system

Abstract

We provide the system. [Solution] A data input means for receiving customer information and automatically generating appropriate proposals based on said customer information, A data analysis means for analyzing customer information received from the data input means, A proposal generation means that generates proposals based on the analysis results of the data analysis means, A result display means for displaying the generated proposals, A system that includes this.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance as a response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In a conventional sales floor, in order to propose an appropriate smartphone or Internet plan to a customer, it was necessary for an employee to accurately understand the customer's needs and make a proposal based on rich knowledge. However, for a new recruit, such a high - level response was difficult, and it was impossible to make a prompt and appropriate proposal to the customer. In addition, in a conventional system, analysis of customer information and generation of proposals were often performed manually, resulting in low efficiency. Therefore, there has been a demand for a system that automates the proposal process in the sales floor and enables even a new recruit to make an appropriate proposal to a customer.

Means for Solving the Problems

[0005] The present invention provides a system including a data input means for inputting customer information, a data analysis means for analyzing the input customer information, a proposal generation means for generating proposals based on the analysis results, and a results display means for displaying the generated proposals. The data input means allows employees to easily input customer information. The data analysis means analyzes customer information using past customer data and product information, and the proposal generation means filters multiple proposals based on specific conditions and selects the optimal proposal. The results display means displays the generated proposals on a screen, allowing employees to make quick and appropriate proposals to customers based on these. This enables even new crew members to make proposals similar to those of experienced crew members, thereby improving the quality of service to customers.

[0006] "Customer information" refers to information such as customers' smartphone and internet usage, dissatisfaction with communication speed, insufficient data capacity, and budget.

[0007] "Data entry means" refers to a device or software that provides an interface for employees to input customer information.

[0008] "Data analysis means" refers to a device or software used to analyze received customer information, and the analysis is performed using past customer data and product information.

[0009] "Proposal generation means" refers to a device or software that filters multiple proposals based on analysis results and selects the optimal proposal.

[0010] "Result display means" refers to a device or software for displaying the generated suggestions.

[0011] "Filtering" refers to the process of selecting the best option from multiple suggestions based on specific criteria.

[0012] A "new crew member" refers to an employee who has recently been assigned to a sales floor and is not yet accustomed to their duties.

[0013] "Proposal" refers to recommending the optimal plan or service based on the customer's smartphone and internet usage. [Brief explanation of the drawing]

[0014] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] This is a sequence diagram showing the processing flow of the data processing system in Example 2, when an emotion engine is combined. [Figure 14]It is a sequence diagram showing the processing flow of a data processing system in Application Example 2 when a sentiment engine is combined.

Embodiments for Carrying Out the Invention

[0015] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0016] First, the terms used in the following description will be explained.

[0017] In the following embodiments, a processor with a reference number (hereinafter simply referred to as "processor") may be one arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be one type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0018] In the following embodiments, a RAM (Random Access Memory) with a reference number is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0019] In the following embodiments, a storage with a reference number is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, and the like.

[0020] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0021] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0022] [First Embodiment]

[0023] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0024] As shown in Figure 1, the 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.

[0025] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0026] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0027] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and 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.

[0028] 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 perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0029] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0030] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0031] As shown in Figure 2, in the data processing device 12, a specific processing 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" related to the technology of this 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 according to the specific processing program 56 executed on the RAM 30.

[0032] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0033] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0034] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0035] System Overview

[0036] As a form of implementing the invention, this system provides support to new crew members in the sales area, enabling them to propose appropriate smartphones and internet plans to customers. The system mainly consists of the following components:

[0037] 1. Data input means

[0038] 2. Data Analysis Methods

[0039] 3. Proposal generation means

[0040] 4. Results display means

[0041] Data input means

[0042] The terminal provides a customer information input screen. This allows users to easily input information obtained from customers. Input fields include the customer's smartphone and internet usage, dissatisfaction with communication speed, insufficient data capacity, budget, etc.

[0043] Specific example:

[0044] The user logs into their device and enters customer information such as "slow internet speed" or "insufficient data capacity."

[0045] Data analysis means

[0046] The server receives customer information sent from the terminal and analyzes it. This analysis involves referencing past customer data and product information. This establishes criteria for identifying the plan best suited to the customer's needs.

[0047] Specific example:

[0048] The server analyzes whether a user is dissatisfied with their internet speed and recommends a faster plan, or whether they are experiencing insufficient data capacity and should consider an unlimited plan or an option to purchase additional data.

[0049] Proposal generation means

[0050] The server generates a proposal based on the analysis results. This proposal includes specific information such as the plan name, price, features, and special offers.

[0051] Specific example:

[0052] The server generates specific proposals such as "5G plan" and "unlimited data plan," and adds related benefits and campaign information.

[0053] Results display means

[0054] The server generates a proposal and sends it to the terminal, which then displays it to the user. Based on this proposal, the user can quickly make appropriate suggestions to the customer.

[0055] Specific example:

[0056] The system then displays a suggestion on the user's device screen and explains to the customer, "Switching to this 5G plan will dramatically improve your communication speed, and with an unlimited data plan, you'll never have to worry about running out of data."

[0057] This system enables even new crew members to make suggestions on par with experienced employees, thereby improving customer satisfaction. Furthermore, automating the suggestion process reduces the burden on employees and streamlines the suggestion process.

[0058] The following describes the processing flow.

[0059] Step 1:

[0060] The device displays the login screen. The user enters their username and password and presses the login button. The device sends the entered authentication information to the server.

[0061] Step 2:

[0062] The server compares the received authentication information with the database. The server determines whether authentication was successful and sends the authentication result to the terminal. If the terminal successfully authenticates, it displays the data entry screen.

[0063] Step 3:

[0064] The terminal displays a customer information input screen. Input fields include the customer's smartphone and internet usage, dissatisfaction with communication speed, insufficient data capacity, and budget. The user then enters the customer information.

[0065] Step 4:

[0066] The user completes entering customer information and presses the submit button. The terminal then sends the entered customer information to the server.

[0067] Step 5:

[0068] The server passes the received customer information to a module for analysis. The server then filters the information to extract appropriate smartphone and internet plans based on the customer's requests. For example, if a customer is dissatisfied with their internet speed, the server will prioritize 5G plans over 4G plans.

[0069] Step 6:

[0070] The server compares past customer data and product information to select the most suitable recommendation. For example, if there is a "data capacity shortage," it will prioritize unlimited plans or additional data purchase options.

[0071] Step 7:

[0072] The server then selects the most suitable plan from the extracted options. This includes information such as the plan name, price, features, and special offers.

[0073] Step 8:

[0074] The server formats the generated proposals as a data package. The server then sends the proposal content to the terminal.

[0075] Step 9:

[0076] The device renders the received proposal content on the display screen. The user checks the device screen and shares the proposal content with the customer. For example, the user might explain, "Switching to this 5G plan will dramatically improve communication speed, and with the unlimited data plan, you won't have to worry about running out of data."

[0077] (Example 1)

[0078] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0079] Traditional customer service presented challenges, particularly for new employees, in proposing appropriate communication plans to customers. Furthermore, inconsistencies in the quality and speed of proposals led to decreased customer satisfaction and increased workload for employees.

[0080] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0081] In this invention, the server includes an input means for receiving customer information and automatically generating appropriate suggestions based on the customer information, an analysis means for analyzing the customer information received from the input means, and a generation means for generating suggestions based on the analysis results of the analysis means. This makes it possible for new employees to make suggestions equivalent to those of experienced employees, thereby improving customer satisfaction and reducing the burden on employees.

[0082] An "input method" is a means of receiving customer information and inputting it into the system.

[0083] "Analysis means" refers to means for analyzing customer information received from input means and evaluating data based on the analysis results.

[0084] "Generation means" refers to means for generating appropriate proposals based on the analysis results of the analysis means.

[0085] "Display means" refers to means for displaying the proposals generated by the generation means to the user.

[0086] A "customer database" is a database that stores past customer information.

[0087] "Product information" refers to information about the products handled by the system.

[0088] "Filtering" is the process of selecting from multiple proposals based on specific criteria.

[0089] "The optimal proposal" refers to the proposal that best suits the customer's needs.

[0090] "Analysis results" refer to the results of the analysis tool's evaluation of customer information received from the input tool.

[0091] As a form of implementing the invention, this system provides support to new employees in the sales area, enabling them to propose appropriate smartphones and internet plans to customers. The system mainly consists of the following components:

[0092] 1. Input Method (Terminal): The terminal provides an input screen for receiving customer information. Users can use this screen to input information such as their smartphone and internet usage, dissatisfaction with communication speed, insufficient data capacity, and budget. A specific example is a user logging into the terminal and inputting information such as "slow communication speed" or "insufficient data capacity."

[0093] 2. Analysis Method (Server): The server receives customer information transmitted from the terminal. The received information is analyzed by the server. In this process, the server refers to past customer databases and product information to set criteria for identifying the plan best suited to the customer's needs. For example, the server might analyze a faster communication speed plan for "dissatisfaction with communication speed" and an unlimited plan or additional data purchase option for "insufficient data capacity."

[0094] 3. Generation Method (Server): Based on the analysis results, the server generates proposals. These proposals include specific information such as plan name, price, features, and special offers. For example, the server generates specific proposals such as "5G plan" and "unlimited data plan," and adds related benefits and campaign information.

[0095] 4. Display means (terminal): The generated proposal content is sent to the terminal, which displays it to the user. Based on this proposal content, the user can make quick and appropriate proposals to the customer. For example, the user could explain to the customer, "If you switch to this 5G plan, your communication speed will dramatically improve, and with the unlimited data plan, you won't have to worry about running out of data."

[0096] Example of a prompt

[0097] "Please propose the best internet plan for a customer who is dissatisfied with their current internet speed and lacks sufficient data capacity. The budget is within ¥XX."

[0098] This system enables even new employees to make proposals on par with experienced employees, thereby improving customer satisfaction. Furthermore, automating the proposal process reduces the burden on employees and streamlines the proposal process.

[0099] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0100] System program processing flow

[0101] Step 1:

[0102] The user operates the terminal and enters customer information. Specifically, information such as the customer's smartphone and internet usage, dissatisfaction with communication speed, insufficient data capacity, and budget is collected through the terminal's input screen. The entered information is then organized for data processing.

[0103] Input: Customer information (e.g., dissatisfaction with communication speed, insufficient data capacity)

[0104] Output: Organized customer information

[0105] Specific example:

[0106] The user logs into their device and enters information such as "the internet speed is slow" or "there isn't enough data."

[0107] Step 2:

[0108] The terminal sends the entered customer information to the server. This transmission is encrypted for security reasons. The server stores the received information in its database.

[0109] Input: Organized customer information

[0110] Output: Customer information sent to the server

[0111] Specific example:

[0112] The terminal encrypts customer information and sends it to the server.

[0113] Step 3:

[0114] The server analyzes the customer information it receives. This analysis involves referencing past customer databases and product information to establish criteria for identifying the best plan to meet the customer's needs.

[0115] Input: Customer information sent to the server

[0116] Output: Criteria based on customer needs (after data processing)

[0117] Specific example:

[0118] The server analyzes and matches "dissatisfaction with communication speed" with plans offering faster communication speeds, and "insufficient data capacity" with unlimited plans or additional data purchase options.

[0119] Step 4:

[0120] The server generates a proposal based on the analysis results. This proposal includes specific information such as the plan name, price, features, and special offers. The generated proposal is then saved back to the database.

[0121] Input: Criteria based on analyzed customer needs

[0122] Output: Generated proposals

[0123] Specific example:

[0124] The server generates specific proposals such as "5G plan" and "unlimited data plan," and adds related benefits and campaign information.

[0125] Step 5:

[0126] The server generates a proposal and sends it to the terminal, which then displays it to the user. The user reviews the displayed proposal and explains it to the customer.

[0127] Input: Generated suggestion content

[0128] Output: Suggestions displayed on the terminal

[0129] Specific example:

[0130] The server sends the generated suggestions to the terminal, and the terminal displays the content on the user's screen.

[0131] Step 6:

[0132] The user reviews the proposal displayed on their device and makes a quick and appropriate proposal to the customer. When explaining the proposal to the customer, the user emphasizes the benefits and advantages of the proposal.

[0133] Input: Suggestions displayed on the device

[0134] Output: Proposal explanation to the customer

[0135] Specific example:

[0136] The user explains to the customer, "By switching to this 5G plan, your communication speed will dramatically improve, and with the unlimited data plan, you'll never have to worry about running out of data."

[0137] (Application Example 1)

[0138] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0139] Traditional proposal support systems based on customer information had the drawback of not adequately supporting employees in making quick and accurate proposals in person. Furthermore, there was a lack of support tools to enable new employees to make proposals on par with experienced staff, making it difficult to improve customer satisfaction. In addition, the generation and display of proposal content was inefficient, placing a heavy burden on employees.

[0140] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0141] In this invention, the server includes: data input means for receiving customer information and automatically generating appropriate suggestions based on the customer information; data analysis means for analyzing the customer information received from the data input means; suggestion generation means for generating suggestions based on the analysis results of the data analysis means; result display means for displaying the generated suggestions; means for inputting customer information using a smart device; means for generating analysis results using cloud service technology; means for analyzing customer data using a machine learning model; and means for displaying the generated suggestions on a wearable device. This enables even new employees to make suggestions efficiently and accurately, improving customer satisfaction and reducing the burden on employees.

[0142] "Customer information" refers to personal information and related data such as the customer's age, frequency of use, purchase history, and preferences.

[0143] "Data entry means" refers to devices or applications that provide an interface for collecting and inputting customer information.

[0144] "Data analysis means" refers to processing equipment or software used to perform analysis based on received customer information.

[0145] A "proposal generation system" is a system that has the function of automatically generating appropriate proposals for customers based on analysis results.

[0146] A "result display means" refers to a device or application that displays the generated suggestions in a format that the user can view.

[0147] A "smart device" is a portable electronic device with advanced functions, such as a smartphone, tablet, or smart glasses.

[0148] "Cloud service technology" refers to technologies and services that enable data storage, management, and analysis via the internet.

[0149] A "machine learning model" is a type of artificial intelligence that learns from large amounts of data and performs predictions and analyses.

[0150] A "wearable device" is an electronic device worn on the body and used for displaying or inputting information.

[0151] As a specific embodiment of this invention, a system is provided that inputs customer information, analyzes it, generates appropriate suggestions, and displays them. Details are described below.

[0152] System Overview

[0153] This system consists of the following main components:

[0154] 1. Data input means

[0155] 2. Data Analysis Methods

[0156] 3. Proposal generation means

[0157] 4. Results display means

[0158] 5. Means of inputting customer information using smart devices

[0159] 6. Means for generating analysis results using cloud service technology

[0160] 7. Means of analyzing customer data using machine learning models

[0161] 8. Means for displaying the generated suggestions on a wearable device.

[0162] Data input means

[0163] Users input customer information using smart devices such as smartphones and tablets. These input devices provide an interface that allows for the input of a wide range of customer information, including age, frequency of use, purchase history, and preferences.

[0164] Data analysis means

[0165] The server receives customer information transmitted from smart devices and analyzes it. During this process, it references past customer data and product information to perform more accurate analysis. Real-time analysis is possible by using cloud service technology. Specifically, cloud services such as Amazon Web Services (AWS®) are used.

[0166] Proposal generation means

[0167] The server generates optimal suggestions based on the analysis results obtained by the data analysis method. Using a generative AI model, it generates suggestions using prompt sentences like the following as input.

[0168] Customer: {'name': 'Taro Yamada', 'age': 28, 'usage': 'high', 'complaints': ['slow speed', 'insufficient data'], 'budget': 5000}

[0169] Analysis: {'recommended_plans': ['5G plan', 'unlimited data plan'], 'benefits': ['high-speed internet', 'no additional data required']}

[0170] Generate a sales proposal that includes plan names, prices, benefits, and any special offers.

[0171] The generative AI model used is OpenAI's GPT-3®.

[0172] Results display means

[0173] The server sends the generated suggestions to the smart device and displays them to the user. The suggestions can also be displayed on wearable devices (e.g., smart glasses), allowing users to explain things smoothly to customers. Specific display applications are developed using React Native and Unity.

[0174] Cloud service technology

[0175] The server performs analysis using cloud service technology. This enables the processing of large datasets and real-time analysis. An example of this is Amazon Web Services (AWS).

[0176] Machine learning models

[0177] The server analyzes customer data using machine learning models. This analysis enables the server to provide recommendations best suited to the customer's needs. Specifically, machine learning libraries such as scikit-learn and TENSORFLOW® are used.

[0178] Specific example

[0179] For example, suppose a user uses smart glasses to input customer information, and the analysis performed by a cloud service recommends a "5G plan" and an "unlimited data plan." Based on this information, a generative AI model creates a suggestion message which is displayed on the user's smartphone or smart glasses. This suggestion includes specific explanations such as, "Switching to the 5G plan will dramatically improve your communication speed, and the unlimited data plan will eliminate any worries about running out of data."

[0180] In this way, by using this system, even new employees can make proposals efficiently and accurately, leading to improved customer satisfaction and reduced workload for employees.

[0181] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0182] Step 1:

[0183] Users enter customer information using a smart device (smartphone or smart glasses). This involves entering a wide range of information into the device's input interface, including age, usage frequency, purchase history, preferences, dissatisfaction with communication speed, insufficient data capacity, and budget. The entered information is sent from the device to the server in JSON format.

[0184] Input: Customer information (age, frequency of use, purchase history, preferences, dissatisfaction with communication speed, insufficient data capacity, budget)

[0185] Output: Customer information data in JSON format

[0186] Operation: The terminal verifies the information entered by the user and then sends it to the server.

[0187] Step 2:

[0188] The server receives customer information sent from the terminal and begins data analysis using cloud service technology. Specifically, it uses Amazon Web Services (AWS) to analyze customer needs based on past customer data and product information. This analysis generates information to identify the most suitable plans and products for the customer's needs.

[0189] Input: Customer information data in JSON format

[0190] Output: Analysis results (list of candidate plans and products)

[0191] Operation: The server analyzes the received customer information on AWS and identifies candidate plans by referring to historical data and product information.

[0192] Step 3:

[0193] The server generates specific proposals using proposal generation means based on the analysis results obtained by the data analysis means. A generative AI model is utilized here. The server creates proposal statements based on the generative AI model (e.g., GPT-3) using the following prompt statements.

[0194] Customer: {'name': 'Taro Yamada', 'age': 28, 'usage': 'high', 'complaints': ['slow speed', 'insufficient data'], 'budget': 5000}

[0195] Analysis: {'recommended_plans': ['5G plan', 'unlimited data plan'], 'benefits': ['high-speed internet', 'no additional data required']}

[0196] Generate a sales proposal that includes plan names, prices, benefits, and any special offers.

[0197] Input: Analysis results (list of candidate plans and products) and prompt text

[0198] Output: Proposal (details of specific products or plans)

[0199] Operation: The server generates a prompt sentence based on the analysis results, inputs it into the generation AI model, and generates a suggested sentence.

[0200] Step 4:

[0201] The server sends the generated proposal text to the terminal and displays it to the user. Furthermore, the same proposal is also sent and displayed to a wearable device (smart glasses), enabling the user to smoothly make proposals to customers. The display application is developed using React Native and Unity.

[0202] Input: Proposal (details of specific products or plans)

[0203] Output: Suggestions displayed on the user terminal and wearable device screens.

[0204] Operation: The server sends the generated proposal text to the terminal and wearable device, and displays the proposal content.

[0205] These processing steps enable the system to quickly and accurately provide optimal suggestions based on customer information. This allows even new employees to make suggestions on par with experienced staff, thereby improving customer satisfaction.

[0206] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0207] System Overview

[0208] This invention is a powerful support system that enables even new crew members at the sales floor to propose appropriate smartphones and internet plans to customers, and further incorporates an emotion engine that recognizes user emotions. The system consists of the following main components:

[0209] 1. Data input means

[0210] 2. Data Analysis Methods

[0211] 3. Proposal generation means

[0212] 4. Results display means

[0213] 5. Emotional Engine

[0214] Data input means

[0215] The terminal provides a customer information input screen, allowing users to easily input information obtained from customers. Input fields include customer smartphone and internet usage, dissatisfaction with communication speed, insufficient data capacity, and budget.

[0216] Specific example:

[0217] The user logs into their device and enters customer information such as "slow internet speed" or "insufficient data capacity."

[0218] Emotional Engine

[0219] The device captures the user's voice and facial expressions and sends the data to the server. The server analyzes the emotions using an emotion engine and provides the analysis results to the data analysis means and the suggestion generation means. Through this process, suggestions that reflect the customer's emotional state are generated.

[0220] Specific example:

[0221] If a customer's facial expression indicates displeasure while listening to an explanation, the emotion engine provides this information as analytical data and generates suggestions for providing a more thorough explanation.

[0222] Data analysis means

[0223] The server receives customer information and sentiment data sent from the terminal and analyzes it. This analysis is performed by referencing past customer data and product information. This establishes criteria for identifying the optimal plan based on the customer's needs and emotional state.

[0224] Specific example:

[0225] The server analyzes data to recommend faster plans based on "dissatisfaction with communication speed" and unlimited plans or additional data purchase options based on "insufficient data capacity." It also prioritizes suggestions that help customers relax based on emotional data.

[0226] Proposal generation means

[0227] The server generates suggestions based on the analysis results. These suggestions include the plan name, price, features, benefits, and information based on the customer's emotional state.

[0228] Specific example:

[0229] The server generates specific proposals such as "5G plan" and "unlimited data plan," and adds explanations that take customer emotions into consideration.

[0230] Results display means

[0231] The server generates a proposal and sends it to the terminal, which then displays it to the user. Based on this proposal, the user can quickly make appropriate suggestions to the customer.

[0232] Specific example:

[0233] The user reviews the offer displayed on their device screen and explains to the customer, "If you switch to this 5G plan, your communication speed will dramatically improve, and you'll never have to worry about running out of data with the unlimited data plan. What do you think?"

[0234] Overall flow

[0235] In this system, the server automatically generates the optimal plan based on customer information and emotional data entered by new crew members. This allows new crew members to make suggestions on par with experienced employees, improving customer satisfaction and operational efficiency. Furthermore, the introduction of an emotional engine enables suggestions that take into account the customer's emotional state, leading to an even greater improvement in customer satisfaction.

[0236] The following describes the processing flow.

[0237] Step 1:

[0238] The device displays the login screen. The user enters their username and password and presses the login button. The device sends the entered authentication information to the server.

[0239] Step 2:

[0240] The server compares the received authentication information with the database. The server determines whether authentication was successful and sends the authentication result to the terminal. If the terminal successfully authenticates, it displays the data entry screen.

[0241] Step 3:

[0242] The terminal displays a customer information input screen. Input fields include the customer's smartphone and internet usage, dissatisfaction with communication speed, insufficient data capacity, and budget. The user then enters the customer information.

[0243] Step 4:

[0244] The user completes entering customer information and presses the submit button. The terminal then sends the entered customer information to the server.

[0245] Step 5:

[0246] The device captures the user's voice and facial expressions. The captured data is then sent to a server.

[0247] Step 6:

[0248] The server uses an emotion engine to analyze the received audio and facial expression data. This analysis identifies the user's emotional state (e.g., satisfaction, dissatisfaction, doubt, etc.).

[0249] Step 7:

[0250] The server passes customer information and sentiment data to the analysis module. Based on the customer's requests and sentiments, the server performs filtering to extract appropriate smartphone and internet plans. For example, if there is "dissatisfaction with communication speed," 5G plans will be prioritized over 4G plans, and if there is "insufficient data capacity," unlimited plans or additional data purchase options will be prioritized.

[0251] Step 8:

[0252] The server compares past customer data and product information to select the most suitable proposal. Furthermore, it selects proposals that take into account the user's emotional state. For example, if a customer is dissatisfied, it will propose a more attractive offer or additional services.

[0253] Step 9:

[0254] The server then selects the most suitable plan from the extracted options. This includes information such as the plan name, price, features, and special offers.

[0255] Step 10:

[0256] The server formats the generated proposals as a data package. The server then sends the proposal content to the terminal.

[0257] Step 11:

[0258] The device renders the received proposal content on the display screen. The user checks the device screen and shares the proposal content with the customer. For example, the user might explain, "If you switch to this 5G plan, your communication speed will dramatically improve, and with the unlimited data plan, you won't have to worry about running out of data." Depending on the customer's emotional state, additional information such as, "Furthermore, as part of a current sign-up campaign, the first month is free," may also be provided.

[0259] (Example 2)

[0260] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0261] Traditional sales support systems had a problem in that it was difficult for new crew members to propose appropriate smartphone and internet plans to customers. Furthermore, they were unable to make proposals that took into account the customer's emotional state, making it difficult to interact with customers and increasing the risk of decreased customer satisfaction. Therefore, there is a need for a system that allows even new crew members to effectively interact with customers and quickly make appropriate proposals that reflect the customer's emotional state.

[0262] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0263] In this invention, the server includes data input means for receiving customer information and automatically generating appropriate suggestions; emotion analysis means for transmitting customer information received from the data input means and emotion data captured from voice and facial expressions to the server; and data analysis means for analyzing the data transmitted by the emotion analysis means and generating optimal suggestions based on the customer's needs and emotional state. This makes it possible for even new crew members to make suggestions of the same quality as experienced ones, and furthermore, to make suggestions that reflect the customer's emotional state, thereby improving customer satisfaction.

[0264] "Data input means" refers to means for receiving customer information and automatically generating appropriate suggestions based on said customer information.

[0265] "Emotion analysis means" refers to a means of transmitting customer information received from data input means, as well as emotional data captured from voice and facial expressions, to a server.

[0266] "Data analysis means" refers to a means of analyzing data transmitted by emotion analysis means and generating optimal suggestions based on customer needs and emotional state.

[0267] "Proposal generation means" refers to means for generating proposals based on the analysis results of data analysis means.

[0268] "Result display means" refers to means for displaying the generated proposals.

[0269] "Customer information" refers to information such as the customer's smartphone and internet usage, dissatisfaction with communication speed, insufficient data capacity, and budget.

[0270] "Emotional data" refers to data captured from customers' voices and facial expressions.

[0271] A "server" is a computer system that includes data input means, sentiment analysis means, data analysis means, and proposal generation means.

[0272] System Overview

[0273] This invention is a powerful support system that enables even new crew members in sales to propose appropriate smartphones and internet plans to customers, and further incorporates an emotion engine that recognizes customer emotions. This system consists of the following main components.

[0274] 1. Data input means

[0275] 2. Emotion analysis method

[0276] 3. Data analysis means

[0277] 4. Proposal generation means

[0278] 5. Result display means

[0279] Data input means

[0280] The terminal provides a screen for the user to input customer information. The user inputs customer information on this screen. The input items include the usage status of the customer's smartphone and the Internet, dissatisfaction with communication speed, insufficient data capacity, budget, etc.

[0281] Specific example:

[0282] The user logs in to the terminal and inputs information such as "slow communication speed", "insufficient data capacity", and "monthly budget up to 5,000 yen". The input data is sent to the server.

[0283] Emotion analysis means

[0284] The terminal captures the voices and expressions of the user and the customer and sends them to the server. The server analyzes these data by means of an emotion engine and provides the analysis results to the data analysis means and the proposal generation means.

[0285] Specific example:

[0286] During the interaction between the user and the customer, the camera of the terminal captures the customer's expression in real time, and at the same time the microphone records the customer's voice. These data are sent to the server, and the emotion engine generates analysis results such as "the customer is dissatisfied" or "the customer is relaxed".

[0287] Data analysis means

[0288] The server receives customer information and sentiment data sent from the terminal and analyzes it. By referring to past customer data and product information, it identifies the optimal plan based on the customer's needs and emotional state.

[0289] Specific example:

[0290] The server will suggest a high-speed plan for complaints about slow internet speeds and an unlimited plan for complaints about insufficient data capacity. Furthermore, if the customer is unhappy, the server will prioritize offering suggestions with more detailed explanations.

[0291] Proposal generation means

[0292] The server generates specific suggestions based on the analysis results. These suggestions include the plan name, price, features, and special offers. They also include information based on the analyzed sentiment data.

[0293] Specific example:

[0294] The server generates suggestions such as "5G plan" and "unlimited data plan," and adds explanations such as, "This plan offers fast communication speeds, allowing you to watch videos without any issues."

[0295] Results display means

[0296] The server generates a proposal and sends it to the terminal, which then displays it to the user. Based on this proposal, the user can quickly and appropriately explain the proposal to the customer.

[0297] Specific example:

[0298] The user reviews the offer displayed on their device screen and explains to the customer, "Switching to a 5G plan will dramatically improve your communication speed, and with an unlimited data plan, you'll never have to worry about running out of data."

[0299] Examples of input prompts for a generative AI model

[0300] 1. Prompt sentence: "The customer is dissatisfied with the communication speed. Which plan should be proposed?"

[0301] 2. Prompt sentence: "The customer has a displeased expression during the explanation. How should we respond?"

[0302] This system aims to improve customer satisfaction because even new recruits can make high-quality proposals equivalent to those of experienced staff, and furthermore, it can make proposals that reflect the customer's emotional state.

[0303] The flow of the specific process in Example 2 will be described using FIG. 13.

[0304] Flow of the system program processing

[0305] Step 1:

[0306] The terminal provides a customer information input screen. The user logs in to the terminal and enters the customer's smartphone or Internet usage situation, dissatisfaction with the communication speed, lack of data capacity, budget, etc. The input data is sent from the terminal to the server.

[0307] Input: The customer's smartphone or Internet usage situation, dissatisfaction with the communication speed, lack of data capacity, budget, etc.

[0308] Data processing: Sorting and formatting of customer information

[0309] Output: Sorted customer information data

[0310] Step 2:

[0311] [[ID=4))4]]The terminal captures the voices and expressions of the user and the customer. This data is sent from the terminal to the server.

[0312] Input: Customer's voice, expression

[0313] Data processing: Audio recording, facial expression capture.

[0314] Output: Audio data, facial expression data

[0315] Step 3:

[0316] The server receives the data sent in Step 1 and Step 2. It integrates and analyzes the received customer information and sentiment data. It also refers to and analyzes past customer data and product information.

[0317] Input: Organized customer information data, voice data, facial expression data, historical customer data, product information

[0318] Data processing: Identifying customer needs, analyzing emotional states.

[0319] Output: Analysis results (identification of the optimal plan, evaluation of emotional state)

[0320] Step 4:

[0321] The server generates suggestions based on the analysis results. The generated suggestions include the plan name, price, features, and special offers, and also incorporate information based on the customer's emotional state.

[0322] Input: Analysis results (identification of the optimal plan, evaluation of emotional state)

[0323] Data processing: Assembling the proposal

[0324] Output: Generated proposals

[0325] Step 5:

[0326] The server generates a proposal and sends it to the terminal. The terminal displays this proposal to the user, who then uses the proposal to explain it to the customer.

[0327] Input: Generated proposal

[0328] Data processing: Converting the proposed content to a display format.

[0329] Output: Suggestions displayed on the user's device

[0330] Examples of specific prompt statements in processing steps

[0331] Example of a prompt:

[0332] Prompt 1: "The customer is dissatisfied with their internet speed. Which plan should I suggest?"

[0333] Prompt 2: "The customer is looking unhappy during the explanation. How should you respond?"

[0334] Through the steps described above, this system supports even rookie crew members in making high-quality suggestions comparable to those of experienced individuals, and further improves customer satisfaction by making suggestions that take into account the customer's emotional state.

[0335] (Application Example 2)

[0336] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0337] Traditional proposal systems made it difficult for new staff to make appropriate suggestions to customers, sometimes leading to decreased customer satisfaction. Furthermore, they failed to consider customer emotions when making suggestions, making it difficult to improve service quality. The lack of technology to acquire and instantly display customer and emotional information in real time was also a challenge.

[0338] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes a data input means for receiving customer information and automatically generating appropriate suggestions based on the customer information; a data analysis means for analyzing the customer information received from the data input means; a suggestion generation means for generating suggestions based on the analysis results of the data analysis means; a result display means for displaying the generated suggestions; an emotion engine for analyzing customer emotion information; a means for adjusting appropriate suggestions based on the emotion information analyzed by the emotion engine; and a means for acquiring and displaying customer information and emotion information in real time using smart glasses or a head-mounted display. As a result, even new staff members can make appropriate suggestions while considering customer emotions, which enables improved customer satisfaction and service quality.

[0339] "Customer information" refers to information such as the customer's smartphone usage, dissatisfaction with communication speed, insufficient data capacity, and budget.

[0340] "Data entry means" refers to a device or system for receiving and entering customer information.

[0341] "Data analysis means" refers to a device or system for analyzing received customer information and providing the results to the proposal generation means.

[0342] "Proposal generation means" refers to a device or system that generates appropriate proposals for customers based on the results of data analysis means.

[0343] "Result display means" refers to a device or system for displaying the generated proposals to users or customers.

[0344] An "emotion engine" is a device or system that analyzes customer emotional information and provides the results to data analysis means and proposal generation means.

[0345] "Smart glasses" are glasses-type devices that users wear and that can display information in real time.

[0346] A "head-mounted display" is a device that is worn by the user to display information within their field of vision.

[0347] Modes for carrying out the invention

[0348] This invention is a system for new staff members to make appropriate suggestions to customers, and it utilizes smart glasses or a head-mounted display to analyze customer emotional information and display the suggested content in real time.

[0349] Hardware and software configuration

[0350] 1. Hardware:

[0351] Smart glasses (e.g., Google Glass®)

[0352] Head-mounted displays (e.g., Microsoft HoloLens®)

[0353] 2. Software:

[0354] Face recognition software (e.g., OpenCV)

[0355] Speech recognition software (e.g., Google Cloud Speech-to-Text)

[0356] Database systems (e.g., MySQL (registered trademark))

[0357] Server-side applications (e.g., Node.js)

[0358] System programs and their processes

[0359] 1. Data entry means:

[0360] The server captures customer facial expressions using cameras in smart glasses or head-mounted displays, and records and transcribes customer requests and complaints via voice input. It also inputs specific information such as customer smartphone usage and budget. This information functions as a data entry tool.

[0361] 2. Emotional Engine:

[0362] The server uses facial recognition software and speech recognition software to analyze captured customer facial expression data in real time. The analyzed emotional information is transmitted to the server and provided to the data analysis means and the suggestion generation means.

[0363] 3. Data analysis methods:

[0364] The server sends the collected customer information and sentiment data to a database system for analysis. Based on past customer data and product information, it identifies the optimal plan that best suits the customer's needs.

[0365] 4. Proposal generation means:

[0366] Based on the analysis results, the server generates appropriate smartphone and internet plans. This recommendation includes details about pricing and services, as well as explanations that take sentiment analysis results into account.

[0367] 5. Results display means:

[0368] The suggested content is displayed in real time on smart glasses or a head-mounted display. Store staff can check the displayed content and make suggestions to customers.

[0369] Specific example

[0370] Consider a scenario where a customer visits a physical store. A staff member wears smart glasses or a head-mounted display, capturing the customer's facial expressions with a camera. Voice recognition software automatically transcribes the customer's requests and complaints, such as "the internet speed is slow" or "there isn't enough data," into text. The system sends this information to a server in real time for analysis by an emotion engine. Based on the analysis results, the system generates suggestions such as a "5G plan" or an "unlimited data plan" and displays them on the smart glasses. Staff members can review this information in real time and make appropriate suggestions to the customer.

[0371] Example of a prompt

[0372] Follow these steps to create your customer support application:

[0373] 1. Use smart glasses to capture the customer's facial expressions, record their voice, and transcribe it into text.

[0374] 2. Use the emotion engine to analyze customer emotions in real time.

[0375] 3. Send customer information and sentiment data to the server for analysis.

[0376] 4. Refer to past database records to identify the optimal smartphone and internet plan for you.

[0377] 5. Generate the proposal content and display it in real time on the smart glasses.

[0378] This allows even new staff members to make appropriate suggestions to customers, just like experienced staff, which is expected to improve customer satisfaction.

[0379] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0380] Program processing steps

[0381] Step 1:

[0382] The server uses cameras on smart glasses or head-mounted displays to capture the customer's facial expressions and acquire audio. The input consists of captured image and audio data, while the output consists of facial expression data analyzed by facial recognition software and audio data transcribed into text through speech recognition software. Specifically, facial recognition software is used to identify emotions from facial expressions, and speech recognition software is used to convert the customer's words into text data.

[0383] Step 2:

[0384] The server transmits captured facial expression and audio data to the emotion engine for real-time emotion analysis. The input is facial expression data and transcribed audio data, and the output is the analyzed emotion information. Specifically, the emotion engine determines the customer's emotional state from the facial expressions and audio and provides the result to the data analysis system.

[0385] Step 3:

[0386] The server transmits customer information received from the data input means and sentiment data obtained from the sentiment engine to the database system, where it performs analysis while referring to past customer data and product information. The input is customer information and sentiment data, and the output is the analysis results for identifying the optimal plan. Specifically, the database system searches for a plan that matches the customer's requests and past data, and provides the analysis results to the proposal generation means.

[0387] Step 4:

[0388] The server operates a suggestion generation system that generates appropriate suggestions based on the results of the data analysis system. The input is the results of the data analysis system, and the output is the generated suggestion content. Specifically, the suggestion generation system generates a plan that includes fees and service details, and adds explanatory text that takes the sentiment analysis results into account.

[0389] Step 5:

[0390] The server transmits the generated proposals to smart glasses or a head-mounted display in real time, activating the result display device. The input is the generated proposals, and the output is the proposals displayed on the smart glasses or head-mounted display. Specifically, the display device shows the proposals to the staff, who then review the information and make proposals to the customer.

[0391] Thus, in the processing steps of this system, customer information and sentiment data can be collected in real time through smart glasses or head-mounted displays, and based on this, optimal suggestions can be generated and displayed.

[0392] 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating 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.

[0393] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0394] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0395] [Second Embodiment]

[0396] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0397] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0398] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0399] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0400] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0401] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0402] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0403] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0404] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[0405] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0406] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0407] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. 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".

[0408] System Overview

[0409] As a form of implementing the invention, this system provides support to new crew members in the sales area, enabling them to propose appropriate smartphones and internet plans to customers. The system mainly consists of the following components:

[0410] 1. Data input means

[0411] 2. Data Analysis Methods

[0412] 3. Proposal generation means

[0413] 4. Results display means

[0414] Data input means

[0415] The terminal provides a customer information input screen. This allows users to easily input information obtained from customers. Input fields include the customer's smartphone and internet usage, dissatisfaction with communication speed, insufficient data capacity, budget, etc.

[0416] Specific example:

[0417] The user logs into their device and enters customer information such as "slow internet speed" or "insufficient data capacity."

[0418] Data analysis means

[0419] The server receives customer information sent from the terminal and analyzes it. This analysis involves referencing past customer data and product information. This establishes criteria for identifying the plan best suited to the customer's needs.

[0420] Specific example:

[0421] The server analyzes whether a user is dissatisfied with their internet speed and recommends a faster plan, or whether they are experiencing insufficient data capacity and should consider an unlimited plan or an option to purchase additional data.

[0422] Proposal generation means

[0423] The server generates a proposal based on the analysis results. This proposal includes specific information such as the plan name, price, features, and special offers.

[0424] Specific example:

[0425] The server generates specific proposals such as "5G plan" and "unlimited data plan," and adds related benefits and campaign information.

[0426] Results display means

[0427] The server generates a proposal and sends it to the terminal, which then displays it to the user. Based on this proposal, the user can quickly make appropriate suggestions to the customer.

[0428] Specific example:

[0429] The system then displays a suggestion on the user's device screen and explains to the customer, "Switching to this 5G plan will dramatically improve your communication speed, and with an unlimited data plan, you'll never have to worry about running out of data."

[0430] This system enables even new crew members to make suggestions on par with experienced employees, thereby improving customer satisfaction. Furthermore, automating the suggestion process reduces the burden on employees and streamlines the suggestion process.

[0431] The following describes the processing flow.

[0432] Step 1:

[0433] The device displays the login screen. The user enters their username and password and presses the login button. The device sends the entered authentication information to the server.

[0434] Step 2:

[0435] The server compares the received authentication information with the database. The server determines whether authentication was successful and sends the authentication result to the terminal. If the terminal successfully authenticates, it displays the data entry screen.

[0436] Step 3:

[0437] The terminal displays a customer information input screen. Input fields include the customer's smartphone and internet usage, dissatisfaction with communication speed, insufficient data capacity, and budget. The user then enters the customer information.

[0438] Step 4:

[0439] The user completes entering customer information and presses the submit button. The terminal then sends the entered customer information to the server.

[0440] Step 5:

[0441] The server passes the received customer information to a module for analysis. The server then filters the information to extract appropriate smartphone and internet plans based on the customer's requests. For example, if a customer is dissatisfied with their internet speed, the server will prioritize 5G plans over 4G plans.

[0442] Step 6:

[0443] The server compares past customer data and product information to select the most suitable recommendation. For example, if there is a "data capacity shortage," it will prioritize unlimited plans or additional data purchase options.

[0444] Step 7:

[0445] The server then selects the most suitable plan from the extracted options. This includes information such as the plan name, price, features, and special offers.

[0446] Step 8:

[0447] The server formats the generated proposals as a data package. The server then sends the proposal content to the terminal.

[0448] Step 9:

[0449] The device renders the received proposal content on the display screen. The user checks the device screen and shares the proposal content with the customer. For example, the user might explain, "Switching to this 5G plan will dramatically improve communication speed, and with the unlimited data plan, you won't have to worry about running out of data."

[0450] (Example 1)

[0451] Next, we will describe Example 1. 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".

[0452] Traditional customer service presented challenges, particularly for new employees, in proposing appropriate communication plans to customers. Furthermore, inconsistencies in the quality and speed of proposals led to decreased customer satisfaction and increased workload for employees.

[0453] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0454] In this invention, the server includes an input means for receiving customer information and automatically generating appropriate suggestions based on the customer information, an analysis means for analyzing the customer information received from the input means, and a generation means for generating suggestions based on the analysis results of the analysis means. This makes it possible for new employees to make suggestions equivalent to those of experienced employees, thereby improving customer satisfaction and reducing the burden on employees.

[0455] An "input method" is a means of receiving customer information and inputting it into the system.

[0456] "Analysis means" refers to means for analyzing customer information received from input means and evaluating data based on the analysis results.

[0457] "Generation means" refers to means for generating appropriate proposals based on the analysis results of the analysis means.

[0458] "Display means" refers to means for displaying the proposals generated by the generation means to the user.

[0459] A "customer database" is a database that stores past customer information.

[0460] "Product information" refers to information about the products handled by the system.

[0461] "Filtering" is the process of selecting from multiple proposals based on specific criteria.

[0462] "The optimal proposal" refers to the proposal that best suits the customer's needs.

[0463] "Analysis results" refer to the results of the analysis tool's evaluation of customer information received from the input tool.

[0464] As a form of implementing the invention, this system provides support to new employees in the sales area to help them propose appropriate smartphones and internet plans to customers. The system mainly consists of the following components:

[0465] 1. Input Method (Terminal): The terminal provides an input screen for receiving customer information. Users can use this screen to input information such as their smartphone and internet usage, dissatisfaction with communication speed, insufficient data capacity, and budget. A specific example is a user logging into the terminal and inputting information such as "slow communication speed" or "insufficient data capacity."

[0466] 2. Analysis Method (Server): The server receives customer information transmitted from the terminal. The received information is analyzed by the server. In this process, the server refers to past customer databases and product information to set criteria for identifying the plan best suited to the customer's needs. For example, the server might analyze a faster communication speed plan for "dissatisfaction with communication speed" and an unlimited plan or additional data purchase option for "insufficient data capacity."

[0467] 3. Generation Method (Server): Based on the analysis results, the server generates proposals. These proposals include specific information such as plan name, price, features, and special offers. For example, the server generates specific proposals such as "5G plan" and "unlimited data plan," and adds related benefits and campaign information.

[0468] 4. Display means (terminal): The generated proposal content is sent to the terminal, which displays it to the user. Based on this proposal content, the user can make quick and appropriate proposals to the customer. For example, the user could explain to the customer, "If you switch to this 5G plan, your communication speed will dramatically improve, and with the unlimited data plan, you won't have to worry about running out of data."

[0469] Example of a prompt

[0470] "Please propose the best internet plan for a customer who is dissatisfied with their current internet speed and lacks sufficient data capacity. The budget is within ¥XX."

[0471] This system enables even new employees to make proposals on par with experienced employees, thereby improving customer satisfaction. Furthermore, automating the proposal process reduces the burden on employees and streamlines the proposal process.

[0472] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0473] System program processing flow

[0474] Step 1:

[0475] The user operates the terminal and enters customer information. Specifically, information such as the customer's smartphone and internet usage, dissatisfaction with communication speed, insufficient data capacity, and budget is collected through the terminal's input screen. The entered information is then organized for data processing.

[0476] Input: Customer information (e.g., dissatisfaction with communication speed, insufficient data capacity)

[0477] Output: Organized customer information

[0478] Specific example:

[0479] The user logs into their device and enters information such as "the internet speed is slow" or "there isn't enough data."

[0480] Step 2:

[0481] The terminal sends the entered customer information to the server. This transmission is encrypted for security reasons. The server stores the received information in its database.

[0482] Input: Organized customer information

[0483] Output: Customer information sent to the server

[0484] Specific example:

[0485] The terminal encrypts customer information and sends it to the server.

[0486] Step 3:

[0487] The server analyzes the customer information it receives. This analysis involves referencing past customer databases and product information to establish criteria for identifying the best plan to meet the customer's needs.

[0488] Input: Customer information sent to the server

[0489] Output: Criteria based on customer needs (after data processing)

[0490] Specific example:

[0491] The server analyzes and matches "dissatisfaction with communication speed" with plans offering faster communication speeds, and "insufficient data capacity" with unlimited plans or additional data purchase options.

[0492] Step 4:

[0493] The server generates a proposal based on the analysis results. This proposal includes specific information such as the plan name, price, features, and special offers. The generated proposal is then saved back to the database.

[0494] Input: Criteria based on analyzed customer needs

[0495] Output: Generated proposals

[0496] Specific example:

[0497] The server generates specific proposals such as "5G plan" and "unlimited data plan," and adds related benefits and campaign information.

[0498] Step 5:

[0499] The server generates a proposal and sends it to the terminal, which then displays it to the user. The user reviews the displayed proposal and explains it to the customer.

[0500] Input: Generated suggestion content

[0501] Output: Suggestions displayed on the terminal

[0502] Specific example:

[0503] The server sends the generated suggestions to the terminal, and the terminal displays the content on the user's screen.

[0504] Step 6:

[0505] The user reviews the proposal displayed on their device and makes a quick and appropriate proposal to the customer. When explaining the proposal to the customer, the user emphasizes the benefits and advantages of the proposal.

[0506] Input: Suggestions displayed on the device

[0507] Output: Proposal explanation to the customer

[0508] Specific example:

[0509] The user explains to the customer, "By switching to this 5G plan, your communication speed will dramatically improve, and with the unlimited data plan, you'll never have to worry about running out of data."

[0510] (Application Example 1)

[0511] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0512] Traditional proposal support systems based on customer information had the drawback of not adequately supporting employees in making quick and accurate proposals in person. Furthermore, there was a lack of support tools to enable new employees to make proposals on par with experienced staff, making it difficult to improve customer satisfaction. In addition, the generation and display of proposal content was inefficient, placing a heavy burden on employees.

[0513] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0514] In this invention, the server includes: data input means for receiving customer information and automatically generating appropriate suggestions based on the customer information; data analysis means for analyzing the customer information received from the data input means; suggestion generation means for generating suggestions based on the analysis results of the data analysis means; result display means for displaying the generated suggestions; means for inputting customer information using a smart device; means for generating analysis results using cloud service technology; means for analyzing customer data using a machine learning model; and means for displaying the generated suggestions on a wearable device. This enables even new employees to make suggestions efficiently and accurately, improving customer satisfaction and reducing the burden on employees.

[0515] "Customer information" refers to personal information and related data such as the customer's age, frequency of use, purchase history, and preferences.

[0516] "Data entry means" refers to devices or applications that provide an interface for collecting and inputting customer information.

[0517] "Data analysis means" refers to processing equipment or software used to perform analysis based on received customer information.

[0518] A "proposal generation system" is a system that has the function of automatically generating appropriate proposals for customers based on analysis results.

[0519] A "result display means" refers to a device or application that displays the generated suggestions in a format that the user can view.

[0520] A "smart device" is a portable electronic device with advanced functions, such as a smartphone, tablet, or smart glasses.

[0521] "Cloud service technology" refers to technologies and services that enable data storage, management, and analysis via the internet.

[0522] A "machine learning model" is a type of artificial intelligence that learns from large amounts of data and performs predictions and analyses.

[0523] A "wearable device" is an electronic device worn on the body and used for displaying or inputting information.

[0524] As a specific embodiment of this invention, a system is provided that inputs customer information, analyzes it, generates appropriate suggestions, and displays them. Details are described below.

[0525] System Overview

[0526] This system consists of the following main components:

[0527] 1. Data input means

[0528] 2. Data Analysis Methods

[0529] 3. Proposal generation means

[0530] 4. Results display means

[0531] 5. Means of inputting customer information using smart devices

[0532] 6. Means for generating analysis results using cloud service technology

[0533] 7. Means of analyzing customer data using machine learning models

[0534] 8. Means for displaying the generated suggestions on a wearable device.

[0535] Data input means

[0536] Users input customer information using smart devices such as smartphones and tablets. These input devices provide an interface that allows for the input of a wide range of customer information, including age, frequency of use, purchase history, and preferences.

[0537] Data analysis means

[0538] The server receives customer information transmitted from smart devices and analyzes it. During this process, it references past customer data and product information to perform more accurate analysis. Cloud service technology enables real-time analysis. Specifically, cloud services such as Amazon Web Services (AWS) are used.

[0539] Proposal generation means

[0540] The server generates optimal suggestions based on the analysis results obtained by the data analysis method. Using a generative AI model, it generates suggestions using prompt sentences like the following as input.

[0541] Customer: {'name': 'Taro Yamada', 'age': 28, 'usage': 'high', 'complaints': ['slow speed', 'insufficient data'], 'budget': 5000}

[0542] Analysis: {'recommended_plans': ['5G plan', 'unlimited data plan'], 'benefits': ['high-speed internet', 'no additional data required']}

[0543] Generate a sales proposal that includes plan names, prices, benefits, and any special offers.

[0544] The generative AI model used is OpenAI's GPT-3.

[0545] Results display means

[0546] The server sends the generated suggestions to the smart device and displays them to the user. The suggestions can also be displayed on wearable devices (e.g., smart glasses), allowing users to explain things smoothly to customers. Specific display applications are developed using React Native and Unity.

[0547] Cloud service technology

[0548] The server performs analysis using cloud service technology. This enables the processing of large datasets and real-time analysis. An example of this is Amazon Web Services (AWS).

[0549] Machine learning models

[0550] The server analyzes customer data using machine learning models. This analysis enables the server to provide recommendations best suited to the customer's needs. Specifically, machine learning libraries such as scikit-learn and TensorFlow are used.

[0551] Specific example

[0552] For example, suppose a user uses smart glasses to input customer information, and the analysis performed by a cloud service recommends a "5G plan" and an "unlimited data plan." Based on this information, a generative AI model creates a suggestion message which is displayed on the user's smartphone or smart glasses. This suggestion includes specific explanations such as, "Switching to the 5G plan will dramatically improve your communication speed, and the unlimited data plan will eliminate any worries about running out of data."

[0553] In this way, by using this system, even new employees can make proposals efficiently and accurately, leading to improved customer satisfaction and reduced workload for employees.

[0554] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0555] Step 1:

[0556] Users enter customer information using a smart device (smartphone or smart glasses). This involves entering a wide range of information into the device's input interface, including age, usage frequency, purchase history, preferences, dissatisfaction with communication speed, insufficient data capacity, and budget. The entered information is sent from the device to the server in JSON format.

[0557] Input: Customer information (age, frequency of use, purchase history, preferences, dissatisfaction with communication speed, insufficient data capacity, budget)

[0558] Output: Customer information data in JSON format

[0559] Operation: The terminal verifies the information entered by the user and then sends it to the server.

[0560] Step 2:

[0561] The server receives customer information sent from the terminal and begins data analysis using cloud service technology. Specifically, it uses Amazon Web Services (AWS) to analyze customer needs based on past customer data and product information. This analysis generates information to identify the most suitable plans and products for the customer's needs.

[0562] Input: Customer information data in JSON format

[0563] Output: Analysis results (list of candidate plans and products)

[0564] Operation: The server analyzes the received customer information on AWS and identifies candidate plans by referring to historical data and product information.

[0565] Step 3:

[0566] The server generates specific proposals using proposal generation means based on the analysis results obtained by the data analysis means. A generative AI model is utilized here. The server creates proposal statements based on the generative AI model (e.g., GPT-3) using the following prompt statements.

[0567] Customer: {'name': 'Taro Yamada', 'age': 28, 'usage': 'high', 'complaints': ['slow speed', 'insufficient data'], 'budget': 5000}

[0568] Analysis: {'recommended_plans': ['5G plan', 'unlimited data plan'], 'benefits': ['high-speed internet', 'no additional data required']}

[0569] Generate a sales proposal that includes plan names, prices, benefits, and any special offers.

[0570] Input: Analysis results (list of candidate plans and products) and prompt text

[0571] Output: Proposal (details of specific products or plans)

[0572] Operation: The server generates a prompt sentence based on the analysis results, inputs it into the generation AI model, and generates a suggested sentence.

[0573] Step 4:

[0574] The server sends the generated proposal text to the terminal and displays it to the user. Furthermore, the same proposal is also sent and displayed to a wearable device (smart glasses), enabling the user to smoothly make proposals to customers. The display application is developed using React Native and Unity.

[0575] Input: Proposal (details of specific products or plans)

[0576] Output: Suggestions displayed on the user terminal and wearable device screens.

[0577] Operation: The server sends the generated proposal text to the terminal and wearable device, and displays the proposal content.

[0578] These processing steps enable the system to quickly and accurately provide optimal suggestions based on customer information. This allows even new employees to make suggestions on par with experienced staff, thereby improving customer satisfaction.

[0579] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0580] System Overview

[0581] This invention is a powerful support system that enables even new crew members at the sales floor to propose appropriate smartphones and internet plans to customers, and further incorporates an emotion engine that recognizes user emotions. The system consists of the following main components:

[0582] 1. Data input means

[0583] 2. Data Analysis Methods

[0584] 3. Proposal generation means

[0585] 4. Results display means

[0586] 5. Emotional Engine

[0587] Data input means

[0588] The terminal provides a customer information input screen, allowing users to easily input information obtained from customers. Input fields include customer smartphone and internet usage, dissatisfaction with communication speed, insufficient data capacity, and budget.

[0589] Specific example:

[0590] The user logs into their device and enters customer information such as "slow internet speed" or "insufficient data capacity."

[0591] Emotional Engine

[0592] The device captures the user's voice and facial expressions and sends the data to the server. The server analyzes the emotions using an emotion engine and provides the analysis results to the data analysis means and the suggestion generation means. Through this process, suggestions that reflect the customer's emotional state are generated.

[0593] Specific example:

[0594] If a customer's facial expression indicates displeasure while listening to an explanation, the emotion engine provides this information as analytical data and generates suggestions for providing a more thorough explanation.

[0595] Data analysis means

[0596] The server receives customer information and sentiment data sent from the terminal and analyzes it. This analysis is performed by referencing past customer data and product information. This establishes criteria for identifying the optimal plan based on the customer's needs and emotional state.

[0597] Specific example:

[0598] The server analyzes data to recommend faster plans based on "dissatisfaction with communication speed" and unlimited plans or additional data purchase options based on "insufficient data capacity." It also prioritizes suggestions that help customers relax based on emotional data.

[0599] Proposal generation means

[0600] The server generates suggestions based on the analysis results. These suggestions include the plan name, price, features, benefits, and information based on the customer's emotional state.

[0601] Specific example:

[0602] The server generates specific proposals such as "5G plan" and "unlimited data plan," and adds explanations that take customer emotions into consideration.

[0603] Results display means

[0604] The server generates a proposal and sends it to the terminal, which then displays it to the user. Based on this proposal, the user can quickly make appropriate suggestions to the customer.

[0605] Specific example:

[0606] The user reviews the offer displayed on their device screen and explains to the customer, "If you switch to this 5G plan, your communication speed will dramatically improve, and you'll never have to worry about running out of data with the unlimited data plan. What do you think?"

[0607] Overall flow

[0608] In this system, the server automatically generates the optimal plan based on customer information and emotional data entered by new crew members. This allows new crew members to make suggestions on par with experienced employees, improving customer satisfaction and operational efficiency. Furthermore, the introduction of an emotional engine enables suggestions that take into account the customer's emotional state, leading to an even greater improvement in customer satisfaction.

[0609] The following describes the processing flow.

[0610] Step 1:

[0611] The device displays the login screen. The user enters their username and password and presses the login button. The device sends the entered authentication information to the server.

[0612] Step 2:

[0613] The server compares the received authentication information with the database. The server determines whether authentication was successful and sends the authentication result to the terminal. If the terminal successfully authenticates, it displays the data entry screen.

[0614] Step 3:

[0615] The terminal displays a customer information input screen. Input fields include the customer's smartphone and internet usage, dissatisfaction with communication speed, insufficient data capacity, and budget. The user then enters the customer information.

[0616] Step 4:

[0617] The user completes entering customer information and presses the submit button. The terminal then sends the entered customer information to the server.

[0618] Step 5:

[0619] The device captures the user's voice and facial expressions. The captured data is then sent to a server.

[0620] Step 6:

[0621] The server uses an emotion engine to analyze the received audio and facial expression data. This analysis identifies the user's emotional state (e.g., satisfaction, dissatisfaction, doubt, etc.).

[0622] Step 7:

[0623] The server passes customer information and sentiment data to the analysis module. Based on the customer's requests and sentiments, the server performs filtering to extract appropriate smartphone and internet plans. For example, if there is "dissatisfaction with communication speed," 5G plans will be prioritized over 4G plans, and if there is "insufficient data capacity," unlimited plans or additional data purchase options will be prioritized.

[0624] Step 8:

[0625] The server compares past customer data and product information to select the most suitable proposal. Furthermore, it selects proposals that take into account the user's emotional state. For example, if a customer is dissatisfied, it will propose a more attractive offer or additional services.

[0626] Step 9:

[0627] The server then selects the most suitable plan from the extracted options. This includes information such as the plan name, price, features, and special offers.

[0628] Step 10:

[0629] The server formats the generated proposals as a data package. The server then sends the proposal content to the terminal.

[0630] Step 11:

[0631] The device renders the received proposal content on the display screen. The user checks the device screen and shares the proposal content with the customer. For example, the user might explain, "If you switch to this 5G plan, your communication speed will dramatically improve, and with the unlimited data plan, you won't have to worry about running out of data." Depending on the customer's emotional state, additional information such as, "Furthermore, as part of a current sign-up campaign, the first month is free," may also be provided.

[0632] (Example 2)

[0633] Next, we will describe Example 2. 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".

[0634] Traditional sales support systems had a problem in that it was difficult for new crew members to propose appropriate smartphone and internet plans to customers. Furthermore, they were unable to make proposals that took into account the customer's emotional state, making it difficult to interact with customers and increasing the risk of decreased customer satisfaction. Therefore, there is a need for a system that allows even new crew members to effectively interact with customers and quickly make appropriate proposals that reflect the customer's emotional state.

[0635] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0636] In this invention, the server includes data input means for receiving customer information and automatically generating appropriate suggestions; emotion analysis means for transmitting customer information received from the data input means and emotion data captured from voice and facial expressions to the server; and data analysis means for analyzing the data transmitted by the emotion analysis means and generating optimal suggestions based on the customer's needs and emotional state. This makes it possible for even new crew members to make suggestions of the same quality as experienced ones, and furthermore, to make suggestions that reflect the customer's emotional state, thereby improving customer satisfaction.

[0637] "Data input means" refers to means for receiving customer information and automatically generating appropriate suggestions based on said customer information.

[0638] "Emotion analysis means" refers to a means of transmitting customer information received from data input means, as well as emotional data captured from voice and facial expressions, to a server.

[0639] "Data analysis means" refers to a means of analyzing data transmitted by emotion analysis means and generating optimal suggestions based on customer needs and emotional state.

[0640] "Proposal generation means" refers to means for generating proposals based on the analysis results of data analysis means.

[0641] "Result display means" refers to means for displaying the generated proposals.

[0642] "Customer information" refers to information such as the customer's smartphone and internet usage, dissatisfaction with communication speed, insufficient data capacity, and budget.

[0643] "Emotional data" refers to data captured from customers' voices and facial expressions.

[0644] A "server" is a computer system that includes data input means, sentiment analysis means, data analysis means, and proposal generation means.

[0645] System Overview

[0646] This invention is a powerful support system that enables even new crew members in sales to propose appropriate smartphones and internet plans to customers, and further incorporates an emotion engine that recognizes customer emotions. This system consists of the following main components.

[0647] 1. Data input means

[0648] 2. Emotion analysis method

[0649] 3. Data Analysis Methods

[0650] 4. Proposal generation means

[0651] 5. Results display means

[0652] Data input means

[0653] The terminal provides a screen for entering customer information. The user enters customer information on this screen. Input fields include the customer's smartphone and internet usage, dissatisfaction with communication speed, insufficient data capacity, budget, etc.

[0654] Specific example:

[0655] The user logs into their device and enters information such as "slow internet speed," "insufficient data capacity," and "monthly budget of up to 5000 yen." This entered data is then sent to the server.

[0656] Emotion analysis means

[0657] The terminal captures the voice and facial expressions of users and customers and transmits them to the server. The server analyzes this data using an emotion engine and provides the analysis results to the data analysis means and the suggestion generation means.

[0658] Specific example:

[0659] While the user interacts with a customer, the device's camera captures the customer's facial expressions in real time, and the microphone simultaneously records the customer's voice. This data is sent to a server, where an emotion engine generates analysis results such as "the customer is unhappy" or "the customer is relaxed."

[0660] Data analysis means

[0661] The server receives customer information and sentiment data sent from the terminal and analyzes it. By referring to past customer data and product information, it identifies the optimal plan based on the customer's needs and emotional state.

[0662] Specific example:

[0663] The server will suggest a high-speed plan for complaints about slow internet speeds and an unlimited plan for complaints about insufficient data capacity. Furthermore, if the customer is unhappy, the server will prioritize offering suggestions with more detailed explanations.

[0664] Proposal generation means

[0665] The server generates specific suggestions based on the analysis results. These suggestions include the plan name, price, features, and special offers. They also include information based on the analyzed sentiment data.

[0666] Specific example:

[0667] The server generates suggestions such as "5G plan" and "unlimited data plan," and adds explanations such as, "This plan offers fast communication speeds, allowing you to watch videos without any issues."

[0668] Results display means

[0669] The server generates a proposal and sends it to the terminal, which then displays it to the user. Based on this proposal, the user can quickly and appropriately explain the proposal to the customer.

[0670] Specific example:

[0671] The user reviews the offer displayed on their device screen and explains to the customer, "Switching to a 5G plan will dramatically improve your communication speed, and with an unlimited data plan, you'll never have to worry about running out of data."

[0672] Examples of input prompts for a generative AI model

[0673] 1. Prompt: "The customer is dissatisfied with their internet speed. Which plan should I suggest?"

[0674] 2. Prompt: "The customer is looking unhappy during the explanation. How should you respond?"

[0675] This system aims to improve customer satisfaction by enabling even rookie crew members to make high-quality suggestions on par with experienced staff, and by allowing them to make suggestions that reflect the customer's emotional state.

[0676] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0677] System program processing flow

[0678] Step 1:

[0679] The terminal provides a customer information input screen. The user logs into the terminal and inputs information such as the customer's smartphone and internet usage, dissatisfaction with communication speed, insufficient data capacity, and budget. The input data is sent from the terminal to the server.

[0680] Input: Customer's smartphone and internet usage, dissatisfaction with communication speed, insufficient data capacity, budget, etc.

[0681] Data processing: Organizing and formatting customer information

[0682] Output: Organized customer information data

[0683] Step 2:

[0684] The device captures the voice and facial expressions of users and customers. This data is then transmitted from the device to the server.

[0685] Input: Customer's voice, facial expressions

[0686] Data processing: Audio recording, facial expression capture.

[0687] Output: Audio data, facial expression data

[0688] Step 3:

[0689] The server receives the data sent in Step 1 and Step 2. It integrates and analyzes the received customer information and sentiment data. It also refers to and analyzes past customer data and product information.

[0690] Input: Organized customer information data, voice data, facial expression data, historical customer data, product information

[0691] Data processing: Identifying customer needs, analyzing emotional states.

[0692] Output: Analysis results (identification of the optimal plan, evaluation of emotional state)

[0693] Step 4:

[0694] The server generates suggestions based on the analysis results. The generated suggestions include the plan name, price, features, and special offers, and also incorporate information based on the customer's emotional state.

[0695] Input: Analysis results (identification of the optimal plan, evaluation of emotional state)

[0696] Data processing: Assembling the proposal

[0697] Output: Generated proposals

[0698] Step 5:

[0699] The server generates a proposal and sends it to the terminal. The terminal displays this proposal to the user, who then uses the proposal to explain it to the customer.

[0700] Input: Generated proposal

[0701] Data processing: Converting the proposed content to a display format.

[0702] Output: Suggestions displayed on the user's device

[0703] Examples of specific prompt statements in processing steps

[0704] Example of a prompt:

[0705] Prompt 1: "The customer is dissatisfied with their internet speed. Which plan should I suggest?"

[0706] Prompt 2: "The customer is looking unhappy during the explanation. How should you respond?"

[0707] Through the steps described above, this system supports even rookie crew members in making high-quality suggestions comparable to those of experienced individuals, and further improves customer satisfaction by making suggestions that take into account the customer's emotional state.

[0708] (Application Example 2)

[0709] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0710] Traditional proposal systems made it difficult for new staff to make appropriate suggestions to customers, sometimes leading to decreased customer satisfaction. Furthermore, they failed to consider customer emotions when making suggestions, making it difficult to improve service quality. The lack of technology to acquire and instantly display customer and emotional information in real time was also a challenge.

[0711] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes a data input means for receiving customer information and automatically generating appropriate suggestions based on the customer information; a data analysis means for analyzing the customer information received from the data input means; a suggestion generation means for generating suggestions based on the analysis results of the data analysis means; a result display means for displaying the generated suggestions; an emotion engine for analyzing customer emotion information; a means for adjusting appropriate suggestions based on the emotion information analyzed by the emotion engine; and a means for acquiring and displaying customer information and emotion information in real time using smart glasses or a head-mounted display. As a result, even new staff members can make appropriate suggestions while considering customer emotions, which enables improved customer satisfaction and service quality.

[0712] "Customer information" refers to information such as the customer's smartphone usage, dissatisfaction with communication speed, insufficient data capacity, and budget.

[0713] "Data entry means" refers to a device or system for receiving and entering customer information.

[0714] "Data analysis means" refers to a device or system for analyzing received customer information and providing the results to the proposal generation means.

[0715] "Proposal generation means" refers to a device or system that generates appropriate proposals for customers based on the results of data analysis means.

[0716] "Result display means" refers to a device or system for displaying the generated proposals to users or customers.

[0717] An "emotion engine" is a device or system that analyzes customer emotional information and provides the results to data analysis means and proposal generation means.

[0718] "Smart glasses" are glasses-type devices that users wear and that can display information in real time.

[0719] A "head-mounted display" is a device that is worn by the user to display information within their field of vision.

[0720] Modes for carrying out the invention

[0721] This invention is a system for new staff members to make appropriate suggestions to customers, and it utilizes smart glasses or a head-mounted display to analyze customer emotional information and display the suggested content in real time.

[0722] Hardware and software configuration

[0723] 1. Hardware:

[0724] Smart glasses (e.g., Google Glass)

[0725] Head-mounted display (e.g., Microsoft HoloLens)

[0726] 2. Software:

[0727] Face recognition software (e.g., OpenCV)

[0728] Speech recognition software (e.g., Google Cloud Speech-to-Text)

[0729] Database system (e.g., MySQL)

[0730] Server-side applications (e.g., Node.js)

[0731] System programs and their processes

[0732] 1. Data entry means:

[0733] The server captures customer facial expressions using cameras in smart glasses or head-mounted displays, and records and transcribes customer requests and complaints via voice input. It also inputs specific information such as customer smartphone usage and budget. This information functions as a data entry tool.

[0734] 2. Emotional Engine:

[0735] The server uses facial recognition software and speech recognition software to analyze captured customer facial expression data in real time. The analyzed emotional information is transmitted to the server and provided to the data analysis means and the suggestion generation means.

[0736] 3. Data analysis methods:

[0737] The server sends the collected customer information and sentiment data to a database system for analysis. Based on past customer data and product information, it identifies the optimal plan that best suits the customer's needs.

[0738] 4. Proposal generation means:

[0739] Based on the analysis results, the server generates appropriate smartphone and internet plans. This recommendation includes details about pricing and services, as well as explanations that take sentiment analysis results into account.

[0740] 5. Results display means:

[0741] The suggested content is displayed in real time on smart glasses or a head-mounted display. Store staff can check the displayed content and make suggestions to customers.

[0742] Specific example

[0743] Consider a scenario where a customer visits a physical store. A staff member wears smart glasses or a head-mounted display, capturing the customer's facial expressions with a camera. Voice recognition software automatically transcribes the customer's requests and complaints, such as "the internet speed is slow" or "there isn't enough data," into text. The system sends this information to a server in real time for analysis by an emotion engine. Based on the analysis results, the system generates suggestions such as a "5G plan" or an "unlimited data plan" and displays them on the smart glasses. Staff members can review this information in real time and make appropriate suggestions to the customer.

[0744] Example of a prompt

[0745] Follow these steps to create your customer support application:

[0746] 1. Use smart glasses to capture the customer's facial expressions, record their voice, and transcribe it into text.

[0747] 2. Use the emotion engine to analyze customer emotions in real time.

[0748] 3. Send customer information and sentiment data to the server for analysis.

[0749] 4. Refer to past database records to identify the optimal smartphone and internet plan for you.

[0750] 5. Generate the proposal content and display it in real time on the smart glasses.

[0751] This allows even new staff members to make appropriate suggestions to customers, just like experienced staff, which is expected to improve customer satisfaction.

[0752] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0753] Program processing steps

[0754] Step 1:

[0755] The server uses cameras on smart glasses or head-mounted displays to capture the customer's facial expressions and acquire audio. The input consists of captured image and audio data, while the output consists of facial expression data analyzed by facial recognition software and audio data transcribed into text through speech recognition software. Specifically, facial recognition software is used to identify emotions from facial expressions, and speech recognition software is used to convert the customer's words into text data.

[0756] Step 2:

[0757] The server transmits captured facial expression and audio data to the emotion engine for real-time emotion analysis. The input is facial expression data and transcribed audio data, and the output is the analyzed emotion information. Specifically, the emotion engine determines the customer's emotional state from the facial expressions and audio and provides the result to the data analysis system.

[0758] Step 3:

[0759] The server transmits customer information received from the data input means and sentiment data obtained from the sentiment engine to the database system, where it performs analysis while referring to past customer data and product information. The input is customer information and sentiment data, and the output is the analysis results for identifying the optimal plan. Specifically, the database system searches for a plan that matches the customer's requests and past data, and provides the analysis results to the proposal generation means.

[0760] Step 4:

[0761] The server operates a suggestion generation system that generates appropriate suggestions based on the results of the data analysis system. The input is the results of the data analysis system, and the output is the generated suggestion content. Specifically, the suggestion generation system generates a plan that includes fees and service details, and adds explanatory text that takes the sentiment analysis results into account.

[0762] Step 5:

[0763] The server transmits the generated proposals to smart glasses or a head-mounted display in real time, activating the result display device. The input is the generated proposals, and the output is the proposals displayed on the smart glasses or head-mounted display. Specifically, the display device shows the proposals to the staff, who then review the information and make proposals to the customer.

[0764] Thus, in the processing steps of this system, customer information and sentiment data can be collected in real time through smart glasses or head-mounted displays, and based on this, optimal suggestions can be generated and displayed.

[0765] 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0766] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0767] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0768] [Third Embodiment]

[0769] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0770] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0771] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0772] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0773] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0774] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0775] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0776] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0777] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[0778] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0779] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0780] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0781] System Overview

[0782] As a form of implementing the invention, this system provides support to new crew members in the sales area, enabling them to propose appropriate smartphones and internet plans to customers. The system mainly consists of the following components:

[0783] 1. Data input means

[0784] 2. Data Analysis Methods

[0785] 3. Proposal generation means

[0786] 4. Results display means

[0787] Data input means

[0788] The terminal provides a customer information input screen. This allows users to easily input information obtained from customers. Input fields include the customer's smartphone and internet usage, dissatisfaction with communication speed, insufficient data capacity, budget, etc.

[0789] Specific example:

[0790] The user logs into their device and enters customer information such as "slow internet speed" or "insufficient data capacity."

[0791] Data analysis means

[0792] The server receives customer information sent from the terminal and analyzes it. This analysis involves referencing past customer data and product information. This establishes criteria for identifying the plan best suited to the customer's needs.

[0793] Specific example:

[0794] The server analyzes whether a user is dissatisfied with their internet speed and recommends a faster plan, or whether they are experiencing insufficient data capacity and should consider an unlimited plan or an option to purchase additional data.

[0795] Proposal generation means

[0796] The server generates a proposal based on the analysis results. This proposal includes specific information such as the plan name, price, features, and special offers.

[0797] Specific example:

[0798] The server generates specific proposals such as "5G plan" and "unlimited data plan," and adds related benefits and campaign information.

[0799] Results display means

[0800] The server generates a proposal and sends it to the terminal, which then displays it to the user. Based on this proposal, the user can quickly make appropriate suggestions to the customer.

[0801] Specific example:

[0802] The system then displays a suggestion on the user's device screen and explains to the customer, "Switching to this 5G plan will dramatically improve your communication speed, and with an unlimited data plan, you'll never have to worry about running out of data."

[0803] This system enables even new crew members to make suggestions on par with experienced employees, thereby improving customer satisfaction. Furthermore, automating the suggestion process reduces the burden on employees and streamlines the suggestion process.

[0804] The following describes the processing flow.

[0805] Step 1:

[0806] The device displays the login screen. The user enters their username and password and presses the login button. The device sends the entered authentication information to the server.

[0807] Step 2:

[0808] The server compares the received authentication information with the database. The server determines whether authentication was successful and sends the authentication result to the terminal. If the terminal successfully authenticates, it displays the data entry screen.

[0809] Step 3:

[0810] The terminal displays a customer information input screen. Input fields include the customer's smartphone and internet usage, dissatisfaction with communication speed, insufficient data capacity, and budget. The user then enters the customer information.

[0811] Step 4:

[0812] The user completes entering customer information and presses the submit button. The terminal then sends the entered customer information to the server.

[0813] Step 5:

[0814] The server passes the received customer information to a module for analysis. The server then filters the information to extract appropriate smartphone and internet plans based on the customer's requests. For example, if a customer is dissatisfied with their internet speed, the server will prioritize 5G plans over 4G plans.

[0815] Step 6:

[0816] The server compares past customer data and product information to select the most suitable recommendation. For example, if there is a "data capacity shortage," it will prioritize unlimited plans or additional data purchase options.

[0817] Step 7:

[0818] The server then selects the most suitable plan from the extracted options. This includes information such as the plan name, price, features, and special offers.

[0819] Step 8:

[0820] The server formats the generated proposals as a data package. The server then sends the proposal content to the terminal.

[0821] Step 9:

[0822] The device renders the received proposal content on the display screen. The user checks the device screen and shares the proposal content with the customer. For example, the user might explain, "Switching to this 5G plan will dramatically improve communication speed, and with the unlimited data plan, you won't have to worry about running out of data."

[0823] (Example 1)

[0824] Next, we will describe Example 1. 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."

[0825] Traditional customer service presented challenges, particularly for new employees, in proposing appropriate communication plans to customers. Furthermore, inconsistencies in the quality and speed of proposals led to decreased customer satisfaction and increased workload for employees.

[0826] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0827] In this invention, the server includes an input means for receiving customer information and automatically generating appropriate suggestions based on the customer information, an analysis means for analyzing the customer information received from the input means, and a generation means for generating suggestions based on the analysis results of the analysis means. This makes it possible for new employees to make suggestions equivalent to those of experienced employees, thereby improving customer satisfaction and reducing the burden on employees.

[0828] An "input method" is a means of receiving customer information and inputting it into the system.

[0829] "Analysis means" refers to means for analyzing customer information received from input means and evaluating data based on the analysis results.

[0830] "Generation means" refers to means for generating appropriate proposals based on the analysis results of the analysis means.

[0831] "Display means" refers to means for displaying the proposals generated by the generation means to the user.

[0832] A "customer database" is a database that stores past customer information.

[0833] "Product information" refers to information about the products handled by the system.

[0834] "Filtering" is the process of selecting from multiple proposals based on specific criteria.

[0835] "The optimal proposal" refers to the proposal that best suits the customer's needs.

[0836] "Analysis results" refer to the results of the analysis tool's evaluation of customer information received from the input tool.

[0837] As a form of implementing the invention, this system provides support to new employees in the sales area to help them propose appropriate smartphones and internet plans to customers. The system mainly consists of the following components:

[0838] 1. Input Method (Terminal): The terminal provides an input screen for receiving customer information. Users can use this screen to input information such as their smartphone and internet usage, dissatisfaction with communication speed, insufficient data capacity, and budget. A specific example is a user logging into the terminal and inputting information such as "slow communication speed" or "insufficient data capacity."

[0839] 2. Analysis Method (Server): The server receives customer information transmitted from the terminal. The received information is analyzed by the server. In this process, the server refers to past customer databases and product information to set criteria for identifying the plan best suited to the customer's needs. For example, the server might analyze a faster communication speed plan for "dissatisfaction with communication speed" and an unlimited plan or additional data purchase option for "insufficient data capacity."

[0840] 3. Generation Method (Server): Based on the analysis results, the server generates proposals. These proposals include specific information such as plan name, price, features, and special offers. For example, the server generates specific proposals such as "5G plan" and "unlimited data plan," and adds related benefits and campaign information.

[0841] 4. Display means (terminal): The generated proposal content is sent to the terminal, which displays it to the user. Based on this proposal content, the user can make quick and appropriate proposals to the customer. For example, the user could explain to the customer, "If you switch to this 5G plan, your communication speed will dramatically improve, and with the unlimited data plan, you won't have to worry about running out of data."

[0842] Example of a prompt

[0843] "Please propose the best internet plan for a customer who is dissatisfied with their current internet speed and lacks sufficient data capacity. The budget is within ¥XX."

[0844] This system enables even new employees to make proposals on par with experienced employees, thereby improving customer satisfaction. Furthermore, automating the proposal process reduces the burden on employees and streamlines the proposal process.

[0845] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0846] System program processing flow

[0847] Step 1:

[0848] The user operates the terminal and enters customer information. Specifically, information such as the customer's smartphone and internet usage, dissatisfaction with communication speed, insufficient data capacity, and budget is collected through the terminal's input screen. The entered information is then organized for data processing.

[0849] Input: Customer information (e.g., dissatisfaction with communication speed, insufficient data capacity)

[0850] Output: Organized customer information

[0851] Specific example:

[0852] The user logs into their device and enters information such as "the internet speed is slow" or "there isn't enough data."

[0853] Step 2:

[0854] The terminal sends the entered customer information to the server. This transmission is encrypted for security reasons. The server stores the received information in its database.

[0855] Input: Organized customer information

[0856] Output: Customer information sent to the server

[0857] Specific example:

[0858] The terminal encrypts customer information and sends it to the server.

[0859] Step 3:

[0860] The server analyzes the customer information it receives. This analysis involves referencing past customer databases and product information to establish criteria for identifying the best plan to meet the customer's needs.

[0861] Input: Customer information sent to the server

[0862] Output: Criteria based on customer needs (after data processing)

[0863] Specific example:

[0864] The server analyzes and matches "dissatisfaction with communication speed" with plans offering faster communication speeds, and "insufficient data capacity" with unlimited plans or additional data purchase options.

[0865] Step 4:

[0866] The server generates a proposal based on the analysis results. This proposal includes specific information such as the plan name, price, features, and special offers. The generated proposal is then saved back to the database.

[0867] Input: Criteria based on analyzed customer needs

[0868] Output: Generated proposals

[0869] Specific example:

[0870] The server generates specific proposals such as "5G plan" and "unlimited data plan," and adds related benefits and campaign information.

[0871] Step 5:

[0872] The server generates a proposal and sends it to the terminal, which then displays it to the user. The user reviews the displayed proposal and explains it to the customer.

[0873] Input: Generated suggestion content

[0874] Output: Suggestions displayed on the terminal

[0875] Specific example:

[0876] The server sends the generated suggestions to the terminal, and the terminal displays the content on the user's screen.

[0877] Step 6:

[0878] The user reviews the proposal displayed on their device and makes a quick and appropriate proposal to the customer. When explaining the proposal to the customer, the user emphasizes the benefits and advantages of the proposal.

[0879] Input: Suggestions displayed on the device

[0880] Output: Proposal explanation to the customer

[0881] Specific example:

[0882] The user explains to the customer, "By switching to this 5G plan, your communication speed will dramatically improve, and with the unlimited data plan, you'll never have to worry about running out of data."

[0883] (Application Example 1)

[0884] Next, we will explain Application Example 1. In the following explanation, 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."

[0885] Traditional proposal support systems based on customer information had the drawback of not adequately supporting employees in making quick and accurate proposals in person. Furthermore, there was a lack of support tools to enable new employees to make proposals on par with experienced staff, making it difficult to improve customer satisfaction. In addition, the generation and display of proposal content was inefficient, placing a heavy burden on employees.

[0886] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0887] In this invention, the server includes: data input means for receiving customer information and automatically generating appropriate suggestions based on the customer information; data analysis means for analyzing the customer information received from the data input means; suggestion generation means for generating suggestions based on the analysis results of the data analysis means; result display means for displaying the generated suggestions; means for inputting customer information using a smart device; means for generating analysis results using cloud service technology; means for analyzing customer data using a machine learning model; and means for displaying the generated suggestions on a wearable device. This enables even new employees to make suggestions efficiently and accurately, improving customer satisfaction and reducing the burden on employees.

[0888] "Customer information" refers to personal information and related data such as the customer's age, frequency of use, purchase history, and preferences.

[0889] "Data entry means" refers to devices or applications that provide an interface for collecting and inputting customer information.

[0890] "Data analysis means" refers to processing equipment or software used to perform analysis based on received customer information.

[0891] A "proposal generation system" is a system that has the function of automatically generating appropriate proposals for customers based on analysis results.

[0892] A "result display means" refers to a device or application that displays the generated suggestions in a format that the user can view.

[0893] A "smart device" is a portable electronic device with advanced functions, such as a smartphone, tablet, or smart glasses.

[0894] "Cloud service technology" refers to technologies and services that enable data storage, management, and analysis via the internet.

[0895] A "machine learning model" is a type of artificial intelligence that learns from large amounts of data and performs predictions and analyses.

[0896] A "wearable device" is an electronic device worn on the body and used for displaying or inputting information.

[0897] As a specific embodiment of this invention, a system is provided that inputs customer information, analyzes it, generates appropriate suggestions, and displays them. Details are described below.

[0898] System Overview

[0899] This system consists of the following main components:

[0900] 1. Data input means

[0901] 2. Data Analysis Methods

[0902] 3. Proposal generation means

[0903] 4. Results display means

[0904] 5. Means of inputting customer information using smart devices

[0905] 6. Means for generating analysis results using cloud service technology

[0906] 7. Means of analyzing customer data using machine learning models

[0907] 8. Means for displaying the generated suggestions on a wearable device.

[0908] Data input means

[0909] Users input customer information using smart devices such as smartphones and tablets. These input devices provide an interface that allows for the input of a wide range of customer information, including age, frequency of use, purchase history, and preferences.

[0910] Data analysis means

[0911] The server receives customer information transmitted from smart devices and analyzes it. During this process, it references past customer data and product information to perform more accurate analysis. Cloud service technology enables real-time analysis. Specifically, cloud services such as Amazon Web Services (AWS) are used.

[0912] Proposal generation means

[0913] The server generates optimal suggestions based on the analysis results obtained by the data analysis method. Using a generative AI model, it generates suggestions using prompt sentences like the following as input.

[0914] Customer: {'name': 'Taro Yamada', 'age': 28, 'usage': 'high', 'complaints': ['slow speed', 'insufficient data'], 'budget': 5000}

[0915] Analysis: {'recommended_plans': ['5G plan', 'unlimited data plan'], 'benefits': ['high-speed internet', 'no additional data required']}

[0916] Generate a sales proposal that includes plan names, prices, benefits, and any special offers.

[0917] The generative AI model used is OpenAI's GPT-3.

[0918] Results display means

[0919] The server sends the generated suggestions to the smart device and displays them to the user. The suggestions can also be displayed on wearable devices (e.g., smart glasses), allowing users to explain things smoothly to customers. Specific display applications are developed using React Native and Unity.

[0920] Cloud service technology

[0921] The server performs analysis using cloud service technology. This enables the processing of large datasets and real-time analysis. An example of this is Amazon Web Services (AWS).

[0922] Machine learning models

[0923] The server analyzes customer data using machine learning models. This analysis enables the server to provide recommendations best suited to the customer's needs. Specifically, machine learning libraries such as scikit-learn and TensorFlow are used.

[0924] Specific example

[0925] For example, suppose a user uses smart glasses to input customer information, and the analysis performed by a cloud service recommends a "5G plan" and an "unlimited data plan." Based on this information, a generative AI model creates a suggestion message which is displayed on the user's smartphone or smart glasses. This suggestion includes specific explanations such as, "Switching to the 5G plan will dramatically improve your communication speed, and the unlimited data plan will eliminate any worries about running out of data."

[0926] In this way, by using this system, even new employees can make proposals efficiently and accurately, leading to improved customer satisfaction and reduced workload for employees.

[0927] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0928] Step 1:

[0929] Users enter customer information using a smart device (smartphone or smart glasses). This involves entering a wide range of information into the device's input interface, including age, usage frequency, purchase history, preferences, dissatisfaction with communication speed, insufficient data capacity, and budget. The entered information is sent from the device to the server in JSON format.

[0930] Input: Customer information (age, frequency of use, purchase history, preferences, dissatisfaction with communication speed, insufficient data capacity, budget)

[0931] Output: Customer information data in JSON format

[0932] Operation: The terminal verifies the information entered by the user and then sends it to the server.

[0933] Step 2:

[0934] The server receives customer information sent from the terminal and begins data analysis using cloud service technology. Specifically, it uses Amazon Web Services (AWS) to analyze customer needs based on past customer data and product information. This analysis generates information to identify the most suitable plans and products for the customer's needs.

[0935] Input: Customer information data in JSON format

[0936] Output: Analysis results (list of candidate plans and products)

[0937] Operation: The server analyzes the received customer information on AWS and identifies candidate plans by referring to historical data and product information.

[0938] Step 3:

[0939] The server generates specific proposals using proposal generation means based on the analysis results obtained by the data analysis means. A generative AI model is utilized here. The server creates proposal statements based on the generative AI model (e.g., GPT-3) using the following prompt statements.

[0940] Customer: {'name': 'Taro Yamada', 'age': 28, 'usage': 'high', 'complaints': ['slow speed', 'insufficient data'], 'budget': 5000}

[0941] Analysis: {'recommended_plans': ['5G plan', 'unlimited data plan'], 'benefits': ['high-speed internet', 'no additional data required']}

[0942] Generate a sales proposal that includes plan names, prices, benefits, and any special offers.

[0943] Input: Analysis results (list of candidate plans and products) and prompt text

[0944] Output: Proposal (details of specific products or plans)

[0945] Operation: The server generates a prompt sentence based on the analysis results, inputs it into the generation AI model, and generates a suggested sentence.

[0946] Step 4:

[0947] The server sends the generated proposal text to the terminal and displays it to the user. Furthermore, the same proposal is also sent and displayed to a wearable device (smart glasses), enabling the user to smoothly make proposals to customers. The display application is developed using React Native and Unity.

[0948] Input: Proposal (details of specific products or plans)

[0949] Output: Suggestions displayed on the user terminal and wearable device screens.

[0950] Operation: The server sends the generated proposal text to the terminal and wearable device, and displays the proposal content.

[0951] These processing steps enable the system to quickly and accurately provide optimal suggestions based on customer information. This allows even new employees to make suggestions on par with experienced staff, thereby improving customer satisfaction.

[0952] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0953] System Overview

[0954] This invention is a powerful support system that enables even new crew members at the sales floor to propose appropriate smartphones and internet plans to customers, and further incorporates an emotion engine that recognizes user emotions. The system consists of the following main components:

[0955] 1. Data input means

[0956] 2. Data Analysis Methods

[0957] 3. Proposal generation means

[0958] 4. Results display means

[0959] 5. Emotional Engine

[0960] Data input means

[0961] The terminal provides a customer information input screen, allowing users to easily input information obtained from customers. Input fields include customer smartphone and internet usage, dissatisfaction with communication speed, insufficient data capacity, and budget.

[0962] Specific example:

[0963] The user logs into their device and enters customer information such as "slow internet speed" or "insufficient data capacity."

[0964] Emotional Engine

[0965] The device captures the user's voice and facial expressions and sends the data to the server. The server analyzes the emotions using an emotion engine and provides the analysis results to the data analysis means and the suggestion generation means. Through this process, suggestions that reflect the customer's emotional state are generated.

[0966] Specific example:

[0967] If a customer's facial expression indicates displeasure while listening to an explanation, the emotion engine provides this information as analytical data and generates suggestions for providing a more thorough explanation.

[0968] Data analysis means

[0969] The server receives customer information and sentiment data sent from the terminal and analyzes it. This analysis is performed by referencing past customer data and product information. This establishes criteria for identifying the optimal plan based on the customer's needs and emotional state.

[0970] Specific example:

[0971] The server analyzes data to recommend faster plans based on "dissatisfaction with communication speed" and unlimited plans or additional data purchase options based on "insufficient data capacity." It also prioritizes suggestions that help customers relax based on emotional data.

[0972] Proposal generation means

[0973] The server generates suggestions based on the analysis results. These suggestions include the plan name, price, features, benefits, and information based on the customer's emotional state.

[0974] Specific example:

[0975] The server generates specific proposals such as "5G plan" and "unlimited data plan," and adds explanations that take customer emotions into consideration.

[0976] Results display means

[0977] The server generates a proposal and sends it to the terminal, which then displays it to the user. Based on this proposal, the user can quickly make appropriate suggestions to the customer.

[0978] Specific example:

[0979] The user reviews the offer displayed on their device screen and explains to the customer, "If you switch to this 5G plan, your communication speed will dramatically improve, and you'll never have to worry about running out of data with the unlimited data plan. What do you think?"

[0980] Overall flow

[0981] In this system, the server automatically generates the optimal plan based on customer information and emotional data entered by new crew members. This allows new crew members to make suggestions on par with experienced employees, improving customer satisfaction and operational efficiency. Furthermore, the introduction of an emotional engine enables suggestions that take into account the customer's emotional state, leading to an even greater improvement in customer satisfaction.

[0982] The following describes the processing flow.

[0983] Step 1:

[0984] The device displays the login screen. The user enters their username and password and presses the login button. The device sends the entered authentication information to the server.

[0985] Step 2:

[0986] The server compares the received authentication information with the database. The server determines whether authentication was successful and sends the authentication result to the terminal. If the terminal successfully authenticates, it displays the data entry screen.

[0987] Step 3:

[0988] The terminal displays a customer information input screen. Input fields include the customer's smartphone and internet usage, dissatisfaction with communication speed, insufficient data capacity, and budget. The user then enters the customer information.

[0989] Step 4:

[0990] The user completes entering customer information and presses the submit button. The terminal then sends the entered customer information to the server.

[0991] Step 5:

[0992] The device captures the user's voice and facial expressions. The captured data is then sent to a server.

[0993] Step 6:

[0994] The server uses an emotion engine to analyze the received audio and facial expression data. This analysis identifies the user's emotional state (e.g., satisfaction, dissatisfaction, doubt, etc.).

[0995] Step 7:

[0996] The server passes customer information and sentiment data to the analysis module. Based on the customer's requests and sentiments, the server performs filtering to extract appropriate smartphone and internet plans. For example, if there is "dissatisfaction with communication speed," 5G plans will be prioritized over 4G plans, and if there is "insufficient data capacity," unlimited plans or additional data purchase options will be prioritized.

[0997] Step 8:

[0998] The server compares past customer data and product information to select the most suitable proposal. Furthermore, it selects proposals that take into account the user's emotional state. For example, if a customer is dissatisfied, it will propose a more attractive offer or additional services.

[0999] Step 9:

[1000] The server then selects the most suitable plan from the extracted options. This includes information such as the plan name, price, features, and special offers.

[1001] Step 10:

[1002] The server formats the generated proposals as a data package. The server then sends the proposal content to the terminal.

[1003] Step 11:

[1004] The device renders the received proposal content on the display screen. The user checks the device screen and shares the proposal content with the customer. For example, the user might explain, "If you switch to this 5G plan, your communication speed will dramatically improve, and with the unlimited data plan, you won't have to worry about running out of data." Depending on the customer's emotional state, additional information such as, "Furthermore, as part of a current sign-up campaign, the first month is free," may also be provided.

[1005] (Example 2)

[1006] Next, we will describe Example 2. 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."

[1007] Traditional sales support systems had a problem in that it was difficult for new crew members to propose appropriate smartphone and internet plans to customers. Furthermore, they were unable to make proposals that took into account the customer's emotional state, making it difficult to interact with customers and increasing the risk of decreased customer satisfaction. Therefore, there is a need for a system that allows even new crew members to effectively interact with customers and quickly make appropriate proposals that reflect the customer's emotional state.

[1008] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[1009] In this invention, the server includes data input means for receiving customer information and automatically generating appropriate suggestions; emotion analysis means for transmitting customer information received from the data input means and emotion data captured from voice and facial expressions to the server; and data analysis means for analyzing the data transmitted by the emotion analysis means and generating optimal suggestions based on the customer's needs and emotional state. This makes it possible for even new crew members to make suggestions of the same quality as experienced ones, and furthermore, to make suggestions that reflect the customer's emotional state, thereby improving customer satisfaction.

[1010] "Data input means" refers to means for receiving customer information and automatically generating appropriate suggestions based on said customer information.

[1011] "Emotion analysis means" refers to a means of transmitting customer information received from data input means, as well as emotional data captured from voice and facial expressions, to a server.

[1012] "Data analysis means" refers to a means of analyzing data transmitted by emotion analysis means and generating optimal suggestions based on customer needs and emotional state.

[1013] "Proposal generation means" refers to means for generating proposals based on the analysis results of data analysis means.

[1014] "Result display means" refers to means for displaying the generated proposals.

[1015] "Customer information" refers to information such as the customer's smartphone and internet usage, dissatisfaction with communication speed, insufficient data capacity, and budget.

[1016] "Emotional data" refers to data captured from customers' voices and facial expressions.

[1017] A "server" is a computer system that includes data input means, sentiment analysis means, data analysis means, and proposal generation means.

[1018] System Overview

[1019] This invention is a powerful support system that enables even new crew members in sales to propose appropriate smartphones and internet plans to customers, and further incorporates an emotion engine that recognizes customer emotions. This system consists of the following main components.

[1020] 1. Data input means

[1021] 2. Emotion analysis method

[1022] 3. Data Analysis Methods

[1023] 4. Proposal generation means

[1024] 5. Results display means

[1025] Data input means

[1026] The terminal provides a screen for entering customer information. The user enters customer information on this screen. Input fields include the customer's smartphone and internet usage, dissatisfaction with communication speed, insufficient data capacity, budget, etc.

[1027] Specific example:

[1028] The user logs into their device and enters information such as "slow internet speed," "insufficient data capacity," and "monthly budget of up to 5000 yen." This entered data is then sent to the server.

[1029] Emotion analysis means

[1030] The terminal captures the voice and facial expressions of users and customers and transmits them to the server. The server analyzes this data using an emotion engine and provides the analysis results to the data analysis means and the suggestion generation means.

[1031] Specific example:

[1032] While the user interacts with a customer, the device's camera captures the customer's facial expressions in real time, and the microphone simultaneously records the customer's voice. This data is sent to a server, where an emotion engine generates analysis results such as "the customer is unhappy" or "the customer is relaxed."

[1033] Data analysis means

[1034] The server receives customer information and sentiment data sent from the terminal and analyzes it. By referring to past customer data and product information, it identifies the optimal plan based on the customer's needs and emotional state.

[1035] Specific example:

[1036] The server will suggest a high-speed plan for complaints about slow internet speeds and an unlimited plan for complaints about insufficient data capacity. Furthermore, if the customer is unhappy, the server will prioritize offering suggestions with more detailed explanations.

[1037] Proposal generation means

[1038] The server generates specific suggestions based on the analysis results. These suggestions include the plan name, price, features, and special offers. They also include information based on the analyzed sentiment data.

[1039] Specific example:

[1040] The server generates suggestions such as "5G plan" and "unlimited data plan," and adds explanations such as, "This plan offers fast communication speeds, allowing you to watch videos without any issues."

[1041] Results display means

[1042] The server generates a proposal and sends it to the terminal, which then displays it to the user. Based on this proposal, the user can quickly and appropriately explain the proposal to the customer.

[1043] Specific example:

[1044] The user reviews the offer displayed on their device screen and explains to the customer, "Switching to a 5G plan will dramatically improve your communication speed, and with an unlimited data plan, you'll never have to worry about running out of data."

[1045] Examples of input prompts for a generative AI model

[1046] 1. Prompt: "The customer is dissatisfied with their internet speed. Which plan should I suggest?"

[1047] 2. Prompt: "The customer is looking unhappy during the explanation. How should you respond?"

[1048] This system aims to improve customer satisfaction by enabling even rookie crew members to make high-quality suggestions on par with experienced staff, and by allowing them to make suggestions that reflect the customer's emotional state.

[1049] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1050] System program processing flow

[1051] Step 1:

[1052] The terminal provides a customer information input screen. The user logs into the terminal and inputs information such as the customer's smartphone and internet usage, dissatisfaction with communication speed, insufficient data capacity, and budget. The input data is sent from the terminal to the server.

[1053] Input: Customer's smartphone and internet usage, dissatisfaction with communication speed, insufficient data capacity, budget, etc.

[1054] Data processing: Organizing and formatting customer information

[1055] Output: Organized customer information data

[1056] Step 2:

[1057] The device captures the voice and facial expressions of users and customers. This data is then transmitted from the device to the server.

[1058] Input: Customer's voice, facial expressions

[1059] Data processing: Audio recording, facial expression capture.

[1060] Output: Audio data, facial expression data

[1061] Step 3:

[1062] The server receives the data sent in Step 1 and Step 2. It integrates and analyzes the received customer information and sentiment data. It also refers to and analyzes past customer data and product information.

[1063] Input: Organized customer information data, voice data, facial expression data, historical customer data, product information

[1064] Data processing: Identifying customer needs, analyzing emotional states.

[1065] Output: Analysis results (identification of the optimal plan, evaluation of emotional state)

[1066] Step 4:

[1067] The server generates suggestions based on the analysis results. The generated suggestions include the plan name, price, features, and special offers, and also incorporate information based on the customer's emotional state.

[1068] Input: Analysis results (identification of the optimal plan, evaluation of emotional state)

[1069] Data processing: Assembling the proposal

[1070] Output: Generated proposals

[1071] Step 5:

[1072] The server generates a proposal and sends it to the terminal. The terminal displays this proposal to the user, who then uses the proposal to explain it to the customer.

[1073] Input: Generated proposal

[1074] Data processing: Converting the proposed content to a display format.

[1075] Output: Suggestions displayed on the user's device

[1076] Examples of specific prompt statements in processing steps

[1077] Example of a prompt:

[1078] Prompt 1: "The customer is dissatisfied with their internet speed. Which plan should I suggest?"

[1079] Prompt 2: "The customer is looking unhappy during the explanation. How should you respond?"

[1080] Through the steps described above, this system supports even rookie crew members in making high-quality suggestions comparable to those of experienced individuals, and further improves customer satisfaction by making suggestions that take into account the customer's emotional state.

[1081] (Application Example 2)

[1082] Next, we will explain application example 2. In the following explanation, 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."

[1083] Traditional proposal systems made it difficult for new staff to make appropriate suggestions to customers, sometimes leading to decreased customer satisfaction. Furthermore, they failed to consider customer emotions when making suggestions, making it difficult to improve service quality. The lack of technology to acquire and instantly display customer and emotional information in real time was also a challenge.

[1084] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes a data input means for receiving customer information and automatically generating appropriate suggestions based on the customer information; a data analysis means for analyzing the customer information received from the data input means; a suggestion generation means for generating suggestions based on the analysis results of the data analysis means; a result display means for displaying the generated suggestions; an emotion engine for analyzing customer emotion information; a means for adjusting appropriate suggestions based on the emotion information analyzed by the emotion engine; and a means for acquiring and displaying customer information and emotion information in real time using smart glasses or a head-mounted display. As a result, even new staff members can make appropriate suggestions while considering customer emotions, which enables improved customer satisfaction and service quality.

[1085] "Customer information" refers to information such as the customer's smartphone usage, dissatisfaction with communication speed, insufficient data capacity, and budget.

[1086] "Data entry means" refers to a device or system for receiving and entering customer information.

[1087] "Data analysis means" refers to a device or system for analyzing received customer information and providing the results to the proposal generation means.

[1088] "Proposal generation means" refers to a device or system that generates appropriate proposals for customers based on the results of data analysis means.

[1089] "Result display means" refers to a device or system for displaying the generated proposals to users or customers.

[1090] An "emotion engine" is a device or system that analyzes customer emotional information and provides the results to data analysis means and proposal generation means.

[1091] "Smart glasses" are glasses-type devices that users wear and that can display information in real time.

[1092] A "head-mounted display" is a device that is worn by the user to display information within their field of vision.

[1093] Modes for carrying out the invention

[1094] This invention is a system for new staff members to make appropriate suggestions to customers, and it utilizes smart glasses or a head-mounted display to analyze customer emotional information and display the suggested content in real time.

[1095] Hardware and software configuration

[1096] 1. Hardware:

[1097] Smart glasses (e.g., Google Glass)

[1098] Head-mounted display (e.g., Microsoft HoloLens)

[1099] 2. Software:

[1100] Face recognition software (e.g., OpenCV)

[1101] Speech recognition software (e.g., Google Cloud Speech-to-Text)

[1102] Database system (e.g., MySQL)

[1103] Server-side applications (e.g., Node.js)

[1104] System programs and their processes

[1105] 1. Data entry means:

[1106] The server captures customer facial expressions using cameras in smart glasses or head-mounted displays, and records and transcribes customer requests and complaints via voice input. It also inputs specific information such as customer smartphone usage and budget. This information functions as a data entry tool.

[1107] 2. Emotional Engine:

[1108] The server uses facial recognition software and speech recognition software to analyze captured customer facial expression data in real time. The analyzed emotional information is transmitted to the server and provided to the data analysis means and the suggestion generation means.

[1109] 3. Data analysis methods:

[1110] The server sends the collected customer information and sentiment data to a database system for analysis. Based on past customer data and product information, it identifies the optimal plan that best suits the customer's needs.

[1111] 4. Proposal generation means:

[1112] Based on the analysis results, the server generates appropriate smartphone and internet plans. This recommendation includes details about pricing and services, as well as explanations that take sentiment analysis results into account.

[1113] 5. Results display means:

[1114] The suggested content is displayed in real time on smart glasses or a head-mounted display. Store staff can check the displayed content and make suggestions to customers.

[1115] Specific example

[1116] Consider a scenario where a customer visits a physical store. A staff member wears smart glasses or a head-mounted display, capturing the customer's facial expressions with a camera. Voice recognition software automatically transcribes the customer's requests and complaints, such as "the internet speed is slow" or "there isn't enough data," into text. The system sends this information to a server in real time for analysis by an emotion engine. Based on the analysis results, the system generates suggestions such as a "5G plan" or an "unlimited data plan" and displays them on the smart glasses. Staff members can review this information in real time and make appropriate suggestions to the customer.

[1117] Example of a prompt

[1118] Follow these steps to create your customer support application:

[1119] 1. Use smart glasses to capture the customer's facial expressions, record their voice, and transcribe it into text.

[1120] 2. Use the emotion engine to analyze customer emotions in real time.

[1121] 3. Send customer information and sentiment data to the server for analysis.

[1122] 4. Refer to past database records to identify the optimal smartphone and internet plan for you.

[1123] 5. Generate the proposal content and display it in real time on the smart glasses.

[1124] This allows even new staff members to make appropriate suggestions to customers, just like experienced staff, which is expected to improve customer satisfaction.

[1125] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1126] Program processing steps

[1127] Step 1:

[1128] The server uses cameras on smart glasses or head-mounted displays to capture the customer's facial expressions and acquire audio. The input consists of captured image and audio data, while the output consists of facial expression data analyzed by facial recognition software and audio data transcribed into text through speech recognition software. Specifically, facial recognition software is used to identify emotions from facial expressions, and speech recognition software is used to convert the customer's words into text data.

[1129] Step 2:

[1130] The server transmits captured facial expression and audio data to the emotion engine for real-time emotion analysis. The input is facial expression data and transcribed audio data, and the output is the analyzed emotion information. Specifically, the emotion engine determines the customer's emotional state from the facial expressions and audio and provides the result to the data analysis system.

[1131] Step 3:

[1132] The server transmits customer information received from the data input means and sentiment data obtained from the sentiment engine to the database system, where it performs analysis while referring to past customer data and product information. The input is customer information and sentiment data, and the output is the analysis results for identifying the optimal plan. Specifically, the database system searches for a plan that matches the customer's requests and past data, and provides the analysis results to the proposal generation means.

[1133] Step 4:

[1134] The server operates a suggestion generation system that generates appropriate suggestions based on the results of the data analysis system. The input is the results of the data analysis system, and the output is the generated suggestion content. Specifically, the suggestion generation system generates a plan that includes fees and service details, and adds explanatory text that takes the sentiment analysis results into account.

[1135] Step 5:

[1136] The server transmits the generated proposals to smart glasses or a head-mounted display in real time, activating the result display device. The input is the generated proposals, and the output is the proposals displayed on the smart glasses or head-mounted display. Specifically, the display device shows the proposals to the staff, who then review the information and make proposals to the customer.

[1137] Thus, in the processing steps of this system, customer information and sentiment data can be collected in real time through smart glasses or head-mounted displays, and based on this, optimal suggestions can be generated and displayed.

[1138] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[1139] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1140] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[1141] [Fourth Embodiment]

[1142] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[1143] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1144] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1145] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[1146] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[1147] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[1148] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[1149] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[1150] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[1151] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[1152] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1153] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[1154] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1155] System Overview

[1156] As a form of implementing the invention, this system provides support to new crew members in the sales area, enabling them to propose appropriate smartphones and internet plans to customers. The system mainly consists of the following components:

[1157] 1. Data input means

[1158] 2. Data Analysis Methods

[1159] 3. Proposal generation means

[1160] 4. Results display means

[1161] Data input means

[1162] The terminal provides a customer information input screen. This allows users to easily input information obtained from customers. Input fields include the customer's smartphone and internet usage, dissatisfaction with communication speed, insufficient data capacity, budget, etc.

[1163] Specific example:

[1164] The user logs into their device and enters customer information such as "slow internet speed" or "insufficient data capacity."

[1165] Data analysis means

[1166] The server receives customer information sent from the terminal and analyzes it. This analysis involves referencing past customer data and product information. This establishes criteria for identifying the plan best suited to the customer's needs.

[1167] Specific example:

[1168] The server analyzes whether a user is dissatisfied with their internet speed and recommends a faster plan, or whether they are experiencing insufficient data capacity and should consider an unlimited plan or an option to purchase additional data.

[1169] Proposal generation means

[1170] The server generates a proposal based on the analysis results. This proposal includes specific information such as the plan name, price, features, and special offers.

[1171] Specific example:

[1172] The server generates specific proposals such as "5G plan" and "unlimited data plan," and adds related benefits and campaign information.

[1173] Results display means

[1174] The server generates a proposal and sends it to the terminal, which then displays it to the user. Based on this proposal, the user can quickly make appropriate suggestions to the customer.

[1175] Specific example:

[1176] The system then displays a suggestion on the user's device screen and explains to the customer, "Switching to this 5G plan will dramatically improve your communication speed, and with an unlimited data plan, you'll never have to worry about running out of data."

[1177] This system enables even new crew members to make suggestions on par with experienced employees, thereby improving customer satisfaction. Furthermore, automating the suggestion process reduces the burden on employees and streamlines the suggestion process.

[1178] The following describes the processing flow.

[1179] Step 1:

[1180] The device displays the login screen. The user enters their username and password and presses the login button. The device sends the entered authentication information to the server.

[1181] Step 2:

[1182] The server compares the received authentication information with the database. The server determines whether authentication was successful and sends the authentication result to the terminal. If the terminal successfully authenticates, it displays the data entry screen.

[1183] Step 3:

[1184] The terminal displays a customer information input screen. Input fields include the customer's smartphone and internet usage, dissatisfaction with communication speed, insufficient data capacity, and budget. The user then enters the customer information.

[1185] Step 4:

[1186] The user completes entering customer information and presses the submit button. The terminal then sends the entered customer information to the server.

[1187] Step 5:

[1188] The server passes the received customer information to a module for analysis. The server then filters the information to extract appropriate smartphone and internet plans based on the customer's requests. For example, if a customer is dissatisfied with their internet speed, the server will prioritize 5G plans over 4G plans.

[1189] Step 6:

[1190] The server compares past customer data and product information to select the most suitable recommendation. For example, if there is a "data capacity shortage," it will prioritize unlimited plans or additional data purchase options.

[1191] Step 7:

[1192] The server then selects the most suitable plan from the extracted options. This includes information such as the plan name, price, features, and special offers.

[1193] Step 8:

[1194] The server formats the generated proposals as a data package. The server then sends the proposal content to the terminal.

[1195] Step 9:

[1196] The device renders the received proposal content on the display screen. The user checks the device screen and shares the proposal content with the customer. For example, the user might explain, "Switching to this 5G plan will dramatically improve communication speed, and with the unlimited data plan, you won't have to worry about running out of data."

[1197] (Example 1)

[1198] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1199] Traditional customer service presented challenges, particularly for new employees, in proposing appropriate communication plans to customers. Furthermore, inconsistencies in the quality and speed of proposals led to decreased customer satisfaction and increased workload for employees.

[1200] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[1201] In this invention, the server includes an input means for receiving customer information and automatically generating appropriate suggestions based on the customer information, an analysis means for analyzing the customer information received from the input means, and a generation means for generating suggestions based on the analysis results of the analysis means. This makes it possible for new employees to make suggestions equivalent to those of experienced employees, thereby improving customer satisfaction and reducing the burden on employees.

[1202] An "input method" is a means of receiving customer information and inputting it into the system.

[1203] "Analysis means" refers to means for analyzing customer information received from input means and evaluating data based on the analysis results.

[1204] "Generation means" refers to means for generating appropriate proposals based on the analysis results of the analysis means.

[1205] "Display means" refers to means for displaying the proposals generated by the generation means to the user.

[1206] A "customer database" is a database that stores past customer information.

[1207] "Product information" refers to information about the products handled by the system.

[1208] "Filtering" is the process of selecting from multiple proposals based on specific criteria.

[1209] "The optimal proposal" refers to the proposal that best suits the customer's needs.

[1210] "Analysis results" refer to the results of the analysis tool's evaluation of customer information received from the input tool.

[1211] As a form of implementing the invention, this system provides support to new employees in the sales area to help them propose appropriate smartphones and internet plans to customers. The system mainly consists of the following components:

[1212] 1. Input Method (Terminal): The terminal provides an input screen for receiving customer information. Users can use this screen to input information such as their smartphone and internet usage, dissatisfaction with communication speed, insufficient data capacity, and budget. A specific example is a user logging into the terminal and inputting information such as "slow communication speed" or "insufficient data capacity."

[1213] 2. Analysis Method (Server): The server receives customer information transmitted from the terminal. The received information is analyzed by the server. In this process, the server refers to past customer databases and product information to set criteria for identifying the plan best suited to the customer's needs. For example, the server might analyze a faster communication speed plan for "dissatisfaction with communication speed" and an unlimited plan or additional data purchase option for "insufficient data capacity."

[1214] 3. Generation Method (Server): Based on the analysis results, the server generates proposals. These proposals include specific information such as plan name, price, features, and special offers. For example, the server generates specific proposals such as "5G plan" and "unlimited data plan," and adds related benefits and campaign information.

[1215] 4. Display means (terminal): The generated proposal content is sent to the terminal, which displays it to the user. Based on this proposal content, the user can make quick and appropriate proposals to the customer. For example, the user could explain to the customer, "If you switch to this 5G plan, your communication speed will dramatically improve, and with the unlimited data plan, you won't have to worry about running out of data."

[1216] Example of a prompt

[1217] "Please propose the best internet plan for a customer who is dissatisfied with their current internet speed and lacks sufficient data capacity. The budget is within ¥XX."

[1218] This system enables even new employees to make proposals on par with experienced employees, thereby improving customer satisfaction. Furthermore, automating the proposal process reduces the burden on employees and streamlines the proposal process.

[1219] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1220] System program processing flow

[1221] Step 1:

[1222] The user operates the terminal and enters customer information. Specifically, information such as the customer's smartphone and internet usage, dissatisfaction with communication speed, insufficient data capacity, and budget is collected through the terminal's input screen. The entered information is then organized for data processing.

[1223] Input: Customer information (e.g., dissatisfaction with communication speed, insufficient data capacity)

[1224] Output: Organized customer information

[1225] Specific example:

[1226] The user logs into their device and enters information such as "the internet speed is slow" or "there isn't enough data."

[1227] Step 2:

[1228] The terminal sends the entered customer information to the server. This transmission is encrypted for security reasons. The server stores the received information in its database.

[1229] Input: Organized customer information

[1230] Output: Customer information sent to the server

[1231] Specific example:

[1232] The terminal encrypts customer information and sends it to the server.

[1233] Step 3:

[1234] The server analyzes the customer information it receives. This analysis involves referencing past customer databases and product information to establish criteria for identifying the best plan to meet the customer's needs.

[1235] Input: Customer information sent to the server

[1236] Output: Criteria based on customer needs (after data processing)

[1237] Specific example:

[1238] The server analyzes and matches "dissatisfaction with communication speed" with plans offering faster communication speeds, and "insufficient data capacity" with unlimited plans or additional data purchase options.

[1239] Step 4:

[1240] The server generates a proposal based on the analysis results. This proposal includes specific information such as the plan name, price, features, and special offers. The generated proposal is then saved back to the database.

[1241] Input: Criteria based on analyzed customer needs

[1242] Output: Generated proposals

[1243] Specific example:

[1244] The server generates specific proposals such as "5G plan" and "unlimited data plan," and adds related benefits and campaign information.

[1245] Step 5:

[1246] The server generates a proposal and sends it to the terminal, which then displays it to the user. The user reviews the displayed proposal and explains it to the customer.

[1247] Input: Generated suggestion content

[1248] Output: Suggestions displayed on the terminal

[1249] Specific example:

[1250] The server sends the generated suggestions to the terminal, and the terminal displays the content on the user's screen.

[1251] Step 6:

[1252] The user reviews the proposal displayed on their device and makes a quick and appropriate proposal to the customer. When explaining the proposal to the customer, the user emphasizes the benefits and advantages of the proposal.

[1253] Input: Suggestions displayed on the device

[1254] Output: Proposal explanation to the customer

[1255] Specific example:

[1256] The user explains to the customer, "By switching to this 5G plan, your communication speed will dramatically improve, and with the unlimited data plan, you'll never have to worry about running out of data."

[1257] (Application Example 1)

[1258] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1259] Traditional proposal support systems based on customer information had the drawback of not adequately supporting employees in making quick and accurate proposals in person. Furthermore, there was a lack of support tools to enable new employees to make proposals on par with experienced staff, making it difficult to improve customer satisfaction. In addition, the generation and display of proposal content was inefficient, placing a heavy burden on employees.

[1260] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[1261] In this invention, the server includes: data input means for receiving customer information and automatically generating appropriate suggestions based on the customer information; data analysis means for analyzing the customer information received from the data input means; suggestion generation means for generating suggestions based on the analysis results of the data analysis means; result display means for displaying the generated suggestions; means for inputting customer information using a smart device; means for generating analysis results using cloud service technology; means for analyzing customer data using a machine learning model; and means for displaying the generated suggestions on a wearable device. This enables even new employees to make suggestions efficiently and accurately, improving customer satisfaction and reducing the burden on employees.

[1262] "Customer information" refers to personal information and related data such as the customer's age, frequency of use, purchase history, and preferences.

[1263] "Data entry means" refers to devices or applications that provide an interface for collecting and inputting customer information.

[1264] "Data analysis means" refers to processing equipment or software used to perform analysis based on received customer information.

[1265] A "proposal generation system" is a system that has the function of automatically generating appropriate proposals for customers based on analysis results.

[1266] A "result display means" refers to a device or application that displays the generated suggestions in a format that the user can view.

[1267] A "smart device" is a portable electronic device with advanced functions, such as a smartphone, tablet, or smart glasses.

[1268] "Cloud service technology" refers to technologies and services that enable data storage, management, and analysis via the internet.

[1269] A "machine learning model" is a type of artificial intelligence that learns from large amounts of data and performs predictions and analyses.

[1270] A "wearable device" is an electronic device worn on the body and used for displaying or inputting information.

[1271] As a specific embodiment of this invention, a system is provided that inputs customer information, analyzes it, generates appropriate suggestions, and displays them. Details are described below.

[1272] System Overview

[1273] This system consists of the following main components:

[1274] 1. Data input means

[1275] 2. Data Analysis Methods

[1276] 3. Proposal generation means

[1277] 4. Results display means

[1278] 5. Means of inputting customer information using smart devices

[1279] 6. Means for generating analysis results using cloud service technology

[1280] 7. Means of analyzing customer data using machine learning models

[1281] 8. Means for displaying the generated suggestions on a wearable device.

[1282] Data input means

[1283] Users input customer information using smart devices such as smartphones and tablets. These input devices provide an interface that allows for the input of a wide range of customer information, including age, frequency of use, purchase history, and preferences.

[1284] Data analysis means

[1285] The server receives customer information transmitted from smart devices and analyzes it. During this process, it references past customer data and product information to perform more accurate analysis. Cloud service technology enables real-time analysis. Specifically, cloud services such as Amazon Web Services (AWS) are used.

[1286] Proposal generation means

[1287] The server generates optimal suggestions based on the analysis results obtained by the data analysis method. Using a generative AI model, it generates suggestions using prompt sentences like the following as input.

[1288] Customer: {'name': 'Taro Yamada', 'age': 28, 'usage': 'high', 'complaints': ['slow speed', 'insufficient data'], 'budget': 5000}

[1289] Analysis: {'recommended_plans': ['5G plan', 'unlimited data plan'], 'benefits': ['high-speed internet', 'no additional data required']}

[1290] Generate a sales proposal that includes plan names, prices, benefits, and any special offers.

[1291] The generative AI model used is OpenAI's GPT-3.

[1292] Results display means

[1293] The server sends the generated suggestions to the smart device and displays them to the user. The suggestions can also be displayed on wearable devices (e.g., smart glasses), allowing users to explain things smoothly to customers. Specific display applications are developed using React Native and Unity.

[1294] Cloud service technology

[1295] The server performs analysis using cloud service technology. This enables the processing of large datasets and real-time analysis. An example of this is Amazon Web Services (AWS).

[1296] Machine learning models

[1297] The server analyzes customer data using machine learning models. This analysis enables the server to provide recommendations best suited to the customer's needs. Specifically, machine learning libraries such as scikit-learn and TensorFlow are used.

[1298] Specific example

[1299] For example, suppose a user uses smart glasses to input customer information, and the analysis performed by a cloud service recommends a "5G plan" and an "unlimited data plan." Based on this information, a generative AI model creates a suggestion message which is displayed on the user's smartphone or smart glasses. This suggestion includes specific explanations such as, "Switching to the 5G plan will dramatically improve your communication speed, and the unlimited data plan will eliminate any worries about running out of data."

[1300] In this way, by using this system, even new employees can make proposals efficiently and accurately, leading to improved customer satisfaction and reduced workload for employees.

[1301] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1302] Step 1:

[1303] Users enter customer information using a smart device (smartphone or smart glasses). This involves entering a wide range of information into the device's input interface, including age, usage frequency, purchase history, preferences, dissatisfaction with communication speed, insufficient data capacity, and budget. The entered information is sent from the device to the server in JSON format.

[1304] Input: Customer information (age, frequency of use, purchase history, preferences, dissatisfaction with communication speed, insufficient data capacity, budget)

[1305] Output: Customer information data in JSON format

[1306] Operation: The terminal verifies the information entered by the user and then sends it to the server.

[1307] Step 2:

[1308] The server receives customer information sent from the terminal and begins data analysis using cloud service technology. Specifically, it uses Amazon Web Services (AWS) to analyze customer needs based on past customer data and product information. This analysis generates information to identify the most suitable plans and products for the customer's needs.

[1309] Input: Customer information data in JSON format

[1310] Output: Analysis results (list of candidate plans and products)

[1311] Operation: The server analyzes the received customer information on AWS and identifies candidate plans by referring to historical data and product information.

[1312] Step 3:

[1313] The server generates specific proposals using proposal generation means based on the analysis results obtained by the data analysis means. A generative AI model is utilized here. The server creates proposal statements based on the generative AI model (e.g., GPT-3) using the following prompt statements.

[1314] Customer: {'name': 'Taro Yamada', 'age': 28, 'usage': 'high', 'complaints': ['slow speed', 'insufficient data'], 'budget': 5000}

[1315] Analysis: {'recommended_plans': ['5G plan', 'unlimited data plan'], 'benefits': ['high-speed internet', 'no additional data required']}

[1316] Generate a sales proposal that includes plan names, prices, benefits, and any special offers.

[1317] Input: Analysis results (list of candidate plans and products) and prompt text

[1318] Output: Proposal (details of specific products or plans)

[1319] Operation: The server generates a prompt sentence based on the analysis results, inputs it into the generation AI model, and generates a suggested sentence.

[1320] Step 4:

[1321] The server sends the generated proposal text to the terminal and displays it to the user. Furthermore, the same proposal is also sent and displayed to a wearable device (smart glasses), enabling the user to smoothly make proposals to customers. The display application is developed using React Native and Unity.

[1322] Input: Proposal (details of specific products or plans)

[1323] Output: Suggestions displayed on the user terminal and wearable device screens.

[1324] Operation: The server sends the generated proposal text to the terminal and wearable device, and displays the proposal content.

[1325] These processing steps enable the system to quickly and accurately provide optimal suggestions based on customer information. This allows even new employees to make suggestions on par with experienced staff, thereby improving customer satisfaction.

[1326] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[1327] System Overview

[1328] This invention is a powerful support system that enables even new crew members at the sales floor to propose appropriate smartphones and internet plans to customers, and further incorporates an emotion engine that recognizes user emotions. The system consists of the following main components:

[1329] 1. Data input means

[1330] 2. Data Analysis Methods

[1331] 3. Proposal generation means

[1332] 4. Results display means

[1333] 5. Emotional Engine

[1334] Data input means

[1335] The terminal provides a customer information input screen, allowing users to easily input information obtained from customers. Input fields include customer smartphone and internet usage, dissatisfaction with communication speed, insufficient data capacity, and budget.

[1336] Specific example:

[1337] The user logs into their device and enters customer information such as "slow internet speed" or "insufficient data capacity."

[1338] Emotional Engine

[1339] The device captures the user's voice and facial expressions and sends the data to the server. The server analyzes the emotions using an emotion engine and provides the analysis results to the data analysis means and the suggestion generation means. Through this process, suggestions that reflect the customer's emotional state are generated.

[1340] Specific example:

[1341] If a customer's facial expression indicates displeasure while listening to an explanation, the emotion engine provides this information as analytical data and generates suggestions for providing a more thorough explanation.

[1342] Data analysis means

[1343] The server receives customer information and sentiment data sent from the terminal and analyzes it. This analysis is performed by referencing past customer data and product information. This establishes criteria for identifying the optimal plan based on the customer's needs and emotional state.

[1344] Specific example:

[1345] The server analyzes data to recommend faster plans based on "dissatisfaction with communication speed" and unlimited plans or additional data purchase options based on "insufficient data capacity." It also prioritizes suggestions that help customers relax based on emotional data.

[1346] Proposal generation means

[1347] The server generates suggestions based on the analysis results. These suggestions include the plan name, price, features, benefits, and information based on the customer's emotional state.

[1348] Specific example:

[1349] The server generates specific proposals such as "5G plan" and "unlimited data plan," and adds explanations that take customer emotions into consideration.

[1350] Results display means

[1351] The server generates a proposal and sends it to the terminal, which then displays it to the user. Based on this proposal, the user can quickly make appropriate suggestions to the customer.

[1352] Specific example:

[1353] The user reviews the offer displayed on their device screen and explains to the customer, "If you switch to this 5G plan, your communication speed will dramatically improve, and you'll never have to worry about running out of data with the unlimited data plan. What do you think?"

[1354] Overall flow

[1355] In this system, the server automatically generates the optimal plan based on customer information and emotional data entered by new crew members. This allows new crew members to make suggestions on par with experienced employees, improving customer satisfaction and operational efficiency. Furthermore, the introduction of an emotional engine enables suggestions that take into account the customer's emotional state, leading to an even greater improvement in customer satisfaction.

[1356] The following describes the processing flow.

[1357] Step 1:

[1358] The device displays the login screen. The user enters their username and password and presses the login button. The device sends the entered authentication information to the server.

[1359] Step 2:

[1360] The server compares the received authentication information with the database. The server determines whether authentication was successful and sends the authentication result to the terminal. If the terminal successfully authenticates, it displays the data entry screen.

[1361] Step 3:

[1362] The terminal displays a customer information input screen. Input fields include the customer's smartphone and internet usage, dissatisfaction with communication speed, insufficient data capacity, and budget. The user then enters the customer information.

[1363] Step 4:

[1364] The user completes entering customer information and presses the submit button. The terminal then sends the entered customer information to the server.

[1365] Step 5:

[1366] The device captures the user's voice and facial expressions. The captured data is then sent to a server.

[1367] Step 6:

[1368] The server uses an emotion engine to analyze the received audio and facial expression data. This analysis identifies the user's emotional state (e.g., satisfaction, dissatisfaction, doubt, etc.).

[1369] Step 7:

[1370] The server passes customer information and sentiment data to the analysis module. Based on the customer's requests and sentiments, the server performs filtering to extract appropriate smartphone and internet plans. For example, if there is "dissatisfaction with communication speed," 5G plans will be prioritized over 4G plans, and if there is "insufficient data capacity," unlimited plans or additional data purchase options will be prioritized.

[1371] Step 8:

[1372] The server compares past customer data and product information to select the most suitable proposal. Furthermore, it selects proposals that take into account the user's emotional state. For example, if a customer is dissatisfied, it will propose a more attractive offer or additional services.

[1373] Step 9:

[1374] The server then selects the most suitable plan from the extracted options. This includes information such as the plan name, price, features, and special offers.

[1375] Step 10:

[1376] The server formats the generated proposals as a data package. The server then sends the proposal content to the terminal.

[1377] Step 11:

[1378] The device renders the received proposal content on the display screen. The user checks the device screen and shares the proposal content with the customer. For example, the user might explain, "If you switch to this 5G plan, your communication speed will dramatically improve, and with the unlimited data plan, you won't have to worry about running out of data." Depending on the customer's emotional state, additional information such as, "Furthermore, as part of a current sign-up campaign, the first month is free," may also be provided.

[1379] (Example 2)

[1380] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1381] Traditional sales support systems had a problem in that it was difficult for new crew members to propose appropriate smartphone and internet plans to customers. Furthermore, they were unable to make proposals that took into account the customer's emotional state, making it difficult to interact with customers and increasing the risk of decreased customer satisfaction. Therefore, there is a need for a system that allows even new crew members to effectively interact with customers and quickly make appropriate proposals that reflect the customer's emotional state.

[1382] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[1383] In this invention, the server includes data input means for receiving customer information and automatically generating appropriate suggestions; emotion analysis means for transmitting customer information received from the data input means and emotion data captured from voice and facial expressions to the server; and data analysis means for analyzing the data transmitted by the emotion analysis means and generating optimal suggestions based on the customer's needs and emotional state. This makes it possible for even new crew members to make suggestions of the same quality as experienced ones, and furthermore, to make suggestions that reflect the customer's emotional state, thereby improving customer satisfaction.

[1384] "Data input means" refers to means for receiving customer information and automatically generating appropriate suggestions based on said customer information.

[1385] "Emotion analysis means" refers to a means of transmitting customer information received from data input means, as well as emotional data captured from voice and facial expressions, to a server.

[1386] "Data analysis means" refers to a means of analyzing data transmitted by emotion analysis means and generating optimal suggestions based on customer needs and emotional state.

[1387] "Proposal generation means" refers to means for generating proposals based on the analysis results of data analysis means.

[1388] "Result display means" refers to means for displaying the generated proposals.

[1389] "Customer information" refers to information such as the customer's smartphone and internet usage, dissatisfaction with communication speed, insufficient data capacity, and budget.

[1390] "Emotional data" refers to data captured from customers' voices and facial expressions.

[1391] A "server" is a computer system that includes data input means, sentiment analysis means, data analysis means, and proposal generation means.

[1392] System Overview

[1393] This invention is a powerful support system that enables even new crew members in sales to propose appropriate smartphones and internet plans to customers, and further incorporates an emotion engine that recognizes customer emotions. This system consists of the following main components.

[1394] 1. Data input means

[1395] 2. Emotion analysis method

[1396] 3. Data Analysis Methods

[1397] 4. Proposal generation means

[1398] 5. Results display means

[1399] Data input means

[1400] The terminal provides a screen for entering customer information. The user enters customer information on this screen. Input fields include the customer's smartphone and internet usage, dissatisfaction with communication speed, insufficient data capacity, budget, etc.

[1401] Specific example:

[1402] The user logs into their device and enters information such as "slow internet speed," "insufficient data capacity," and "monthly budget of up to 5000 yen." This entered data is then sent to the server.

[1403] Emotion analysis means

[1404] The terminal captures the voice and facial expressions of users and customers and transmits them to the server. The server analyzes this data using an emotion engine and provides the analysis results to the data analysis means and the suggestion generation means.

[1405] Specific example:

[1406] While the user interacts with a customer, the device's camera captures the customer's facial expressions in real time, and the microphone simultaneously records the customer's voice. This data is sent to a server, where an emotion engine generates analysis results such as "the customer is unhappy" or "the customer is relaxed."

[1407] Data analysis means

[1408] The server receives customer information and sentiment data sent from the terminal and analyzes it. By referring to past customer data and product information, it identifies the optimal plan based on the customer's needs and emotional state.

[1409] Specific example:

[1410] The server will suggest a high-speed plan for complaints about slow internet speeds and an unlimited plan for complaints about insufficient data capacity. Furthermore, if the customer is unhappy, the server will prioritize offering suggestions with more detailed explanations.

[1411] Proposal generation means

[1412] The server generates specific suggestions based on the analysis results. These suggestions include the plan name, price, features, and special offers. They also include information based on the analyzed sentiment data.

[1413] Specific example:

[1414] The server generates suggestions such as "5G plan" and "unlimited data plan," and adds explanations such as, "This plan offers fast communication speeds, allowing you to watch videos without any issues."

[1415] Results display means

[1416] The server generates a proposal and sends it to the terminal, which then displays it to the user. Based on this proposal, the user can quickly and appropriately explain the proposal to the customer.

[1417] Specific example:

[1418] The user reviews the offer displayed on their device screen and explains to the customer, "Switching to a 5G plan will dramatically improve your communication speed, and with an unlimited data plan, you'll never have to worry about running out of data."

[1419] Examples of input prompts for a generative AI model

[1420] 1. Prompt: "The customer is dissatisfied with their internet speed. Which plan should I suggest?"

[1421] 2. Prompt: "The customer is looking unhappy during the explanation. How should you respond?"

[1422] This system aims to improve customer satisfaction by enabling even rookie crew members to make high-quality suggestions on par with experienced staff, and by allowing them to make suggestions that reflect the customer's emotional state.

[1423] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1424] System program processing flow

[1425] Step 1:

[1426] The terminal provides a customer information input screen. The user logs into the terminal and inputs information such as the customer's smartphone and internet usage, dissatisfaction with communication speed, insufficient data capacity, and budget. The input data is sent from the terminal to the server.

[1427] Input: Customer's smartphone and internet usage, dissatisfaction with communication speed, insufficient data capacity, budget, etc.

[1428] Data processing: Organizing and formatting customer information

[1429] Output: Organized customer information data

[1430] Step 2:

[1431] The device captures the voice and facial expressions of users and customers. This data is then transmitted from the device to the server.

[1432] Input: Customer's voice, facial expressions

[1433] Data processing: Audio recording, facial expression capture.

[1434] Output: Audio data, facial expression data

[1435] Step 3:

[1436] The server receives the data sent in Step 1 and Step 2. It integrates and analyzes the received customer information and sentiment data. It also refers to and analyzes past customer data and product information.

[1437] Input: Organized customer information data, voice data, facial expression data, historical customer data, product information

[1438] Data processing: Identifying customer needs, analyzing emotional states.

[1439] Output: Analysis results (identification of the optimal plan, evaluation of emotional state)

[1440] Step 4:

[1441] The server generates suggestions based on the analysis results. The generated suggestions include the plan name, price, features, and special offers, and also incorporate information based on the customer's emotional state.

[1442] Input: Analysis results (identification of the optimal plan, evaluation of emotional state)

[1443] Data processing: Assembling the proposal

[1444] Output: Generated proposals

[1445] Step 5:

[1446] The server generates a proposal and sends it to the terminal. The terminal displays this proposal to the user, who then uses the proposal to explain it to the customer.

[1447] Input: Generated proposal

[1448] Data processing: Converting the proposed content to a display format.

[1449] Output: Suggestions displayed on the user's device

[1450] Examples of specific prompt statements in processing steps

[1451] Example of a prompt:

[1452] Prompt 1: "The customer is dissatisfied with their internet speed. Which plan should I suggest?"

[1453] Prompt 2: "The customer is looking unhappy during the explanation. How should you respond?"

[1454] Through the steps described above, this system supports even rookie crew members in making high-quality suggestions comparable to those of experienced individuals, and further improves customer satisfaction by making suggestions that take into account the customer's emotional state.

[1455] (Application Example 2)

[1456] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1457] Traditional proposal systems made it difficult for new staff to make appropriate suggestions to customers, sometimes leading to decreased customer satisfaction. Furthermore, they failed to consider customer emotions when making suggestions, making it difficult to improve service quality. The lack of technology to acquire and instantly display customer and emotional information in real time was also a challenge.

[1458] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes a data input means for receiving customer information and automatically generating appropriate suggestions based on the customer information; a data analysis means for analyzing the customer information received from the data input means; a suggestion generation means for generating suggestions based on the analysis results of the data analysis means; a result display means for displaying the generated suggestions; an emotion engine for analyzing customer emotion information; a means for adjusting appropriate suggestions based on the emotion information analyzed by the emotion engine; and a means for acquiring and displaying customer information and emotion information in real time using smart glasses or a head-mounted display. As a result, even new staff members can make appropriate suggestions while considering customer emotions, which enables improved customer satisfaction and service quality.

[1459] "Customer information" refers to information such as the customer's smartphone usage, dissatisfaction with communication speed, insufficient data capacity, and budget.

[1460] "Data entry means" refers to a device or system for receiving and entering customer information.

[1461] "Data analysis means" refers to a device or system for analyzing received customer information and providing the results to the proposal generation means.

[1462] "Proposal generation means" refers to a device or system that generates appropriate proposals for customers based on the results of data analysis means.

[1463] "Result display means" refers to a device or system for displaying the generated proposals to users or customers.

[1464] An "emotion engine" is a device or system that analyzes customer emotional information and provides the results to data analysis means and proposal generation means.

[1465] "Smart glasses" are glasses-type devices that users wear and that can display information in real time.

[1466] A "head-mounted display" is a device that is worn by the user to display information within their field of vision.

[1467] Modes for carrying out the invention

[1468] This invention is a system for new staff members to make appropriate suggestions to customers, and it utilizes smart glasses or a head-mounted display to analyze customer emotional information and display the suggested content in real time.

[1469] Hardware and software configuration

[1470] 1. Hardware:

[1471] Smart glasses (e.g., Google Glass)

[1472] Head-mounted display (e.g., Microsoft HoloLens)

[1473] 2. Software:

[1474] Face recognition software (e.g., OpenCV)

[1475] Speech recognition software (e.g., Google Cloud Speech-to-Text)

[1476] Database system (e.g., MySQL)

[1477] Server-side applications (e.g., Node.js)

[1478] System programs and their processes

[1479] 1. Data entry means:

[1480] The server captures customer facial expressions using cameras in smart glasses or head-mounted displays, and records and transcribes customer requests and complaints via voice input. It also inputs specific information such as customer smartphone usage and budget. This information functions as a data entry tool.

[1481] 2. Emotional Engine:

[1482] The server uses facial recognition software and speech recognition software to analyze captured customer facial expression data in real time. The analyzed emotional information is transmitted to the server and provided to the data analysis means and the suggestion generation means.

[1483] 3. Data analysis methods:

[1484] The server sends the collected customer information and sentiment data to a database system for analysis. Based on past customer data and product information, it identifies the optimal plan that best suits the customer's needs.

[1485] 4. Proposal generation means:

[1486] Based on the analysis results, the server generates appropriate smartphone and internet plans. This recommendation includes details about pricing and services, as well as explanations that take sentiment analysis results into account.

[1487] 5. Results display means:

[1488] The suggested content is displayed in real time on smart glasses or a head-mounted display. Store staff can check the displayed content and make suggestions to customers.

[1489] Specific example

[1490] Consider a scenario where a customer visits a physical store. A staff member wears smart glasses or a head-mounted display, capturing the customer's facial expressions with a camera. Voice recognition software automatically transcribes the customer's requests and complaints, such as "the internet speed is slow" or "there isn't enough data," into text. The system sends this information to a server in real time for analysis by an emotion engine. Based on the analysis results, the system generates suggestions such as a "5G plan" or an "unlimited data plan" and displays them on the smart glasses. Staff members can review this information in real time and make appropriate suggestions to the customer.

[1491] Example of a prompt

[1492] Follow these steps to create your customer support application:

[1493] 1. Use smart glasses to capture the customer's facial expressions, record their voice, and transcribe it into text.

[1494] 2. Use the emotion engine to analyze customer emotions in real time.

[1495] 3. Send customer information and sentiment data to the server for analysis.

[1496] 4. Refer to past database records to identify the optimal smartphone and internet plan for you.

[1497] 5. Generate the proposal content and display it in real time on the smart glasses.

[1498] This allows even new staff members to make appropriate suggestions to customers, just like experienced staff, which is expected to improve customer satisfaction.

[1499] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1500] Program processing steps

[1501] Step 1:

[1502] The server uses cameras on smart glasses or head-mounted displays to capture the customer's facial expressions and acquire audio. The input consists of captured image and audio data, while the output consists of facial expression data analyzed by facial recognition software and audio data transcribed into text through speech recognition software. Specifically, facial recognition software is used to identify emotions from facial expressions, and speech recognition software is used to convert the customer's words into text data.

[1503] Step 2:

[1504] The server transmits captured facial expression and audio data to the emotion engine for real-time emotion analysis. The input is facial expression data and transcribed audio data, and the output is the analyzed emotion information. Specifically, the emotion engine determines the customer's emotional state from the facial expressions and audio and provides the result to the data analysis system.

[1505] Step 3:

[1506] The server transmits customer information received from the data input means and sentiment data obtained from the sentiment engine to the database system, where it performs analysis while referring to past customer data and product information. The input is customer information and sentiment data, and the output is the analysis results for identifying the optimal plan. Specifically, the database system searches for a plan that matches the customer's requests and past data, and provides the analysis results to the proposal generation means.

[1507] Step 4:

[1508] The server operates a suggestion generation system that generates appropriate suggestions based on the results of the data analysis system. The input is the results of the data analysis system, and the output is the generated suggestion content. Specifically, the suggestion generation system generates a plan that includes fees and service details, and adds explanatory text that takes the sentiment analysis results into account.

[1509] Step 5:

[1510] The server transmits the generated proposals to smart glasses or a head-mounted display in real time, activating the result display device. The input is the generated proposals, and the output is the proposals displayed on the smart glasses or head-mounted display. Specifically, the display device shows the proposals to the staff, who then review the information and make proposals to the customer.

[1511] Thus, in the processing steps of this system, customer information and sentiment data can be collected in real time through smart glasses or head-mounted displays, and based on this, optimal suggestions can be generated and displayed.

[1512] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[1513] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1514] 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 this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[1515] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1516] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[1517] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[1518] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[1519] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[1520] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[1521] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[1522] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[1523] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[1524] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[1525] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[1526] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[1527] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[1528] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[1529] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[1530] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[1531] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[1532] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[1533] The following is further disclosed regarding the embodiments described above.

[1534] (Claim 1)

[1535] A data input means for receiving customer information and automatically generating appropriate proposals based on said customer information,

[1536] A data analysis means for analyzing customer information received from the data input means,

[1537] A proposal generation means that generates proposals based on the analysis results of the data analysis means,

[1538] A result display means for displaying the generated proposals,

[1539] A system that includes this.

[1540] (Claim 2)

[1541] The system according to claim 1, wherein the data analysis means performs analysis using past customer data and product information.

[1542] (Claim 3)

[1543] The system according to claim 1, wherein the proposal generation means filters a plurality of proposals based on specific conditions and selects the optimal proposal.

[1544] "Example 1"

[1545] (Claim 1)

[1546] An input means for receiving customer information and automatically generating appropriate suggestions based on said customer information,

[1547] An analysis means for analyzing customer information received from the input means,

[1548] A generation means that generates a proposal based on the analysis results of the aforementioned analysis means,

[1549] A display means for displaying the generated proposals,

[1550] A system that includes this.

[1551] (Claim 2)

[1552] The system according to claim 1, wherein the analysis means performs analysis using past customer databases and product information.

[1553] (Claim 3)

[1554] The system according to claim 1, wherein the generation means filters a plurality of proposals based on specific conditions and selects the optimal proposal.

[1555] "Application Example 1"

[1556] (Claim 1)

[1557] A data input means for receiving customer information and automatically generating appropriate proposals based on said customer information,

[1558] A data analysis means for analyzing customer information received from the data input means,

[1559] A proposal generation means that generates proposals based on the analysis results of the data analysis means,

[1560] A result display means for displaying the generated proposals,

[1561] A method for entering customer information using a smart device,

[1562] A means of generating analysis results using cloud service technology,

[1563] A method for analyzing customer data using machine learning models,

[1564] A means of displaying the generated suggestions on a wearable device,

[1565] A system that includes this.

[1566] (Claim 2)

[1567] The system according to claim 1, wherein the data analysis means performs analysis using past customer data and product information.

[1568] (Claim 3)

[1569] The system according to claim 1, wherein the proposal generation means filters a plurality of proposals based on specific conditions and selects the optimal proposal.

[1570] "Example 2 of combining an emotion engine"

[1571] (Claim 1)

[1572] A data input means for receiving customer information and automatically generating appropriate proposals based on said customer information,

[1573] A sentiment analysis means that transmits customer information received from the data input means and sentiment data captured from voice and facial expressions to a server.

[1574] A data analysis means that analyzes the data transmitted by the emotion analysis means and generates an optimal proposal based on the customer's needs and emotional state,

[1575] A proposal generation means that generates proposals based on the analysis results of the data analysis means,

[1576] A result display means for displaying the generated proposals,

[1577] A system that includes this.

[1578] (Claim 2)

[1579] The system according to claim 1, wherein the data analysis means performs analysis using past customer data and product information.

[1580] (Claim 3)

[1581] The system according to claim 1, wherein the proposal generation means filters a plurality of proposals based on specific conditions and selects the optimal proposal.

[1582] "Application example 2 of combining emotional engines"

[1583] (Claim 1)

[1584] A data input means for receiving customer information and automatically generating appropriate proposals based on said customer information,

[1585] A data analysis means for analyzing customer information received from the data input means,

[1586] A proposal generation means that generates proposals based on the analysis results of the data analysis means,

[1587] A result display means for displaying the generated proposals,

[1588] An emotion engine that analyzes customer emotional information,

[1589] A means for adjusting appropriate suggestions based on emotional information analyzed by the aforementioned emotion engine,

[1590] A means of acquiring and displaying customer information and sentiment information in real time using smart glasses or head-mounted displays,

[1591] A system that includes this.

[1592] (Claim 2)

[1593] The system according to claim 1, wherein the data analysis means performs analysis using past customer data and product information.

[1594] (Claim 3)

[1595] The system according to claim 1, wherein the proposal generation means filters a plurality of proposals based on specific conditions and selects the optimal proposal. [Explanation of Symbols]

[1596] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A data input means for receiving customer information and automatically generating appropriate proposals based on said customer information, A data analysis means for analyzing customer information received from the data input means, A proposal generation means that generates proposals based on the analysis results of the data analysis means, A result display means for displaying the generated proposals, A system that includes this.

2. The system according to claim 1, wherein the data analysis means performs analysis using past customer data and product information.

3. The system according to claim 1, wherein the proposal generation means filters a plurality of proposals based on specific conditions and selects the optimal proposal.

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