AI-based artificial customer service auxiliary processing method and device, and television

Abstract

The invention discloses an AI-based artificial customer service auxiliary processing method and device and a television, and the method comprises the steps: obtaining the dialogue information of a front-end robot and a user in real time, and generating a front-end dialogue record; judging whether a manual customer service processing application switching instruction is detected or not; when a manual customer service processing application instruction is detected, controlling, triggering and automatically calling a preset AI library, analyzing and summarizing the front-end dialogue record, determining user problem type data of the front-end dialogue record, and searching preset solution suggestion information corresponding to the user problem type data of the front-end dialogue record; and according to the searched solution suggestion information corresponding to the user question type data recorded by the front-end conversation, outputting the solution suggestion information to the user side. According to the method, the character summarization capability of the AI is utilized to automatically summarize the user appeals, and the response efficiency of customer service staff to the user appeals is improved.

Description

Technical Field

[0001] The present invention relates to the field of artificial intelligence technology, and in particular to an AI-based artificial customer service auxiliary processing method, device, AI terminal and storage medium. Background Art

[0002] Nowadays, customer service systems first receive users through robots, allowing users to describe the problem. When the robot finds that it cannot solve the problem on its own, it will guide the user to switch to manual customer service for processing.

[0003] In the prior art, since the user may have input a lot of information, the customer service staff needs to spend a lot of time viewing the user's previous problem descriptions before they can have a certain understanding of the user's problem and then actually start to receive the user. This process is time-consuming, and different customer service staff have different abilities, which may lead to missing important information, resulting in deviations in the understanding of the user's problem, thereby greatly affecting the efficiency of receiving users.

[0004] Therefore, the existing technology still needs to be improved and developed. Summary of the invention

[0005] The technical problem to be solved by the present invention is to provide an AI-based manual customer service auxiliary processing method, device, AI terminal and storage medium to address the problems and defects of the above-mentioned prior art. The present invention utilizes the text summarizing ability of AI to automatically summarize user demands and improve the response efficiency of customer service personnel to user demands.

[0006] The technical solution adopted by the present invention to solve the problem is as follows:

[0007] An artificial customer service assisted processing method based on AI, comprising:

[0008] Obtain the conversation information between the front-end robot and the user in real time, and generate the front-end conversation record;

[0009] Determine whether an instruction to apply for switching to manual customer service processing is detected;

[0010] When an instruction to switch to manual customer service is detected, the control triggers the automatic call of the preset AI library, analyzes and summarizes the front-end dialogue record, determines the user problem type data of the front-end dialogue record, and searches for preset solution suggestion information corresponding to the user problem type data of the front-end dialogue record;

[0011] The solution suggestion information corresponding to the user problem type data of the front-end dialogue record is found and the solution suggestion information is output to the user terminal.

[0012] The AI-based manual customer service auxiliary processing method, wherein the step of obtaining the conversation information between the front-end robot and the user in real time and generating the front-end conversation record includes:

[0013] Various user problem type data and corresponding solution suggestion information are pre-entered and stored in the AI ​​library.

[0014] The AI-based manual customer service assisted processing method, wherein the user problem type data includes: problem type, user demand, order information or product information.

[0015] In the AI-based manual customer service auxiliary processing method, the step of acquiring the conversation information between the front-end robot and the user in real time and generating the front-end conversation record includes:

[0016] Check whether there is a customer service phone line connection;

[0017] When a customer service call is detected, the front-end robot is first controlled to automatically answer the customer service call and conduct a conversation;

[0018] Acquire the conversation information between the front-end robot and the user in real time, and generate front-end conversation records.

[0019] The AI-based manual customer service assisted processing method, wherein the step of determining whether an instruction to apply for switching to manual customer service processing is detected comprises:

[0020] During the conversation between the front-end robot and the user, a check is performed to see whether an instruction to switch to manual customer service has been received.

[0021] The AI-based manual customer service auxiliary processing method, wherein when an instruction to switch to manual customer service is detected, the control triggers the automatic call of a preset AI library, analyzes and summarizes the front-end dialogue record, determines the user problem type data of the front-end dialogue record, and searches for preset solution suggestion information corresponding to the user problem type data of the front-end dialogue record, including the following steps:

[0022] When an instruction to switch to manual customer service is detected, the control triggers the automatic call of the preset AI library to analyze and summarize the front-end conversation record, including: the type of question asked, user demands, order information or product information;

[0023] Determine the user question type data of the front-end dialogue record according to the summary content;

[0024] Based on the determined user question type data of the front-end dialogue record, searching the preset AI library for solution suggestion information corresponding to the user question type data of the front-end dialogue record;

[0025] And extract the solution suggestion information corresponding to the user problem type data of the front-end dialogue record.

[0026] The AI-based manual customer service assisted processing method, wherein the step of outputting the solution suggestion information to the user terminal according to the found solution suggestion information corresponding to the user problem type data of the front-end dialogue record includes:

[0027] Obtaining solution suggestion information corresponding to the user problem type data of the front-end conversation record;

[0028] The solution suggestion information corresponding to the user problem type data in the front-end dialogue record is displayed on the terminal computer of the manual customer service according to a preset reminder format, and the solution suggestion information is output to the user end.

[0029] An AI-based artificial customer service auxiliary processing device, wherein the device comprises:

[0030] The first pre-setting module is used to pre-enter various user problem type data and corresponding solution suggestion information and store them in the AI ​​library;

[0031] The acquisition and generation module is used to acquire the conversation information between the front-end robot and the user in real time and generate the front-end conversation record;

[0032] A judgment module is used to judge whether an instruction to apply for switching to manual customer service processing is detected;

[0033] A calling and searching module is used to control the triggering of automatically calling a preset AI library when an instruction to switch to manual customer service is detected, analyze and summarize the front-end conversation record, determine the user problem type data of the front-end conversation record, and search for preset solution suggestion information corresponding to the user problem type data of the front-end conversation record;

[0034] The output control module is used to output the solution suggestion information to the user terminal according to the found solution suggestion information corresponding to the user problem type data in the front-end dialogue record.

[0035] An AI terminal includes a memory and one or more programs, wherein the one or more programs are stored in the memory and are configured to be executed by one or more processors to include the method for executing any one of the methods described above.

[0036] A non-transitory computer-readable storage medium, wherein when instructions in the storage medium are executed by a processor of an electronic device, the electronic device is enabled to execute any one of the methods described above.

[0037] Beneficial effects of the present invention: The present invention provides an AI-based manual customer service auxiliary processing method, device, AI terminal and storage medium, which automatically summarizes the problem content and related information fed back by users based on AI's powerful text summarizing ability, so that after customer service personnel access, they can directly clarify user problems and related information based on the summary, thereby improving reception efficiency and providing convenience for users. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0039] Figure 1 It is a flowchart of the AI-based manual customer service assisted processing method provided in an embodiment of the present invention.

[0040] Figure 2 It is a flowchart of the AI-based manual customer service assisted processing method provided in an embodiment of the present invention.

[0041] Figure 3 It is a principle block diagram of an embodiment of an AI-based artificial customer service auxiliary processing device provided by the present invention.

[0042] Figure 4 It is a block diagram of the internal structure principle of the AI ​​terminal provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0043] In order to make the purpose, technical solution and advantages of the present invention clearer and more specific, the present invention is further described in detail below with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0044] It should be noted that if the embodiments of the present invention involve directional indications (such as up, down, left, right, front, back, etc.), the directional indications are only used to explain the relative position relationship, movement status, etc. between the components under a certain specific posture (as shown in the accompanying drawings). If the specific posture changes, the directional indication will also change accordingly.

[0045] Robot customer service refers to an automated service system created using artificial intelligence technology, designed to provide real-time consultation and support to customers. Robot customer service usually simulates the role of human customer service to meet user needs and solve problems through technologies such as natural language processing (NLP), machine learning, and dialogue management.

[0046] Therefore, the present invention proposes an AI-based manual customer service assisted processing method, which automatically summarizes the problem content and related information fed back by users based on AI's powerful text summarizing ability, so that after customer service personnel access the site, they can directly clarify user problems and related information based on the summary, thereby improving reception efficiency.

[0047] like Figure 1 As shown, an AI-based artificial customer service assisted processing method according to Embodiment 1 of the present invention includes the following steps:

[0048] Step S100: Acquire the conversation information between the front-end robot and the user in real time, and generate a front-end conversation record;

[0049] The present invention is explained by taking the customer service system as an example. In specific implementation, when a user calls the customer service phone, the customer service system will be connected. In the process of the user interacting with the front-end chat robot, the system can instantly capture the content of each conversation. This real-time data collection is usually achieved through technologies such as API or WebSocket to ensure that information can be transmitted and processed immediately.

[0050] Then, generating the front-end conversation record is to organize the acquired conversation information into a viewable and storable record. This record may include information such as the user's question, the robot's response, and the conversation timestamp, and is displayed on the user interface or stored in the back-end database for future retrieval or analysis.

[0051] In this step, real-time recording allows users to easily review previous conversations, which is especially helpful for them to understand the handling process of historical issues when consulting on complex issues. By analyzing conversation records, common problems or user feedback can be discovered, thereby optimizing the chatbot's response strategy and improving the overall service quality and efficiency.

[0052] Furthermore, the step S100 specifically includes:

[0053] Step S101: Check whether there is a customer service phone connection

[0054] This step is the initial stage of the system and is used to monitor whether there are customers calling the customer service telephone. The present invention can use automated telephone monitoring technology (such as call management system) to identify incoming calls.

[0055] Step S102: When a customer service call is detected, firstly, the front-end robot is controlled to automatically answer the customer service call and have a conversation;

[0056] In this step, after confirming the incoming call, the chatbot is automatically instructed to answer the call. This means that the robot can start interacting with the customer, providing basic information and solutions, or collecting customer questions in preparation for subsequent manual service.

[0057] S103, obtaining the conversation information between the front-end robot and the user in real time, and generating a front-end conversation record;

[0058] In this step, during the conversation between the robot and the customer, the present invention will instantly record all the conversation content, including the customer's inquiry, the robot's response, etc. These records can not only be in text form, but also include timestamps and related conversation metadata.

[0059] The benefit of the above steps is that by automatically answering and handling common questions, the chatbot can effectively save the time of customers and customer service staff, allowing customers to obtain the required information faster. And the robot can answer the phone at any time, while manual customer service may be limited by working hours. This means that no matter when the customer calls, they can get an immediate response, improving customer satisfaction. In addition, the present invention can provide a basis for subsequent data analysis through real-time acquisition of conversation records. By analyzing these data, common problems can be identified, and then services can be improved or products optimized. If the robot cannot solve the customer's problem, the conversation can be smoothly transferred to the manual customer service, and the manual customer service can quickly understand the problem based on the conversation record, so as to provide targeted suggestions.

[0060] For example, when an Internet service company provides a technical support phone number, the user dials the customer service phone number, and the system first executes S101 to detect an incoming call. Then, it executes S102. The call is picked up, and the front-end robot begins to ask the user about the specific problem they encountered, such as: "What problem did you encounter? Is it a login problem or a software installation problem?" The user describes the difficulty they encountered, and the robot provides guidance based on the preset answer.

[0061] During this communication process, the system executes S103 and records the content of the user's questions and the robot's answers in real time. The record may include information such as time, user feedback, and solutions provided by the robot. In this way, when the user's problem has not been solved and manual customer service intervention is required, the customer service staff can immediately view the previous conversation records, quickly understand the user's problem, avoid asking questions again, and improve the continuity and efficiency of the service. It can be seen that the design of the steps of the present invention can not only improve customer service efficiency and optimize customer experience, but also provide valuable data support for enterprises.

[0062] Furthermore, in the embodiment of the present invention, before the specific implementation: various user problem type data and corresponding solution suggestion information need to be pre-entered and stored in the AI ​​library (artificial intelligence library). The user problem type data includes: problem type, user demand, order information or product information.

[0063] The main goal of this step is to build an efficient knowledge base that covers the various types of questions that users may ask and their corresponding solutions. This knowledge base should contain information at multiple levels so that the team can query at any time and respond to user needs efficiently.

[0064] Specifically, the user question type data of the embodiment of the present invention includes the following aspects:

[0065] 1) Problem type: various types of problems commonly encountered by users, such as account problems, payment problems, logistics inquiries, technical support, etc.

[0066] 2) User demands: The user’s specific expectations and demands for the issue, such as requesting a refund, checking order status, or obtaining product usage guidance.

[0067] 3) Order information or product information: Background information directly related to the user's question, such as order number, purchased product model or specifications, so as to provide more specific suggestions.

[0068] For example, when an e-commerce platform wants to improve customer support efficiency, the company will first collect and organize common types of questions (such as "how to refund", "order not shipped", "how to change address", etc.) and enter the corresponding solutions for each problem. For example:

[0069] Problem type 1: Refund request; User demand: The user wants to know the refund process; Solution: Provide a detailed refund step link and explain that the refund time is generally 3-5 working days.

[0070] Problem type 2: Logistics inquiry; User demand: The user inquires about the current status of the order; Solution: Provide an online link and customer service phone number for logistics inquiry so that users can immediately obtain the latest logistics information.

[0071] Question type 3: Product usage issue; User request: User asks how to set up the product; Solution: Attach a link to the product manual or video tutorial.

[0072] Therefore, establishing such an AI knowledge base not only optimizes the customer service process, but also improves the overall user experience. It is convenient to remind customer service staff to reply in time when transferring to manual service. It can display relevant solutions based on the entered knowledge base information, thereby quickly responding to user needs.

[0073] The benefit of this step is that since a large number of common problems and corresponding solutions have been pre-stored in the knowledge base, the team can quickly obtain this information after receiving customer inquiries, significantly improving the efficiency of problem solving. In addition, the construction of the knowledge base allows many common problems to be directly solved through automatic response systems (such as chatbots), reducing dependence on manual customer service and saving human resources.

[0074] Step S200, determining whether an instruction for applying to switch to manual customer service processing is detected;

[0075] In this step, during the conversation between the front-end robot and the user, it is detected whether the instruction to switch to manual customer service is received. The core task of this step is to monitor the user's input in real time during the interaction between the user and the chat robot to determine whether the user has made a request to switch to manual customer service. This process is usually implemented through natural language processing (NLP) technology. The system can analyze the user's language expression and identify instructions or keywords related to "switching to manual customer service."

[0076] For example, the instructions that a user may use include: "I want to chat with a human customer service representative", "Please transfer me to a human customer service representative", "This is not what I want, let someone else handle it", etc. After detecting these instructions, the present invention will trigger the relevant process and transfer the conversation from the robot to the human customer service representative.

[0077] The benefit of doing so is that, by implementing detection, the present invention enables the system to quickly identify changes in user needs, so that when the user feels that the robot cannot meet their problems, they can quickly get manual help, thereby improving user satisfaction. If a user encounters difficulties when interacting with the robot and cannot get a satisfactory solution, being able to quickly switch to manual customer service can reduce the user's frustration and avoid negative impressions of the brand due to information lags. Moreover, each user's needs and problems are unique. Once it is detected that the user wants to switch to manual customer service, the company can arrange customer service representatives with professional skills and experience to handle it, providing more personalized and accurate help.

[0078] Step S300: When an instruction to switch to manual customer service is detected, the control triggers the automatic call of the preset AI library, analyzes and summarizes the front-end dialogue record, determines the user problem type data of the front-end dialogue record, and searches for preset solution suggestion information corresponding to the user problem type data of the front-end dialogue record;

[0079] The core of this step is that when a user requests to be transferred to manual customer service, the present invention not only simply switches to manual customer service, but also automatically analyzes the user's previous conversation records to obtain key information.

[0080] Specifically, when a user makes a switching request, the present invention will quickly call the pre-established AI knowledge base (artificial intelligence knowledge base) to prepare for analyzing the conversation record between the user and the robot. The system will summarize the entire conversation and extract key data, such as the user's question type, demands, and related information. This can be achieved through natural language processing technology, analyzing context and keywords to understand the user's real needs.

[0081] After the present invention has identified the type of user's question, it will search the knowledge base to find solutions and suggestions related to the type of question. This information will help manual customer service understand user needs more quickly, thereby providing more effective services.

[0082] For example, when a user in an airline's online customer service system just asked about the flight change policy through a chatbot, the robot answered relevant information. However, during the conversation, the user said: "This is not what I want, let's transfer it to a human customer service!".

[0083] When this request is detected, the system will immediately trigger the automatic call to the preset AI library and start analyzing the previous conversation records. The preset AI library concludes that the user's main problem is "flight change" and understands the user's concerns. After finding the corresponding solution, it provides the manual customer service with relevant information, such as the specific terms and fees for flight changes, and how to help users make actual changes.

[0084] The present invention, when manual customer service is connected, can quickly access this information and communicate with the user: "Thank you for your patience! Regarding your flight change, I learned from the system that you are concerned about the change policy. What specific issues do you want to know?" In this way, manual customer service can help users more efficiently, improve the experience and solve problems at the same time.

[0085] It can be seen that the implementation of this step in the present invention not only improves service efficiency, but also ensures that users can get consistent and efficient help when switching to manual customer service, giving the company a more competitive advantage in customer service quality.

[0086] The advantage of the present invention is that, by analyzing the front-end conversation records, the manual customer service can quickly grasp the user's problem, thereby avoiding the user's repeated description of the situation, saving time, and improving service efficiency. And the problem type and user demands automatically extracted by the system can help the manual customer service accurately locate the problem, making the customer service response more targeted and easier to find a suitable solution. In addition, the present invention provides personalized services and responds to user needs in a timely manner, which can improve customer satisfaction and cultivate good brand loyalty.

[0087] Furthermore, the step S300 specifically includes:

[0088] S301, when an instruction to switch to manual customer service is detected, the control trigger automatically calls the preset AI library to analyze and summarize the front-end conversation record, and the summary includes: the type of question asked, user demands, order information or product information;

[0089] In this step, when it is detected that the user requests to switch to manual customer service, the present invention will automatically call the preset AI knowledge base and start analyzing the conversation record between the user and the robot. The results of the analysis include several key elements: the type of question raised by the user, the user's actual demands, and the order information or product information related to it. This analysis process mainly relies on natural language processing technology to ensure that the user's needs and background can be accurately understood.

[0090] S302, determining the user question type data of the front-end dialogue record according to the summary content;

[0091] In this step, the present invention will clarify the specific type of the user's question based on the analysis results of S301. The determination of this type depends not only on the matching of keywords, but also on the understanding of the context to ensure the accuracy of the classification. For example, for a user asking "how to apply for a return", the question type will be defined as "return application".

[0092] S303: based on the determined user problem type data of the front-end dialogue record, searching the preset AI library for solution suggestion information corresponding to the user problem type data of the front-end dialogue record;

[0093] In this step, the present invention will search for appropriate solutions and suggestions from the pre-entered AI knowledge base according to the problem type determined in step S302. This matching process ensures that the human customer service can quickly access effective information to solve the user's problem and provide users with more personalized services.

[0094] S304, extracting solution suggestion information corresponding to the user problem type data in the front-end dialogue record;

[0095] Finally, after the above analysis, classification and matching, the embodiment of the present invention will extract solutions related to the user's problem and prepare this information so that the manual customer service can use it immediately when taking over. This process can ensure the accurate transmission of information so that the customer service can take quick action to meet the user's needs.

[0096] For example, imagine a customer service system of an online shopping platform. A user asks a chatbot: "I want to return the coat I bought last week, but I'm not sure how to do it." After the user sends this message, the system detects that the user has requested to switch to human customer service. The following process can be initiated:

[0097] S301: The system analyzes this conversation and identifies that the user's question type is "return application" and the user's request is "how to return the goods", and records the relevant order information.

[0098] S302: The system confirms that the user's question type is "return application", which ensures the accuracy of subsequent processing.

[0099] S303: Based on this type of question, the present invention searches for solutions related to the return application from the AI ​​knowledge base, such as "Please prepare the order number and reason for return, and then follow the return process on our website" and related links.

[0100] S304: Finally, the system extracts these suggestions and prepares guidance information for human customer service. After the customer service takes over, they can say to the user: "I see that you want to return the product. If you have the order number, I can help you process it or provide a detailed return process."

[0101] It can be seen that the present invention can greatly improve the efficiency and quality of customer service through this series of steps, and ensure that users can obtain systematic and rapid responses when transferring to manual customer service.

[0102] Through the above steps, the present invention enables manual customer service to obtain user background information and problem type immediately when taking over, reducing the time required to inquire about user background and improving response efficiency. In addition, automated analysis and solution matching can reduce human errors and ensure that user problems are properly handled. In addition, customer service can provide users with higher professionalism and pertinence, thereby improving overall customer satisfaction.

[0103] Step S400: outputting the solution suggestion information to the user terminal according to the found solution suggestion information corresponding to the user problem type data in the front-end dialogue record.

[0104] In the embodiment of this step, in this step, the present invention provides specific suggestion information to the user based on the solution related to the user's problem type found previously. Specifically, it includes: 1) Extracting the search results. The present invention first extracts the solution corresponding to the user's problem type from the preset AI knowledge base. This information can be in various forms such as FAQ lists, specific step-by-step guides, or even video links. 2) Structured information. To ensure the clarity and readability of the information, the content of the solution will be structured in an easy-to-understand manner. It may include step-by-step instructions, diagrams, or recommended links. 3) Output information. Finally, the system pushes these solutions to the user end in a friendly interactive manner to ensure that the user can clearly see the suggestions and understand the execution steps.

[0105] For example, when a user chats with an online customer service representative on an online travel agency platform, he asks: "I have a problem booking a hotel, can you help me?" After the previous steps, the present invention can confirm that the user's problem type is "hotel booking problem" and search for solutions related to this from the AI ​​knowledge base, and finally find the following information:

[0106] 1) Check your network connection.

[0107] 2) Make sure all information is filled in correctly, including check-in and check-out dates.

[0108] 3) If the problem persists, please visit our FAQ page.

[0109] On this basis, the present invention structures these solutions and outputs the following message to the user end:

[0110] "Hello! Regarding your hotel reservation issue, please try the following steps:

[0111] Please check your network connection.

[0112] Make sure all the information you fill in including the check-in and check-out dates are correct.

[0113] If the problem persists, you can click here to view our FAQ page for further help".

[0114] In this way, users can get solutions quickly and follow the steps, which not only speeds up the problem-solving process but also allows users to feel the efficiency and professionalism of the company.

[0115] In this way, the present invention can proactively provide practical solutions, so that users can solve the problems they encounter more quickly, thereby improving their satisfaction with customer service support. After obtaining clear and detailed solutions, users will have fewer doubts, thereby reducing the need for further inquiries and optimizing customer service resources. Efficient and professional services can establish a positive brand image in the minds of customers, make users feel cared for and supported, and help improve customer loyalty. In addition, the solution output and its effects (such as user feedback or resolution rate) recorded by the system of the present invention can provide a basis for later data analysis, helping enterprises to make strategic adjustments in a timely manner.

[0116] In a further embodiment, the step S400 specifically includes:

[0117] S401, obtaining solution suggestion information corresponding to the user problem type data of the front-end dialogue record;

[0118] In this step, the present invention will focus on obtaining solutions that match the user's problem type that was previously identified. This acquisition process is based on the problem type defined in the previous step, and will extract accurate suggestions and information corresponding to it from the AI ​​knowledge base. These suggestions may be relevant operating steps, solution links, or other support content that the user may need. The purpose is to ensure that the customer service can quickly obtain effective help information for use in the next service.

[0119] S402, displaying the solution suggestion information corresponding to the user problem type data in the front-end dialogue record on the terminal computer of the manual customer service according to a preset reminder format, so that the user end outputs the solution suggestion information;

[0120] In this step, the solution suggestions obtained will be displayed on the terminal of the manual customer service in a preset format. This means that the solution of the present invention is not just a simple text, but may also include charts, step lists and even links, making the information more intuitive and easy to understand. This formatted display is intended to improve the efficiency and professionalism of manual customer service when communicating with users. The present invention can also ensure the prominence of important information through the reminder format, helping manual customer service to successfully solve customer problems.

[0121] For example, when a user chats with an online customer service representative in a customer service system of a financial services company, he asks: "I want to know the status of my loan application. Can you tell me the progress?" After the analysis of the steps of the present invention, it is confirmed that the user's question type is "loan application status inquiry". Then the embodiment of the present invention finds the corresponding solution according to this question type, which may include the following information:

[0122] A step to query the status (such as accessing a specific client area).

[0123] Provides common status query results (such as "under review", "approved", etc.).

[0124] After executing step S401, the system successfully obtains this information. Next, in step S402, the system displays this information on the customer service terminal in the following format:

[0125] User question: Loan application status inquiry;

[0126] Suggested steps:

[0127] 1. Please visit our [Online Inquiry System](link) and enter their loan application number to obtain the latest status.

[0128] 2. Common status:

[0129] -Under review

[0130] - Approved

[0131] -Rejected

[0132] In this way, in the embodiment of the present invention, after seeing this information, the manual customer service can quickly explain to the user: "Regarding the status of your loan application, you can visit our online inquiry system and enter the application number to obtain the latest information." In this way, the customer service not only responds to the user's request quickly, but also provides detailed guidance, demonstrates a professional service level, and further enhances user satisfaction.

[0133] The advantage of the present invention is that manual customer service can quickly find information related to user problems, reducing time waste and being able to handle customer needs more promptly. The solution provided by the present invention is based on the analysis of existing data, which can ensure the accuracy of information and reduce the probability of incorrect answers due to insufficient knowledge of manual customer service. In addition, by displaying information in a clear and structured reminder format, customers can experience a professional service experience, thereby enhancing their sense of trust and satisfaction. Moreover, when facing different problems, customer service can quickly refer to specific solutions to help them respond to customers' changing needs more flexibly.

[0134] Based on the above embodiments, the present invention further describes in detail an AI-based artificial customer service auxiliary processing method of the present invention through a specific application embodiment:

[0135] An AI-based artificial customer service assisted processing method of this specific application embodiment is as follows: Figure 2 As shown, this specific embodiment includes the following steps:

[0136] Step S10, the system enters the user's question type data and proceeds to step S11;

[0137] Step S11, determine whether the user applies to switch to manual customer service, if yes, proceed to step S12, if no, proceed to step S14;

[0138] Step S12, the system summarizes the user's previous problem description information, generates a summary, displays it, and then enters step S13;

[0139] Step S13: The customer service staff obtains a summary of the problem, receives the user, and responds to the user, and then proceeds to step S14;

[0140] Step S14, end.

[0141] That is, in a specific embodiment of the present invention, user problem type data, solution suggestions and other information are collected and entered in advance. When a user applies to switch to manual customer service, the system is triggered to automatically call the summary capability of the AI ​​library to summarize the conversation record between the user and the reception robot. The summary content includes: problem type, user demands, order information or product information, and solution suggestions. When applying to switch to manual service, the present invention can immediately receive the user based on the summary content output by the system after the customer service personnel formally intervenes. It can be seen that the present invention uses the text summary capability of AI to automatically summarize user demands and improve the efficiency of customer service personnel in responding to user demands.

[0142] Exemplary Devices

[0143] like Figure 3 As shown, an embodiment of the present invention provides an AI-based artificial customer service auxiliary processing device, the device comprising:

[0144] A first pre-setting module 310 is used to pre-enter various user problem type data and corresponding solution suggestion information and store them in the AI ​​library;

[0145] The acquisition and generation module 320 is used to acquire the conversation information between the front-end robot and the user in real time and generate the front-end conversation record;

[0146] The judgment module 330 is used to judge whether an instruction to apply for switching to manual customer service processing is detected;

[0147] The calling and searching module 340 is used to control the triggering of automatically calling the preset AI library when an instruction to switch to manual customer service is detected, analyze and summarize the front-end dialogue record, determine the user problem type data of the front-end dialogue record, and search for preset solution suggestion information corresponding to the user problem type data of the front-end dialogue record;

[0148] The output control module 350 is used to output the solution suggestion information to the user terminal according to the found solution suggestion information corresponding to the user problem type data in the front-end dialogue record, as described above.

[0149] Based on the above embodiment, the present invention further provides an AI terminal, which can be a server, and its principle block diagram can be as follows: Figure 4As shown. The AI ​​terminal includes a processor, a memory, a network interface, a display screen, and a database connected via a system bus. Among them, the processor of the AI ​​terminal is used to provide computing and control capabilities. The memory of the AI ​​terminal includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The network interface of the AI ​​terminal is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, an AI-based artificial customer service auxiliary processing method is implemented. The database of the AI ​​terminal is used to store an AI-based artificial customer service auxiliary processing program.

[0150] Those skilled in the art will understand that Figure 4 The principle block diagram shown in the figure is only a block diagram of a partial structure related to the solution of the present invention, and does not constitute a limitation on the AI ​​terminal to which the solution of the present invention is applied. The specific AI terminal may include more or fewer components than those shown in the figure, or combine certain components, or have a different component arrangement.

[0151] In one embodiment, an AI terminal is provided, comprising a memory and one or more programs, wherein the one or more programs are stored in the memory and are configured to be executed by one or more processors, wherein the one or more programs include instructions for performing the following operations:

[0152] Obtain the conversation information between the front-end robot and the user in real time, and generate the front-end conversation record;

[0153] Determine whether an instruction to apply for switching to manual customer service processing is detected;

[0154] When an instruction to switch to manual customer service is detected, the control triggers the automatic call of the preset AI library, analyzes and summarizes the front-end dialogue record, determines the user problem type data of the front-end dialogue record, and searches for preset solution suggestion information corresponding to the user problem type data of the front-end dialogue record;

[0155] The solution suggestion information corresponding to the user problem type data of the front-end dialogue record is found and the solution suggestion information is output to the user terminal, as described above.

[0156] The step of obtaining the conversation information between the front-end robot and the user in real time and generating the front-end conversation record includes:

[0157] Various user problem type data and corresponding solution suggestion information are pre-entered and stored in the AI ​​library.

[0158] The user question type data includes: question type, user demand, order information or product information.

[0159] The step of acquiring the conversation information between the front-end robot and the user in real time and generating the front-end conversation record includes:

[0160] Check whether there is a customer service phone line connection;

[0161] When a customer service call is detected, the front-end robot is first controlled to automatically answer the customer service call and conduct a conversation;

[0162] Acquire the conversation information between the front-end robot and the user in real time, and generate front-end conversation records.

[0163] The step of determining whether an instruction to apply for switching to manual customer service processing is detected includes:

[0164] During the conversation between the front-end robot and the user, a check is performed to see whether an instruction to switch to manual customer service has been received.

[0165] Among them, when the instruction to apply for switching to manual customer service processing is detected, the control triggers the automatic call of the preset AI library, analyzes and summarizes the front-end dialogue record, determines the user problem type data of the front-end dialogue record, and searches for the preset solution suggestion information corresponding to the user problem type data of the front-end dialogue record, including:

[0166] When an instruction to switch to manual customer service is detected, the control triggers the automatic call of the preset AI library to analyze and summarize the front-end conversation record, including: the type of question asked, user demands, order information or product information;

[0167] Determine the user question type data of the front-end dialogue record according to the summary content;

[0168] Based on the determined user question type data of the front-end dialogue record, searching the preset AI library for solution suggestion information corresponding to the user question type data of the front-end dialogue record;

[0169] And extract the solution suggestion information corresponding to the user problem type data of the front-end dialogue record.

[0170] The step of outputting the solution suggestion information to the user terminal according to the found solution suggestion information corresponding to the user problem type data of the front-end dialogue record includes:

[0171] Obtaining solution suggestion information corresponding to the user problem type data of the front-end conversation record;

[0172] The solution suggestion information corresponding to the user problem type data in the front-end dialogue record is displayed on the terminal computer of the manual customer service according to the preset reminder format, and the solution suggestion information is outputted by the user end, as described above.

[0173] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided by the present invention can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0174] In summary, the present invention provides an AI-based manual customer service auxiliary processing method, device, AI terminal and storage medium. Based on the powerful text summarizing ability of AI, it automatically summarizes the problem content and related information fed back by users, so that after the customer service personnel access the system, they can directly clarify the user's problems and related information based on the summary, thereby improving reception efficiency and providing convenience for users.

Claims

1. An AI-based artificial customer service assisted processing method, characterized in that: include: Obtain the conversation information between the front-end robot and the user in real time, and generate the front-end conversation record; Determine whether an instruction to apply for switching to manual customer service processing is detected; When an instruction to switch to manual customer service is detected, the control triggers the automatic call of the preset AI library, analyzes and summarizes the front-end dialogue record, determines the user problem type data of the front-end dialogue record, and searches for preset solution suggestion information corresponding to the user problem type data of the front-end dialogue record; The solution suggestion information corresponding to the user problem type data of the front-end dialogue record is found and the solution suggestion information is output to the user terminal.

2. The AI-based artificial customer service assisted processing method according to claim 1, characterized in that: The step of obtaining the conversation information between the front-end robot and the user in real time and generating the front-end conversation record includes: Various user problem type data and corresponding solution suggestion information are pre-entered and stored in the AI ​​library.

3. The AI-based artificial customer service assisted processing method according to claim 1, characterized in that: The user question type data includes: question type, user demand, order information or product information.

4. The AI-based artificial customer service assisted processing method according to claim 1, characterized in that: The step of acquiring the conversation information between the front-end robot and the user in real time and generating the front-end conversation record comprises: Check whether there is a customer service phone line connection; When a customer service call is detected, the front-end robot is first controlled to automatically answer the customer service call and conduct a conversation; Acquire the conversation information between the front-end robot and the user in real time, and generate front-end conversation records.

5. The AI-based artificial customer service assisted processing method according to claim 1, characterized in that: The step of determining whether an instruction to apply for switching to manual customer service processing is detected comprises: During the conversation between the front-end robot and the user, a check is performed to see whether an instruction to switch to manual customer service has been received.

6. The AI-based artificial customer service assisted processing method according to claim 1, characterized in that: The step of automatically calling a preset AI library when detecting an instruction to switch to manual customer service processing, analyzing and summarizing the front-end dialogue record, determining the user problem type data of the front-end dialogue record, and searching for preset solution suggestion information corresponding to the user problem type data of the front-end dialogue record includes: When an instruction to switch to manual customer service is detected, the control triggers the automatic call of the preset AI library to analyze and summarize the front-end conversation record, including: the type of question asked, user demands, order information or product information; Determine the user question type data of the front-end dialogue record according to the summary content; Based on the determined user question type data of the front-end dialogue record, searching the preset AI library for solution suggestion information corresponding to the user question type data of the front-end dialogue record; And extract the solution suggestion information corresponding to the user problem type data of the front-end dialogue record.

7. The AI-based artificial customer service assisted processing method according to claim 1, characterized in that: The step of outputting the solution suggestion information to the user terminal according to the found solution suggestion information corresponding to the user problem type data of the front-end dialogue record comprises: Obtaining solution suggestion information corresponding to the user problem type data of the front-end conversation record; The solution suggestion information corresponding to the user problem type data in the front-end dialogue record is displayed on the terminal computer of the manual customer service according to a preset reminder format, and the solution suggestion information is output to the user end.

8. An AI-based artificial customer service auxiliary processing device, characterized in that: The device comprises: The first pre-setting module is used to pre-enter various user problem type data and corresponding solution suggestion information and store them in the AI ​​library; The acquisition and generation module is used to obtain the conversation information between the front-end robot and the user in real time and generate the front-end conversation record; A judgment module is used to judge whether an instruction to apply for switching to manual customer service processing is detected; The calling and searching module is used to control the triggering of automatically calling the preset AI library when an instruction to switch to manual customer service is detected, analyze and summarize the front-end dialogue record, determine the user problem type data of the front-end dialogue record, and search for preset solution suggestion information corresponding to the user problem type data of the front-end dialogue record; The output control module is used to output the solution suggestion information to the user terminal according to the found solution suggestion information corresponding to the user problem type data of the front-end dialogue record.

9. An AI terminal, characterized in that: The device comprises a memory and one or more programs, wherein the one or more programs are stored in the memory and are configured to be executed by one or more processors, and the one or more programs include being used to execute the method according to any one of claims 1 to 7.

10. A non-transitory computer-readable storage medium, characterized in that: When the instructions in the storage medium are executed by a processor of an electronic device, the electronic device is enabled to execute the method as described in any one of claims 1 to 7.

Images