed on the user's terminal.

[1613] Step 5:

[1614] The user adjusts the price of the product based on the price adjustment proposal results.

[1615] Input: The proposed price adjustment result.

[1616] Specific operation: The user adjusts the price of their company's products based on the proposed price adjustment results.

[1617] Output: The adjusted price of the product.

[1618] Example 2

[1619] Next, a description will be given of Example 2 of Form 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."

[1620] Conventional product price proposal systems have difficulty in calculating the appropriate price of new products based on the price information of existing products. Furthermore, they lack a means to effectively utilize the information entered by users to make highly accurate price proposals. This means that companies need time and effort to set prices for new products, potentially resulting in a loss of competitiveness.

[1621] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1622] In this invention, the server includes means for inputting the customer's company size, intended use, and prices of already introduced products, means for displaying a list of prices of currently used products based on this information, means for inputting information on products being considered for new introduction, means for preprocessing price information on existing products and information on products being considered for new introduction, means for inputting the preprocessed data into a generative AI model to calculate an appropriate price, and means for proposing price information obtained from the generative AI model. This enables users to set prices for new products efficiently and accurately.

[1623] "Customer's company size" is information indicating the size of the company, such as the number of employees, sales, and capital.

[1624] "Usage" is information indicating the purpose and situation in which the product will be used.

[1625] "Prices of already introduced products" refers to price information of products currently being used by the company.

[1626] "Information on new products being considered for introduction" refers to information such as the type, features, and target market of the products that a company is considering purchasing.

[1627] "Preprocessing" refers to the processing of data before inputting it into a generative AI model, such as data cleaning, normalization, and feature extraction.

[1628] A "generative AI model" is a model that uses artificial intelligence technology to analyze data and calculate appropriate prices.

[1629] A "price proposal" is the act of presenting price information obtained from a generative AI model to a user.

[1630] "In-house tools" refers to software and systems for internal use by a company.

[1631] This invention relates to a system for proposing prices for commercial products. Specifically, it is a system that uses a generative AI model to calculate an appropriate price for a commercial product that is being considered for new purchase and proposes it to the user.

[1632] System configuration

[1633] This system consists of three main components: a server, a terminal, and a user.

[1634] server

[1635] The server has the following functions:

[1636] 1. Data Collection:

[1637] The server retrieves pricing information for existing products from a database that includes information such as past product prices, sales history, and demand forecasts.

[1638] 2. Data Preprocessing:

[1639] The server preprocesses the acquired price information of existing products and the information entered by the user, specifically by cleaning the data, normalizing it, and extracting features.

[1640] 3. Price Calculation:

[1641] The server then inputs the preprocessed data into a generative AI model, such as OpenAI's GPT-4.

[1642] The server inputs the following prompt to the generative AI model:

[1643] "The information about the new product we are considering introducing is as follows: Type: Electronic device, Features: High-performance battery, Target market: Young people. Please propose an appropriate price for this product based on the pricing information of existing products."

[1644] The generative AI model calculates the appropriate price for a new product based on the input information.

[1645] 4. Price Proposal:

[1646] The server proposes price information obtained from the generative AI model to the user.

[1647] Terminal

[1648] The terminal is a device where the user enters information and sees the proposed price. The terminal has the following functions:

[1649] 1. Enter your information:

[1650] The user uses a terminal to input information about the new product they are considering introducing, such as the product type, features, and target market.

[1651] 2. Price Check:

[1652] The user can check the price proposed by the server through the terminal.

[1653] User

[1654] The user is responsible for operating the system and setting the prices of the products. The user performs the following operations:

[1655] 1. Enter your information:

[1656] The user uses the terminal to input information about a new product they are considering introducing. For example, they input information about a "smartphone with a high-performance battery."

[1657] 2. Price Check:

[1658] The user can check the price proposed by the server and make corrections or reevaluations as necessary.

[1659] Specific examples

[1660] For example, if a user is looking to purchase a new smartphone with a high-performance battery, they can input the following prompt into the generative AI model:

[1661] "The information about a new product we are considering introducing is as follows: Type: Smartphone, Features: High-performance battery, Target market: Young people. Please propose an appropriate price for this product based on the pricing information of existing products."

[1662] The generative AI model calculates the appropriate price for a new smartphone based on past price information and information entered by the user. The server then proposes this price information to the user, who can then check the price via their device.

[1663] In this way, users can set prices for new products efficiently and accurately.

[1664] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1665] Step 1: Data collection

[1666] The server retrieves price information for existing products from the database.

[1667] Input: Database connection information, query

[1668] Data processing: Extract information such as past product prices, sales history, and demand forecasts from the database.

[1669] Output: A list of retrieved price information

[1670] Step 2: Enter user information

[1671] The user inputs information about the new product they are considering introducing into the terminal.

[1672] Input: Information on product type, features, target market, etc.

[1673] Data processing: Sending the entered information to the system.

[1674] Output: Product information entered by the user

[1675] Step 3: Data Preprocessing

[1676] The server preprocesses the acquired price information of existing products and the information input by the user.

[1677] Input: Price information of existing products, product information entered by the user

[1678] Data processing: Data cleaning, normalization, and feature extraction, such as imputing missing values ​​and correcting outliers.

[1679] Output: Preprocessed dataset

[1680] Step 4: Price calculation

[1681] The server inputs the preprocessed data into a generative AI model.

[1682] Input: Preprocessed dataset

[1683] Data calculation: Enter a prompt into the generative AI model to calculate an appropriate price.

[1684] Example prompt sentence:

[1685] "The information about a new product we are considering introducing is as follows: Type: Smartphone, Features: High-performance battery, Target market: Young people. Please propose an appropriate price for this product based on the pricing information of existing products."

[1686] Output: Price information obtained from the generative AI model

[1687] Step 5: Price Proposal

[1688] The server proposes price information obtained from the generative AI model to the user.

[1689] Input: Price information obtained from a generative AI model

[1690] Data processing: Convert the proposal into a format that is easy for users to understand.

[1691] Output: Proposed pricing information

[1692] Step 6: Price confirmation

[1693] The user confirms the proposed price through the terminal.

[1694] Input: Proposed pricing information

[1695] Data processing: Display suggested pricing information.

[1696] Output: Price information confirmed by the user

[1697] In this way, users can set prices for new products efficiently and accurately.

[1698] (Application example 2)

[1699] Next, a description will be given of Application Example 2 of Form 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."

[1700] Conventional product price proposal systems have difficulty in proposing appropriate prices for new products based on information such as the price information of existing products, company size, and intended use. Furthermore, the accuracy of price proposals is low, making it impossible to calculate the optimal price for the user. Furthermore, the price proposal process is often done manually, which is time-consuming and labor-intensive.

[1701] The specification processing by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for inputting the customer's company size, intended use, and prices of already introduced products, means for displaying a list of prices of currently used products based on this information, means for proposing prices of products being considered for new introduction, and means for calculating an appropriate price for a new product using a generative AI model and proposing it to the user. This enables the user to quickly and accurately receive an optimal price proposal using the generative AI model based on price information of existing products and the characteristics of the new product.

[1702] "Customer's corporate size" is information that indicates the size and economic scale of a company, such as the number of employees and sales.

[1703] "Usage" is information indicating the purpose and situation in which the product will be used.

[1704] "Prices of already introduced products" refers to price information of products currently being used by the company.

[1705] "Input means" refers to a method or device that allows a user to input the required information into the system.

[1706] The "means for displaying a list of prices of currently used products" refers to a method or device for displaying price information of existing products in a list format.

[1707] The "means for proposing the price of a new product being considered for introduction" refers to a method or device for proposing the price of a new product to users.

[1708] A "generative AI model" is an algorithm or model that uses artificial intelligence to generate data and perform specific tasks.

[1709] "Means for calculating the appropriate price of a new product and proposing it to users" refers to a method or device for calculating the optimal price of a new product using a generative AI model and presenting that price to users.

[1710] A system for carrying out this invention has the following configuration: The server includes means for inputting the size of the customer's company, intended use, and prices of merchandise already introduced, means for displaying a list of prices of merchandise currently being used based on this information, means for proposing prices for merchandise being considered for new introduction, and means for calculating appropriate prices for new merchandise using a generative AI model and proposing the prices to the user.

[1711] Hardware and software used

[1712] Hardware: Smartphones, servers

[1713] Software: Python, OpenAI API, Pandas

[1714] Data processing and calculation

[1715] 1. Data loading: The server loads the price information of existing products from the CSV file. This retrieves the price information of existing products as a data frame.

[1716] 2. User input: The user inputs the name and characteristics of the new product using a smartphone. This information is sent to the server.

[1717] 3. Use of generative AI model: The server uses OpenAI's API to generate an appropriate price for the new product based on the price information of existing products and user-entered information. Specifically, it sends a prompt to the generative AI model, and the AI ​​calculates the price.

[1718] 4. Price Proposal: The generated price is sent from the server to the user's smartphone and displayed to the user.

[1719] Specific examples

[1720] For example, suppose the price information for existing products is stored in a CSV file as shown below.

[1721] Product A, 1000

[1722] Product B, 1500

[1723] Product C, 2000

[1724] If a user enters "Product D" as the name of a new product and "Made of high-quality materials and highly durable" as its features, the server will send the following prompt to the generative AI model.

[1725] Prompt Sentence Examples

[1726] Existing product pricing information: {'Product A': 1000, 'Product B': 1500, 'Product C': 2000}

[1727] New product name: Product D

[1728] Features of the new product: Made from high-quality materials and highly durable

[1729] Please suggest a reasonable price for this new product.

[1730] The generative AI model calculates the appropriate price for the new product based on this prompt and returns the result to the server. The server then sends the result to the user's smartphone and displays it to the user. This allows the user to quickly and accurately find out the appropriate price for the new product.

[1731] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1732] Step 1:

[1733] The server reads the price information of existing products from a CSV file. Specifically, it uses the Pandas library to read the CSV file as a data frame. The input is a CSV file, and the output is the price information of existing products in data frame format.

[1734] Step 2:

[1735] The user uses a smartphone to input the name and characteristics of a new product. The input is the name and characteristics of the new product, and the output is sending this information to the server. Specifically, the user enters the information about the new product into the input form on the smartphone and presses the send button.

[1736] Step 3:

[1737] The server receives the name and characteristics of the new product sent by the user and combines them with the price information of the existing product to generate a prompt. The input is the name and characteristics of the new product and the price information of the existing product, and the output is the generated prompt. Specifically, the prompt is constructed using string manipulation.

[1738] Step 4:

[1739] The server sends the generated prompt text to OpenAI's API and uses the generative AI model to calculate the appropriate price for the new product. The input is the prompt text, and the output is the price information for the new product returned by the generative AI model. Specifically, the server sends the prompt text to the API using an HTTP request and receives a response.

[1740] Step 5:

[1741] The server receives the price information for new products returned from the generative AI model and sends it to the user's smartphone. The input is the price information from the generative AI model, and the output is the price information displayed on the user's smartphone. Specifically, it performs communication processing to send the price information to the user's smartphone.

[1742] Step 6:

[1743] The user checks the price information of a new product displayed on the smartphone. The input is the price information sent from the server, and the output is the price information checked by the user. Specifically, the user views the price information displayed on the smartphone screen.

[1744] Example 3

[1745] Next, a third embodiment of the third embodiment will be described. 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."

[1746] Determining the appropriate price for a new product a company is considering introducing is extremely important for maintaining the company's competitiveness. However, determining an appropriate price by taking into account the product's features, manufacturing costs, and competitor pricing information is a time-consuming and labor-intensive task. Furthermore, the pricing process is prone to subjective judgment, making it difficult to find the optimal price.

[1747] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[1748] In this invention, the server includes a means for a user to input product information, a means for the server to save the input information in a database, a means for the server to send a prompt to the generative AI model, a means for the generative AI model to propose an appropriate price, a means for the server to provide the proposed price to the user, a means for the user to determine a final price, and a means for the server to save the determined price in a database. This enables companies to efficiently and objectively determine an appropriate price for a new product they are considering introducing.

[1749] "Customer's company size" is information indicating the size of the company, such as the number of employees, sales, and capital.

[1750] "Usage" is information that indicates the purpose for which a company will use a product.

[1751] "Already implemented products" refer to products that a company has already purchased and is using.

[1752] "Price input means" refers to the interface or method by which a user inputs product pricing information into the system.

[1753] "Means for displaying prices in a list" refers to an interface or method for displaying entered price information in a list format.

[1754] "Means for suggesting a price" refers to the method or algorithm by which the system calculates an appropriate price and suggests it to the user.

[1755] "Means for users to input product information" refers to the interface or method by which users input product features, costs, competitor pricing information, etc. into the system.

[1756] "Means for the server to save the input information in a database" refers to the method or technology by which the server saves the information input by the user in a database.

[1757] "Means by which the server sends prompt sentences to the generative AI model" refers to the methods and technologies by which the server generates and sends appropriate prompt sentences to the generative AI model.

[1758] "Means by which the generative AI model suggests an appropriate price" refers to the methods and algorithms by which the generative AI model calculates and suggests an appropriate price based on the input prompt.

[1759] "Means by which the server provides the suggested price to the user" refers to the interface or method by which the server displays the suggested price from the generative AI model to the user.

[1760] "Means for users to determine final prices" refers to an interface or method by which a user determines a final price based on the proposed prices and inputs it into the system.

[1761] "Means for the server to store the determined price in a database" refers to a method or technology for the server to store the final price determined by the user in a database.

[1762] "Business-to-business transactions" refer to transactions in which companies buy and sell products or services.

[1763] "Tools for internal use" refers to software and systems for use within a company.

[1764] This invention is a system for determining the appropriate price of a new product that a company is considering introducing. In this system, the user inputs product information, and the server uses a generative AI model based on that information to propose an appropriate price.

[1765] First, a user uses a company's device to input product features (e.g., screen size, battery capacity, camera performance, etc.), manufacturing costs, competitor pricing information, etc. This information is entered through the device's interface.

[1766] The server then receives the information entered by the user and stores it in a database. This database is managed using a database management system such as MySQL. The stored data is divided into fields such as product ID, features, cost, and competitive price.

[1767] The server generates a prompt based on the product information stored in the database. The generated prompt is sent to a generative AI model (e.g., OpenAI's GPT-4). Examples of prompts include:

[1768] Product: Smartphone

[1769] Features: 6.5-inch display, 5000mAh battery, 48MP camera

[1770] Manufacturing cost: $200

[1771] Competitor's Price: $300

[1772] Please suggest a reasonable price.

[1773] The generative AI model analyzes the prompt sent from the server and proposes an appropriate price for the product. This proposed price is calculated based on the generative AI model's algorithm.

[1774] The server receives the proposed price from the generative AI model and provides it to the user, who can then view the proposed price through their device.

[1775] The user decides on the final price based on the price proposal provided by the server. The decided price is sent back to the server and saved in the database. This saved price information can be used for future analysis and reference.

[1776] This system enables a company to efficiently and objectively determine an appropriate price for a new product that the company is considering introducing. The flow of the specification process in the third embodiment will be described with reference to FIG.

[1777] Step 1:

[1778] The user enters product information.

[1779] Users use a company's terminal to input product features (e.g., screen size, battery capacity, camera performance, etc.), manufacturing costs, and competitor pricing information. The input information is sent to the server through the terminal's interface. Input data includes product name, features, costs, and competitor pricing.

[1780] Step 2:

[1781] The server stores the entered information in a database.

[1782] The server receives the product information sent by the user and stores it in a database. The database is managed using a database management system such as MySQL. The stored data includes fields such as product ID, features, cost, and competitive price. The input data is appropriately mapped to each field in the database.

[1783] Step 3:

[1784] The server sends a prompt to the generative AI model.

[1785] The server generates a prompt based on the product information stored in the database. The generated prompt is sent to a generative AI model (e.g., OpenAI's GPT-4). Examples of prompts include:

[1786] Product: Smartphone

[1787] Features: 6.5-inch display, 5000mAh battery, 48MP camera

[1788] Manufacturing cost: $200

[1789] Competitor's Price: $300

[1790] Please suggest a reasonable price.

[1791] The input data is product information obtained from the database, and the output data is the generated prompt sentence.

[1792] Step 4:

[1793] A generative AI model suggests the right price.

[1794] The generative AI model analyzes the prompt sent from the server and proposes an appropriate price for the product. This proposed price is calculated based on the generative AI model's algorithm. The input data is the prompt, and the output data is the proposed price.

[1795] Step 5:

[1796] The server provides the suggested price to the user.

[1797] The server receives the proposed price from the generative AI model and displays it on the user's device. The user can check the proposed price on the device screen. The input data is the proposed price, and the output data is the price information displayed to the user.

[1798] Step 6:

[1799] The user decides the final price.

[1800] The user decides on the final price based on the price proposal provided by the server. The decided price is sent to the server via the terminal. The input data is the proposed price, and the output data is the final decided price.

[1801] Step 7:

[1802] The server stores the determined price in a database.

[1803] The server receives the final price sent by the user and stores it in a database. The stored price information is used for future analysis and reference. The input data is the final determined price, and the output data is the price information stored in the database.

[1804] (Application example 3)

[1805] Next, a description will be given of Application Example 3 of Form Example 3. 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."

[1806] Determining the appropriate price for a new product a company is considering introducing is an important issue in its business strategy. However, traditional methods require a great deal of time and effort to collect and analyze the information necessary for pricing decisions. It is also difficult to evaluate the appropriateness of a price by comparing it with past price data. This can prevent companies from quickly determining an appropriate price, potentially resulting in a loss of competitiveness.

[1807] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 3 is realized by the following means.

[1808] In this invention, the server includes means for inputting the size of the customer's company, intended use, and prices of already introduced products, means for displaying a list of prices of currently used products based on this information, means for proposing prices for products being considered for new introduction, means for proposing an appropriate price using a generative AI model, means for determining prices based on the proposed prices, and means for evaluating the appropriateness of the prices by comparing with past price data. This enables companies to quickly and appropriately determine prices for products being considered for new introduction.

[1809] "Company size" is an indicator that shows the size of a company, such as the number of employees, sales, and capital.

[1810] "Usage" refers to the purpose and situation in which a particular product or service is used.

[1811] "Merchandise" refers to goods or products that a company handles for sale or use.

[1812] "Price" refers to the monetary value assigned to a product or service.

[1813] A "generative AI model" is an algorithm or system that uses artificial intelligence technology to generate new information or suggestions from data.

[1814] A "prompt" is a sentence of instructions or questions that is input to a generative AI model.

[1815] A "price proposal" is the act and result of presenting an appropriate price for a particular product.

[1816] "Pricing" refers to the process of determining the final price based on the proposed price.

[1817] "Price reasonableness" is a criterion for evaluating whether the proposed price is appropriate compared to market and historical data.

[1818] "BtoB" refers to business-to-business transactions, a business model in which companies provide products and services to other companies.

[1819] The system for carrying out the present invention is for appropriately determining the price of a new product that a company is considering introducing. A specific embodiment of this system is described below.

[1820] System Configuration

[1821] The system consists of the following main components:

[1822] 1. Input method: Provides an interface for users to input information such as company size, usage, and prices of products already in use. This can be done using devices such as smartphones or PCs.

[1823] 2. Display method: Based on the information entered, the prices of the products currently being used are displayed in a list. This is also displayed on the screen of a smartphone or computer.

[1824] 3. Proposal method: Propose a price for a new product being considered for introduction. This proposal is made using a generative AI model.

[1825] 4. Pricing method: The final price is determined based on the proposed price.

[1826] 5. Evaluation measures: Evaluate the reasonableness of the proposed price by comparing it with historical price data.

[1827] Program processing

[1828] The server performs the following process.

[1829] 1. Data entry: The user enters the company size, usage, and prices of products already in use. This data is sent to the server via the interface of a smartphone or PC.

[1830] 2. Data display: The server displays a list of prices for the currently used products based on the entered information.

[1831] 3. Price Proposal: The server proposes a price for the new product being considered for introduction using the generative AI model. The generative AI model is implemented using OpenAI's API.

[1832] 4. Price determination: The user determines the final price based on the proposed prices.

[1833] 5. Price Evaluation: The server evaluates the reasonableness of the proposed price by comparing it with historical pricing data.

[1834] Hardware and software used

[1835] Hardware: smartphones, PCs, servers

[1836] Software: Python, OpenAI API

[1837] Specific examples

[1838] For example, if a user inputs "high-performance battery" as a new product they are considering introducing, the following prompt sentence will be sent to the generative AI model.

[1839] Prompt Sentence Examples

[1840] Information on the new product: Product name: High-performance battery, Specifications: 5000mAh, Price range: 3000 yen to 5000 yen

[1841] Please suggest a reasonable price.

[1842] The generative AI model will then suggest an appropriate price based on this prompt and display the results to the user, who can then decide on a final price based on the suggested price and evaluate its appropriateness by comparing it with past price data.

[1843] In this way, companies can quickly and appropriately determine the prices of new products they are considering introducing.

[1844] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[1845] Step 1:

[1846] The user enters the company size, intended use, and the price of the products already introduced.

[1847] Input: Company size, usage, price of already introduced products

[1848] Specific operation: Through the interface of a smartphone or PC, the user inputs the company size (e.g., number of employees, sales), usage (e.g., manufacturing, sales), and price of already introduced products (e.g., price of product A). This data is sent from the device to the server.

[1849] Step 2:

[1850] The server displays a list of prices for the currently used products based on the information entered.

[1851] Input: Company size, usage, price of already introduced products

[1852] Output: Price list of currently used products

[1853] Specific operation: The server processes the received data and displays the prices of the currently used products in a list format. The displayed price list is sent to the user's device and displayed on the screen.

[1854] Step 3:

[1855] The server generates a prompt message to suggest the price of the new product that is being considered for introduction.

[1856] Input: Information about the new product you are considering introducing (e.g. product name, specifications, price range)

[1857] Output: prompt statement

[1858] Specific operation: When a user enters information about a new product they are considering introducing, the server uses that information to generate a prompt to send to the generative AI model. For example, it generates a prompt like this: "Information about the new product: Product name: High-performance battery, Specifications: 5000mAh, Price range: 3000 to 5000 yen. Please suggest an appropriate price."

[1859] Step 4:

[1860] The server uses a generative AI model to suggest an appropriate price.

[1861] Input: prompt statement

[1862] Output: Proposed price

[1863] Specific operation: The server sends the generated prompt to OpenAI's API and receives an appropriate price suggestion from the generative AI model. For example, the generative AI model suggests a price of "4,500 yen."

[1864] Step 5:

[1865] The server will determine the final price based on the proposed price.

[1866] Input: Proposed Price

[1867] Output: Final price

[1868] How it works: The user checks the price suggested by the generative AI model and decides on the final price based on that price. The decided price is sent to the server and recorded.

[1869] Step 6:

[1870] The server evaluates the reasonableness of the proposed price by comparing it with historical pricing data.

[1871] Inputs: Proposed price, historical price data

[1872] Output: Price justification evaluation result

[1873] How it works: The server compares the proposed price with past price data to evaluate its validity. The evaluation result is sent to the user's device and displayed on the screen.

[1874] In this way, companies can quickly and appropriately determine the prices of new products they are considering introducing.

[1875] 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.

[1876] "Example 1"

[1877] As one embodiment of the present invention, a system incorporating an emotion engine is provided. This system inputs the user's company size, intended use, and prices of already implemented products, and based on this information, displays a list of prices for currently used products. It also proposes prices for products that are being considered for new implementation. As a proposal method, it uses a generation AI to propose product prices. This system is a tool for in-company use in B2B.

[1878] "Example 2"

[1879] The emotion engine recognizes the user's emotions and adjusts the price of the product based on those emotions. For example, if the user is feeling stressed, the emotion engine will collect that information and reduce the price of the product to reduce the user's stress.

[1880] "Example 3"

[1881] The emotion engine also optimizes product pricing based on user emotions. For example, if a user is feeling happy, the emotion engine will collect that information and increase the product price to maximize profits.

[1882] The processing flow of each embodiment will be described below.

[1883] "Example 1"

[1884] Step 1: The user enters the company size, intended use, and prices of products already implemented into the system.

[1885] Step 2: The system will display a list of prices for the products you are currently using based on the information you entered.

[1886] Step 3: The system uses AI to suggest prices for new products that are being considered for introduction.

[1887] "Example 2"

[1888] Step 1: The emotion engine recognizes the user's emotion.

[1889] Step 2: The emotion engine adjusts the price of the product based on the emotion it recognizes.

[1890] Step 3: For example, if the user is feeling stressed, the emotion engine will collect that information and reduce the user's stress by lowering the price of the product.

[1891] "Example 3"

[1892] Step 1: The emotion engine recognizes the user's emotion.

[1893] Step 2: The emotion engine optimizes the price suggestions for the product based on the emotions it recognizes.

[1894] Step 3: For example, if the user is feeling happy, the emotion engine will collect that information and maximize profits by increasing the price of the product.

[1895] Example 1

[1896] Next, a description will be given of Example 1 of Form 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."

[1897] With conventional systems, it is difficult for companies to check the pricing information of their own products at a glance, and there is a lack of means to propose appropriate prices for products that they are considering introducing. In addition, in business-to-business transactions, the optimal price proposal based on the size of the company or the purpose of use is not made, making it difficult to efficiently select products.

[1898] 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.

[1899] In this invention, the server includes means for inputting the customer's company size, intended use, and prices of already introduced products, means for displaying a list of prices of currently used products based on this information, means for proposing prices for products being considered for new introduction, means for displaying the generated price information to the user, and means for generating prices for products being considered for new introduction using a generative AI model. This allows companies to check price information for their own products at a glance and receive optimal price proposals based on their company size and intended use.

[1900] "Company size" is an indicator that shows the size of a company, such as the number of employees and sales.

[1901] "Usage" is information indicating the purpose for which a company will use the product.

[1902] "Merchandise" refers to products or services that a company purchases or uses.

[1903] "Price" refers to the monetary value paid for a commodity.

[1904] "Input means" refers to an interface through which a user provides information to a system.

[1905] "Display means" refers to an interface that allows the system to visually present information to the user.

[1906] "Proposal means" refers to a function that allows the system to present the price of a new product to the user.

[1907] A "generative AI model" refers to an algorithm or system that uses artificial intelligence to analyze data and generate new information.

[1908] A "prompt" is text data that is input to a generative AI model and contains instructions for the model to generate output.

[1909] "Business-to-business transactions" refer to commercial transactions conducted between businesses.

[1910] This invention is a system that allows a company to check price information of its own products at a glance and proposes appropriate prices for products that the company is considering introducing. A specific embodiment of this system will be described below.

[1911] The user accesses the system using a device (PC, tablet, smartphone, etc.). The user opens the device's browser and accesses the system's web application. The user enters information into a form that asks for the company size (e.g., small and medium-sized enterprise), purpose of use (e.g., manufacturing), and price of the product already introduced (e.g., 1 million yen), and clicks the "Submit" button.

[1912] The terminal sends the entered information to the server as an HTTP request. Specifically, it sends data using a POST request. The request body includes the company size, purpose of use, and price of existing products.

[1913] The server analyzes the received information and executes an INSERT query to store the information in a database, which stores information such as the company size, usage, and prices of existing products.

[1914] Next, the server queries and obtains the price of the currently used product based on the information stored in the database.The server executes a SELECT query to obtain the price information of the currently used product from the database.

[1915] The server converts the acquired price information into JSON format and sends it to the terminal as an HTTP response. The terminal parses the received JSON data and displays the price information in a list on the user interface. The user can then check the price information on their browser.

[1916] Furthermore, the server uses the generative AI model to generate a price for a new product that is being considered for introduction. A prompt statement is generated for the generative AI model and input into the model. The prompt statement includes information about the company size, intended use, and pricing information for existing products. The generative AI model generates a price for the new product based on the input information.

[1917] The server converts the price information output by the generative AI model into JSON format and sends it to the terminal as an HTTP response. The terminal analyzes the received JSON data and displays the generated price information on the user interface. The user can then check the price of the new product they are considering introducing.

[1918] As a specific example, consider the case where a small or medium-sized enterprise wants to know the price of a new product it is considering introducing. The user enters the company size as "Small or Medium-sized Enterprise," the use as "Manufacturing," and the price of the product already introduced as "1 million yen." Based on this information, the system displays a list of prices for the products currently being used and uses a generative AI model to suggest a price for the new product being con...

Claims

1. A means for collecting user information including the price of merchandise that the user has already introduced; A means for proposing a price of a product that the user is considering introducing based on the user information; A means for analyzing the user's feelings regarding the proposed price of the product; A means for dynamically changing and proposing a price of the product based on the analyzed sentiment of the user; A system including:

2. The suggesting means proposes the price of the product using a generating AI. The system of claim 1 .

3. The user information includes at least one of information on the user's company size and the usage purpose of the introduced product, The system of claim 1 .

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