System

Abstract

A system is provided.SOLUTION: Means for automatically generating a new customer list based on conditions such as a business type, an area, a related keyword, and a sales scale, means for automatically creating an appropriate reply / follow-up mail in response to an inquiry from a customer, means for automatically generating an estimate from a price list of a product or a service, customer behavior analysis means for creating a marketing measure from a purchase history or an access history, competition investigation means for analyzing a differentiation point of a product or a service of a company, means for creating an assumed question and answer before a direct business negotiation with a customer, means for calculating the required time and proposing the shortest approach to closing.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 rapidly changing industries where it is difficult to explain products (such as IT companies, retail, and real estate), sales representatives face challenges in staying up-to-date with the latest product and service information and making accurate proposals and customer responses. Furthermore, a lack of efficient sales activities and accumulated in-house know-how makes it difficult to understand customer needs and make optimal proposals. Furthermore, while quick and accurate responses are required in customer inquiries and sales negotiations, limited human resources present a challenge. [Means for solving the problem]

[0005] To solve these problems, the present invention provides the following means: a system that automatically generates new customer lists based on conditions such as industry, region, related keywords, and sales volume; automatically creates appropriate reply and follow-up emails in response to customer inquiries; automatically generates quotes from product and service price lists; analyzes customer behavior to create marketing strategies based on purchase and access histories; conducts competitive research to analyze the differentiating points of a company's products and services; creates anticipated questions and answers before directly negotiating with customers; and, when an agenda and related information are input, summarizes the points of discussion necessary to reach a conclusion, calculates the required time, and proposes the shortest approach to closing. This system improves the efficiency of sales activities, enables understanding of customer needs, optimal proposals, and rapid responses, enabling sales activities that can flexibly adapt to change.

[0006] "Conditions" refer to criteria or factors for filtering or selecting specific information, such as industry, region, related keywords, or sales volume.

[0007] "New Customer List" refers to a list of potential customers automatically selected based on pre-set conditions.

[0008] An "inquiry" refers to a question, request, or problem report from a customer or potential customer, typically made via email, phone, chat, or other means.

[0009] "Reply / Follow-up Email" refers to an email that contains a response to a customer inquiry or provides additional information.

[0010] A "price list" refers to a list of organized pricing information for products or services, and typically includes detailed information such as base price, discounts, and optional fees.

[0011] "Quote" means a price projection for products or services to be provided on specified terms, usually in written or electronic form.

[0012] "Purchase history" refers to a record of products and services previously purchased by a particular customer.

[0013] "Access history" refers to records of a particular customer's access to a website or application.

[0014] "Marketing measures" refer to specific plans and strategies for sales promotion and strengthening customer relationships that are formulated based on customer behavior analysis.

[0015] "Customer behavior analysis" refers to the process of analyzing data such as customer purchase history and access history to identify trends and patterns.

[0016] "Points of differentiation" refer to the unique features and advantages that make your company's products and services different from those of your competitors.

[0017] "Anticipated questions and answers" refers to a list of questions that are anticipated to come from customers and their answers that are prepared in advance before a business meeting.

[0018] An "issue" refers to a specific topic or issue related to an agenda item, and is the focus of decision-making or discussion.

[0019] "Closing" refers to the final stage of a business negotiation or deal, and the process of reaching an agreement or contract.

[0020] An "approach" refers to the strategy or method used to achieve a goal or solve a problem. [Brief explanation of the drawings]

[0021] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0022] 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.

[0023] First, the terms used in the following description will be explained.

[0024] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0025] 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.

[0026] 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.

[0027] 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.

[0028] 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."

[0029] [First embodiment]

[0030] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0031] 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.

[0032] 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).

[0033] 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.

[0034] 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.

[0035] 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.

[0036] 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.

[0037] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0038] 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.

[0039] 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.

[0040] 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.

[0041] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0042] MODE FOR CARRYING OUT THE INVENTION

[0043] This invention provides a system with functions to automatically generate new customer lists based on criteria such as industry, region, related keywords, and sales volume, as well as to automatically create appropriate replies and follow-up emails to inquiries. This system also includes a customer behavior analysis function that automatically generates quotes from product and service price lists and creates marketing strategies based on purchase and access history. Furthermore, the system also has functions to analyze points of differentiation through competitive research, create anticipated questions and answers before negotiations, calculate the required time by entering the agenda and related information, and propose the shortest approach to closing.

[0044] Program processing details

[0045] Automatic generation of new customer lists

[0046] The server accepts user input of criteria such as industry, region, related keywords, and sales volume, and issues queries to external and internal databases to retrieve appropriate company data. The retrieved data is then filtered and a new customer list is automatically generated. The generated list is periodically updated and provided to the user via their device.

[0047] Examples:

[0048] The user enters the conditions "IT company," "Tokyo," and "cloud service," and the server creates a new customer list based on this.

[0049] Auto-reply and follow-up email creation function

[0050] When the server receives an inquiry email from a customer, it analyzes the content using natural language processing technology and searches for the most appropriate answer from the FAQ database. Based on the selected answer, it selects an email template and automatically creates a reply email. The reply email is then automatically sent to the customer.

[0051] Examples:

[0052] When a customer inquires about the specifications of a new product, the server creates and sends a reply email containing the appropriate specification information.

[0053] Automatic quote generation function

[0054] When the user inputs the product or service conditions (type, quantity, duration, etc.), the terminal retrieves the corresponding price information from the price database. The server calculates the estimate based on this information and creates a quote in PDF format. The quote is then provided to the user via the terminal.

[0055] Examples:

[0056] When the user selects an annual cloud service contract and a support package, the device automatically generates a quote.

[0057] Customer behavior analysis function

[0058] The server collects customer purchase and access histories and performs analysis based on this data. It identifies trends and patterns and generates useful insights. Based on this, it creates specific marketing proposals.

[0059] Examples:

[0060] The server analyzes the product categories that a particular customer frequently purchases and proposes new product promotion strategies.

[0061] Competitive research feature

[0062] The server collects information on competitors' products from external databases and the Internet, performs comparative analysis with the company's own products, extracts points of differentiation, and develops sales strategies based on these.

[0063] Examples:

[0064] Through comparative analysis with competing products, Server identifies that the advantage of its products is their "extensive support system," and reflects this information in its sales materials.

[0065] Function to create hypothetical questions and answers

[0066] The server predicts questions customers will have based on past sales negotiation history and FAQ data, and creates a list of answers. This is provided to the user via their device to help them prepare for sales negotiations.

[0067] Examples:

[0068] The server prepares questions and answers regarding "the cost of introducing a new product" in advance and provides them to the user.

[0069] Proposal function for the shortest approach to closing

[0070] The server analyzes the agenda and related information entered by the user, summarizes the points of discussion necessary to reach a conclusion, calculates the time required for each discussion, and proposes the optimal approach to closing the meeting, which is then provided to the user via their device.

[0071] Examples:

[0072] If a user wants to discuss "how to simplify the introduction of a new product," the server will calculate the required time and propose the optimal approach, and provide it to the user.

[0073] The above is a specific example of an embodiment of the invention and details of the program processing. This system makes it possible to improve the efficiency of sales activities, grasp customer needs, make optimal proposals, and respond quickly.

[0074] The processing flow will be explained below.

[0075] Automatic generation of new customer lists

[0076] Step 1:

[0077] The user inputs conditions such as industry, region, related keywords, and sales volume into the terminal.

[0078] Step 2:

[0079] The terminal transmits the input conditions to the server.

[0080] Step 3:

[0081] The server accesses the external database and the internal database based on the received condition data to obtain the matching company data.

[0082] Step 4:

[0083] The server filters the acquired company data and removes duplicates and irrelevant data.

[0084] Step 5:

[0085] The server formats the filtered data into a new customer list.

[0086] Step 6:

[0087] The server schedules periodic updates of the new customer list.

[0088] Step 7:

[0089] The terminal displays the new customer list to the user and provides it in a downloadable format (CSV, Excel, etc.).

[0090] Auto-reply and follow-up email creation function

[0091] Step 1:

[0092] The server receives an inquiry email from the customer.

[0093] Step 2:

[0094] The server analyzes the content of the received inquiry email using natural language processing technology.

[0095] Step 3:

[0096] The server searches the FAQ database for the best answer based on the analysis results.

[0097] Step 4:

[0098] The server selects an appropriate email template based on the selected answer.

[0099] Step 5:

[0100] The server inserts the reply content into the template and automatically creates a reply email.

[0101] Step 6:

[0102] The server automatically sends the created reply mail to the customer who made the inquiry.

[0103] Automatic quote generation function

[0104] Step 1:

[0105] The user inputs the product or service conditions (type, quantity, period, etc.) into the terminal.

[0106] Step 2:

[0107] The terminal transmits the input conditions to the server.

[0108] Step 3:

[0109] The server queries the price database based on the condition data and obtains the corresponding price information.

[0110] Step 4:

[0111] The server calculates an estimate based on the acquired price information.

[0112] Step 5:

[0113] The server formats the calculation results into a PDF estimate.

[0114] Step 6:

[0115] The terminal displays the generated quote to the user and provides it in a downloadable format.

[0116] Customer behavior analysis function

[0117] Step 1:

[0118] The server automatically collects customer purchase history and access history.

[0119] Step 2:

[0120] The server analyzes the collected data using an analysis tool.

[0121] Step 3:

[0122] The server identifies trends and patterns based on the analysis results.

[0123] Step 4:

[0124] The server generates useful insights (such as recommended products and marketing strategies).

[0125] Step 5:

[0126] The server creates specific marketing proposals based on the generated insights.

[0127] Step 6:

[0128] The terminal displays the proposal to the user and provides related materials.

[0129] Competitive research feature

[0130] Step 1:

[0131] The server collects competitor product information from external databases and the web.

[0132] Step 2:

[0133] The server organizes the collected information and compiles it into a format that makes it easy to compare with the company's own products and services.

[0134] Step 3:

[0135] The server compares and analyzes the features, prices, advantages, etc. of its own products with those of its competitors.

[0136] Step 4:

[0137] The server extracts points of differentiation from the results of the comparative analysis.

[0138] Step 5:

[0139] The terminal provides users with a point of differentiation that can be utilized in sales activities.

[0140] Function to create hypothetical questions and answers

[0141] Step 1:

[0142] The server collects past business negotiation history and an FAQ database.

[0143] Step 2:

[0144] The server generates questions and appropriate answers based on the collected information.

[0145] Step 3:

[0146] The server formats the generated questions and answers into a list.

[0147] Step 4:

[0148] The terminal displays a list of expected questions and answers to the user to assist in preparation before the business negotiation.

[0149] Proposal function for the shortest approach to closing

[0150] Step 1:

[0151] The user inputs the agenda and related information into the terminal.

[0152] Step 2:

[0153] The terminal transmits the input information to the server.

[0154] Step 3:

[0155] The server analyzes the agenda and related information and summarizes the points needed to reach a conclusion.

[0156] Step 4:

[0157] The server calculates the time required to discuss each topic.

[0158] Step 5:

[0159] The server will propose the shortest approach to closing based on the required time and points of discussion.

[0160] Step 6:

[0161] The terminal displays the proposal contents to the user and optimizes the progress of the business negotiations.

[0162] The above are the specific processing steps for each function in the embodiment of the invention.

[0163] Example 1

[0164] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0165] Modern sales and marketing activities require the ability to quickly and accurately generate new customer lists and conduct effective follow-up. However, performing these tasks manually takes a significant amount of time and effort and is prone to errors. It is also difficult to efficiently perform a wide range of tasks, such as competitor research, creating quotes, and preparing for sales negotiations. Furthermore, analyzing customer behavior and developing optimal marketing strategies are also necessary. To solve these challenges, a system that automates and optimizes all processes is needed.

[0166] 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.

[0167] In this invention, the server includes: means for automatically generating a new customer list based on criteria such as industry, region, related keywords, and sales volume; means for receiving inquiry emails from customers, analyzing the content using natural language processing technology, and automatically creating and sending appropriate reply and follow-up emails; means for retrieving information from a price database based on product or service criteria (type, quantity, duration, etc.), automatically generating quotes, and creating quote documents in PDF format; means for analyzing customer purchase histories and access histories to create marketing strategies; means for conducting competitive research by collecting information on competing products from external databases and the Internet and comparing and analyzing them with the company's own products to identify points of differentiation; means for predicting customer questions based on past sales negotiation history and FAQ data and creating a list of anticipated questions and answers; and means for summarizing the points of discussion necessary to reach a conclusion, calculating the required time, and proposing the shortest approach to closing a deal when the topic and related information are input. This enables more efficient sales activities, early identification of customer needs, appropriate proposals, and rapid responses.

[0168] "Means for automatically generating new customer lists" is a function that automatically generates new customer lists by retrieving and filtering appropriate company data from external and internal databases based on conditions entered by the user, such as industry, region, related keywords, and sales volume.

[0169] "Means for automatically creating and sending appropriate reply / follow-up emails" refers to a function that receives inquiry emails from customers, analyzes the content using natural language processing technology, searches for the most appropriate answer from the FAQ database, and automatically creates and sends reply / follow-up emails using email templates.

[0170] "Means to automatically generate quotes and create quotes in PDF format" refers to a function that, when a user inputs the product or service conditions (type, quantity, period, etc.), retrieves the relevant price information from a price database, calculates a quote based on this, and creates a quote in PDF format.

[0171] "Customer behavior analysis tools" are functions that collect customer purchase history and access history, analyze this data to identify trends and patterns, generate useful insights, and propose specific marketing measures.

[0172] "Competitive research tools" is a function that collects information on competitors' products from external databases and the Internet, performs comparative analysis with your own products, extracts points of differentiation, and develops sales strategies.

[0173] "A means to create a list of anticipated questions and answers" is a function that predicts questions from customers based on past sales negotiation history and FAQ data, and compiles and creates a list of answers.

[0174] "A means of inputting the agenda and related information, summarizing the points needed to reach a conclusion, calculating the required time, and proposing the shortest approach to closing" is a function that, when a user inputs the agenda and related information, analyzes them, summarizes the points needed to reach a conclusion, calculates the required time for each discussion, and proposes the optimal closing approach.

[0175] MODE FOR CARRYING OUT THE INVENTION

[0176] This invention provides a system with functions to automatically generate new customer lists based on criteria such as industry, region, related keywords, and sales volume, as well as to automatically create appropriate replies and follow-up emails to inquiries. This system also includes a customer behavior analysis function that automatically generates quotes from product and service price lists and creates marketing strategies based on purchase and access history. Furthermore, the system also has functions to analyze points of differentiation through competitive research, create anticipated questions and answers before sales negotiations, calculate the required time by entering the agenda and related information, and propose the shortest approach to closing.

[0177] Overall structure

[0178] The system mainly consists of a server and a terminal. The server processes and analyzes data, while the terminal accepts input from users and displays the results. The server incorporates natural language processing technology and is connected to external and internal databases. The terminal provides a user interface and communicates with the server in response to user input.

[0179] Automatic generation of new customer lists

[0180] The server accepts user input of criteria such as industry, region, related keywords, and sales volume, and issues queries to external and internal databases to retrieve appropriate company data. The retrieved data is then filtered and a new customer list is automatically generated. The generated list is periodically updated and provided to the user via their device.

[0181] Examples:

[0182] The user enters the conditions "IT company," "Tokyo," and "cloud service" via the terminal, and the server creates a new customer list based on this.

[0183] Auto-reply and follow-up email creation function

[0184] When the server receives an inquiry email from a customer, it analyzes the content using natural language processing technology and searches for the most appropriate answer from the FAQ database. Based on the selected answer, it selects an email template and automatically creates a reply email. The reply email is then automatically sent to the customer.

[0185] Examples:

[0186] When a customer inquires about the specifications of a new product, the server creates and sends a reply email containing the appropriate specification information.

[0187] Automatic quote generation function

[0188] When the user inputs the product or service conditions (type, quantity, duration, etc.), the terminal retrieves the corresponding price information from the price database. The server calculates the estimate based on this information and creates a quote in PDF format. The quote is then provided to the user via the terminal.

[0189] Examples:

[0190] When the user selects an annual cloud service contract and a support package, the device automatically generates a quote.

[0191] Customer behavior analysis function

[0192] The server collects customer purchase and access histories and performs analysis based on this data. It identifies trends and patterns and generates useful insights. Based on this, it creates specific marketing proposals.

[0193] Examples:

[0194] The server analyzes the product categories that a particular customer frequently purchases and proposes new product promotion strategies.

[0195] Competitive research feature

[0196] The server collects information on competitors' products from external databases and the Internet, performs comparative analysis with the company's own products, extracts points of differentiation, and develops sales strategies based on these.

[0197] Examples:

[0198] Through comparative analysis with competing products, Server identifies that the advantage of its products is their "extensive support system," and reflects this information in its sales materials.

[0199] Function to create hypothetical questions and answers

[0200] The server predicts questions customers will have based on past sales negotiation history and FAQ data, and creates a list of answers. This is provided to the user via their device to help them prepare for sales negotiations.

[0201] Examples:

[0202] The server prepares questions and answers regarding "the cost of introducing a new product" in advance and provides them to the user.

[0203] Proposal function for the shortest approach to closing

[0204] The server analyzes the agenda and related information entered by the user, summarizes the points of discussion necessary to reach a conclusion, calculates the time required for each discussion, and proposes the optimal approach to closing the meeting, which is then provided to the user via their device.

[0205] Examples:

[0206] If a user wants to discuss "how to simplify the introduction of a new product," the server will calculate the required time and propose the optimal approach, and provide it to the user.

[0207] This system will enable more efficient sales activities, understanding of customer needs, optimal proposals, and quick responses.

[0208] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0209] Automatic generation of new customer lists

[0210] Step 1: Enter the condition

[0211] The user inputs conditions such as industry, region, related keywords, sales volume, etc. via a terminal. This input is sent to the server in the form of a query.

[0212] Step 2: Query the database

[0213] The server issues queries to external and internal databases based on the criteria received from the user, and the databases return company data that matches the specified criteria.

[0214] Step 3: Filtering the data

[0215] The server filters the acquired company data, specifically by organizing the data based on industry and region, and prioritizing data that matches related keywords and sales volume.

[0216] Step 4: Generate a customer list

[0217] The server generates a new customer list based on the filtered data, and outputs the list in the specified format (e.g., CSV, Excel, etc.).

[0218] Step 5: Provide a list

[0219] The server provides the generated new customer list to the user through the terminal, and the user downloads the list as needed.

[0220] ---

[0221] Auto-reply and follow-up email creation function

[0222] Step 1: Receiving an inquiry email

[0223] The server receives email inquiries from customers, which are then passed to the natural language processing module.

[0224] Step 2: Content Analysis

[0225] The server uses natural language processing technology to analyze the content of the inquiry email, extracting the main questions and keywords.

[0226] Step 3: Search for answers in the FAQ database

[0227] The server searches the FAQ database for the best answer based on the analysis results, and the search results also include the reliability and relevance of the answer.

[0228] Step 4: Select a template and create an email

[0229] The server then selects the appropriate email template based on the selected answer and automatically creates a reply email, adding personalized information for the customer.

[0230] Step 5: Sending an email

[0231] The server automatically sends a reply email to the customer. A sending log is saved, allowing you to check and resend the email if necessary.

[0232] ---

[0233] Automatic quote generation function

[0234] Step 1: Enter the condition

[0235] The user inputs product or service conditions (type, quantity, period, etc.) into the terminal. This input is sent to the server.

[0236] Step 2: Get pricing information

[0237] The terminal retrieves the relevant price information from the price database via the server, and the retrieved data is temporarily stored in memory.

[0238] Step 3: Calculate the estimate

[0239] The server calculates a quote based on the retrieved pricing information, which reflects the terms and conditions of the product or service.

[0240] Step 4: Create a quote

[0241] The server generates a quote in PDF format based on the calculation results, and the generated PDF file is saved on the server.

[0242] Step 5: Provide a quote

[0243] The server provides the generated estimate to the user through the terminal, and the user can download and print the estimate.

[0244] ---

[0245] Customer behavior analysis function

[0246] Step 1: Collect data

[0247] The server collects customer purchase and access history, and the collected data is stored in a database that is updated regularly.

[0248] Step 2: Analyze the data

[0249] The server analyzes the collected data, using statistical methods and machine learning algorithms.

[0250] Step 3: Generate insights

[0251] The server generates useful insights based on the analysis results, including customer purchasing patterns and trends.

[0252] Step 4: Propose marketing measures

[0253] The server proposes specific marketing measures based on the generated insights, and outputs these proposals in the form of a report.

[0254] Step 5: Provide a proposal

[0255] The server provides the created proposal to the user via the terminal, and the user downloads and checks the proposal report and uses it to implement measures.

[0256] ---

[0257] Competitive research feature

[0258] Step 1: Collect data

[0259] The server collects competitor product information from external databases and the Internet, and the collected data is stored in an internal database.

[0260] Step 2: Comparative product analysis

[0261] The server compares and analyzes the company's products with the collected information on competing products, including extracting points of differentiation.

[0262] Step 3: Identifying points of differentiation

[0263] The server extracts points of differentiation from the comparative analysis, which then become the basis for sales strategies.

[0264] Step 4: Develop a sales strategy

[0265] The server then creates a sales strategy based on the extracted differentiation points, and outputs the created strategy as a report.

[0266] Step 5: Deliver a strategy

[0267] The server provides the planned strategy to the user via the terminal, who then checks the strategy report and reflects it in their sales activities.

[0268] ---

[0269] Function to create hypothetical questions and answers

[0270] Step 1: Collect historical data

[0271] The server collects past business negotiation history and FAQ data, which is then stored in a database.

[0272] Step 2: Anticipate questions

[0273] The server uses collected data to predict what questions customers will ask, using machine learning algorithms.

[0274] Step 3: Prepare your response

[0275] The server compiles answers to the predicted questions, and organizes the answers in an appropriate format.

[0276] Step 4: Create a list

[0277] The server creates a list of questions and answers, which are used to prepare for the meeting.

[0278] Step 5: Provide a list

[0279] The server provides the created list to the user via the terminal, who can refer to the list and use it to prepare for business negotiations.

[0280] ---

[0281] Proposal function for the shortest approach to closing

[0282] Step 1: Enter your agenda

[0283] The user inputs the agenda and related information into the terminal, which is then sent to the server.

[0284] Step 2: Analyze the information

[0285] The server analyzes the input agenda and related information, and this analysis clarifies the necessary points of discussion.

[0286] Step 3: Summary

[0287] The server summarizes the arguments needed to reach a conclusion, which are used to calculate the time required in step 4.

[0288] Step 4: Calculate the time required

[0289] The server calculates the time required for each point, and the results serve as data to guide the optimal closing approach.

[0290] Step 5: Providing an approach

[0291] The server proposes the optimal approach to closing and provides it to the user via the terminal. The user then carries out closing activities based on the proposed approach.

[0292] This detailed processing flow enables users to efficiently carry out sales and marketing activities, and improve the accuracy and speed of customer service.

[0293] (Application example 1)

[0294] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0295] In today's society, there is a demand for more efficient sales activities and faster customer responses. However, traditional sales support systems separate the processes of generating new customer lists, responding to inquiries, creating quotes, analyzing customer behavior, researching competitors, preparing sales negotiations, and closing sales, and lack integrated support. As a result, the efficiency of sales activities can decrease and the quality of customer responses can also be compromised.

[0296] 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.

[0297] In this invention, the server includes: means for automatically generating a new customer list based on criteria such as industry, region, related keywords, and sales volume; means for automatically creating appropriate reply and follow-up emails in response to customer inquiries; means for automatically generating quotations from product and service price lists; means for analyzing customer behavior to create marketing strategies based on purchase history and access history; means for conducting competitive research to analyze the differentiation points of a company's products and services; means for creating anticipated questions and answers before directly negotiating with customers; means for inputting an agenda and related information, summarizing the points of discussion necessary to reach a conclusion, calculating the required time, and proposing the shortest approach to closing; means for analyzing customer inquiries using natural language processing technology and searching for optimal answers from an FAQ database; means for retrieving data from external and internal databases based on query criteria, filtering, and automatically updating the list; and means for documenting the generated information in PDF format and electronically transmitting it. This enables integrated support for sales activities and significantly improves the efficiency and quality of customer service.

[0298] 1. "Automatic generation of new customer lists"

[0299] Automated generation of new customer lists is the process of automatically creating lists of new customers based on criteria such as industry, region, related keywords, and sales volume.

[0300] 2. "Creating Auto-Reply and Follow-Up Emails"

[0301] Auto-reply and follow-up email creation is the process of automatically generating and sending appropriate replies and follow-up emails in response to customer inquiries.

[0302] 3. "Automatic quote generation"

[0303] Auto-generating quotes is the process of automatically calculating and generating quotes based on specified criteria using a price list for a product or service.

[0304] 4. “Customer behavior analysis”

[0305] Customer behavior analysis is a method for formulating marketing strategies by collecting and analyzing behavioral data such as customer purchase history and access history.

[0306] 5. "Competitive Research"

[0307] Competitive research is the process of collecting information about competitors from external databases and the Internet and conducting a comparative analysis of their products and services.

[0308] 6. "Creating anticipated questions and answers"

[0309] Creating anticipated questions and answers is a procedure for preparing questions that customers may have and their answers in advance.

[0310] 7. "Proposing the quickest approach to closing"

[0311] Proposing the shortest approach to closing is a method of calculating and proposing the shortest steps required to successfully close a business negotiation based on the agenda and related information entered.

[0312] 8. "Natural language processing technology"

[0313] Natural language processing technology is a technology that enables computers to understand, interpret, and generate human language.

[0314] 9. "FAQ Database"

[0315] An FAQ database is a database that compiles frequently asked questions and their answers, and is used to respond to inquiries.

[0316] 10. Query Conditions

[0317] A query condition is a search condition for retrieving information from a database.

[0318] 11. "External Database"

[0319] An external database is a database that is an accessible source of information that exists outside the enterprise.

[0320] 12. "Internal Database"

[0321] An internal database is a collection of information managed within a company, and is a database used for data management and analysis within the company.

[0322] 13. “PDF format”

[0323] PDF is an abbreviation for Portable Document Format, and is a file format for saving documents as electronic files while preserving their layout.

[0324] 14. "Electronic Transmissions"

[0325] Electronic transmission is the process of sending electronic files over the Internet to other devices.

[0326] This invention is a system for streamlining and optimizing sales activities for security services. This system includes various functions such as automatically generating new customer lists, creating automatic replies and follow-up emails, automatically generating quotes, analyzing customer behavior, researching competitors, creating anticipated questions and answers, and proposing the shortest approach to closing a deal.

[0327] Automatic generation of new customer lists

[0328] The server receives user inputs such as industry, region, related keywords, and sales volume, and issues queries to external and internal databases to retrieve company data. The retrieved data is then filtered and a new customer list is automatically generated. The list is updated periodically, and the generated information is documented in PDF format and sent electronically.

[0329] Create auto-reply and follow-up emails

[0330] When the server receives an inquiry email from a customer, it analyzes the content using natural language processing technology and searches for the most appropriate answer from the FAQ database. Based on the selected answer, it selects an email template, automatically creates a reply email, and sends it electronically.

[0331] Auto-generate quotes

[0332] When the user inputs the product or service conditions (type, quantity, duration, etc.), the terminal retrieves the corresponding price information from the price database. The server calculates the estimate based on this information and creates a quote in PDF format.

[0333] customer behavior analysis

[0334] The server collects customer purchase and access histories and analyzes them to identify trends and patterns, generating useful insights and suggesting specific marketing strategies.

[0335] Competitive Research

[0336] The server collects information on competitors' products from external databases and the Internet, performs comparative analysis with the company's own products, extracts points of differentiation, and develops sales strategies based on these.

[0337] Creating anticipated questions and answers

[0338] The server predicts questions customers will have based on past sales negotiation history and FAQ data, and creates a list of answers. The list is provided to the user via their device to help them prepare for sales negotiations.

[0339] Proposal for the shortest approach to closing

[0340] The server analyzes the agenda and related information entered by the user, summarizes the points of discussion necessary to reach a conclusion, calculates the time required for each discussion, and proposes the optimal approach to closing the meeting, which is then provided to the user via their device.

[0341] Hardware and software used

[0342] Hardware: Smartphone (iOS / Android)

[0343] Software: Python, Pandas, Scikit-Learn, SMTP, Natural Language Processing library

[0344] Specific examples

[0345] For example, if a user enters "I would like to propose security services to IT companies in Tokyo," the server will filter the relevant companies from a database called "potential_clients.csv" and automatically create a new customer list. Also, if a customer inquires about "service fees," the server will automatically find the appropriate answer from the FAQ file and immediately create and send a reply email.

[0346] Prompt Sentence Examples

[0347] Use the "Security Sales Support App" to automatically generate a list of IT companies in Tokyo and respond immediately to customer inquiries about pricing.

[0348] In this way, the present invention can realize comprehensive support for sales activities, and can significantly improve the efficiency and quality of customer service.

[0349] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0350] Step 1: Enter customer terms and conditions

[0351] The user inputs conditions such as industry, region, related keywords, and sales volume into the terminal. This becomes the input data for generating a new customer list.

[0352] Step 2: Generate a new customer list

[0353] The server issues queries to external and internal databases based on the conditions sent by the user, filters the acquired company data, and automatically generates a new customer list. The generated list is documented in PDF format and sent to the terminal.

[0354] Step 3: Receiving an inquiry

[0355] An inquiry email from a customer is sent to the server, and this email becomes the input data for the automatic reply.

[0356] Step 4: Natural Language Processing Analysis

[0357] The server analyzes the content of the inquiry email using natural language processing techniques (e.g., TfidfVectorizer and cosine similarity), and searches the FAQ database for the best answer based on the analysis results.

[0358] Step 5: Create an autoresponder

[0359] The server selects an email template based on the selected answer and automatically creates a reply email, which is then electronically sent back to the customer.

[0360] Step 6: Enter your quotation criteria

[0361] The user inputs conditions such as the type of product or service, quantity, and period into the terminal. This becomes the input data for automatically generating a quote.

[0362] Step 7: Auto-generate quotes

[0363] The server retrieves the relevant price information from the price database based on the conditions entered by the user, calculates an estimate based on the retrieved price information, and creates an estimate in PDF format. The estimate is then sent to the terminal.

[0364] Step 8: Collect customer data

[0365] The server continuously collects customer purchase and access histories, which serve as input data for customer behavior analysis.

[0366] Step 9: Analyze customer behavior

[0367] The server analyzes the collected customer data to identify trends and patterns, and the results are used to propose specific marketing strategies.

[0368] Step 10: Gather Competitive Intelligence

[0369] The server collects competitor product information from external databases and the Internet, and this information becomes input data for competitive research.

[0370] Step 11: Competitive analysis

[0371] The server compares and analyzes the collected information on competitors and the company's own products to extract points of differentiation, and then develops a sales strategy based on this.

[0372] Step 12: Prepare possible questions and answers

[0373] The server predicts questions customers will have based on past business negotiation history and FAQ data, and creates a list of answers. The list is then sent to the terminal and provided to the user.

[0374] Step 13: Closing Calculations

[0375] The user inputs the agenda and related information of the business negotiation into the terminal. The server analyzes the input data, summarizes the points necessary to reach a conclusion, calculates the required time, and proposes the shortest closing approach and sends it to the terminal.

[0376] 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.

[0377] MODE FOR CARRYING OUT THE INVENTION

[0378] This invention provides a system with functions to automatically generate new customer lists based on criteria such as industry, region, related keywords, and sales volume, as well as to automatically create appropriate replies and follow-up emails to inquiries. This system also includes a customer behavior analysis function that automatically generates quotes from product and service price lists and creates marketing strategies based on purchase and access history. It also has functions to analyze points of differentiation through competitive research, create anticipated questions and answers before sales negotiations, calculate the required time based on the input of the agenda and related information, and propose the shortest approach to closing. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, it is possible to dynamically adjust response content and sales strategies.

[0379] Program processing details

[0380] Automatic generation of new customer lists

[0381] The server accepts user input of criteria such as industry, region, related keywords, and sales volume, and issues queries to external and internal databases to retrieve appropriate company data. The retrieved data is then filtered and a new customer list is automatically generated. The generated list is periodically updated and provided to the user via their device.

[0382] Examples:

[0383] The user enters the conditions "IT company," "Tokyo," and "cloud service," and the server creates a new customer list based on this.

[0384] Auto-reply and follow-up email creation function

[0385] When the server receives an inquiry email from a customer, it analyzes the content using natural language processing technology and searches for the most appropriate answer from the FAQ database. Based on the selected answer, it selects an email template and automatically creates a reply email. The reply email is then automatically sent to the customer.

[0386] Examples:

[0387] When a customer inquires about the specifications of a new product, the server creates and sends a reply email containing the appropriate specification information.

[0388] Automatic quote generation function

[0389] When the user inputs the product or service conditions (type, quantity, duration, etc.), the terminal retrieves the corresponding price information from the price database. The server calculates the estimate based on this information and creates a quote in PDF format. The quote is then provided to the user via the terminal.

[0390] Examples:

[0391] When the user selects an annual cloud service contract and a support package, the device automatically generates a quote.

[0392] Customer behavior analysis function

[0393] The server collects customer purchase and access histories and performs analysis based on this data. It identifies trends and patterns and generates useful insights. Based on this, it creates specific marketing proposals.

[0394] Examples:

[0395] The server analyzes the product categories that a particular customer frequently purchases and proposes new product promotion strategies.

[0396] Competitive research feature

[0397] The server collects information on competitors' products from external databases and the Internet, performs comparative analysis with the company's own products, extracts points of differentiation, and develops sales strategies based on these.

[0398] Examples:

[0399] Through comparative analysis with competing products, Server identifies that the advantage of its products is their "extensive support system," and reflects this information in its sales materials.

[0400] Function to create hypothetical questions and answers

[0401] The server predicts questions customers will have based on past sales negotiation history and FAQ data, and creates a list of answers. This is provided to the user via their device to help them prepare for sales negotiations.

[0402] Examples:

[0403] The server prepares questions and answers regarding "the cost of introducing a new product" in advance and provides them to the user.

[0404] Proposal function for the shortest approach to closing

[0405] The server analyzes the agenda and related information entered by the user, summarizes the points of discussion necessary to reach a conclusion, calculates the time required for each discussion, and proposes the optimal approach to closing the meeting, which is then provided to the user via their device.

[0406] Examples:

[0407] If a user wants to discuss "how to simplify the introduction of a new product," the server will calculate the required time and propose the optimal approach, and provide it to the user.

[0408] Combining Emotion Engines

[0409] The server incorporates an emotion engine that recognizes the user's emotional state based on user input and voice analysis. The emotion engine analyzes the user's or customer's emotional state in real time and appropriately adjusts the content and timing of responses based on that data.

[0410] Examples:

[0411] The emotion engine analyzes the emotional tone (e.g., dissatisfaction, interest) of customer inquiry emails, and the server automatically generates the optimal response based on that. It also analyzes the stress felt by users and the level of interest of customers in real time during sales, and dynamically changes sales strategies based on that data.

[0412] The above are the details of the specific processing steps and operations for each function of the invention that combines the emotion engine. This system makes it possible to improve the efficiency of sales activities, grasp customer needs, make optimal proposals, and respond quickly. Furthermore, the introduction of the emotion engine enables more personalized customer service.

[0413] The processing flow will be explained below.

[0414] Automatic generation of new customer lists

[0415] Step 1:

[0416] The user inputs conditions such as industry, region, related keywords, and sales volume into the terminal.

[0417] Step 2:

[0418] The terminal transmits the input condition data to the server.

[0419] Step 3:

[0420] The server issues queries to external and internal databases based on the received condition data to obtain matching company data.

[0421] Step 4:

[0422] The server filters the acquired company data and removes duplicates and irrelevant data.

[0423] Step 5:

[0424] The server formats the filtered data into a new customer list format and generates the new customer list.

[0425] Step 6:

[0426] The server schedules periodic updates of the generated new customer list.

[0427] Step 7:

[0428] The terminal displays the new customer list to the user and provides it in a downloadable format (CSV, Excel, etc.).

[0429] Auto-reply and follow-up email creation function

[0430] Step 1:

[0431] The server receives an inquiry email from the customer.

[0432] Step 2:

[0433] The server analyzes the content of the received inquiry email using natural language processing technology.

[0434] Step 3:

[0435] The server searches the FAQ database for the best answer based on the analysis results.

[0436] Step 4:

[0437] The server selects an appropriate email template based on the best answer.

[0438] Step 5:

[0439] The server inserts the response content into the email template and creates a reply email.

[0440] Step 6:

[0441] The server automatically sends the created reply mail to the customer who made the inquiry.

[0442] Automatic quote generation function

[0443] Step 1:

[0444] The user inputs the product or service conditions (type, quantity, period, etc.) into the terminal.

[0445] Step 2:

[0446] The terminal transmits the input condition data to the server.

[0447] Step 3:

[0448] The server queries the price database based on the condition data and obtains the corresponding price information.

[0449] Step 4:

[0450] The server calculates an estimate based on the acquired price information.

[0451] Step 5:

[0452] The server formats the calculation results into a PDF estimate.

[0453] Step 6:

[0454] The terminal displays the generated quote to the user and provides it in a downloadable format.

[0455] Customer behavior analysis function

[0456] Step 1:

[0457] The server automatically collects customer purchase history and access history.

[0458] Step 2:

[0459] The server analyzes the collected data using an analysis tool.

[0460] Step 3:

[0461] The server identifies trends and patterns based on the analysis results.

[0462] Step 4:

[0463] The server generates useful insights (such as recommended products and marketing strategies).

[0464] Step 5:

[0465] The server creates specific marketing proposals based on the generated insights.

[0466] Step 6:

[0467] The terminal displays the proposal to the user and provides related materials.

[0468] Competitive research feature

[0469] Step 1:

[0470] The server collects competitor product information from external databases and the web.

[0471] Step 2:

[0472] The server organizes the collected information and compiles it into a format that makes it easy to compare with the company's own products and services.

[0473] Step 3:

[0474] The server compares and analyzes the features, prices, advantages, etc. of its own products with those of its competitors.

[0475] Step 4:

[0476] The server extracts points of differentiation from the results of the comparative analysis.

[0477] Step 5:

[0478] The terminal provides users with a point of differentiation that can be utilized in sales activities.

[0479] Function to create hypothetical questions and answers

[0480] Step 1:

[0481] The server collects past business negotiation history and an FAQ database.

[0482] Step 2:

[0483] The server generates questions and appropriate answers based on the collected information.

[0484] Step 3:

[0485] The server formats the generated questions and answers into a list.

[0486] Step 4:

[0487] The terminal displays a list of expected questions and answers to the user to assist in preparation before the business negotiation.

[0488] Proposal function for the shortest approach to closing

[0489] Step 1:

[0490] The user inputs the agenda and related information into the terminal.

[0491] Step 2:

[0492] The terminal transmits the input information to the server.

[0493] Step 3:

[0494] The server analyzes the agenda and related information and summarizes the points needed to reach a conclusion.

[0495] Step 4:

[0496] The server calculates the time required to discuss each topic.

[0497] Step 5:

[0498] The server will propose the shortest approach to closing based on the required time and points of discussion.

[0499] Step 6:

[0500] The terminal displays the proposal contents to the user and optimizes the progress of the business negotiations.

[0501] Combining Emotion Engines

[0502] Step 1:

[0503] The server sends user input and voice data to the emotion engine.

[0504] Step 2:

[0505] The emotion engine analyzes input data and recognizes the emotional state of the user or customer.

[0506] Step 3:

[0507] The server adjusts the content and timing of the response based on the emotional state data obtained from the emotion engine.

[0508] Step 4:

[0509] The terminal provides the user with an optimized response based on the emotional state.

[0510] The above are the specific processing steps for each function of the invention combined with the emotion engine.

[0511] Example 2

[0512] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0513] Traditionally, sales activities required a wide range of tasks, such as creating a list of new customers, responding to inquiries, generating quotes, analyzing customer behavior, researching competitors, preparing for sales negotiations, and making proposals up to closing, each of which required a great deal of time and effort.In addition, it was difficult to grasp the emotional state of customers and users in real time and respond accordingly, which limited the improvement of customer satisfaction.

[0514] The identification processing by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes: means for automatically generating a new customer list based on conditions such as industry, region, related keywords, and sales volume; means for automatically creating appropriate reply and follow-up emails in response to customer inquiries; means for automatically generating quotations from product and service price lists; means for analyzing customer behavior to create marketing strategies based on purchase history and access history; means for conducting competitive research to analyze the differentiation points of the company's products and services; means for creating anticipated questions and answers before directly negotiating with customers; means for summarizing the points of discussion necessary to reach a conclusion based on input of an agenda and related information, calculating the required time, and proposing the shortest approach to closing; and means for using an emotion engine to recognize the user's emotional state based on user input and voice analysis and adjust the content and timing of responses. This not only improves the efficiency of sales activities but also enables rapid understanding of customer needs and optimal proposals. Furthermore, the introduction of the emotion engine enables more personalized customer service.

[0515] "Means for automatically generating new customer lists" is a function that filters appropriate company data based on conditions such as industry, region, related keywords, and sales volume, and automatically creates new customer lists.

[0516] "Means for automatically creating appropriate reply and follow-up emails" refers to a function that uses natural language processing technology to analyze the content of customer inquiries, search for appropriate answers, and automatically generate and send reply and follow-up emails.

[0517] The "means for automatically generating a quote" is a function that, when you input the conditions of a product or service, retrieves price information from a price database, calculates a quote based on this, and automatically generates a quote.

[0518] "Customer behavior analysis tools" are functions that collect customer purchase history and access history, analyze this data, identify trends and patterns, and generate useful insights.

[0519] "Competitive research tools" is a function that collects information on competitors' products from external databases and the Internet, conducts comparative analysis with your own products, extracts points of differentiation, and develops sales strategies.

[0520] "A means of creating anticipated questions and answers" is a function that predicts questions from customers based on past sales negotiation history and FAQ data, and creates a list of answers.

[0521] "A means of inputting the agenda and related information to summarize the points needed to reach a conclusion, calculate the required time, and propose the shortest approach to closing" is a function that analyzes the agenda and related information input by the user, organizes the necessary points, calculates the required time for each discussion, and proposes the optimal approach to closing.

[0522] "Means using an emotion engine" refers to a function that recognizes the user's emotional state based on input and voice analysis, and adjusts the content and timing of responses based on that data.

[0523] MODE FOR CARRYING OUT THE INVENTION

[0524] This invention provides a system with functions to automatically generate new customer lists based on criteria such as industry, region, related keywords, and sales volume, as well as to automatically create appropriate replies and follow-up emails in response to customer inquiries. This system also includes a customer behavior analysis function that automatically generates quotes from product and service price lists and creates marketing strategies based on purchase and access history. It also analyzes points of differentiation through competitive research, creates anticipated questions and answers before sales negotiations, calculates the required time based on the input of the agenda and related information, and proposes the shortest approach to closing. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, it is possible to dynamically adjust response content and sales strategies.

[0525] Automatic generation of new customer lists

[0526] The server accepts user input criteria, such as industry, region, related keywords, and sales volume, often via a web form. Based on these criteria, the server queries external databases (such as a company information database) or internal databases to retrieve relevant company data. It then filters the retrieved data to create a new customer list. The new customer list is updated periodically to keep it up to date.

[0527] Examples:

[0528] When a user enters the conditions "IT company," "Tokyo," and "cloud services," the server creates a new customer list based on this.

[0529] Auto-reply and follow-up email creation function

[0530] When the server receives an inquiry email from a customer, it analyzes the content using natural language processing technology (e.g., Google NLP API).The server then searches for the most appropriate answer from the FAQ database based on the analysis results, and generates a reply email using an email template based on that answer.The generated email is then automatically sent to the customer.

[0531] Examples:

[0532] When a customer inquires about the specifications of a new product, the server analyzes the content, creates a reply email containing the appropriate specification information from the FAQ database, and sends it.

[0533] Automatic quote generation function

[0534] When the user inputs the product or service conditions (type, quantity, duration, etc.), the terminal retrieves the corresponding price information from the price database. The server calculates an estimate based on the retrieved price information and generates a quote in PDF format. The quote is then provided to the user via the terminal.

[0535] Examples:

[0536] When the user selects an "annual cloud service contract" and a "support package" and enters the conditions, the server retrieves information from a price database, generates a quote in PDF format, and provides it to the user via the terminal.

[0537] Customer behavior analysis function

[0538] The server collects and analyzes customer purchase and access histories. The server then analyzes the data using machine learning algorithms (e.g., clustering and regression analysis), identifies trends and patterns, and generates useful insights. Based on these insights, the server proposes specific marketing strategies and provides them to users via their devices.

[0539] Examples:

[0540] The server analyzes the product categories frequently purchased by a particular customer, proposes a promotion strategy for a new product, and provides it to the user through the terminal.

[0541] Competitive research feature

[0542] The server collects information on competitors' products from external databases and the Internet, compares them with its own products, extracts points of differentiation, and uses this information to develop sales strategies.

[0543] Examples:

[0544] Through comparative analysis with competing products, Server identifies that the advantage of its products is their "comprehensive support system," and reflects this in its sales materials.

[0545] Function to create hypothetical questions and answers

[0546] The server predicts questions customers will have based on past sales negotiation history and FAQ data, and creates a list of answers. The list is provided to the user via their device to help them prepare for sales negotiations.

[0547] Examples:

[0548] The server prepares questions and answers regarding "the cost of introducing a new product" in advance and provides them to the user via the terminal.

[0549] Proposal function for the shortest approach to closing

[0550] The server analyzes the agenda and related information entered by the user, organizes the necessary points of discussion, calculates the required time for each discussion, and proposes the optimal approach to closing the meeting, which is then provided to the user via their device.

[0551] Examples:

[0552] If a user wants to discuss "how to simplify the introduction of a new product," the server will calculate the required time and propose the optimal approach, and provide it to the user through the terminal.

[0553] Combining Emotion Engines

[0554] The server uses an emotion engine (e.g., Microsoft Azure Cognitive Services) that recognizes the user's emotional state based on user input and voice analysis. The emotion engine analyzes the user's or customer's emotional state in real time and appropriately adjusts the content and timing of responses based on that data.

[0555] Examples:

[0556] The emotion engine analyzes the emotional tone (e.g., dissatisfaction, interest) of customer inquiry emails, and the server automatically generates the optimal response based on that and sends it via email. It also analyzes the stress felt by users and the level of interest of customers during sales in real time, and dynamically changes sales strategies based on that data.

[0557] The system will streamline sales activities through each function, enabling quick understanding of customer needs and optimal proposals. The introduction of an emotion engine will also enable more personalized customer service.

[0558] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0559] Automatic generation of new customer lists

[0560] Processing Steps

[0561] Step 1: Accept conditions

[0562] The server accepts user inputs from the terminal such as industry, region, related keywords, sales volume, etc. The input data is used to issue subsequent queries.

[0563] Input: User-entered industry, region, related keywords, and sales volume

[0564] Output: Condition data for issuing a query

[0565] Step 2: Query the database

[0566] The server issues queries to external and internal databases based on the input condition data, for example, by generating SQL statements and sending them to the databases.

[0567] Input: Condition data

[0568] Output: A list of companies retrieved from the database

[0569] Step 3: Filtering the data

[0570] The server filters the acquired company data based on conditions, for example, extracting only data from IT companies in the Tokyo region.

[0571] Input: A list of companies retrieved from a database

[0572] Output: Filtered company data

[0573] Step 4: Generate a new customer list

[0574] The server creates a list of new customers based on the filtered company data, often stored in JSON or CSV format.

[0575] Input: Filtered company data

[0576] Output: New customer list

[0577] Step 5: Providing a list of new customers

[0578] The server provides the generated new customer list to the user's terminal, including via a web page or email.

[0579] Input: New Customer List

[0580] Output: A list of new customers displayed on the user's device.

[0581] ---

[0582] Auto-reply and follow-up email creation function

[0583] Processing Steps

[0584] Step 1: Receiving an inquiry email

[0585] The server receives inquiry emails from customers, which is often received via an SMTP server.

[0586] Input: Customer inquiry email

[0587] Output: Contents of inquiry email

[0588] Step 2: Analyzing the email content

[0589] The server analyzes the content of the received inquiry email using natural language processing technology to extract the email's topic and emotional tone.

[0590] Input: Contents of inquiry email

[0591] Output: Parsed email content

[0592] Step 3: Finding the best answer

[0593] The server searches the FAQ database for the best answer based on the analysis results, using a similarity search algorithm to select the most relevant answer.

[0594] Input: Parsed email content

[0595] Output: Best answer

[0596] Step 4: Generate a reply email

[0597] The server generates a reply email using an email template based on the selected answer, with variables embedded in the template that are then replaced with actual data.

[0598] Input: Best Answer

[0599] Output: The generated reply email

[0600] Step 5: Send a reply email

[0601] The server generates a reply email and sends it to the customer, via an SMTP server.

[0602] Input: Generated reply email

[0603] Output: Reply email to customer

[0604] ---

[0605] Automatic quote generation function

[0606] Processing Steps

[0607] Step 1: Enter the condition

[0608] The terminal accepts the product or service conditions (type, quantity, duration, etc.) entered by the user, often via a web form.

[0609] Input: User-entered product or service terms

[0610] Output: Condition data

[0611] Step 2: Get pricing information

[0612] The server retrieves the relevant price information from the price database based on the entered condition data, and uses an SQL query to retrieve the price information.

[0613] Input: Condition data

[0614] Output: Price information

[0615] Step 3: Calculate the estimate

[0616] The server calculates an estimate based on the acquired price information, taking into account conditions such as quantity and period.

[0617] Input: Price Information

[0618] Output: Calculated estimate data

[0619] Step 4: Generate a quote

[0620] The server generates a PDF quotation based on the calculation results using a PDF generation library.

[0621] Input: Estimate data

[0622] Output: PDF quotation

[0623] Step 5: Provide a quote

[0624] The server provides the generated quote to the user via the terminal, which may include sending it by email or providing a download link.

[0625] Input: PDF quotation

[0626] Output: Quote provided to user

[0627] ---

[0628] Customer behavior analysis function

[0629] Processing Steps

[0630] Step 1: Data collection

[0631] The server collects customer purchase and access histories from web logs and transaction databases.

[0632] Input: purchase history, access history

[0633] Output: Collected data

[0634] Step 2: Data analysis

[0635] The server analyzes the collected data using machine learning algorithms (e.g., clustering, regression analysis).

[0636] Input: Collected data

[0637] Output: Analysis results

[0638] Step 3: Generate insights

[0639] The server identifies trends and patterns from the analysis results and generates useful insights.

[0640] Input: Analysis results

[0641] Output:Insight

[0642] Step 4: Propose marketing measures

[0643] The server creates specific marketing proposals based on the generated insights and provides them to the user via the terminal.

[0644] Input: Insight

[0645] Output: Marketing Strategy

[0646] ---

[0647] Combining Emotion Engines

[0648] Processing Steps

[0649] Step 1: Parse the input

[0650] The server accepts user input (text, voice) and analyzes it using natural language processing technology.

[0651] Input: What the user types

[0652] Output: Parsed input

[0653] Step 2: Recognizing your emotional state

[0654] The server uses an emotion engine to recognize the emotional state based on the analysis results, for example, identifying emotions such as excitement, anxiety, and calm.

[0655] Input: Parsed input

[0656] Output: Emotional state

[0657] Step 3: Tailor your response

[0658] The server adjusts the content and timing of responses based on the user's perceived emotional state: for example, if the user is frustrated, a more friendly response will be automatically chosen.

[0659] Input: Emotional state

[0660] Output: Adjusted response content

[0661] Step 4: User feedback

[0662] The server provides tailored responses to the user via the terminal, providing real-time feedback.

[0663] Input: Adjusted response content

[0664] Output: Feedback to the user

[0665] ---

[0666] The above are the specific processing steps for each function of this system. This will improve the efficiency of sales activities, quickly grasp customer needs, and make optimal proposals. The introduction of an emotion engine will also enable more personalized customer service.

[0667] (Application example 2)

[0668] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0669] In today's business environment, companies must efficiently perform a wide range of tasks, including acquiring new customers, responding quickly and appropriately to existing customers, creating product and service quotes, analyzing competitors, and preparing for sales negotiations. However, performing these tasks manually is extremely time-consuming and labor-intensive, resulting in inefficiency and low accuracy. Furthermore, security incident response requires real-time monitoring and appropriate action, and performing this manually carries high risks. To solve these issues, it is necessary to automate these tasks and utilize sentiment analysis to make appropriate decisions quickly.

[0670] 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.

[0671] In this invention, the server includes means for automatically generating a new customer list based on conditions such as industry, region, related keywords, and sales volume, means for automatically creating appropriate reply and follow-up emails in response to inquiries, means for automatically generating quotes from product and service price lists, means for analyzing customer behavior to create marketing strategies based on purchase history and access history, means for conducting competitive research to analyze the differentiating points of a company's products and services, means for creating anticipated questions and answers before directly negotiating with customers, means for summarizing the points of discussion necessary to reach a conclusion based on input of an agenda and related information, calculating the required time, and proposing the shortest approach to closing, and means for analyzing the details of a security incident and determining appropriate actions based on the emotional state.This enables more efficient sales activities, understanding customer needs, optimal proposals, rapid responses, and appropriate security responses based on emotional analysis.

[0672] "Automatic generation of new customer lists" is a system that lists potential new customers based on criteria such as industry, region, related keywords, and sales volume.

[0673] "Creating automatic replies and follow-up emails" is a system that uses natural language processing technology to automatically create appropriate replies to customer inquiries and send them via email.

[0674] "Automatic quotation generation" is a system that automatically creates a quotation based on specified conditions from a price list for a product or service.

[0675] "Customer behavior analysis" is a system that analyzes customers' purchase history and access history and proposes effective marketing measures.

[0676] "Competitive research" is a system that uses collected competitive information to compare your own products and services with those of your competitors and extract points of differentiation.

[0677] "Creating anticipated questions and answers" is a system that prepares anticipated questions and answers before directly negotiating with a customer.

[0678] "Proposing the shortest approach to closing" is a system that, when you input the agenda and related information, summarizes the points needed to reach a conclusion, calculates the required time, and proposes the optimal approach to successfully close a business negotiation.

[0679] "Security Incident Analysis" is a system that analyzes the details of a security incident and determines appropriate actions based on emotional state.

[0680] "Emotion analysis" is a technology that uses natural language processing technology to analyze the emotional state of text or speech and determine an appropriate response based on that.

[0681] MODE FOR CARRYING OUT THE INVENTION

[0682] This invention provides a system with the functions of automatically generating new customer lists based on conditions such as industry, region, related keywords, and sales volume, and automatically creating appropriate replies and follow-up emails to inquiries. Furthermore, the system also includes functions for automatically generating quotes from product and service price lists, analyzing customer behavior to create marketing strategies based on purchase and access histories, analyzing points of differentiation through competitive research, creating anticipated questions and answers before business negotiations, calculating the required time by inputting agenda items and related information, and proposing the shortest approach to closing. It also combines emotional analysis with security incident analysis to dynamically determine appropriate actions.

[0683] System configuration

[0684] The system consists of the following main components:

[0685] 1. Server:

[0686] Hardware: A powerful processor (e.g., Intel Xeon), lots of memory (e.g., 32GB RAM), and fast storage (e.g., SSD).

[0687] Software: Database management systems (e.g., MySQL), natural language processing engines (e.g., NLTK), sentiment analysis engines (e.g., Sentiment Analysis Toolkit), report generators (e.g., ReportLab).

[0688] 2. Terminal:

[0689] Hardware: Smartphone.

[0690] Software: Operating systems (e.g., Android, iOS), mobile applications.

[0691] System Operation

[0692] The server analyzes user input and sensor data in real time and performs the following data processing and calculations:

[0693] Auto-generate new customer lists:

[0694] The server issues queries to external and internal databases based on user-entered criteria such as industry, region, related keywords, and sales volume, and the retrieved data is filtered to automatically generate a new customer list.

[0695] Creating Auto-Reply & Follow-Up Emails:

[0696] The server uses natural language processing technology to analyze the inquiry and search for the appropriate answer in the FAQ database, then automatically creates and sends a reply email based on that answer.

[0697] Auto-generate quotes:

[0698] The server retrieves the relevant information from a price database based on the product or service conditions entered by the user, and automatically calculates a quote. The quote is generated in PDF format and provided via the terminal.

[0699] Customer behavior analysis:

[0700] The server collects customer purchase and access histories and analyzes the data, which is then used to create marketing strategies.

[0701] Competitive Research:

[0702] The server collects information on competitors from external databases and the Internet, and performs comparative analysis with the company's own products. Differentiating points are extracted and reflected in sales strategies.

[0703] Creating anticipated questions and answers:

[0704] The server creates a list of anticipated questions and their answers based on past business negotiation history and FAQ data, thereby supporting pre-negotiation preparation.

[0705] Suggested quickest approach to closing:

[0706] Based on the agenda and related information, the server summarizes the points of discussion and calculates the required time to propose the optimal closing approach.

[0707] Security incident analysis:

[0708] The server analyzes the details of the security incident and determines the appropriate action based on the emotional state, enabling appropriate responses in real time.

[0709] Specific examples

[0710] Suppose a user is in charge of security management for a company that holds art exhibitions. Security incidents often occur when a new exhibition opens. Using SmartGuard-S, the user can continuously monitor new incidents and view details in the application. If the incident is deemed urgent, the sentiment analysis engine will issue an "urgent alert" and the appropriate response method will be automatically displayed. The user can also automatically generate new customer lists and quotes based on specific conditions (e.g., exhibition location, type of exhibit, security requirements).

[0711] Prompt Sentence Examples

[0712] "How can I analyze the details of a recent security incident, classify its emotional state, and generate applicable actions and reports?"

[0713] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0714] Processing Steps

[0715] Step 1:

[0716] The user uses a terminal to input conditions such as industry, region, related keywords, sales volume, etc. This input data is sent to the server.

[0717] Step 2:

[0718] The server issues queries to external and internal databases based on the received criteria, thereby retrieving the relevant company data.

[0719] Step 3:

[0720] The server filters the acquired company data and automatically generates a new customer list, which is updated periodically.

[0721] Step 4:

[0722] When a user sends an inquiry email using a terminal, the server receives it and analyzes it using natural language processing technology.

[0723] Step 5:

[0724] The server searches the FAQ database for the best answer based on the analysis results, and automatically creates a reply email based on the selected answer.

[0725] Step 6:

[0726] The server sends the created reply mail to the user's terminal, and also automatically creates and sends a follow-up mail.

[0727] Step 7:

[0728] The user inputs product or service conditions (type, quantity, period, etc.) into the terminal. This input data is sent to the server.

[0729] Step 8:

[0730] The server retrieves the relevant price information from the price database, calculates the estimate based on that information, and creates a quote in PDF format based on the calculation results.

[0731] Step 9:

[0732] The server sends the estimate to the terminal and provides it to the user.

[0733] Step 10:

[0734] The server collects and analyzes customer purchase history and access history from a database and creates marketing strategies.

[0735] Step 11:

[0736] The server collects information on competitors from external databases and the Internet, performs comparative analysis with the company's own products, extracts points of differentiation, and reflects them in sales strategies.

[0737] Step 12:

[0738] The server creates a list of predicted and anticipated questions and their answers based on past business negotiation history and FAQ data.

[0739] Step 13:

[0740] Based on the agenda and related information entered by the user, the server summarizes the points needed to reach a conclusion, calculates the required time, and proposes a closing approach.

[0741] Step 14:

[0742] The server analyzes the details of the security incident and classifies the emotional state of the incident using an emotional analysis engine.

[0743] Step 15:

[0744] Based on the classification results, the server determines the appropriate action to take, such as high alert, monitoring, low alert, etc. The generated report is provided to the user in a format that can be viewed in real time.

[0745] Specific examples of processing

[0746] Step 1:

[0747] The user uses a terminal to enter conditions such as "IT company," "Tokyo," "cloud service," and "sales size: small and medium-sized enterprises," and sends the results to the server.

[0748] Input: "IT company", "Tokyo", "Cloud service", "Sales size: Small and medium-sized enterprises"

[0749] Output: The condition is sent to the server.

[0750] Step 2:

[0751] The server retrieves relevant company data from external and internal databases based on the received conditions.

[0752] Input: Received condition data

[0753] Output: Acquisition of relevant company data

[0754] Step 3:

[0755] The server filters the acquired company data and automatically generates a new customer list, which is updated periodically.

[0756] Input: Acquired company data

[0757] Output: Generate and update new customer list

[0758] Step 4:

[0759] The user sends an inquiry email from the terminal, which is received by the server and analyzed using natural language processing technology.

[0760] Input: Inquiry email

[0761] Output: Analysis results

[0762] Step 5:

[0763] The server searches the FAQ database for the best answer and automatically creates a reply email.

[0764] Input: Analysis results

[0765] Output: Auto-generated reply email

[0766] Step 6:

[0767] The server sends the reply email to the user's terminal and also creates and sends a follow-up email.

[0768] Input: Draft of reply email

[0769] Output: Reply and follow-up emails sent

[0770] Step 7:

[0771] The user enters conditions such as "cloud service," "annual contract," and "5 licenses" on the device. The input data is sent to the server.

[0772] Input: Terms such as "Cloud service," "Annual contract," and "5 licenses"

[0773] Output: The condition is sent to the server

[0774] Step 8:

[0775] The server retrieves the relevant price information from the price database, automatically calculates an estimate based on that information, and creates an estimate in PDF format.

[0776] Input: Submitted condition data

[0777] Output: PDF quotation

[0778] Step 9:

[0779] The server sends the estimate in PDF format to the terminal and provides it to the user.

[0780] Input: PDF quotation

[0781] Output: Quote provided to user

[0782] Step 10:

[0783] The server collects customer purchase history and access history from a database, analyzes them, and creates marketing strategies.

[0784] Input: Customer purchase history and access history

[0785] Output: Marketing Strategy

[0786] Step 11:

[0787] The server collects information on competitors, performs comparative analysis with its own products, and extracts points of differentiation.

[0788] Input: Competitor Information

[0789] Output: Differentiation points and sales strategies

[0790] Step 12:

[0791] The server creates a list of anticipated questions and answers before the business meeting and provides it to the user.

[0792] Input: Sales history and FAQ data

[0793] Output: List of expected questions and answers

[0794] Step 13:

[0795] When the user inputs the agenda and related information, the server summarizes the necessary points, calculates the required time, and suggests a closing approach.

[0796] Input: Agenda and related information

[0797] Output: Shortest approach to closing

[0798] Step 14:

[0799] The server analyzes the details of the security incident and classifies the emotional state.

[0800] Input: Security incident details

[0801] Output: Emotional state classification result

[0802] Step 15:

[0803] The server determines the appropriate action based on the classification results and performs incident response. The generated report is provided to the user in real time.

[0804] Input: Emotional state classification results

[0805] Output: Appropriate actions and incident response report

[0806] 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.

[0807] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0808] 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.

[0809] [Second embodiment]

[0810] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0811] 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.

[0812] 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).

[0813] 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.

[0814] 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.

[0815] 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).

[0816] 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.

[0817] 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.

[0818] 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.

[0819] 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.

[0820] In the smart glasses 214, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0821] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0822] MODE FOR CARRYING OUT THE INVENTION

[0823] This invention provides a system with functions to automatically generate new customer lists based on criteria such as industry, region, related keywords, and sales volume, as well as to automatically create appropriate replies and follow-up emails to inquiries. This system also includes a customer behavior analysis function that automatically generates quotes from product and service price lists and creates marketing strategies based on purchase and access history. Furthermore, the system also has functions to analyze points of differentiation through competitive research, create anticipated questions and answers before negotiations, calculate the required time by entering the agenda and related information, and propose the shortest approach to closing.

[0824] Program processing details

[0825] Automatic generation of new customer lists

[0826] The server accepts user input of criteria such as industry, region, related keywords, and sales volume, and issues queries to external and internal databases to retrieve appropriate company data. The retrieved data is then filtered and a new customer list is automatically generated. The generated list is periodically updated and provided to the user via their device.

[0827] Examples:

[0828] The user enters the conditions "IT company," "Tokyo," and "cloud service," and the server creates a new customer list based on this.

[0829] Auto-reply and follow-up email creation function

[0830] When the server receives an inquiry email from a customer, it analyzes the content using natural language processing technology and searches for the most appropriate answer from the FAQ database. Based on the selected answer, it selects an email template and automatically creates a reply email. The reply email is then automatically sent to the customer.

[0831] Examples:

[0832] When a customer inquires about the specifications of a new product, the server creates and sends a reply email containing the appropriate specification information.

[0833] Automatic quote generation function

[0834] When the user inputs the product or service conditions (type, quantity, duration, etc.), the terminal retrieves the corresponding price information from the price database. The server calculates the estimate based on this information and creates a quote in PDF format. The quote is then provided to the user via the terminal.

[0835] Examples:

[0836] When the user selects an annual cloud service contract and a support package, the device automatically generates a quote.

[0837] Customer behavior analysis function

[0838] The server collects customer purchase and access histories and performs analysis based on this data. It identifies trends and patterns and generates useful insights. Based on this, it creates specific marketing proposals.

[0839] Examples:

[0840] The server analyzes the product categories that a particular customer frequently purchases and proposes new product promotion strategies.

[0841] Competitive research feature

[0842] The server collects information on competitors' products from external databases and the Internet, performs comparative analysis with the company's own products, extracts points of differentiation, and develops sales strategies based on these.

[0843] Examples:

[0844] Through comparative analysis with competing products, Server identifies that the advantage of its products is their "extensive support system," and reflects this information in its sales materials.

[0845] Function to create hypothetical questions and answers

[0846] The server predicts questions customers will have based on past sales negotiation history and FAQ data, and creates a list of answers. This is provided to the user via their device to help them prepare for sales negotiations.

[0847] Examples:

[0848] The server prepares questions and answers regarding "the cost of introducing a new product" in advance and provides them to the user.

[0849] Proposal function for the shortest approach to closing

[0850] The server analyzes the agenda and related information entered by the user, summarizes the points of discussion necessary to reach a conclusion, calculates the time required for each discussion, and proposes the optimal approach to closing the meeting, which is then provided to the user via their device.

[0851] Examples:

[0852] If a user wants to discuss "how to simplify the introduction of a new product," the server will calculate the required time and propose the optimal approach, and provide it to the user.

[0853] The above is a specific example of an embodiment of the invention and details of the program processing. This system makes it possible to improve the efficiency of sales activities, grasp customer needs, make optimal proposals, and respond quickly.

[0854] The processing flow will be explained below.

[0855] Automatic generation of new customer lists

[0856] Step 1:

[0857] The user inputs conditions such as industry, region, related keywords, and sales volume into the terminal.

[0858] Step 2:

[0859] The terminal transmits the input conditions to the server.

[0860] Step 3:

[0861] The server accesses the external database and the internal database based on the received condition data to obtain the matching company data.

[0862] Step 4:

[0863] The server filters the acquired company data and removes duplicates and irrelevant data.

[0864] Step 5:

[0865] The server formats the filtered data into a new customer list.

[0866] Step 6:

[0867] The server schedules periodic updates of the new customer list.

[0868] Step 7:

[0869] The terminal displays the new customer list to the user and provides it in a downloadable format (CSV, Excel, etc.).

[0870] Auto-reply and follow-up email creation function

[0871] Step 1:

[0872] The server receives an inquiry email from the customer.

[0873] Step 2:

[0874] The server analyzes the content of the received inquiry email using natural language processing technology.

[0875] Step 3:

[0876] The server searches the FAQ database for the best answer based on the analysis results.

[0877] Step 4:

[0878] The server selects an appropriate email template based on the selected answer.

[0879] Step 5:

[0880] The server inserts the reply content into the template and automatically creates a reply email.

[0881] Step 6:

[0882] The server automatically sends the created reply mail to the customer who made the inquiry.

[0883] Automatic quote generation function

[0884] Step 1:

[0885] The user inputs the product or service conditions (type, quantity, period, etc.) into the terminal.

[0886] Step 2:

[0887] The terminal transmits the input conditions to the server.

[0888] Step 3:

[0889] The server queries the price database based on the condition data and obtains the corresponding price information.

[0890] Step 4:

[0891] The server calculates an estimate based on the acquired price information.

[0892] Step 5:

[0893] The server formats the calculation results into a PDF estimate.

[0894] Step 6:

[0895] The terminal displays the generated quote to the user and provides it in a downloadable format.

[0896] Customer behavior analysis function

[0897] Step 1:

[0898] The server automatically collects customer purchase history and access history.

[0899] Step 2:

[0900] The server analyzes the collected data using an analysis tool.

[0901] Step 3:

[0902] The server identifies trends and patterns based on the analysis results.

[0903] Step 4:

[0904] The server generates useful insights (such as recommended products and marketing strategies).

[0905] Step 5:

[0906] The server creates specific marketing proposals based on the generated insights.

[0907] Step 6:

[0908] The terminal displays the proposal to the user and provides related materials.

[0909] Competitive research feature

[0910] Step 1:

[0911] The server collects competitor product information from external databases and the web.

[0912] Step 2:

[0913] The server organizes the collected information and compiles it into a format that makes it easy to compare with the company's own products and services.

[0914] Step 3:

[0915] The server compares and analyzes the features, prices, advantages, etc. of its own products with those of its competitors.

[0916] Step 4:

[0917] The server extracts points of differentiation from the results of the comparative analysis.

[0918] Step 5:

[0919] The terminal provides users with a point of differentiation that can be utilized in sales activities.

[0920] Function to create hypothetical questions and answers

[0921] Step 1:

[0922] The server collects past business negotiation history and an FAQ database.

[0923] Step 2:

[0924] The server generates questions and appropriate answers based on the collected information.

[0925] Step 3:

[0926] The server formats the generated questions and answers into a list.

[0927] Step 4:

[0928] The terminal displays a list of expected questions and answers to the user to assist in preparation before the business negotiation.

[0929] Proposal function for the shortest approach to closing

[0930] Step 1:

[0931] The user inputs the agenda and related information into the terminal.

[0932] Step 2:

[0933] The terminal transmits the input information to the server.

[0934] Step 3:

[0935] The server analyzes the agenda and related information and summarizes the points needed to reach a conclusion.

[0936] Step 4:

[0937] The server calculates the time required to discuss each topic.

[0938] Step 5:

[0939] The server will propose the shortest approach to closing based on the required time and points of discussion.

[0940] Step 6:

[0941] The terminal displays the proposal contents to the user and optimizes the progress of the business negotiations.

[0942] The above are the specific processing steps for each function in the embodiment of the invention.

[0943] Example 1

[0944] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0945] Modern sales and marketing activities require the ability to quickly and accurately generate new customer lists and conduct effective follow-up. However, performing these tasks manually takes a significant amount of time and effort and is prone to errors. It is also difficult to efficiently perform a wide range of tasks, such as competitor research, creating quotes, and preparing for sales negotiations. Furthermore, analyzing customer behavior and developing optimal marketing strategies are also necessary. To solve these challenges, a system that automates and optimizes all processes is needed.

[0946] 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.

[0947] In this invention, the server includes: means for automatically generating a new customer list based on criteria such as industry, region, related keywords, and sales volume; means for receiving inquiry emails from customers, analyzing the content using natural language processing technology, and automatically creating and sending appropriate reply and follow-up emails; means for retrieving information from a price database based on product or service criteria (type, quantity, duration, etc.), automatically generating quotes, and creating quote documents in PDF format; means for analyzing customer purchase histories and access histories to create marketing strategies; means for conducting competitive research by collecting information on competing products from external databases and the Internet and comparing and analyzing them with the company's own products to identify points of differentiation; means for predicting customer questions based on past sales negotiation history and FAQ data and creating a list of anticipated questions and answers; and means for summarizing the points of discussion necessary to reach a conclusion, calculating the required time, and proposing the shortest approach to closing a deal when the topic and related information are input. This enables more efficient sales activities, early identification of customer needs, appropriate proposals, and rapid responses.

[0948] "Means for automatically generating new customer lists" is a function that automatically generates new customer lists by retrieving and filtering appropriate company data from external and internal databases based on conditions entered by the user, such as industry, region, related keywords, and sales volume.

[0949] "Means for automatically creating and sending appropriate reply / follow-up emails" refers to a function that receives inquiry emails from customers, analyzes the content using natural language processing technology, searches for the most appropriate answer from the FAQ database, and automatically creates and sends reply / follow-up emails using email templates.

[0950] "Means to automatically generate quotes and create quotes in PDF format" refers to a function that, when a user inputs the product or service conditions (type, quantity, period, etc.), retrieves the relevant price information from a price database, calculates a quote based on this, and creates a quote in PDF format.

[0951] "Customer behavior analysis tools" are functions that collect customer purchase history and access history, analyze this data to identify trends and patterns, generate useful insights, and propose specific marketing measures.

[0952] "Competitive research tools" is a function that collects information on competitors' products from external databases and the Internet, performs comparative analysis with your own products, extracts points of differentiation, and develops sales strategies.

[0953] "A means to create a list of anticipated questions and answers" is a function that predicts questions from customers based on past sales negotiation history and FAQ data, and compiles and creates a list of answers.

[0954] "A means of inputting the agenda and related information, summarizing the points needed to reach a conclusion, calculating the required time, and proposing the shortest approach to closing" is a function that, when a user inputs the agenda and related information, analyzes them, summarizes the points needed to reach a conclusion, calculates the required time for each discussion, and proposes the optimal closing approach.

[0955] MODE FOR CARRYING OUT THE INVENTION

[0956] This invention provides a system with functions to automatically generate new customer lists based on criteria such as industry, region, related keywords, and sales volume, as well as to automatically create appropriate replies and follow-up emails to inquiries. This system also includes a customer behavior analysis function that automatically generates quotes from product and service price lists and creates marketing strategies based on purchase and access history. Furthermore, the system also has functions to analyze points of differentiation through competitive research, create anticipated questions and answers before sales negotiations, calculate the required time by entering the agenda and related information, and propose the shortest approach to closing.

[0957] Overall structure

[0958] The system mainly consists of a server and a terminal. The server processes and analyzes data, while the terminal accepts input from users and displays the results. The server incorporates natural language processing technology and is connected to external and internal databases. The terminal provides a user interface and communicates with the server in response to user input.

[0959] Automatic generation of new customer lists

[0960] The server accepts user input of criteria such as industry, region, related keywords, and sales volume, and issues queries to external and internal databases to retrieve appropriate company data. The retrieved data is then filtered and a new customer list is automatically generated. The generated list is periodically updated and provided to the user via their device.

[0961] Examples:

[0962] The user enters the conditions "IT company," "Tokyo," and "cloud service" via the terminal, and the server creates a new customer list based on this.

[0963] Auto-reply and follow-up email creation function

[0964] When the server receives an inquiry email from a customer, it analyzes the content using natural language processing technology and searches for the most appropriate answer from the FAQ database. Based on the selected answer, it selects an email template and automatically creates a reply email. The reply email is then automatically sent to the customer.

[0965] Examples:

[0966] When a customer inquires about the specifications of a new product, the server creates and sends a reply email containing the appropriate specification information.

[0967] Automatic quote generation function

[0968] When the user inputs the product or service conditions (type, quantity, duration, etc.), the terminal retrieves the corresponding price information from the price database. The server calculates the estimate based on this information and creates a quote in PDF format. The quote is then provided to the user via the terminal.

[0969] Examples:

[0970] When the user selects an annual cloud service contract and a support package, the device automatically generates a quote.

[0971] Customer behavior analysis function

[0972] The server collects customer purchase and access histories and performs analysis based on this data. It identifies trends and patterns and generates useful insights. Based on this, it creates specific marketing proposals.

[0973] Examples:

[0974] The server analyzes the product categories that a particular customer frequently purchases and proposes new product promotion strategies.

[0975] Competitive research feature

[0976] The server collects information on competitors' products from external databases and the Internet, performs comparative analysis with the company's own products, extracts points of differentiation, and develops sales strategies based on these.

[0977] Examples:

[0978] Through comparative analysis with competing products, Server identifies that the advantage of its products is their "extensive support system," and reflects this information in its sales materials.

[0979] Function to create hypothetical questions and answers

[0980] The server predicts questions customers will have based on past sales negotiation history and FAQ data, and creates a list of answers. This is provided to the user via their device to help them prepare for sales negotiations.

[0981] Examples:

[0982] The server prepares questions and answers regarding "the cost of introducing a new product" in advance and provides them to the user.

[0983] Proposal function for the shortest approach to closing

[0984] The server analyzes the agenda and related information entered by the user, summarizes the points of discussion necessary to reach a conclusion, calculates the time required for each discussion, and proposes the optimal approach to closing the meeting, which is then provided to the user via their device.

[0985] Examples:

[0986] If a user wants to discuss "how to simplify the introduction of a new product," the server will calculate the required time and propose the optimal approach, and provide it to the user.

[0987] This system will enable more efficient sales activities, understanding of customer needs, optimal proposals, and quick responses.

[0988] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0989] Automatic generation of new customer lists

[0990] Step 1: Enter the condition

[0991] The user inputs conditions such as industry, region, related keywords, sales volume, etc. via a terminal. This input is sent to the server in the form of a query.

[0992] Step 2: Query the database

[0993] The server issues queries to external and internal databases based on the criteria received from the user, and the databases return company data that matches the specified criteria.

[0994] Step 3: Filtering the data

[0995] The server filters the acquired company data, specifically by organizing the data based on industry and region, and prioritizing data that matches related keywords and sales volume.

[0996] Step 4: Generate a customer list

[0997] The server generates a new customer list based on the filtered data, and outputs the list in the specified format (e.g., CSV, Excel, etc.).

[0998] Step 5: Provide a list

[0999] The server provides the generated new customer list to the user through the terminal, and the user downloads the list as needed.

[1000] ---

[1001] Auto-reply and follow-up email creation function

[1002] Step 1: Receiving an inquiry email

[1003] The server receives email inquiries from customers, which are then passed to the natural language processing module.

[1004] Step 2: Content Analysis

[1005] The server uses natural language processing technology to analyze the content of the inquiry email, extracting the main questions and keywords.

[1006] Step 3: Search for answers in the FAQ database

[1007] The server searches the FAQ database for the best answer based on the analysis results, and the search results also include the reliability and relevance of the answer.

[1008] Step 4: Select a template and create an email

[1009] The server then selects the appropriate email template based on the selected answer and automatically creates a reply email, adding personalized information for the customer.

[1010] Step 5: Sending an email

[1011] The server automatically sends a reply email to the customer. A sending log is saved, allowing you to check and resend the email if necessary.

[1012] ---

[1013] Automatic quote generation function

[1014] Step 1: Enter the condition

[1015] The user inputs product or service conditions (type, quantity, period, etc.) into the terminal. This input is sent to the server.

[1016] Step 2: Get pricing information

[1017] The terminal retrieves the relevant price information from the price database via the server, and the retrieved data is temporarily stored in memory.

[1018] Step 3: Calculate the estimate

[1019] The server calculates a quote based on the retrieved pricing information, which reflects the terms and conditions of the product or service.

[1020] Step 4: Create a quote

[1021] The server generates a quote in PDF format based on the calculation results, and the generated PDF file is saved on the server.

[1022] Step 5: Provide a quote

[1023] The server provides the generated estimate to the user through the terminal, and the user can download and print the estimate.

[1024] ---

[1025] Customer behavior analysis function

[1026] Step 1: Collect data

[1027] The server collects customer purchase and access history, and the collected data is stored in a database that is updated regularly.

[1028] Step 2: Analyze the data

[1029] The server analyzes the collected data, using statistical methods and machine learning algorithms.

[1030] Step 3: Generate insights

[1031] The server generates useful insights based on the analysis results, including customer purchasing patterns and trends.

[1032] Step 4: Propose marketing measures

[1033] The server proposes specific marketing measures based on the generated insights, and outputs these proposals in the form of a report.

[1034] Step 5: Provide a proposal

[1035] The server provides the created proposal to the user via the terminal, and the user downloads and checks the proposal report and uses it to implement measures.

[1036] ---

[1037] Competitive research feature

[1038] Step 1: Collect data

[1039] The server collects competitor product information from external databases and the Internet, and the collected data is stored in an internal database.

[1040] Step 2: Comparative product analysis

[1041] The server compares and analyzes the company's products with the collected information on competing products, including extracting points of differentiation.

[1042] Step 3: Identifying points of differentiation

[1043] The server extracts points of differentiation from the comparative analysis, which then become the basis for sales strategies.

[1044] Step 4: Develop a sales strategy

[1045] The server then creates a sales strategy based on the extracted differentiation points, and outputs the created strategy as a report.

[1046] Step 5: Deliver a strategy

[1047] The server provides the planned strategy to the user via the terminal, who then checks the strategy report and reflects it in their sales activities.

[1048] ---

[1049] Function to create hypothetical questions and answers

[1050] Step 1: Collect historical data

[1051] The server collects past business negotiation history and FAQ data, which is then stored in a database.

[1052] Step 2: Anticipate questions

[1053] The server uses collected data to predict what questions customers will ask, using machine learning algorithms.

[1054] Step 3: Prepare your response

[1055] The server compiles answers to the predicted questions, and organizes the answers in an appropriate format.

[1056] Step 4: Create a list

[1057] The server creates a list of questions and answers, which are used to prepare for the meeting.

[1058] Step 5: Provide a list

[1059] The server provides the created list to the user via the terminal, who can refer to the list and use it to prepare for business negotiations.

[1060] ---

[1061] Proposal function for the shortest approach to closing

[1062] Step 1: Enter your agenda

[1063] The user inputs the agenda and related information into the terminal, which is then sent to the server.

[1064] Step 2: Analyze the information

[1065] The server analyzes the input agenda and related information, and this analysis clarifies the necessary points of discussion.

[1066] Step 3: Summary

[1067] The server summarizes the arguments needed to reach a conclusion, which are used to calculate the time required in step 4.

[1068] Step 4: Calculate the time required

[1069] The server calculates the time required for each point, and the results serve as data to guide the optimal closing approach.

[1070] Step 5: Providing an approach

[1071] The server proposes the optimal approach to closing and provides it to the user via the terminal. The user then carries out closing activities based on the proposed approach.

[1072] This detailed processing flow enables users to efficiently carry out sales and marketing activities, and improve the accuracy and speed of customer service.

[1073] (Application example 1)

[1074] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1075] In today's society, there is a demand for more efficient sales activities and faster customer responses. However, traditional sales support systems separate the processes of generating new customer lists, responding to inquiries, creating quotes, analyzing customer behavior, researching competitors, preparing sales negotiations, and closing sales, and lack integrated support. As a result, the efficiency of sales activities can decrease and the quality of customer responses can also be compromised.

[1076] 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.

[1077] In this invention, the server includes: means for automatically generating a new customer list based on criteria such as industry, region, related keywords, and sales volume; means for automatically creating appropriate reply and follow-up emails in response to customer inquiries; means for automatically generating quotations from product and service price lists; means for analyzing customer behavior to create marketing strategies based on purchase history and access history; means for conducting competitive research to analyze the differentiation points of a company's products and services; means for creating anticipated questions and answers before directly negotiating with customers; means for inputting an agenda and related information, summarizing the points of discussion necessary to reach a conclusion, calculating the required time, and proposing the shortest approach to closing; means for analyzing customer inquiries using natural language processing technology and searching for optimal answers from an FAQ database; means for retrieving data from external and internal databases based on query criteria, filtering, and automatically updating the list; and means for documenting the generated information in PDF format and electronically transmitting it. This enables integrated support for sales activities and significantly improves the efficiency and quality of customer service.

[1078] 1. "Automatic generation of new customer lists"

[1079] Automated generation of new customer lists is the process of automatically creating lists of new customers based on criteria such as industry, region, related keywords, and sales volume.

[1080] 2. "Creating Auto-Reply and Follow-Up Emails"

[1081] Auto-reply and follow-up email creation is the process of automatically generating and sending appropriate replies and follow-up emails in response to customer inquiries.

[1082] 3. "Automatic quote generation"

[1083] Auto-generating quotes is the process of automatically calculating and generating quotes based on specified criteria using a price list for a product or service.

[1084] 4. “Customer behavior analysis”

[1085] Customer behavior analysis is a method for formulating marketing strategies by collecting and analyzing behavioral data such as customer purchase history and access history.

[1086] 5. "Competitive Research"

[1087] Competitive research is the process of collecting information about competitors from external databases and the Internet and conducting a comparative analysis of their products and services.

[1088] 6. "Creating anticipated questions and answers"

[1089] Creating anticipated questions and answers is a procedure for preparing questions that customers may have and their answers in advance.

[1090] 7. "Proposing the quickest approach to closing"

[1091] Proposing the shortest approach to closing is a method of calculating and proposing the shortest steps required to successfully close a business negotiation based on the agenda and related information entered.

[1092] 8. "Natural language processing technology"

[1093] Natural language processing technology is a technology that enables computers to understand, interpret, and generate human language.

[1094] 9. "FAQ Database"

[1095] An FAQ database is a database that compiles frequently asked questions and their answers, and is used to respond to inquiries.

[1096] 10. Query Conditions

[1097] A query condition is a search condition for retrieving information from a database.

[1098] 11. "External Database"

[1099] An external database is a database that is an accessible source of information that exists outside the enterprise.

[1100] 12. "Internal Database"

[1101] An internal database is a collection of information managed within a company, and is a database used for data management and analysis within the company.

[1102] 13. “PDF format”

[1103] PDF is an abbreviation for Portable Document Format, and is a file format for saving documents as electronic files while preserving their layout.

[1104] 14. "Electronic Transmissions"

[1105] Electronic transmission is the process of sending electronic files over the Internet to other devices.

[1106] This invention is a system for streamlining and optimizing sales activities for security services. This system includes various functions such as automatically generating new customer lists, creating automatic replies and follow-up emails, automatically generating quotes, analyzing customer behavior, researching competitors, creating anticipated questions and answers, and proposing the shortest approach to closing a deal.

[1107] Automatic generation of new customer lists

[1108] The server receives user inputs such as industry, region, related keywords, and sales volume, and issues queries to external and internal databases to retrieve company data. The retrieved data is then filtered and a new customer list is automatically generated. The list is updated periodically, and the generated information is documented in PDF format and sent electronically.

[1109] Create auto-reply and follow-up emails

[1110] When the server receives an inquiry email from a customer, it analyzes the content using natural language processing technology and searches for the most appropriate answer from the FAQ database. Based on the selected answer, it selects an email template, automatically creates a reply email, and sends it electronically.

[1111] Auto-generate quotes

[1112] When the user inputs the product or service conditions (type, quantity, duration, etc.), the terminal retrieves the corresponding price information from the price database. The server calculates the estimate based on this information and creates a quote in PDF format.

[1113] customer behavior analysis

[1114] The server collects customer purchase and access histories and analyzes them to identify trends and patterns, generating useful insights and suggesting specific marketing strategies.

[1115] Competitive Research

[1116] The server collects information on competitors' products from external databases and the Internet, performs comparative analysis with the company's own products, extracts points of differentiation, and develops sales strategies based on these.

[1117] Creating anticipated questions and answers

[1118] The server predicts questions customers will have based on past sales negotiation history and FAQ data, and creates a list of answers. The list is provided to the user via their device to help them prepare for sales negotiations.

[1119] Proposal for the shortest approach to closing

[1120] The server analyzes the agenda and related information entered by the user, summarizes the points of discussion necessary to reach a conclusion, calculates the time required for each discussion, and proposes the optimal approach to closing the meeting, which is then provided to the user via their device.

[1121] Hardware and software used

[1122] Hardware: Smartphone (iOS / Android)

[1123] Software: Python, Pandas, Scikit-Learn, SMTP, Natural Language Processing library

[1124] Specific examples

[1125] For example, if a user enters "I would like to propose security services to IT companies in Tokyo," the server will filter the relevant companies from a database called "potential_clients.csv" and automatically create a new customer list. Also, if a customer inquires about "service fees," the server will automatically find the appropriate answer from the FAQ file and immediately create and send a reply email.

[1126] Prompt Sentence Examples

[1127] Use the "Security Sales Support App" to automatically generate a list of IT companies in Tokyo and respond immediately to customer inquiries about pricing.

[1128] In this way, the present invention can realize comprehensive support for sales activities, and can significantly improve the efficiency and quality of customer service.

[1129] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1130] Step 1: Enter customer terms and conditions

[1131] The user inputs conditions such as industry, region, related keywords, and sales volume into the terminal. This becomes the input data for generating a new customer list.

[1132] Step 2: Generate a new customer list

[1133] The server issues queries to external and internal databases based on the conditions sent by the user, filters the acquired company data, and automatically generates a new customer list. The generated list is documented in PDF format and sent to the terminal.

[1134] Step 3: Receiving an inquiry

[1135] An inquiry email from a customer is sent to the server, and this email becomes the input data for the automatic reply.

[1136] Step 4: Natural Language Processing Analysis

[1137] The server analyzes the content of the inquiry email using natural language processing techniques (e.g., TfidfVectorizer and cosine similarity), and searches the FAQ database for the best answer based on the analysis results.

[1138] Step 5: Create an autoresponder

[1139] The server selects an email template based on the selected answer and automatically creates a reply email, which is then electronically sent back to the customer.

[1140] Step 6: Enter your quotation criteria

[1141] The user inputs conditions such as the type of product or service, quantity, and period into the terminal. This becomes the input data for automatically generating a quote.

[1142] Step 7: Auto-generate quotes

[1143] The server retrieves the relevant price information from the price database based on the conditions entered by the user, calculates an estimate based on the retrieved price information, and creates an estimate in PDF format. The estimate is then sent to the terminal.

[1144] Step 8: Collect customer data

[1145] The server continuously collects customer purchase and access histories, which serve as input data for customer behavior analysis.

[1146] Step 9: Analyze customer behavior

[1147] The server analyzes the collected customer data to identify trends and patterns, and the results are used to propose specific marketing strategies.

[1148] Step 10: Gather Competitive Intelligence

[1149] The server collects competitor product information from external databases and the Internet, and this information becomes input data for competitive research.

[1150] Step 11: Competitive analysis

[1151] The server compares and analyzes the collected information on competitors and the company's own products to extract points of differentiation, and then develops a sales strategy based on this.

[1152] Step 12: Prepare possible questions and answers

[1153] The server predicts questions customers will have based on past business negotiation history and FAQ data, and creates a list of answers. The list is then sent to the terminal and provided to the user.

[1154] Step 13: Closing Calculations

[1155] The user inputs the agenda and related information of the business negotiation into the terminal. The server analyzes the input data, summarizes the points necessary to reach a conclusion, calculates the required time, and proposes the shortest closing approach and sends it to the terminal.

[1156] 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.

[1157] MODE FOR CARRYING OUT THE INVENTION

[1158] This invention provides a system with functions to automatically generate new customer lists based on criteria such as industry, region, related keywords, and sales volume, as well as to automatically create appropriate replies and follow-up emails to inquiries. This system also includes a customer behavior analysis function that automatically generates quotes from product and service price lists and creates marketing strategies based on purchase and access history. It also has functions to analyze points of differentiation through competitive research, create anticipated questions and answers before sales negotiations, calculate the required time based on the input of the agenda and related information, and propose the shortest approach to closing. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, it is possible to dynamically adjust response content and sales strategies.

[1159] Program processing details

[1160] Automatic generation of new customer lists

[1161] The server accepts user input of criteria such as industry, region, related keywords, and sales volume, and issues queries to external and internal databases to retrieve appropriate company data. The retrieved data is then filtered and a new customer list is automatically generated. The generated list is periodically updated and provided to the user via their device.

[1162] Examples:

[1163] The user enters the conditions "IT company," "Tokyo," and "cloud service," and the server creates a new customer list based on this.

[1164] Auto-reply and follow-up email creation function

[1165] When the server receives an inquiry email from a customer, it analyzes the content using natural language processing technology and searches for the most appropriate answer from the FAQ database. Based on the selected answer, it selects an email template and automatically creates a reply email. The reply email is then automatically sent to the customer.

[1166] Examples:

[1167] When a customer inquires about the specifications of a new product, the server creates and sends a reply email containing the appropriate specification information.

[1168] Automatic quote generation function

[1169] When the user inputs the product or service conditions (type, quantity, duration, etc.), the terminal retrieves the corresponding price information from the price database. The server calculates the estimate based on this information and creates a quote in PDF format. The quote is then provided to the user via the terminal.

[1170] Examples:

[1171] When the user selects an annual cloud service contract and a support package, the device automatically generates a quote.

[1172] Customer behavior analysis function

[1173] The server collects customer purchase and access histories and performs analysis based on this data. It identifies trends and patterns and generates useful insights. Based on this, it creates specific marketing proposals.

[1174] Examples:

[1175] The server analyzes the product categories that a particular customer frequently purchases and proposes new product promotion strategies.

[1176] Competitive research feature

[1177] The server collects information on competitors' products from external databases and the Internet, performs comparative analysis with the company's own products, extracts points of differentiation, and develops sales strategies based on these.

[1178] Examples:

[1179] Through comparative analysis with competing products, Server identifies that the advantage of its products is their "extensive support system," and reflects this information in its sales materials.

[1180] Function to create hypothetical questions and answers

[1181] The server predicts questions customers will have based on past sales negotiation history and FAQ data, and creates a list of answers. This is provided to the user via their device to help them prepare for sales negotiations.

[1182] Examples:

[1183] The server prepares questions and answers regarding "the cost of introducing a new product" in advance and provides them to the user.

[1184] Proposal function for the shortest approach to closing

[1185] The server analyzes the agenda and related information entered by the user, summarizes the points of discussion necessary to reach a conclusion, calculates the time required for each discussion, and proposes the optimal approach to closing the meeting, which is then provided to the user via their device.

[1186] Examples:

[1187] If a user wants to discuss "how to simplify the introduction of a new product," the server will calculate the required time and propose the optimal approach, and provide it to the user.

[1188] Combining Emotion Engines

[1189] The server incorporates an emotion engine that recognizes the user's emotional state based on user input and voice analysis. The emotion engine analyzes the user's or customer's emotional state in real time and appropriately adjusts the content and timing of responses based on that data.

[1190] Examples:

[1191] The emotion engine analyzes the emotional tone (e.g., dissatisfaction, interest) of customer inquiry emails, and the server automatically generates the optimal response based on that. It also analyzes the stress felt by users and the level of interest of customers in real time during sales, and dynamically changes sales strategies based on that data.

[1192] The above are the details of the specific processing steps and operations for each function of the invention that combines the emotion engine. This system makes it possible to improve the efficiency of sales activities, grasp customer needs, make optimal proposals, and respond quickly. Furthermore, the introduction of the emotion engine enables more personalized customer service.

[1193] The processing flow will be explained below.

[1194] Automatic generation of new customer lists

[1195] Step 1:

[1196] The user inputs conditions such as industry, region, related keywords, and sales volume into the terminal.

[1197] Step 2:

[1198] The terminal transmits the input condition data to the server.

[1199] Step 3:

[1200] The server issues queries to external and internal databases based on the received condition data to obtain matching company data.

[1201] Step 4:

[1202] The server filters the acquired company data and removes duplicates and irrelevant data.

[1203] Step 5:

[1204] The server formats the filtered data into a new customer list format and generates the new customer list.

[1205] Step 6:

[1206] The server schedules periodic updates of the generated new customer list.

[1207] Step 7:

[1208] The terminal displays the new customer list to the user and provides it in a downloadable format (CSV, Excel, etc.).

[1209] Auto-reply and follow-up email creation function

[1210] Step 1:

[1211] The server receives an inquiry email from the customer.

[1212] Step 2:

[1213] The server analyzes the content of the received inquiry email using natural language processing technology.

[1214] Step 3:

[1215] The server searches the FAQ database for the best answer based on the analysis results.

[1216] Step 4:

[1217] The server selects an appropriate email template based on the best answer.

[1218] Step 5:

[1219] The server inserts the response content into the email template and creates a reply email.

[1220] Step 6:

[1221] The server automatically sends the created reply mail to the customer who made the inquiry.

[1222] Automatic quote generation function

[1223] Step 1:

[1224] The user inputs the product or service conditions (type, quantity, period, etc.) into the terminal.

[1225] Step 2:

[1226] The terminal transmits the input condition data to the server.

[1227] Step 3:

[1228] The server queries the price database based on the condition data and obtains the corresponding price information.

[1229] Step 4:

[1230] The server calculates an estimate based on the acquired price information.

[1231] Step 5:

[1232] The server formats the calculation results into a PDF estimate.

[1233] Step 6:

[1234] The terminal displays the generated quote to the user and provides it in a downloadable format.

[1235] Customer behavior analysis function

[1236] Step 1:

[1237] The server automatically collects customer purchase history and access history.

[1238] Step 2:

[1239] The server analyzes the collected data using an analysis tool.

[1240] Step 3:

[1241] The server identifies trends and patterns based on the analysis results.

[1242] Step 4:

[1243] The server generates useful insights (such as recommended products and marketing strategies).

[1244] Step 5:

[1245] The server creates specific marketing proposals based on the generated insights.

[1246] Step 6:

[1247] The terminal displays the proposal to the user and provides related materials.

[1248] Competitive research feature

[1249] Step 1:

[1250] The server collects competitor product information from external databases and the web.

[1251] Step 2:

[1252] The server organizes the collected information and compiles it into a format that makes it easy to compare with the company's own products and services.

[1253] Step 3:

[1254] The server compares and analyzes the features, prices, advantages, etc. of its own products with those of its competitors.

[1255] Step 4:

[1256] The server extracts points of differentiation from the results of the comparative analysis.

[1257] Step 5:

[1258] The terminal provides users with a point of differentiation that can be utilized in sales activities.

[1259] Function to create hypothetical questions and answers

[1260] Step 1:

[1261] The server collects past business negotiation history and an FAQ database.

[1262] Step 2:

[1263] The server generates questions and appropriate answers based on the collected information.

[1264] Step 3:

[1265] The server formats the generated questions and answers into a list.

[1266] Step 4:

[1267] The terminal displays a list of expected questions and answers to the user to assist in preparation before the business negotiation.

[1268] Proposal function for the shortest approach to closing

[1269] Step 1:

[1270] The user inputs the agenda and related information into the terminal.

[1271] Step 2:

[1272] The terminal transmits the input information to the server.

[1273] Step 3:

[1274] The server analyzes the agenda and related information and summarizes the points needed to reach a conclusion.

[1275] Step 4:

[1276] The server calculates the time required to discuss each topic.

[1277] Step 5:

[1278] The server will propose the shortest approach to closing based on the required time and points of discussion.

[1279] Step 6:

[1280] The terminal displays the proposal contents to the user and optimizes the progress of the business negotiations.

[1281] Combining Emotion Engines

[1282] Step 1:

[1283] The server sends user input and voice data to the emotion engine.

[1284] Step 2:

[1285] The emotion engine analyzes input data and recognizes the emotional state of the user or customer.

[1286] Step 3:

[1287] The server adjusts the content and timing of the response based on the emotional state data obtained from the emotion engine.

[1288] Step 4:

[1289] The terminal provides the user with an optimized response based on the emotional state.

[1290] The above are the specific processing steps for each function of the invention combined with the emotion engine.

[1291] Example 2

[1292] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1293] Traditionally, sales activities required a wide range of tasks, such as creating a list of new customers, responding to inquiries, generating quotes, analyzing customer behavior, researching competitors, preparing for sales negotiations, and making proposals up to closing, each of which required a great deal of time and effort.In addition, it was difficult to grasp the emotional state of customers and users in real time and respond accordingly, which limited the improvement of customer satisfaction.

[1294] The identification processing by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes: means for automatically generating a new customer list based on conditions such as industry, region, related keywords, and sales volume; means for automatically creating appropriate reply and follow-up emails in response to customer inquiries; means for automatically generating quotations from product and service price lists; means for analyzing customer behavior to create marketing strategies based on purchase history and access history; means for conducting competitive research to analyze the differentiation points of the company's products and services; means for creating anticipated questions and answers before directly negotiating with customers; means for summarizing the points of discussion necessary to reach a conclusion based on input of an agenda and related information, calculating the required time, and proposing the shortest approach to closing; and means for using an emotion engine to recognize the user's emotional state based on user input and voice analysis and adjust the content and timing of responses. This not only improves the efficiency of sales activities but also enables rapid understanding of customer needs and optimal proposals. Furthermore, the introduction of the emotion engine enables more personalized customer service.

[1295] "Means for automatically generating new customer lists" is a function that filters appropriate company data based on conditions such as industry, region, related keywords, and sales volume, and automatically creates new customer lists.

[1296] "Means for automatically creating appropriate reply and follow-up emails" refers to a function that uses natural language processing technology to analyze the content of customer inquiries, search for appropriate answers, and automatically generate and send reply and follow-up emails.

[1297] The "means for automatically generating a quote" is a function that, when you input the conditions of a product or service, retrieves price information from a price database, calculates a quote based on this, and automatically generates a quote.

[1298] "Customer behavior analysis tools" are functions that collect customer purchase history and access history, analyze this data, identify trends and patterns, and generate useful insights.

[1299] "Competitive research tools" is a function that collects information on competitors' products from external databases and the Internet, conducts comparative analysis with your own products, extracts points of differentiation, and develops sales strategies.

[1300] "A means of creating anticipated questions and answers" is a function that predicts questions from customers based on past sales negotiation history and FAQ data, and creates a list of answers.

[1301] "A means of inputting the agenda and related information to summarize the points needed to reach a conclusion, calculate the required time, and propose the shortest approach to closing" is a function that analyzes the agenda and related information input by the user, organizes the necessary points, calculates the required time for each discussion, and proposes the optimal approach to closing.

[1302] "Means using an emotion engine" refers to a function that recognizes the user's emotional state based on input and voice analysis, and adjusts the content and timing of responses based on that data.

[1303] MODE FOR CARRYING OUT THE INVENTION

[1304] This invention provides a system with functions to automatically generate new customer lists based on criteria such as industry, region, related keywords, and sales volume, as well as to automatically create appropriate replies and follow-up emails in response to customer inquiries. This system also includes a customer behavior analysis function that automatically generates quotes from product and service price lists and creates marketing strategies based on purchase and access history. It also analyzes points of differentiation through competitive research, creates anticipated questions and answers before sales negotiations, calculates the required time based on the input of the agenda and related information, and proposes the shortest approach to closing. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, it is possible to dynamically adjust response content and sales strategies.

[1305] Automatic generation of new customer lists

[1306] The server accepts user input criteria, such as industry, region, related keywords, and sales volume, often via a web form. Based on these criteria, the server queries external databases (such as a company information database) or internal databases to retrieve relevant company data. It then filters the retrieved data to create a new customer list. The new customer list is updated periodically to keep it up to date.

[1307] Examples:

[1308] When a user enters the conditions "IT company," "Tokyo," and "cloud services," the server creates a new customer list based on this.

[1309] Auto-reply and follow-up email creation function

[1310] When the server receives an inquiry email from a customer, it analyzes the content using natural language processing technology (e.g., Google NLP API).The server then searches for the most appropriate answer from the FAQ database based on the analysis results, and generates a reply email using an email template based on that answer.The generated email is then automatically sent to the customer.

[1311] Examples:

[1312] When a customer inquires about the specifications of a new product, the server analyzes the content, creates a reply email containing the appropriate specification information from the FAQ database, and sends it.

[1313] Automatic quote generation function

[1314] When the user inputs the product or service conditions (type, quantity, duration, etc.), the terminal retrieves the corresponding price information from the price database. The server calculates an estimate based on the retrieved price information and generates a quote in PDF format. The quote is then provided to the user via the terminal.

[1315] Examples:

[1316] When the user selects an "annual cloud service contract" and a "support package" and enters the conditions, the server retrieves information from a price database, generates a quote in PDF format, and provides it to the user via the terminal.

[1317] Customer behavior analysis function

[1318] The server collects and analyzes customer purchase and access histories. The server then analyzes the data using machine learning algorithms (e.g., clustering and regression analysis), identifies trends and patterns, and generates useful insights. Based on these insights, the server proposes specific marketing strategies and provides them to users via their devices.

[1319] Examples:

[1320] The server analyzes the product categories frequently purchased by a particular customer, proposes a promotion strategy for a new product, and provides it to the user through the terminal.

[1321] Competitive research feature

[1322] The server collects information on competitors' products from external databases and the Internet, compares them with its own products, extracts points of differentiation, and uses this information to develop sales strategies.

[1323] Examples:

[1324] Through comparative analysis with competing products, Server identifies that the advantage of its products is their "comprehensive support system," and reflects this in its sales materials.

[1325] Function to create hypothetical questions and answers

[1326] The server predicts questions customers will have based on past sales negotiation history and FAQ data, and creates a list of answers. The list is provided to the user via their device to help them prepare for sales negotiations.

[1327] Examples:

[1328] The server prepares questions and answers regarding "the cost of introducing a new product" in advance and provides them to the user via the terminal.

[1329] Proposal function for the shortest approach to closing

[1330] The server analyzes the agenda and related information entered by the user, organizes the necessary points of discussion, calculates the required time for each discussion, and proposes the optimal approach to closing the meeting, which is then provided to the user via their device.

[1331] Examples:

[1332] If a user wants to discuss "how to simplify the introduction of a new product," the server will calculate the required time and propose the optimal approach, and provide it to the user through the terminal.

[1333] Combining Emotion Engines

[1334] The server uses an emotion engine (e.g., Microsoft Azure Cognitive Services) that recognizes the user's emotional state based on user input and voice analysis. The emotion engine analyzes the user's or customer's emotional state in real time and appropriately adjusts the content and timing of responses based on that data.

[1335] Examples:

[1336] The emotion engine analyzes the emotional tone (e.g., dissatisfaction, interest) of customer inquiry emails, and the server automatically generates the optimal response based on that and sends it via email. It also analyzes the stress felt by users and the level of interest of customers during sales in real time, and dynamically changes sales strategies based on that data.

[1337] The system will streamline sales activities through each function, enabling quick understanding of customer needs and optimal proposals. The introduction of an emotion engine will also enable more personalized customer service.

[1338] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1339] Automatic generation of new customer lists

[1340] Processing Steps

[1341] Step 1: Accept conditions

[1342] The server accepts user inputs from the terminal such as industry, region, related keywords, sales volume, etc. The input data is used to issue subsequent queries.

[1343] Input: User-entered industry, region, related keywords, and sales volume

[1344] Output: Condition data for issuing a query

[1345] Step 2: Query the database

[1346] The server issues queries to external and internal databases based on the input condition data, for example, by generating SQL statements and sending them to the databases.

[1347] Input: Condition data

[1348] Output: A list of companies retrieved from the database

[1349] Step 3: Filtering the data

[1350] The server filters the acquired company data based on conditions, for example, extracting only data from IT companies in the Tokyo region.

[1351] Input: A list of companies retrieved from a database

[1352] Output: Filtered company data

[1353] Step 4: Generate a new customer list

[1354] The server creates a list of new customers based on the filtered company data, often stored in JSON or CSV format.

[1355] Input: Filtered company data

[1356] Output: New customer list

[1357] Step 5: Providing a list of new customers

[1358] The server provides the generated new customer list to the user's terminal, including via a web page or email.

[1359] Input: New Customer List

[1360] Output: A list of new customers displayed on the user's device.

[1361] ---

[1362] Auto-reply and follow-up email creation function

[1363] Processing Steps

[1364] Step 1: Receiving an inquiry email

[1365] The server receives inquiry emails from customers, which is often received via an SMTP server.

[1366] Input: Customer inquiry email

[1367] Output: Contents of inquiry email

[1368] Step 2: Analyzing the email content

[1369] The server analyzes the content of the received inquiry email using natural language processing technology to extract the email's topic and emotional tone.

[1370] Input: Contents of inquiry email

[1371] Output: Parsed email content

[1372] Step 3: Finding the best answer

[1373] The server searches the FAQ database for the best answer based on the analysis results, using a similarity search algorithm to select the most relevant answer.

[1374] Input: Parsed email content

[1375] Output: Best answer

[1376] Step 4: Generate a reply email

[1377] The server generates a reply email using an email template based on the selected answer, with variables embedded in the template that are then replaced with actual data.

[1378] Input: Best Answer

[1379] Output: The generated reply email

[1380] Step 5: Send a reply email

[1381] The server generates a reply email and sends it to the customer, via an SMTP server.

[1382] Input: Generated reply email

[1383] Output: Reply email to customer

[1384] ---

[1385] Automatic quote generation function

[1386] Processing Steps

[1387] Step 1: Enter the condition

[1388] The terminal accepts the product or service conditions (type, quantity, duration, etc.) entered by the user, often via a web form.

[1389] Input: User-entered product or service terms

[1390] Output: Condition data

[1391] Step 2: Get pricing information

[1392] The server retrieves the relevant price information from the price database based on the entered condition data, and uses an SQL query to retrieve the price information.

[1393] Input: Condition data

[1394] Output: Price information

[1395] Step 3: Calculate the estimate

[1396] The server calculates an estimate based on the acquired price information, taking into account conditions such as quantity and period.

[1397] Input: Price Information

[1398] Output: Calculated estimate data

[1399] Step 4: Generate a quote

[1400] The server generates a PDF quotation based on the calculation results using a PDF generation library.

[1401] Input: Estimate data

[1402] Output: PDF quotation

[1403] Step 5: Provide a quote

[1404] The server provides the generated quote to the user via the terminal, which may include sending it by email or providing a download link.

[1405] Input: PDF quotation

[1406] Output: Quote provided to user

[1407] ---

[1408] Customer behavior analysis function

[1409] Processing Steps

[1410] Step 1: Data collection

[1411] The server collects customer purchase and access histories from web logs and transaction databases.

[1412] Input: purchase history, access history

[1413] Output: Collected data

[1414] Step 2: Data analysis

[1415] The server analyzes the collected data using machine learning algorithms (e.g., clustering, regression analysis).

[1416] Input: Collected data

[1417] Output: Analysis results

[1418] Step 3: Generate insights

[1419] The server identifies trends and patterns from the analysis results and generates useful insights.

[1420] Input: Analysis results

[1421] Output:Insight

[1422] Step 4: Propose marketing measures

[1423] The server creates specific marketing proposals based on the generated insights and provides them to the user via the terminal.

[1424] Input: Insight

[1425] Output: Marketing Strategy

[1426] ---

[1427] Combining Emotion Engines

[1428] Processing Steps

[1429] Step 1: Parse the input

[1430] The server accepts user input (text, voice) and analyzes it using natural language processing technology.

[1431] Input: What the user types

[1432] Output: Parsed input

[1433] Step 2: Recognizing your emotional state

[1434] The server uses an emotion engine to recognize the emotional state based on the analysis results, for example, identifying emotions such as excitement, anxiety, and calm.

[1435] Input: Parsed input

[1436] Output: Emotional state

[1437] Step 3: Tailor your response

[1438] The server adjusts the content and timing of responses based on the user's perceived emotional state: for example, if the user is frustrated, a more friendly response will be automatically chosen.

[1439] Input: Emotional state

[1440] Output: Adjusted response content

[1441] Step 4: User feedback

[1442] The server provides tailored responses to the user via the terminal, providing real-time feedback.

[1443] Input: Adjusted response content

[1444] Output: Feedback to the user

[1445] ---

[1446] The above are the specific processing steps for each function of this system. This will improve the efficiency of sales activities, quickly grasp customer needs, and make optimal proposals. The introduction of an emotion engine will also enable more personalized customer service.

[1447] (Application example 2)

[1448] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1449] In today's business environment, companies must efficiently perform a wide range of tasks, including acquiring new customers, responding quickly and appropriately to existing customers, creating product and service quotes, analyzing competitors, and preparing for sales negotiations. However, performing these tasks manually is extremely time-consuming and labor-intensive, resulting in inefficiency and low accuracy. Furthermore, security incident response requires real-time monitoring and appropriate action, and performing this manually carries high risks. To solve these issues, it is necessary to automate these tasks and utilize sentiment analysis to make appropriate decisions quickly.

[1450] 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.

[1451] In this invention, the server includes means for automatically generating a new customer list based on conditions such as industry, region, related keywords, and sales volume, means for automatically creating appropriate reply and follow-up emails in response to inquiries, means for automatically generating quotes from product and service price lists, means for analyzing customer behavior to create marketing strategies based on purchase history and access history, means for conducting competitive research to analyze the differentiating points of a company's products and services, means for creating anticipated questions and answers before directly negotiating with customers, means for summarizing the points of discussion necessary to reach a conclusion based on input of an agenda and related information, calculating the required time, and proposing the shortest approach to closing, and means for analyzing the details of a security incident and determining appropriate actions based on the emotional state.This enables more efficient sales activities, understanding customer needs, optimal proposals, rapid responses, and appropriate security responses based on emotional analysis.

[1452] "Automatic generation of new customer lists" is a system that lists potential new customers based on criteria such as industry, region, related keywords, and sales volume.

[1453] "Creating automatic replies and follow-up emails" is a system that uses natural language processing technology to automatically create appropriate replies to customer inquiries and send them via email.

[1454] "Automatic quotation generation" is a system that automatically creates a quotation based on specified conditions from a price list for a product or service.

[1455] "Customer behavior analysis" is a system that analyzes customers' purchase history and access history and proposes effective marketing measures.

[1456] "Competitive research" is a system that uses collected competitive information to compare your own products and services with those of your competitors and extract points of differentiation.

[1457] "Creating anticipated questions and answers" is a system that prepares anticipated questions and answers before directly negotiating with a customer.

[1458] "Proposing the shortest approach to closing" is a system that, when you input the agenda and related information, summarizes the points needed to reach a conclusion, calculates the required time, and proposes the optimal approach to successfully close a business negotiation.

[1459] "Security Incident Analysis" is a system that analyzes the details of a security incident and determines appropriate actions based on emotional state.

[1460] "Emotion analysis" is a technology that uses natural language processing technology to analyze the emotional state of text or speech and determine an appropriate response based on that.

[1461] MODE FOR CARRYING OUT THE INVENTION

[1462] This invention provides a system with the functions of automatically generating new customer lists based on conditions such as industry, region, related keywords, and sales volume, and automatically creating appropriate replies and follow-up emails to inquiries. Furthermore, the system also includes functions for automatically generating quotes from product and service price lists, analyzing customer behavior to create marketing strategies based on purchase and access histories, analyzing points of differentiation through competitive research, creating anticipated questions and answers before business negotiations, calculating the required time by inputting agenda items and related information, and proposing the shortest approach to closing. It also combines emotional analysis with security incident analysis to dynamically determine appropriate actions.

[1463] System configuration

[1464] The system consists of the following main components:

[1465] 1. Server:

[1466] Hardware: A powerful processor (e.g., Intel Xeon), lots of memory (e.g., 32GB RAM), and fast storage (e.g., SSD).

[1467] Software: Database management systems (e.g., MySQL), natural language processing engines (e.g., NLTK), sentiment analysis engines (e.g., Sentiment Analysis Toolkit), report generators (e.g., ReportLab).

[1468] 2. Terminal:

[1469] Hardware: Smartphone.

[1470] Software: Operating systems (e.g., Android, iOS), mobile applications.

[1471] System Operation

[1472] The server analyzes user input and sensor data in real time and performs the following data processing and calculations:

[1473] Auto-generate new customer lists:

[1474] The server issues queries to external and internal databases based on user-entered criteria such as industry, region, related keywords, and sales volume, and the retrieved data is filtered to automatically generate a new customer list.

[1475] Creating Auto-Reply & Follow-Up Emails:

[1476] The server uses natural language processing technology to analyze the inquiry and search for the appropriate answer in the FAQ database, then automatically creates and sends a reply email based on that answer.

[1477] Auto-generate quotes:

[1478] The server retrieves the relevant information from a price database based on the product or service conditions entered by the user, and automatically calculates a quote. The quote is generated in PDF format and provided via the terminal.

[1479] Customer behavior analysis:

[1480] The server collects customer purchase and access histories and analyzes the data, which is then used to create marketing strategies.

[1481] Competitive Research:

[1482] The server collects information on competitors from external databases and the Internet, and performs comparative analysis with the company's own products. Differentiating points are extracted and reflected in sales strategies.

[1483] Creating anticipated questions and answers:

[1484] The server creates a list of anticipated questions and their answers based on past business negotiation history and FAQ data, thereby supporting pre-negotiation preparation.

[1485] Suggested quickest approach to closing:

[1486] Based on the agenda and related information, the server summarizes the points of discussion and calculates the required time to propose the optimal closing approach.

[1487] Security incident analysis:

[1488] The server analyzes the details of the security incident and determines the appropriate action based on the emotional state, enabling appropriate responses in real time.

[1489] Specific examples

[1490] Suppose a user is in charge of security management for a company that holds art exhibitions. Security incidents often occur when a new exhibition opens. Using SmartGuard-S, the user can continuously monitor new incidents and view details in the application. If the incident is deemed urgent, the sentiment analysis engine will issue an "urgent alert" and the appropriate response method will be automatically displayed. The user can also automatically generate new customer lists and quotes based on specific conditions (e.g., exhibition location, type of exhibit, security requirements).

[1491] Prompt Sentence Examples

[1492] "How can I analyze the details of a recent security incident, classify its emotional state, and generate applicable actions and reports?"

[1493] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1494] Processing Steps

[1495] Step 1:

[1496] The user uses a terminal to input conditions such as industry, region, related keywords, sales volume, etc. This input data is sent to the server.

[1497] Step 2:

[1498] The server issues queries to external and internal databases based on the received criteria, thereby retrieving the relevant company data.

[1499] Step 3:

[1500] The server filters the acquired company data and automatically generates a new customer list, which is updated periodically.

[1501] Step 4:

[1502] When a user sends an inquiry email using a terminal, the server receives it and analyzes it using natural language processing technology.

[1503] Step 5:

[1504] The server searches the FAQ database for the best answer based on the analysis results, and automatically creates a reply email based on the selected answer.

[1505] Step 6:

[1506] The server sends the created reply mail to the user's terminal, and also automatically creates and sends a follow-up mail.

[1507] Step 7:

[1508] The user inputs product or service conditions (type, quantity, period, etc.) into the terminal. This input data is sent to the server.

[1509] Step 8:

[1510] The server retrieves the relevant price information from the price database, calculates the estimate based on that information, and creates a quote in PDF format based on the calculation results.

[1511] Step 9:

[1512] The server sends the estimate to the terminal and provides it to the user.

[1513] Step 10:

[1514] The server collects and analyzes customer purchase history and access history from a database and creates marketing strategies.

[1515] Step 11:

[1516] The server collects information on competitors from external databases and the Internet, performs comparative analysis with the company's own products, extracts points of differentiation, and reflects them in sales strategies.

[1517] Step 12:

[1518] The server creates a list of predicted and anticipated questions and their answers based on past business negotiation history and FAQ data.

[1519] Step 13:

[1520] Based on the agenda and related information entered by the user, the server summarizes the points needed to reach a conclusion, calculates the required time, and proposes a closing approach.

[1521] Step 14:

[1522] The server analyzes the details of the security incident and classifies the emotional state of the incident using an emotional analysis engine.

[1523] Step 15:

[1524] Based on the classification results, the server determines the appropriate action to take, such as high alert, monitoring, low alert, etc. The generated report is provided to the user in a format that can be viewed in real time.

[1525] Specific examples of processing

[1526] Step 1:

[1527] The user uses a terminal to enter conditions such as "IT company," "Tokyo," "cloud service," and "sales size: small and medium-sized enterprises," and sends the results to the server.

[1528] Input: "IT company", "Tokyo", "Cloud service", "Sales size: Small and medium-sized enterprises"

[1529] Output: The condition is sent to the server.

[1530] Step 2:

[1531] The server retrieves relevant company data from external and internal databases based on the received conditions.

[1532] Input: Received condition data

[1533] Output: Acquisition of relevant company data

[1534] Step 3:

[1535] The server filters the acquired company data and automatically generates a new customer list, which is updated periodically.

[1536] Input: Acquired company data

[1537] Output: Generate and update new customer list

[1538] Step 4:

[1539] The user sends an inquiry email from the terminal, which is received by the server and analyzed using natural language processing technology.

[1540] Input: Inquiry email

[1541] Output: Analysis results

[1542] Step 5:

[1543] The server searches the FAQ database for the best answer and automatically creates a reply email.

[1544] Input: Analysis results

[1545] Output: Auto-generated reply email

[1546] Step 6:

[1547] The server sends the reply email to the user's terminal and also creates and sends a follow-up email.

[1548] Input: Draft of reply email

[1549] Output: Reply and follow-up emails sent

[1550] Step 7:

[1551] The user enters conditions such as "cloud service," "annual contract," and "5 licenses" on the device. The input data is sent to the server.

[1552] Input: Terms such as "Cloud service," "Annual contract," and "5 licenses"

[1553] Output: The condition is sent to the server

[1554] Step 8:

[1555] The server retrieves the relevant price information from the price database, automatically calculates an estimate based on that information, and creates an estimate in PDF format.

[1556] Input: Submitted condition data

[1557] Output: PDF quotation

[1558] Step 9:

[1559] The server sends the estimate in PDF format to the terminal and provides it to the user.

[1560] Input: PDF quotation

[1561] Output: Quote provided to user

[1562] Step 10:

[1563] The server collects customer purchase history and access history from a database, analyzes them, and creates marketing strategies.

[1564] Input: Customer purchase history and access history

[1565] Output: Marketing Strategy

[1566] Step 11:

[1567] The server collects information on competitors, performs comparative analysis with its own products, and extracts points of differentiation.

[1568] Input: Competitor Information

[1569] Output: Differentiation points and sales strategies

[1570] Step 12:

[1571] The server creates a list of anticipated questions and answers before the business meeting and provides it to the user.

[1572] Input: Sales history and FAQ data

[1573] Output: List of expected questions and answers

[1574] Step 13:

[1575] When the user inputs the agenda and related information, the server summarizes the necessary points, calculates the required time, and suggests a closing approach.

[1576] Input: Agenda and related information

[1577] Output: Shortest approach to closing

[1578] Step 14:

[1579] The server analyzes the details of the security incident and classifies the emotional state.

[1580] Input: Security incident details

[1581] Output: Emotional state classification result

[1582] Step 15:

[1583] The server determines the appropriate action based on the classification results and performs incident response. The generated report is provided to the user in real time.

[1584] Input: Emotional state classification results

[1585] Output: Appropriate actions and incident response report

[1586] 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.

[1587] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1588] 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.

[1589] [Third embodiment]

[1590] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1591] 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.

[1592] 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).

[1593] 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.

[1594] 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.

[1595] 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).

[1596] 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.

[1597] 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.

[1598] 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.

[1599] 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.

[1600] 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.

[1601] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[1602] MODE FOR CARRYING OUT THE INVENTION

[1603] This invention provides a system with functions to automatically generate new customer lists based on criteria such as industry, region, related keywords, and sales volume, as well as to automatically create appropriate replies and follow-up emails to inquiries. This system also includes a customer behavior analysis function that automatically generates quotes from product and service price lists and creates marketing strategies based on purchase and access history. Furthermore, the system also has functions to analyze points of differentiation through competitive research, create anticipated questions and answers before negotiations, calculate the required time by entering the agenda and related information, and propose the shortest approach to closing.

[1604] Program processing details

[1605] Automatic generation of new customer lists

[1606] The server accepts user input of criteria such as industry, region, related keywords, and sales volume, and issues queries to external and internal databases to retrieve appropriate company data. The retrieved data is then filtered and a new customer list is automatically generated. The generated list is periodically updated and provided to the user via their device.

[1607] Examples:

[1608] The user enters the conditions "IT company," "Tokyo," and "cloud service," and the server creates a new customer list based on this.

[1609] Auto-reply and follow-up email creation function

[1610] When the server receives an inquiry email from a customer, it analyzes the content using natural language processing technology and searches for the most appropriate answer from the FAQ database. Based on the selected answer, it selects an email template and automatically creates a reply email. The reply email is then automatically sent to the customer.

[1611] Examples:

[1612] When a customer inquires about the specifications of a new product, the server creates and sends a reply email containing the appropriate specification information.

[1613] Automatic quote generation function

[1614] When the user inputs the product or service conditions (type, quantity, duration, etc.), the terminal retrieves the corresponding price information from the price database. The server calculates the estimate based on this information and creates a quote in PDF format. The quote is then provided to the user via the terminal.

[1615] Examples:

[1616] When the user selects an annual cloud service contract and a support package, the device automatically generates a quote.

[1617] Customer behavior analysis function

[1618] The server collects customer purchase and access histories and performs analysis based on this data. It identifies trends and patterns and generates useful insights. Based on this, it creates specific marketing proposals.

[1619] Examples:

[1620] The server analyzes the product categories that a particular customer frequently purchases and proposes new product promotion strategies.

[1621] Competitive research feature

[1622] The server collects information on competitors' products from external databases and the Internet, performs comparative analysis with the company's own products, extracts points of differentiation, and develops sales strategies based on these.

[1623] Examples:

[1624] Through comparative analysis with competing products, Server identifies that the advantage of its products is their "extensive support system," and reflects this information in its sales materials.

[1625] Function to create hypothetical questions and answers

[1626] The server predicts questions customers will have based on past sales negotiation history and FAQ data, and creates a list of answers. This is provided to the user via their device to help them prepare for sales negotiations.

[1627] Examples:

[1628] The server prepares questions and answers regarding "the cost of introducing a new product" in advance and provides them to the user.

[1629] Proposal function for the shortest approach to closing

[1630] The server analyzes the agenda and related information entered by the user, summarizes the points of discussion necessary to reach a conclusion, calculates the time required for each discussion, and proposes the optimal approach to closing the meeting, which is then provided to the user via their device.

[1631] Examples:

[1632] If a user wants to discuss "how to simplify the introduction of a new product," the server will calculate the required time and propose the optimal approach, and provide it to the user.

[1633] The above is a specific example of an embodiment of the invention and details of the program processing. This system makes it possible to improve the efficiency of sales activities, grasp customer needs, make optimal proposals, and respond quickly.

[1634] The processing flow will be explained below.

[1635] Automatic generation of new customer lists

[1636] Step 1:

[1637] The user inputs conditions such as industry, region, related keywords, and sales volume into the terminal.

[1638] Step 2:

[1639] The terminal transmits the input conditions to the server.

[1640] Step 3:

[1641] The server accesses the external database and the internal database based on the received condition data to obtain the matching company data.

[1642] Step 4:

[1643] The server filters the acquired company data and removes duplicates and irrelevant data.

[1644] Step 5:

[1645] The server formats the filtered data into a new customer list.

[1646] Step 6:

[1647] The server schedules periodic updates of the new customer list.

[1648] Step 7:

[1649] The terminal displays the new customer list to the user and provides it in a downloadable format (CSV, Excel, etc.).

[1650] Auto-reply and follow-up email creation function

[1651] Step 1:

[1652] The server receives an inquiry email from the customer.

[1653] Step 2:

[1654] The server analyzes the content of the received inquiry email using natural language processing technology.

[1655] Step 3:

[1656] The server searches the FAQ database for the best answer based on the analysis results.

[1657] Step 4:

[1658] The server selects an appropriate email template based on the selected answer.

[1659] Step 5:

[1660] The server inserts the reply content into the template and automatically creates a reply email.

[1661] Step 6:

[1662] The server automatically sends the created reply mail to the customer who made the inquiry.

[1663] Automatic quote generation function

[1664] Step 1:

[1665] The user inputs the product or service conditions (type, quantity, period, etc.) into the terminal.

[1666] Step 2:

[1667] The terminal transmits the input conditions to the server.

[1668] Step 3:

[1669] The server queries the price database based on the condition data and obtains the corresponding price information.

[1670] Step 4:

[1671] The server calculates an estimate based on the acquired price information.

[1672] Step 5:

[1673] The server formats the calculation results into a PDF estimate.

[1674] Step 6:

[1675] The terminal displays the generated quote to the user and provides it in a downloadable format.

[1676] Customer behavior analysis function

[1677] Step 1:

[1678] The server automatically collects customer purchase history and access history.

[1679] Step 2:

[1680] The server analyzes the collected data using an analysis tool.

[1681] Step 3:

[1682] The server identifies trends and patterns based on the analysis results.

[1683] Step 4:

[1684] The server generates useful insights (such as recommended products and marketing strategies).

[1685] Step 5:

[1686] The server creates specific marketing proposals based on the generated insights.

[1687] Step 6:

[1688] The terminal displays the proposal to the user and provides related materials.

[1689] Competitive research feature

[1690] Step 1:

[1691] The server collects competitor product information from external databases and the web.

[1692] Step 2:

[1693] The server organizes the collected information and compiles it into a format that makes it easy to compare with the company's own products and services.

[1694] Step 3:

[1695] The server compares and analyzes the features, prices, advantages, etc. of its own products with those of its competitors.

[1696] Step 4:

[1697] The server extracts points of differentiation from the results of the comparative analysis.

[1698] Step 5:

[1699] The terminal provides users with a point of differentiation that can be utilized in sales activities.

[1700] Function to create hypothetical questions and answers

[1701] Step 1:

[1702] The server collects past business negotiation history and an FAQ database.

[1703] Step 2:

[1704] The server generates questions and appropriate answers based on the collected information.

[1705] Step 3:

[1706] The server formats the generated questions and answers into a list.

[1707] Step 4:

[1708] The terminal displays a list of expected questions and answers to the user to assist in preparation before the business negotiation.

[1709] Proposal function for the shortest approach to closing

[1710] Step 1:

[1711] The user inputs the agenda and related information into the terminal.

[1712] Step 2:

[1713] The terminal transmits the input information to the server.

[1714] Step 3:

[1715] The server analyzes the agenda and related information and summarizes the points needed to reach a conclusion.

[1716] Step 4:

[1717] The server calculates the time required to discuss each topic.

[1718] Step 5:

[1719] The server will propose the shortest approach to closing based on the required time and points of discussion.

[1720] Step 6:

[1721] The terminal displays the proposal contents to the user and optimizes the progress of the business negotiations.

[1722] The above are the specific processing steps for each function in the embodiment of the invention.

[1723] Example 1

[1724] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1725] Modern sales and marketing activities require the ability to quickly and accurately generate new customer lists and conduct effective follow-up. However, performing these tasks manually takes a significant amount of time and effort and is prone to errors. It is also difficult to efficiently perform a wide range of tasks, such as competitor research, creating quotes, and preparing for sales negotiations. Furthermore, analyzing customer behavior and developing optimal marketing strategies are also necessary. To solve these challenges, a system that automates and optimizes all processes is needed.

[1726] 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.

[1727] In this invention, the server includes: means for automatically generating a new customer list based on criteria such as industry, region, related keywords, and sales volume; means for receiving inquiry emails from customers, analyzing the content using natural language processing technology, and automatically creating and sending appropriate reply and follow-up emails; means for retrieving information from a price database based on product or service criteria (type, quantity, duration, etc.), automatically generating quotes, and creating quote documents in PDF format; means for analyzing customer purchase histories and access histories to create marketing strategies; means for conducting competitive research by collecting information on competing products from external databases and the Internet and comparing and analyzing them with the company's own products to identify points of differentiation; means for predicting customer questions based on past sales negotiation history and FAQ data and creating a list of anticipated questions and answers; and means for summarizing the points of discussion necessary to reach a conclusion, calculating the required time, and proposing the shortest approach to closing a deal when the topic and related information are input. This enables more efficient sales activities, early identification of customer needs, appropriate proposals, and rapid responses.

[1728] "Means for automatically generating new customer lists" is a function that automatically generates new customer lists by retrieving and filtering appropriate company data from external and internal databases based on conditions entered by the user, such as industry, region, related keywords, and sales volume.

[1729] "Means for automatically creating and sending appropriate reply / follow-up emails" refers to a function that receives inquiry emails from customers, analyzes the content using natural language processing technology, searches for the most appropriate answer from the FAQ database, and automatically creates and sends reply / follow-up emails using email templates.

[1730] "Means to automatically generate quotes and create quotes in PDF format" refers to a function that, when a user inputs the product or service conditions (type, quantity, period, etc.), retrieves the relevant price information from a price database, calculates a quote based on this, and creates a quote in PDF format.

[1731] "Customer behavior analysis tools" are functions that collect customer purchase history and access history, analyze this data to identify trends and patterns, generate useful insights, and propose specific marketing measures.

[1732] "Competitive research tools" is a function that collects information on competitors' products from external databases and the Internet, performs comparative analysis with your own products, extracts points of differentiation, and develops sales strategies.

[1733] "A means to create a list of anticipated questions and answers" is a function that predicts questions from customers based on past sales negotiation history and FAQ data, and compiles and creates a list of answers.

[1734] "A means of inputting the agenda and related information, summarizing the points needed to reach a conclusion, calculating the required time, and proposing the shortest approach to closing" is a function that, when a user inputs the agenda and related information, analyzes them, summarizes the points needed to reach a conclusion, calculates the required time for each discussion, and proposes the optimal closing approach.

[1735] MODE FOR CARRYING OUT THE INVENTION

[1736] This invention provides a system with functions to automatically generate new customer lists based on criteria such as industry, region, related keywords, and sales volume, as well as to automatically create appropriate replies and follow-up emails to inquiries. This system also includes a customer behavior analysis function that automatically generates quotes from product and service price lists and creates marketing strategies based on purchase and access history. Furthermore, the system also has functions to analyze points of differentiation through competitive research, create anticipated questions and answers before sales negotiations, calculate the required time by entering the agenda and related information, and propose the shortest approach to closing.

[1737] Overall structure

[1738] The system mainly consists of a server and a terminal. The server processes and analyzes data, while the terminal accepts input from users and displays the results. The server incorporates natural language processing technology and is connected to external and internal databases. The terminal provides a user interface and communicates with the server in response to user input.

[1739] Automatic generation of new customer lists

[1740] The server accepts user input of criteria such as industry, region, related keywords, and sales volume, and issues queries to external and internal databases to retrieve appropriate company data. The retrieved data is then filtered and a new customer list is automatically generated. The generated list is periodically updated and provided to the user via their device.

[1741] Examples:

[1742] The user enters the conditions "IT company," "Tokyo," and "cloud service" via the terminal, and the server creates a new customer list based on this.

[1743] Auto-reply and follow-up email creation function

[1744] When the server receives an inquiry email from a customer, it analyzes the content using natural language processing technology and searches for the most appropriate answer from the FAQ database. Based on the selected answer, it selects an email template and automatically creates a reply email. The reply email is then automatically sent to the customer.

[1745] Examples:

[1746] When a customer inquires about the specifications of a new product, the server creates and sends a reply email containing the appropriate specification information.

[1747] Automatic quote generation function

[1748] When the user inputs the product or service conditions (type, quantity, duration, etc.), the terminal retrieves the corresponding price information from the price database. The server calculates the estimate based on this information and creates a quote in PDF format. The quote is then provided to the user via the terminal.

[1749] Examples:

[1750] When the user selects an annual cloud service contract and a support package, the device automatically generates a quote.

[1751] Customer behavior analysis function

[1752] The server collects customer purchase and access histories and performs analysis based on this data. It identifies trends and patterns and generates useful insights. Based on this, it creates specific marketing proposals.

[1753] Examples:

[1754] The server analyzes the product categories that a particular customer frequently purchases and proposes new product promotion strategies.

[1755] Competitive research feature

[1756] The server collects information on competitors' products from external databases and the Internet, performs comparative analysis with the company's own products, extracts points of differentiation, and develops sales strategies based on these.

[1757] Examples:

[1758] Through comparative analysis with competing products, Server identifies that the advantage of its products is their "extensive support system," and reflects this information in its sales materials.

[1759] Function to create hypothetical questions and answers

[1760] The server predicts questions customers will have based on past sales negotiation history and FAQ data, and creates a list of answers. This is provided to the user via their device to help them prepare for sales negotiations.

[1761] Examples:

[1762] The server prepares questions and answers regarding "the cost of introducing a new product" in advance and provides them to the user.

[1763] Proposal function for the shortest approach to closing

[1764] The server analyzes the agenda and related information entered by the user, summarizes the points of discussion necessary to reach a conclusion, calculates the time required for each discussion, and proposes the optimal approach to closing the meeting, which is then provided to the user via their device.

[1765] Examples:

[1766] If a user wants to discuss "how to simplify the introduction of a new product," the server will calculate the required time and propose the optimal approach, and provide it to the user.

[1767] This system will enable more efficient sales activities, understanding of customer needs, optimal proposals, and quick responses.

[1768] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1769] Automatic generation of new customer lists

[1770] Step 1: Enter the condition

[1771] The user inputs conditions such as industry, region, related keywords, sales volume, etc. via a terminal. This input is sent to the server in the form of a query.

[1772] Step 2: Query the database

[1773] The server issues queries to external and internal databases based on the criteria received from the user, and the databases return company data that matches the specified criteria.

[1774] Step 3: Filtering the data

[1775] The server filters the acquired company data, specifically by organizing the data based on industry and region, and prioritizing data that matches related keywords and sales volume.

[1776] Step 4: Generate a customer list

[1777] The server generates a new customer list based on the filtered data, and outputs the list in the specified format (e.g., CSV, Excel, etc.).

[1778] Step 5: Provide a list

[1779] The server provides the generated new customer list to the user through the terminal, and the user downloads the list as needed.

[1780] ---

[1781] Auto-reply and follow-up email creation function

[1782] Step 1: Receiving an inquiry email

[1783] The server receives email inquiries from customers, which are then passed to the natural language processing module.

[1784] Step 2: Content Analysis

[1785] The server uses natural language processing technology to analyze the content of the inquiry email, extracting the main questions and keywords.

[1786] Step 3: Search for answers in the FAQ database

[1787] The server searches the FAQ database for the best answer based on the analysis results, and the search results also include the reliability and relevance of the answer.

[1788] Step 4: Select a template and create an email

[1789] The server then selects the appropriate email template based on the selected answer and automatically creates a reply email, adding personalized information for the customer.

[1790] Step 5: Sending an email

[1791] The server automatically sends a reply email to the customer. A sending log is saved, allowing you to check and resend the email if necessary.

[1792] ---

[1793] Automatic quote generation function

[1794] Step 1: Enter the condition

[1795] The user inputs product or service conditions (type, quantity, period, etc.) into the terminal. This input is sent to the server.

[1796] Step 2: Get pricing information

[1797] The terminal retrieves the relevant price information from the price database via the server, and the retrieved data is temporarily stored in memory.

[1798] Step 3: Calculate the estimate

[1799] The server calculates a quote based on the retrieved pricing information, which reflects the terms and conditions of the product or service.

[1800] Step 4: Create a quote

[1801] The server generates a quote in PDF format based on the calculation results, and the generated PDF file is saved on the server.

[1802] Step 5: Provide a quote

[1803] The server provides the generated estimate to the user through the terminal, and the user can download and print the estimate.

[1804] ---

[1805] Customer behavior analysis function

[1806] Step 1: Collect data

[1807] The server collects customer purchase and access history, and the collected data is stored in a database that is updated regularly.

[1808] Step 2: Analyze the data

[1809] The server analyzes the collected data, using statistical methods and machine learning algorithms.

[1810] Step 3: Generate insights

[1811] The server generates useful insights based on the analysis results, including customer purchasing patterns and trends.

[1812] Step 4: Propose marketing measures

[1813] The server proposes specific marketing measures based on the generated insights, and outputs these proposals in the form of a report.

[1814] Step 5: Provide a proposal

[1815] The server provides the created proposal to the user via the terminal, and the user downloads and checks the proposal report and uses it to implement measures.

[1816] ---

[1817] Competitive research feature

[1818] Step 1: Collect data

[1819] The server collects competitor product information from external databases and the Internet, and the collected data is stored in an internal database.

[1820] Step 2: Comparative product analysis

[1821] The server compares and analyzes the company's products with the collected information on competing products, including extracting points of differentiation.

[1822] Step 3: Identifying points of differentiation

[1823] The server extracts points of differentiation from the comparative analysis, which then become the basis for sales strategies.

[1824] Step 4: Develop a sales strategy

[1825] The server then creates a sales strategy based on the extracted differentiation points, and outputs the created strategy as a report.

[1826] Step 5: Deliver a strategy

[1827] The server provides the planned strategy to the user via the terminal, who then checks the strategy report and reflects it in their sales activities.

[1828] ---

[1829] Function to create hypothetical questions and answers

[1830] Step 1: Collect historical data

[1831] The server collects past business negotiation history and FAQ data, which is then stored in a database.

[1832] Step 2: Anticipate questions

[1833] The server uses collected data to predict what questions customers will ask, using machine learning algorithms.

[1834] Step 3: Prepare your response

[1835] The server compiles answers to the predicted questions, and organizes the answers in an appropriate format.

[1836] Step 4: Create a list

[1837] The server creates a list of questions and answers, which are used to prepare for the meeting.

[1838] Step 5: Provide a list

[1839] The server provides the created list to the user via the terminal, who can refer to the list and use it to prepare for business negotiations.

[1840] ---

[1841] Proposal function for the shortest approach to closing

[1842] Step 1: Enter your agenda

[1843] The user inputs the agenda and related information into the terminal, which is then sent to the server.

[1844] Step 2: Analyze the information

[1845] The server analyzes the input agenda and related information, and this analysis clarifies the necessary points of discussion.

[1846] Step 3: Summary

[1847] The server summarizes the arguments needed to reach a conclusion, which are used to calculate the time required in step 4.

[1848] Step 4: Calculate the time required

[1849] The server calculates the time required for each point, and the results serve as data to guide the optimal closing approach.

[1850] Step 5: Providing an approach

[1851] The server proposes the optimal approach to closing and provides it to the user via the terminal. The user then carries out closing activities based on the proposed approach.

[1852] This detailed processing flow enables users to efficiently carry out sales and marketing activities, and improve the accuracy and speed of customer service.

[1853] (Application example 1)

[1854] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1855] In today's society, there is a demand for more efficient sales activities and faster customer responses. However, traditional sales support systems separate the processes of generating new customer lists, responding to inquiries, creating quotes, analyzing customer behavior, researching competitors, preparing sales negotiations, and closing sales, and lack integrated support. As a result, the efficiency of sales activities can decrease and the quality of customer responses can also be compromised.

[1856] 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.

[1857] In this invention, the server includes: means for automatically generating a new customer list based on criteria such as industry, region, related keywords, and sales volume; means for automatically creating appropriate reply and follow-up emails in response to customer inquiries; means for automatically generating quotations from product and service price lists; means for analyzing customer behavior to create marketing strategies based on purchase history and access history; means for conducting competitive research to analyze the differentiation points of a company's products and services; means for creating anticipated questions and answers before directly negotiating with customers; means for inputting an agenda and related information, summarizing the points of discussion necessary to reach a conclusion, calculating the required time, and proposing the shortest approach to closing; means for analyzing customer inquiries using natural language processing technology and searching for optimal answers from an FAQ database; means for retrieving data from external and internal databases based on query criteria, filtering, and automatically updating the list; and means for documenting the generated information in PDF format and electronically transmitting it. This enables integrated support for sales activities and significantly improves the efficiency and quality of customer service.

[1858] 1. "Automatic generation of new customer lists"

[1859] Automated generation of new customer lists is the process of automatically creating lists of new customers based on criteria such as industry, region, related keywords, and sales volume.

[1860] 2. "Creating Auto-Reply and Follow-Up Emails"

[1861] Auto-reply and follow-up email creation is the process of automatically generating and sending appropriate replies and follow-up emails in response to customer inquiries.

[1862] 3. "Automatic quote generation"

[1863] Auto-generating quotes is the process of automatically calculating and generating quotes based on specified criteria using a price list for a product or service.

[1864] 4. “Customer behavior analysis”

[1865] Customer behavior analysis is a method for formulating marketing strategies by collecting and analyzing behavioral data such as customer purchase history and access history.

[1866] 5. "Competitive Research"

[1867] Competitive research is the process of collecting information about competitors from external databases and the Internet and conducting a comparative analysis of their products and services.

[1868] 6. "Creating anticipated questions and answers"

[1869] Creating anticipated questions and answers is a procedure for preparing questions that customers may have and their answers in advance.

[1870] 7. "Proposing the quickest approach to closing"

[1871] Proposing the shortest approach to closing is a method of calculating and proposing the shortest steps required to successfully close a business negotiation based on the agenda and related information entered.

[1872] 8. "Natural language processing technology"

[1873] Natural language processing technology is a technology that enables computers to understand, interpret, and generate human language.

[1874] 9. "FAQ Database"

[1875] An FAQ database is a database that compiles frequently asked questions and their answers, and is used to respond to inquiries.

[1876] 10. Query Conditions

[1877] A query condition is a search condition for retrieving information from a database.

[1878] 11. "External Database"

[1879] An external database is a database that is an accessible source of information that exists outside the enterprise.

[1880] 12. "Internal Database"

[1881] An internal database is a collection of information managed within a company, and is a database used for data management and analysis within the company.

[1882] 13. “PDF format”

[1883] PDF is an abbreviation for Portable Document Format, and is a file format for saving documents as electronic files while preserving their layout.

[1884] 14. "Electronic Transmissions"

[1885] Electronic transmission is the process of sending electronic files over the Internet to other devices.

[1886] This invention is a system for streamlining and optimizing sales activities for security services. This system includes various functions such as automatically generating new customer lists, creating automatic replies and follow-up emails, automatically generating quotes, analyzing customer behavior, researching competitors, creating anticipated questions and answers, and proposing the shortest approach to closing a deal.

[1887] Automatic generation of new customer lists

[1888] The server receives user inputs such as industry, region, related keywords, and sales volume, and issues queries to external and internal databases to retrieve company data. The retrieved data is then filtered and a new customer list is automatically generated. The list is updated periodically, and the generated information is documented in PDF format and sent electronically.

[1889] Create auto-reply and follow-up emails

[1890] When the server receives an inquiry email from a customer, it analyzes the content using natural language processing technology and searches for the most appropriate answer from the FAQ database. Based on the selected answer, it selects an email template, automatically creates a reply email, and sends it electronically.

[1891] Auto-generate quotes

[1892] When the user inputs the product or service conditions (type, quantity, duration, etc.), the terminal retrieves the corresponding price information from the price database. The server calculates the estimate based on this information and creates a quote in PDF format.

[1893] customer behavior analysis

[1894] The server collects customer purchase and access histories and analyzes them to identify trends and patterns, generating useful insights and suggesting specific marketing strategies.

[1895] Competitive Research

[1896] The server collects information on competitors' products from external databases and the Internet, performs comparative analysis with the company's own products, extracts points of differentiation, and develops sales strategies based on these.

[1897] Creating anticipated questions and answers

[1898] The server predicts questions customers will have based on past sales negotiation history and FAQ data, and creates a list of answers. The list is provided to the user via their device to help them prepare for sales negotiations.

[1899] Proposal for the shortest approach to closing

[1900] The server analyzes the agenda and related information entered by the user, summarizes the points of discussion necessary to reach a conclusion, calculates the time required for each discussion, and proposes the optimal approach to closing the meeting, which is then provided to the user via their device.

[1901] Hardware and software used

[1902] Hardware: Smartphone (iOS / Android)

[1903] Software: Python, Pandas, Scikit-Learn, SMTP, Natural Language Processing library

[1904] Specific examples

[1905] For example, if a user enters "I would like to propose security services to IT companies in Tokyo," the server will filter the relevant companies from a database called "potential_clients.csv" and automatically create a new customer list. Also, if a customer inquires about "service fees," the server will automatically find the appropriate answer from the FAQ file and immediately create and send a reply email.

[1906] Prompt Sentence Examples

[1907] Use the "Security Sales Support App" to automatically generate a list of IT companies in Tokyo and respond immediately to customer inquiries about pricing.

[1908] In this way, the present invention can realize comprehensive support for sales activities, and can significantly improve the efficiency and quality of customer service.

[1909] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1910] Step 1: Enter customer terms and conditions

[1911] The user inputs conditions such as industry, region, related keywords, and sales volume into the terminal. This becomes the input data for generating a new customer list.

[1912] Step 2: Generate a new customer list

[1913] The server issues queries to external and internal databases based on the conditions sent by the user, filters the acquired company data, and automatically generates a new customer list. The generated list is documented in PDF format and sent to the terminal.

[1914] Step 3: Receiving an inquiry

[1915] An inquiry email from a customer is sent to the server, and this email becomes the input data for the automatic reply.

[1916] Step 4: Natural Language Processing Analysis

[1917] The server analyzes the content of the inquiry email using natural language processing techniques (e.g., TfidfVectorizer and cosine similarity), and searches the FAQ database for the best answer based on the analysis results.

[1918] Step 5: Create an autoresponder

[1919] The server selects an email template based on the selected answer and automatically creates a reply email, which is then electronically sent back to the customer.

[1920] Step 6: Enter your quotation criteria

[1921] The user inputs conditions such as the type of product or service, quantity, and period into the terminal. This becomes the input data for automatically generating a quote.

[1922] Step 7: Auto-generate quotes

[1923] The server retrieves the relevant price information from the price database based on the conditions entered by the user, calculates an estimate based on the retrieved price information, and creates an estimate in PDF format. The estimate is then sent to the terminal.

[1924] Step 8: Collect customer data

[1925] The server continuously collects customer purchase and access histories, which serve as input data for customer behavior analysis.

[1926] Step 9: Analyze customer behavior

[1927] The server analyzes the collected customer data to identify trends and patterns, and the results are used to propose specific marketing strategies.

[1928] Step 10: Gather Competitive Intelligence

[1929] The server collects competitor product information from external databases and the Internet, and this information becomes input data for competitive research.

[1930] Step 11: Competitive analysis

[1931] The server compares and analyzes the collected information on competitors and the company's own products to extract points of differentiation, and then develops a sales strategy based on this.

[1932] Step 12: Prepare possible questions and answers

[1933] The server predicts questions customers will have based on past business negotiation history and FAQ data, and creates a list of answers. The list is then sent to the terminal and provided to the user.

[1934] Step 13: Closing Calculations

[1935] The user inputs the agenda and related information of the business negotiation into the terminal. The server analyzes the input data, summarizes the points necessary to reach a conclusion, calculates the required time, and proposes the shortest closing approach and sends it to the terminal.

[1936] 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.

[1937] MODE FOR CARRYING OUT THE INVENTION

[1938] This invention provides a system with functions to automatically generate new customer lists based on criteria such as industry, region, related keywords, and sales volume, as well as to automatically create appropriate replies and follow-up emails to inquiries. This system also includes a customer behavior analysis function that automatically generates quotes from product and service price lists and creates marketing strategies based on purchase and access history. It also has functions to analyze points of differentiation through competitive research, create anticipated questions and answers before sales negotiations, calculate the required time based on the input of the agenda and related information, and propose the shortest approach to closing. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, it is possible to dynamically adjust response content and sales strategies.

[1939] Program processing details

[1940] Automatic generation of new customer lists

[1941] The server accepts user input of criteria such as industry, region, related keywords, and sales volume, and issues queries to external and internal databases to retrieve appropriate company data. The retrieved data is then filtered and a new customer list is automatically generated. The generated list is periodically updated and provided to the user via their device.

[1942] Examples:

[1943] The user enters the conditions "IT company," "Tokyo," and "cloud service," and the server creates a new customer list based on this.

[1944] Auto-reply and follow-up email creation function

[1945] When the server receives an inquiry email from a customer, it analyzes the content using natural language processing technology and searches for the most appropriate answer from the FAQ database. Based on the selected answer, it selects an email template and automatically creates a reply email. The reply email is then automatically sent to the customer.

[1946] Examples:

[1947] When a customer inquires about the specifications of a new product, the server creates and sends a reply email containing the appropriate specification information.

[1948] Automatic quote generation function

[1949] When the user inputs the product or service conditions (type, quantity, duration, etc.), the terminal retrieves the corresponding price information from the price database. The server calculates the estimate based on this information and creates a quote in PDF format. The quote is then provided to the user via the terminal.

[1950] Examples:

[1951] When the user selects an annual cloud service contract and a support package, the device automatically generates a quote.

[1952] Customer behavior analysis function

[1953] The server collects customer purchase and access histories and performs analysis based on this data. It identifies trends and patterns and generates useful insights. Based on this, it creates specific marketing proposals.

[1954] Examples:

[1955] The server analyzes the product categories that a particular customer frequently purchases and proposes new product promotion strategies.

[1956] Competitive research feature

[1957] The server collects information on competitors' products from external databases and the Internet, performs comparative analysis with the company's own products, extracts points of differentiation, and develops sales strategies based on these.

[1958] Examples:

[1959] Through comparative analysis with competing products, Server identifies that the advantage of its products is their "extensive support system," and reflects this information in its sales materials.

[1960] Function to create hypothetical questions and answers

[1961] The server predicts questions customers will have based on past sales negotiation history and FAQ data, and creates a list of answers. This is provided to the user via their device to help them prepare for sales negotiations.

[1962] Examples:

[1963] The server prepares questions and answers regarding "the cost of introducing a new product" in advance and provides them to the user.

[1964] Proposal function for the shortest approach to closing

[1965] The server analyzes the agenda and related information entered by the user, summarizes the points of discussion necessary to reach a conclusion, calculates the time required for each discussion, and proposes the optimal approach to closing the meeting, which is then provided to the user via their device.

[1966] Examples:

[1967] If a user wants to discuss "how to simplify the introduction of a new product," the server will calculate the required time and propose the optimal approach, and provide it to the user.

[1968] Combining Emotion Engines

[1969] The server incorporates an emotion engine that recognizes the user's emotional state based on user input and voice analysis. The emotion engine analyzes the user's or customer's emotional state in real time and appropriately adjusts the content and timing of responses based on that data.

[1970] Examples:

[1971] The emotion engine analyzes the emotional tone (e.g., dissatisfaction, interest) of customer inquiry emails, and the server automatically generates the optimal response based on that. It also analyzes the stress felt by users and the level of interest of customers in real time during sales, and dynamically changes sales strategies based on that data.

[1972] The above are the details of the specific processing steps and operations for each function of the invention that combines the emotion engine. This system makes it possible to improve the efficiency of sales activities, grasp customer needs, make optimal proposals, and respond quickly. Furthermore, the introduction of the emotion engine enables more personalized customer service.

[1973] The processing flow will be explained below.

[1974] Automatic generation of new customer lists

[1975] Step 1:

[1976] The user inputs conditions such as industry, region, related keywords, and sales volume into the terminal.

[1977] Step 2:

[1978] The terminal transmits the input condition data to the server.

[1979] Step 3:

[1980] The server issues queries to external and internal databases based on the received condition data to obtain matching company data.

[1981] Step 4:

[1982] The server filters the acquired company data and removes duplicates and irrelevant data.

[1983] Step 5:

[1984] The server formats the filtered data into a new customer list format and generates the new customer list.

[1985] Step 6:

[1986] The server schedules periodic updates of the generated new customer list.

[1987] Step 7:

[1988] The terminal displays the new customer list to the user and provides it in a downloadable format (CSV, Excel, etc.).

[1989] Auto-reply and follow-up email creation function

[1990] Step 1:

[1991] The server receives an inquiry email from the customer.

[1992] Step 2:

[1993] The server analyzes the content of the received inquiry email using natural language processing technology.

[1994] Step 3:

[1995] The server searches the FAQ database for the best answer based on the analysis results.

[1996] Step 4:

[1997] The server selects an appropriate email template based on the best answer.

[1998] Step 5:

[1999] The server inserts the response content into the email template and creates a reply email.

[2000] Step 6:

[2001] The server automatically sends the created reply mail to the customer who made the inquiry.

[2002] Automatic quote generation function

[2003] Step 1:

[2004] The user inputs the product or service conditions (type, quantity, period, etc.) into the terminal.

[2005] Step 2:

[2006] The terminal transmits the input condition data to the server.

[2007] Step 3:

[2008] The server queries the price database based on the condition data and obtains the corresponding price information.

[2009] Step 4:

[2010] The server calculates an estimate based on the acquired price information.

[2011] Step 5:

[2012] The server formats the calculation results into a PDF estimate.

[2013] Step 6:

[2014] The terminal displays the generated quote to the user and provides it in a downloadable format.

[2015] Customer behavior analysis function

[2016] Step 1:

[2017] The server automatically collects customer purchase history and access history.

[2018] Step 2:

[2019] The server analyzes the collected data using an analysis tool.

[2020] Step 3:

[2021] The server identifies trends and patterns based on the analysis results.

[2022] Step 4:

[2023] The server generates useful insights (such as recommended products and marketing strategies).

[2024] Step 5:

[2025] The server creates specific marketing proposals based on the generated insights.

[2026] Step 6:

[2027] The terminal displays the proposal to the user and provides related materials.

[2028] Competitive research feature

[2029] Step 1:

[2030] The server collects competitor product information from external databases and the web.

[2031] Step 2:

[2032] The server organizes the collected information and compiles it into a format that makes it easy to compare with the company's own products and services.

[2033] Step 3:

[2034] The server compares and analyzes the features, prices, advantages, etc. of its own products with those of its competitors.

[2035] Step 4:

[2036] The server extracts points of differentiation from the results of the comparative analysis.

[2037] Step 5:

[2038] The terminal provides users with a point of differentiation that can be utilized in sales activities.

[2039] Function to create hypothetical questions and answers

[2040] Step 1:

[2041] The server collects past business negotiation history and an FAQ database.

[2042] Step 2:

[2043] The server generates questions and appropriate answers based on the collected information.

[2044] Step 3:

[2045] The server formats the generated questions and answers into a list.

[2046] Step 4:

[2047] The terminal displays a list of expected questions and answers to the user to assist in preparation before the business negotiation.

[2048] Proposal function for the shortest approach to closing

[2049] Step 1:

[2050] The user inputs the agenda and related information into the terminal.

[2051] Step 2:

[2052] The terminal transmits the input information to the server.

[2053] Step 3:

[2054] The server analyzes the agenda and related information and summarizes the points needed to reach a conclusion.

[2055] Step 4:

[2056] The server calculates the time required to discuss each topic.

[2057] Step 5:

[2058] The server will propose the shortest approach to closing based on the required time and points of discussion.

[2059] Step 6:

[2060] The terminal displays the proposal contents to the user and optimizes the progress of the business negotiations.

[2061] Combining Emotion Engines

[2062] Step 1:

[2063] The server sends user input and voice data to the emotion engine.

[2064] Step 2:

[2065] The emotion engine analyzes input data and recognizes the emotional state of the user or customer.

[2066] Step 3:

[2067] The server adjusts the content and timing of the response based on the emotional state data obtained from the emotion engine.

[2068] Step 4:

[2069] The terminal provides the user with an optimized response based on the emotional state.

[2070] The above are the specific processing steps for each function of the invention combined with the emotion engine.

[2071] Example 2

[2072] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[2073] Traditionally, sales activities required a wide range of tasks, such as creating a list of new customers, responding to inquiries, generating quotes, analyzing customer behavior, researching competitors, preparing for sales negotiations, and making proposals up to closing, each of which required a great deal of time and effort.In addition, it was difficult to grasp the emotional state of customers and users in real time and respond accordingly, which limited the improvement of customer satisfaction.

[2074] The identification processing by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes: means for automatically generating a new customer list based on conditions such as industry, region, related keywords, and sales volume; means for automatically creating appropriate reply and follow-up emails in response to customer inquiries; means for automatically generating quotations from product and service price lists; means for analyzing customer behavior to create marketing strategies based on purchase history and access history; means for conducting competitive research to analyze the differentiation points of the company's products and services; means for creating anticipated questions and answers before directly negotiating with customers; means for summarizing the points of discussion necessary to reach a conclusion based on input of an agenda and related information, calculating the required time, and proposing the shortest approach to closing; and means for using an emotion engine to recognize the user's emotional state based on user input and voice analysis and adjust the content and timing of responses. This not only improves the efficiency of sales activities but also enables rapid understanding of customer needs and optimal proposals. Furthermore, the introduction of the emotion engine enables more personalized customer service.

[2075] "Means for automatically generating new customer lists" is a function that filters appropriate company data based on conditions such as industry, region, related keywords, and sales volume, and automatically creates new customer lists.

[2076] "Means for automatically creating appropriate reply and follow-up emails" refers to a function that uses natural language processing technology to analyze the content of customer inquiries, search for appropriate answers, and automatically generate and send reply and follow-up emails.

[2077] The "means for automatically generating a quote" is a function that, when you input the conditions of a product or service, retrieves price information from a price database, calculates a quote based on this, and automatically generates a quote.

[2078] "Customer behavior analysis tools" are functions that collect customer purchase history and access history, analyze this data, identify trends and patterns, and generate useful insights.

[2079] "Competitive research tools" is a function that collects information on competitors' products from external databases and the Internet, conducts comparative analysis with your own products, extracts points of differentiation, and develops sales strategies.

[2080] "A means of creating anticipated questions and answers" is a function that predicts questions from customers based on past sales negotiation history and FAQ data, and creates a list of answers.

[2081] "A means of inputting the agenda and related information to summarize the points needed to reach a conclusion, calculate the required time, and propose the shortest approach to closing" is a function that analyzes the agenda and related information input by the user, organizes the necessary points, calculates the required time for each discussion, and proposes the optimal approach to closing.

[2082] "Means using an emotion engine" refers to a function that recognizes the user's emotional state based on input and voice analysis, and adjusts the content and timing of responses based on that data.

[2083] MODE FOR CARRYING OUT THE INVENTION

[2084] This invention provides a system with functions to automatically generate new customer lists based on criteria such as industry, region, related keywords, and sales volume, as well as to automatically create appropriate replies and follow-up emails in response to customer inquiries. This system also includes a customer behavior analysis function that automatically generates quotes from product and service price lists and creates marketing strategies based on purchase and access history. It also analyzes points of differentiation through competitive research, creates anticipated questions and answers before sales negotiations, calculates the required time based on the input of the agenda and related information, and proposes the shortest approach to closing. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, it is possible to dynamically adjust response content and sales strategies.

[2085] Automatic generation of new customer lists

[2086] The server accepts user input criteria, such as industry, region, related keywords, and sales volume, often via a web form. Based on these criteria, the server queries external databases (such as a company information database) or internal databases to retrieve relevant company data. It then filters the retrieved data to create a new customer list. The new customer list is updated periodically to keep it up to date.

[2087] Examples:

[2088] When a user enters the conditions "IT company," "Tokyo," and "cloud services," the server creates a new customer list based on this.

[2089] Auto-reply and follow-up email creation function

[2090] When the server receives an inquiry email from a customer, it analyzes the content using natural language processing technology (e.g., Google NLP API).The server then searches for the most appropriate answer from the FAQ database based on the analysis results, and generates a reply email using an email template based on that answer.The generated email is then automatically sent to the customer.

[2091] Examples:

[2092] When a customer inquires about the specifications of a new product, the server analyzes the content, creates a reply email containing the appropriate specification information from the FAQ database, and sends it.

[2093] Automatic quote generation function

[2094] When the user inputs the product or service conditions (type, quantity, duration, etc.), the terminal retrieves the corresponding price information from the price database. The server calculates an estimate based on the retrieved price information and generates a quote in PDF format. The quote is then provided to the user via the terminal.

[2095] Examples:

[2096] When the user selects an "annual cloud service contract" and a "support package" and enters the conditions, the server retrieves information from a price database, generates a quote in PDF format, and provides it to the user via the terminal.

[2097] Customer behavior analysis function

[2098] The server collects and analyzes customer purchase and access histories. The server then analyzes the data using machine learning algorithms (e.g., clustering and regression analysis), identifies trends and patterns, and generates useful insights. Based on these insights, the server proposes specific marketing strategies and provides them to users via their devices.

[2099] Examples:

[2100] The server analyzes the product categories frequently purchased by a particular customer, proposes a promotion strategy for a new product, and provides it to the user through the terminal.

[2101] Competitive research feature

[2102] The server collects information on competitors' products from external databases and the Internet, compares them with its own products, extracts points of differentiation, and uses this information to develop sales strategies.

[2103] Examples:

[2104] Through comparative analysis with competing products, Server identifies that the advantage of its products is their "comprehensive support system," and reflects this in its sales materials.

[2105] Function to create hypothetical questions and answers

[2106] The server predicts questions customers will have based on past sales negotiation history and FAQ data, and creates a list of answers. The list is provided to the user via their device to help them prepare for sales negotiations.

[2107] Examples:

[2108] The server prepares questions and answers regarding "the cost of introducing a new product" in advance and provides them to the user via the terminal.

[2109] Proposal function for the shortest approach to closing

[2110] The server analyzes the agenda and related information entered by the user, organizes the necessary points of discussion, calculates the required time for each discussion, and proposes the optimal approach to closing the meeting, which is then provided to the user via their device.

[2111] Examples:

[2112] If a user wants to discuss "how to simplify the introduction of a new product," the server will calculate the required time and propose the optimal approach, and provide it to the user through the terminal.

[2113] Combining Emotion Engines

[2114] The server uses an emotion engine (e.g., Microsoft Azure Cognitive Services) that recognizes the user's emotional state based on user input and voice analysis. The emotion engine analyzes the user's or customer's emotional state in real time and appropriately adjusts the content and timing of responses based on that data.

[2115] Examples:

[2116] The emotion engine analyzes the emotional tone (e.g., dissatisfaction, interest) of customer inquiry emails, and the server automatically generates the optimal response based on that and sends it via email. It also analyzes the stress felt by users and the level of interest of customers during sales in real time, and dynamically changes sales strategies based on that data.

[2117] The system will streamline sales activities through each function, enabling quick understanding of customer needs and optimal proposals. The introduction of an emotion engine will also enable more personalized customer service.

[2118] The flow of the identification process in the second embodiment will be described with reference to FIG.

[2119] Automatic generation of new customer lists

[2120] Processing Steps

[2121] Step 1: Accept conditions

[2122] The server accepts user inputs from the terminal such as industry, region, related keywords, sales volume, etc. The input data is used to issue subsequent queries.

[2123] Input: User-entered industry, region, related keywords, and sales volume

[2124] Output: Condition data for issuing a query

[2125] Step 2: Query the database

[2126] The server issues queries to external and internal databases based on the input condition data, for example, by generating SQL statements and sending them to the databases.

[2127] Input: Condition data

[2128] Output: A list of companies retrieved from the database

[2129] Step 3: Filtering the data

[2130] The server filters the acquired company data based on conditions, for example, extracting only data from IT companies in the Tokyo region.

[2131] Input: A list of companies retrieved from a database

[2132] Output: Filtered company data

[2133] Step 4: Generate a new customer list

[2134] The server creates a list of new customers based on the filtered company data, often stored in JSON or CSV format.

[2135] Input: Filtered company data

[2136] Output: New customer list

[2137] Step 5: Providing a list of new customers

[2138] The server provides the generated new customer list to the user's terminal, including via a web page or email.

[2139] Input: New Customer List

[2140] Output: A list of new customers displayed on the user's device.

[2141] ---

[2142] Auto-reply and follow-up email creation function

[2143] Processing Steps

[2144] Step 1: Receiving an inquiry email

[2145] The server receives inquiry emails from customers, which is often received via an SMTP server.

[2146] Input: Customer inquiry email

[2147] Output: Contents of inquiry email

[2148] Step 2: Analyzing the email content

[2149] The server analyzes the content of the received inquiry email using natural language processing technology to extract the email's topic and emotional tone.

[2150] Input: Contents of inquiry email

[2151] Output: Parsed email content

[2152] Step 3: Finding the best answer

[2153] The server searches the FAQ database for the best answer based on the analysis results, using a similarity search algorithm to select the most relevant answer.

[2154] Input: Parsed email content

[2155] Output: Best answer

[2156] Step 4: Generate a reply email

[2157] The server generates a reply email using an email template based on the selected answer, with variables embedded in the template that are then replaced with actual data.

[2158] Input: Best Answer

[2159] Output: The generated reply email

[2160] Step 5: Send a reply email

[2161] The server generates a reply email and sends it to the customer, via an SMTP server.

[2162] Input: Generated reply email

[2163] Output: Reply email to customer

[2164] ---

[2165] Automatic quote generation function

[2166] Processing Steps

[2167] Step 1: Enter the condition

[2168] The terminal accepts the product or service conditions (type, quantity, duration, etc.) entered by the user, often via a web form.

[2169] Input: User-entered product or service terms

[2170] Output: Condition data

[2171] Step 2: Get pricing information

[2172] The server retrieves the relevant price information from the price database based on the entered condition data, and uses an SQL query to retrieve the price information.

[2173] Input: Condition data

[2174] Output: Price information

[2175] Step 3: Calculate the estimate

[2176] The server calculates an estimate based on the acquired price information, taking into account conditions such as quantity and period.

[2177] Input: Price Information

[2178] Output: Calculated estimate data

[2179] Step 4: Generate a quote

[2180] The server generates a PDF quotation based on the calculation results using a PDF generation library.

[2181] Input: Estimate data

[2182] Output: PDF quotation

[2183] Step 5: Provide a quote

[2184] The server provides the generated quote to the user via the terminal, which may include sending it by email or providing a download link.

[2185] Input: PDF quotation

[2186] Output: Quote provided to user

[2187] ---

[2188] Customer behavior analysis function

[2189] Processing Steps

[2190] Step 1: Data collection

[2191] The server collects customer purchase and access histories from web logs and transaction databases.

[2192] Input: purchase history, access history

[2193] Output: Collected data

[2194] Step 2: Data analysis

[2195] The server analyzes the collected data using machine learning algorithms (e.g., clustering, regression analysis).

[2196] Input: Collected data

[2197] Output: Analysis results

[2198] Step 3: Generate insights

[2199] The server identifies trends and patterns from the analysis results and generates useful insights.

[2200] Input: Analysis results

[2201] Output:Insight

[2202] Step 4: Propose marketing measures

[2203] The server creates specific marketing proposals based on the generated insights and provides them to the user via the terminal.

[2204] Input: Insight

[2205] Output: Marketing Strategy

[2206] ---

[2207] Combining Emotion Engines

[2208] Processing Steps

[2209] Step 1: Parse the input

[2210] The server accepts user input (text, voice) and analyzes it using natural language processing technology.

[2211] Input: What the user types

[2212] Output: Parsed input

[2213] Step 2: Recognizing your emotional state

[2214] The server uses an emotion engine to recognize the emotional state based on the analysis results, for example, identifying emotions such as excitement, anxiety, and calm.

[2215] Input: Parsed input

[2216] Output: Emotional state

[2217] Step 3: Tailor your response

[2218] The server adjusts the content and timing of responses based on the user's perceived emotional state: for example, if the user is frustrated, a more friendly response will be automatically chosen.

[2219] Input: Emotional state

[2220] Output: Adjusted response content

[2221] Step 4: User feedback

[2222] The server provides tailored responses to the user via the terminal, providing real-time feedback.

[2223] Input: Adjusted response content

[2224] Output: Feedback to the user

[2225] ---

[2226] The above are the specific processing steps for each function of this system. This will improve the efficiency of sales activities, quickly grasp customer needs, and make optimal proposals. The introduction of an emotion engine will also enable more personalized customer service.

[2227] (Application example 2)

[2228] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[2229] In today's business environment, companies must efficiently perform a wide range of tasks, including acquiring new customers, responding quickly and appropriately to existing customers, creating product and service quotes, analyzing competitors, and preparing for sales negotiations. However, performing these tasks manually is extremely time-consuming and labor-intensive, resulting in inefficiency and low accuracy. Furthermore, security incident response requires real-time monitoring and appropriate action, and performing this manually carries high risks. To solve these issues, it is necessary to automate these tasks and utilize sentiment analysis to make appropriate decisions quickly.

[2230] 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.

[2231] In this invention, the server includes means for automatically generating a new customer list based on conditions such as industry, region, related keywords, and sales volume, means for automatically creating appropriate reply and follow-up emails in response to inquiries, means for automatically generating quotes from product and service price lists, means for analyzing customer behavior to create marketing strategies based on purchase history and access history, means for conducting competitive research to analyze the differentiating points of a company's products and services, means for creating anticipated questions and answers before directly negotiating with customers, means for summarizing the points of discussion necessary to reach a conclusion based on input of an agenda and related information, calculating the required time, and proposing the shortest approach to closing, and means for analyzing the details of a security incident and determining appropriate actions based on the emotional state.This enables more efficient sales activities, understanding customer needs, optimal proposals, rapid responses, and appropriate security responses based on emotional analysis.

[2232] "Automatic generation of new customer lists" is a system that lists potential new customers based on criteria such as industry, region, related keywords, and sales volume.

[2233] "Creating automatic replies and follow-up emails" is a system that uses natural language processing technology to automatically create appropriate replies to customer inquiries and send them via email.

[2234] "Automatic quotation generation" is a system that automatically creates a quotation based on specified conditions from a price list for a product or service.

[2235] "Customer behavior analysis" is a system that analyzes customers' purchase history and access history and proposes effective marketing measures.

[2236] "Competitive research" is a system that uses collected competitive information to compare your own products and services with those of your competitors and extract points of differentiation.

[2237] "Creating anticipated questions and answers" is a system that prepares anticipated questions and answers before directly negotiating with a customer.

[2238] "Proposing the shortest approach to closing" is a system that, when you input the agenda and related information, summarizes the points needed to reach a conclusion, calculates the required time, and proposes the optimal approach to successfully close a business negotiation.

[2239] "Security Incident Analysis" is a system that analyzes the details of a security incident and determines appropriate actions based on emotional state.

[2240] "Emotion analysis" is a technology that uses natural language processing technology to analyze the emotional state of text or speech and determine an appropriate response based on that.

[2241] MODE FOR CARRYING OUT THE INVENTION

[2242] This invention provides a system with the functions of automatically generating new customer lists based on conditions such as industry, region, related keywords, and sales volume, and automatically creating appropriate replies and follow-up emails to inquiries. Furthermore, the system also includes functions for automatically generating quotes from product and service price lists, analyzing customer behavior to create marketing strategies based on purchase and access histories, analyzing points of differentiation through competitive research, creating anticipated questions and answers before business negotiations, calculating the required time by inputting agenda items and related information, and proposing the shortest approach to closing. It also combines emotional analysis with security incident analysis to dynamically determine appropriate actions.

[2243] System configuration

[2244] The system consists of the following main components:

[2245] 1. Server:

[2246] Hardware: A powerful processor (e.g., Intel Xeon), lots of memory (e.g., 32GB RAM), and fast storage (e.g., SSD).

[2247] Software: Database management systems (e.g., MySQL), natural language processing engines (e.g., NLTK), sentiment analysis engines (e.g., Sentiment Analysis Toolkit), report generators (e.g., ReportLab).

[2248] 2. Terminal:

[2249] Hardware: Smartphone.

[2250] Software: Operating systems (e.g., Android, iOS), mobile applications.

[2251] System Operation

[2252] The server analyzes user input and sensor data in real time and performs the following data processing and calculations:

[2253] Auto-generate new customer lists:

[2254] The server issues queries to external and internal databases based on user-entered criteria such as industry, region, related keywords, and sales volume, and the retrieved data is filtered to automatically generate a new customer list.

[2255] Creating Auto-Reply & Follow-Up Emails:

[2256] The server uses natural language processing technology to analyze the inquiry and search for the appropriate answer in the FAQ database, then automatically creates and sends a reply email based on that answer.

[2257] Auto-generate quotes:

[2258] The server retrieves the relevant information from a price database based on the product or service conditions entered by the user, and automatically calculates a quote. The quote is generated in PDF format and provided via the terminal.

[2259] Customer behavior analysis:

[2260] The server collects customer purchase and access histories and analyzes the data, which is then used to create marketing strategies.

[2261] Competitive Research:

[2262] The server collects information on competitors from external databases and the Internet, and performs comparative analysis with the company's own products. Differentiating points are extracted and reflected in sales strategies.

[2263] Creating anticipated questions and answers:

[2264] The server creates a list of anticipated questions and their answers based on past business negotiation history and FAQ data, thereby supporting pre-negotiation preparation.

[2265] Suggested quickest approach to closing:

[2266] Based on the agenda and related information, the server summarizes the points of discussion and calculates the required time to propose the optimal closing approach.

[2267] Security incident analysis:

[2268] The server analyzes the details of the security incident and determines the appropriate action based on the emotional state, enabling appropriate responses in real time.

[2269] Specific examples

[2270] Suppose a user is in charge of security management for a company that holds art exhibitions. Security incidents often occur when a new exhibition opens. Using SmartGuard-S, the user can continuously monitor new incidents and view details in the application. If the incident is deemed urgent, the sentiment analysis engine will issue an "urgent alert" and the appropriate response method will be automatically displayed. The user can also automatically generate new customer lists and quotes based on specific conditions (e.g., exhibition location, type of exhibit, security requirements).

[2271] Prompt Sentence Examples

[2272] "How can I analyze the details of a recent security incident, classify its emotional state, and generate applicable actions and reports?"

[2273] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2274] Processing Steps

[2275] Step 1:

[2276] The user uses a terminal to input conditions such as industry, region, related keywords, sales volume, etc. This input data is sent to the server.

[2277] Step 2:

[2278] The server issues queries to external and internal databases based on the received criteria, thereby retrieving the relevant company data.

[2279] Step 3:

[2280] The server filters the acquired company data and automatically generates a new customer list, which is updated periodically.

[2281] Step 4:

[2282] When a user sends an inquiry email using a terminal, the server receives it and analyzes it using natural language processing technology.

[2283] Step 5:

[2284] The server searches the FAQ database for the best answer based on the analysis results, and automatically creates a reply email based on the selected answer.

[2285] Step 6:

[2286] The server sends the created reply mail to the user's terminal, and also automatically creates and sends a follow-up mail.

[2287] Step 7:

[2288] The user inputs product or service conditions (type, quantity, period, etc.) into the terminal. This input data is sent to the server.

[2289] Step 8:

[2290] The server retrieves the relevant price information from the price database, calculates the estimate based on that information, and creates a quote in PDF format based on the calculation results.

[2291] Step 9:

[2292] The server sends the estimate to the terminal and provides it to the user.

[2293] Step 10:

[2294] The server collects and analyzes customer purchase history and access history from a database and creates marketing strategies.

[2295] Step 11:

[2296] The server collects information on competitors from external databases and the Internet, performs comparative analysis with the company's own products, extracts points of differentiation, and reflects them in sales strategies.

[2297] Step 12:

[2298] The server creates a list of predicted and anticipated questions and their answers based on past business negotiation history and FAQ data.

[2299] Step 13:

[2300] Based on the agenda and related information entered by the user, the server summarizes the points needed to reach a conclusion, calculates the required time, and proposes a closing approach.

[2301] Step 14:

[2302] The server analyzes the details of the security incident and classifies the emotional state of the incident using an emotional analysis engine.

[2303] Step 15:

[2304] Based on the classification results, the server determines the appropriate action to take, such as high alert, monitoring, low alert, etc. The generated report is provided to the user in a format that can be viewed in real time.

[2305] Specific examples of processing

[2306] Step 1:

[2307] The user uses a terminal to enter conditions such as "IT company," "Tokyo," "cloud service," and "sales size: small and medium-sized enterprises," and sends the results to the server.

[2308] Input: "IT company", "Tokyo", "Cloud service", "Sales size: Small and medium-sized enterprises"

[2309] Output: The condition is sent to the server.

[2310] Step 2:

[2311] The server retrieves relevant company data from external and internal databases based on the received conditions.

[2312] Input: Received condition data

[2313] Output: Acquisition of relevant company data

[2314] Step 3:

[2315] The server filters the acquired company data and automatically generates a new customer list, which is updated periodically.

[2316] Input: Acquired company data

[2317] Output: Generate and update new customer list

[2318] Step 4:

[2319] The user sends an inquiry email from the terminal, which is received by the server and analyzed using natural language processing technology.

[2320] Input: Inquiry email

[2321] Output: Analysis results

[2322] Step 5:

[2323] The server searches the FAQ database for the best answer and automatically creates a reply email.

[2324] Input: Analysis results

[2325] Output: Auto-generated reply email

[2326] Step 6:

[2327] The server sends the reply email to the user's terminal and also creates and sends a follow-up email.

[2328] Input: Draft of reply email

[2329] Output: Reply and follow-up emails sent

[2330] Step 7:

[2331] The user enters conditions such as "cloud service," "annual contract," and "5 licenses" on the device. The input data is sent to the server.

[2332] Input: Terms such as "Cloud service," "Annual contract," and "5 licenses"

[2333] Output: The condition is sent to the server

[2334] Step 8:

[2335] The server retrieves the relevant price information from the price database, automatically calculates an estimate based on that information, and creates an estimate in PDF format.

[2336] Input: Submitted condition data

[2337] Output: PDF quotation

[2338] Step 9:

[2339] The server sends the estimate in PDF format to the terminal and provides it to the user.

[2340] Input: PDF quotation

[2341] Output: Quote provided to user

[2342] Step 10:

[2343] The server collects customer purchase history and access history from a database, analyzes them, and creates marketing strategies.

[2344] Input: Customer purchase history and access history

[2345] Output: Marketing Strategy

[2346] Step 11:

[2347] The server collects information on competitors, performs comparative analysis with its own products, and extracts points of differentiation.

[2348] Input: Competitor Information

[2349] Output: Differentiation points and sales strategies

[2350] Step 12:

[2351] The server creates a list of anticipated questions and answers before the business meeting and provides it to the user.

[2352] Input: Sales history and FAQ data

[2353] Output: List of expected questions and answers

[2354] Step 13:

[2355] When the user inputs the agenda and related information, the server summarizes the necessary points, calculates the required time, and suggests a closing approach.

[2356] Input: Agenda and related information

[2357] Output: Shortest approach to closing

[2358] Step 14:

[2359] The server analyzes the details of the security incident and classifies the emotional state.

[2360] Input: Security incident details

[2361] Output: Emotional state classification result

[2362] Step 15:

[2363] The server determines the appropriate action based on the classification results and performs incident response. The generated report is provided to the user in real time.

[2364] Input: Emotional state classification results

[2365] Output: Appropriate actions and incident response report

[2366] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[2367] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[2368] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[2369] [Fourth embodiment]

[2370] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[2371] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[2372] 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).

[2373] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[2374] 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.

[2375] 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).

[2376] 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.

[2377] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[2378] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[2379] 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.

[2380] 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.

[2381] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[2382] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2383] MODE FOR CARRYING OUT THE INVENTION

[2384] This invention provides a system with functions to automatically generate new customer lists based on criteria such as industry, region, related keywords, and sales volume, as well as to automatically create appropriate replies and follow-up emails to inquiries. This system also includes a customer behavior analysis function that automatically generates quotes from product and service price lists and creates marketing strategies based on purchase and access history. Furthermore, the system also has functions to analyze points of differentiation through competitive research, create anticipated questions and answers before negotiations, calculate the required time by entering the agenda and related information, and propose the shortest approach to closing.

[2385] Program processing details

[2386] Automatic generation of new customer lists

[2387] The server accepts user input of criteria such as industry, region, related keywords, and sales volume, and issues queries to external and internal databases to retrieve appropriate company data. The retrieved data is then filtered and a new customer list is automatically generated. The generated list is periodically updated and provided to the user via their device.

[2388] Examples:

[2389] The user enters the conditions "IT company," "Tokyo," and "cloud service," and the server creates a new customer list based on this.

[2390] Auto-reply and follow-up email creation function

[2391] When the server receives an inquiry email from a customer, it analyzes the content using natural language processing technology and searches for the most appropriate answer from the FAQ database. Based on the selected answer, it selects an email template and automatically creates a reply email. The reply email is then automatically sent to the customer.

[2392] Examples:

[2393] When a customer inquires about the specifications of a new product, the server creates and sends a reply email containing the appropriate specification information.

[2394] Automatic quote generation function

[2395] When the user inputs the product or service conditions (type, quantity, duration, etc.), the terminal retrieves the corresponding price information from the price database. The server calculates the estimate based on this information and creates a quote in PDF format. The quote is then provided to the user via the terminal.

[2396] Examples:

[2397] When the user selects an annual cloud service contract and a support package, the device automatically generates a quote.

[2398] Customer behavior analysis function

[2399] The server collects customer purchase and access histories and performs analysis based on this data. It identifies trends and patterns and generates useful insights. Based on this, it creates specific marketing proposals.

[2400] Examples:

[2401] The server analyzes the product categories that a particular customer frequently purchases and proposes new product promotion strategies.

[2402] Competitive research feature

[2403] The server collects information on competitors' products from external databases and the Internet, performs comparative analysis with the company's own products, extracts points of differentiation, and develops sales strategies based on these.

[2404] Examples:

[2405] Through comparative analysis with competing products, Server identifies that the advantage of its products is their "extensive support system," and reflects this information in its sales materials.

[2406] Function to create hypothetical questions and answers

[2407] The server predicts questions customers will have based on past sales negotiation history and FAQ data, and creates a list of answers. This is provided to the user via their device to help them prepare for sales negotiations.

[2408] Examples:

[2409] The server prepares questions and answers regarding "the cost of introducing a new product" in advance and provides them to the user.

[2410] Proposal function for the shortest approach to closing

[2411] The server analyzes the agenda and related information entered by the user, summarizes the points of discussion necessary to reach a conclusion, calculates the time required for each discussion, and proposes the optimal approach to closing the meeting, which is then provided to the user via their device.

[2412] Examples:

[2413] If a user wants to discuss "how to simplify the introduction of a new product," the server will calculate the required time and propose the optimal approach, and provide it to the user.

[2414] The above is a specific example of an embodiment of the invention and details of the program processing. This system makes it possible to improve the efficiency of sales activities, grasp customer needs, make optimal proposals, and respond quickly.

[2415] The processing flow will be explained below.

[2416] Automatic generation of new customer lists

[2417] Step 1:

[2418] The user inputs conditions such as industry, region, related keywords, and sales volume into the terminal.

[2419] Step 2:

[2420] The terminal transmits the input conditions to the server.

[2421] Step 3:

[2422] The server accesses the external database and the internal database based on the received condition data to obtain the matching company data.

[2423] Step 4:

[2424] The server filters the acquired company data and removes duplicates and irrelevant data.

[2425] Step 5:

[2426] The server formats the filtered data into a new customer list.

[2427] Step 6:

[2428] The server schedules periodic updates of the new customer list.

[2429] Step 7:

[2430] The terminal displays the new c...

Claims

1. A means to automatically generate new customer lists based on criteria such as industry, region, related keywords, and sales volume, A means to automatically create appropriate replies and follow-up emails to customer inquiries, A means to automatically generate quotes from price lists for products and services; A customer behavior analysis tool that creates marketing strategies based on purchase history and access history, Competitive research methods to analyze the points of differentiation of your company's products and services, A way to create anticipated questions and answers before directly negotiating with customers, By inputting the agenda and related information, it summarizes the points necessary to reach a conclusion, calculates the required time, and proposes the shortest approach to closing. A system including:

2. 2. The system according to claim 1, further comprising means for analyzing the content of the inquiry using natural language processing technology and selecting an appropriate answer.

3. 2. The system according to claim 1, further comprising means for comparatively analyzing the company's products and competitor products based on the collected competitive information, and extracting points of differentiation.

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