Customer service intelligent interaction method and system based on AI and medium

Abstract

The invention provides an AI-based customer service intelligent interaction method and system, and a medium. The method comprises the following steps: collecting attribute information and behavior track information of a target customer, processing to obtain a customer information portrait, extracting personalized demand information of the target customer according to the customer information portrait, executing intelligent interaction service based on the personalized demand information, monitoring an interaction service process in real time, collecting service state parameters, and sending the service state parameters to the target customer. Whether manual customer service switching needs to be executed or not is judged according to the service state parameters, intelligent interaction service in a preset time period is monitored, service index data is extracted, quantitative evaluation processing is conducted according to the service index data, a service reliability coefficient is obtained, the reliability of the intelligent interaction service is judged, and corresponding optimization measures are taken. Therefore, the AI-based customer service intelligent interaction technology is realized.

Description

Technical Field

[0001] The present application relates to the field of intelligent interaction technology, and more specifically, to an AI-based customer service intelligent interaction method, system, and medium. Background Art

[0002] With the rapid development of the Internet and information technology, the importance of customer service in corporate operations has become increasingly prominent. The traditional customer service model mainly relies on manual customer service, which has problems such as low efficiency, high cost, and uneven service quality. Although the existing intelligent customer service system can handle some simple customer inquiries, it is unable to comprehensively collect and analyze customer information, and it is difficult to accurately grasp the personalized needs of customers. It lacks flexibility and adaptability in the interaction process, and cannot adjust service strategies in time according to service status, resulting in low customer satisfaction and difficulty in ensuring service reliability.

[0003] In response to the above problems, effective technical solutions are urgently needed. Summary of the Invention

[0004] The purpose of this application is to provide an AI-based customer service intelligent interaction method, system and medium, which can collect the attribute information and behavior trajectory information of the target customers, and process them to obtain customer information portraits, extract the personalized demand information of the target customers based on the customer information portraits, perform intelligent interactive services, monitor the interactive service process in real time, and collect service status parameters to determine whether manual customer service transfer is required, monitor the intelligent interactive services within a preset time period, and extract service indicator data, further quantify and evaluate the data, obtain the service reliability coefficient, determine the reliability of the intelligent interactive service, and take corresponding optimization measures to realize AI-based customer service intelligent interaction technology.

[0005] This application also provides an AI-based customer service intelligent interaction method, including the following steps: Collect target customers' attribute information and behavior trajectory information, and process them to obtain customer information portraits; Extracting personalized demand information of the target customer based on the customer information portrait; Execute intelligent interactive services based on the personalized demand information, monitor the interactive service process in real time, and collect service status parameters; Determine whether manual customer service transfer is required based on the service status parameters; Monitoring the intelligent interactive service within a preset time period and extracting service indicator data; A quantitative evaluation process is performed based on the service indicator data to obtain a service reliability coefficient, and the reliability of the intelligent interactive service is judged and corresponding optimization measures are taken.

[0006] Optionally, in the AI-based customer service intelligent interaction method described in the present application, collecting the target customer's attribute information and behavior trajectory information, and processing to obtain the customer information profile, includes: Collect target customers' attribute information and behavior trajectory information; The attribute information includes age, gender, region and spending capacity; The behavior trajectory information includes historical purchase records, consultation frequency, question type, and channel preference; Based on the age, gender, region and spending capacity, combined with the historical purchase records, consultation frequency, question type and channel preference, a profile description is performed to obtain a customer information profile.

[0007] Optionally, in the AI-based customer service intelligent interaction method described in the present application, extracting the personalized demand information of the target customer based on the customer information portrait includes: Extracting personalized demand information based on the customer information portrait; The personalized demand information includes product function requirements, service category requirements and product after-sales requirements.

[0008] Optionally, in the AI-based customer service intelligent interaction method described in the present application, executing intelligent interactive services based on the personalized demand information, monitoring the interactive service process in real time, and collecting service status parameters include: According to the product function requirements, service category requirements and product after-sales requirements, matching is performed through the preset demand strategy library to obtain an adaptation demand strategy; Executing intelligent interactive services according to the adaptation demand strategy; Monitor the interactive service process in real time and collect service status parameters; The service status parameters include problem complexity, customer emotional tension, problem resolution satisfaction, service response efficiency, and service duration.

[0009] Optionally, in the AI-based customer service intelligent interaction method described in the present application, determining whether manual customer service transfer is required based on the service status parameter includes: The service transfer evaluation coefficient is obtained by processing the problem complexity, customer emotional tension, problem resolution satisfaction, service response efficiency and service time through a preset transfer mechanism evaluation model; comparing the service transfer assessment coefficient with a preset service transfer assessment threshold, and determining whether manual customer service transfer is required based on the comparison result; If the service transfer evaluation coefficient is less than the preset service transfer evaluation threshold, manual customer service transfer is not required; If the service transfer evaluation coefficient is greater than or equal to the preset service transfer evaluation threshold, manual customer service transfer needs to be performed.

[0010] Optionally, in the AI-based customer service intelligent interaction method described in the present application, monitoring the intelligent interactive service within a preset time period and extracting service indicator data includes: Monitoring the intelligent interactive service within a preset time period and extracting service index data, including accuracy index data, efficiency index data, satisfaction index data, and stability index data; The accuracy index data includes question answering accuracy and intent recognition accuracy; The efficiency indicator data includes average response time and average problem resolution time; The satisfaction index data includes customer satisfaction and net promoter score; The stability index data includes system failure rate and result consistency.

[0011] In a second aspect, the present application provides an AI-based customer service intelligent interaction system, the system comprising: a memory and a processor, the memory comprising a program for an AI-based customer service intelligent interaction method, and the program for the AI-based customer service intelligent interaction method, when executed by the processor, implements the following steps: Collect target customers' attribute information and behavior trajectory information, and process them to obtain customer information portraits; Extracting personalized demand information of the target customer based on the customer information portrait; Execute intelligent interactive services based on the personalized demand information, monitor the interactive service process in real time, and collect service status parameters; Determine whether manual customer service transfer is required based on the service status parameters; Monitoring the intelligent interactive service within a preset time period and extracting service indicator data; A quantitative evaluation process is performed based on the service indicator data to obtain a service reliability coefficient, and the reliability of the intelligent interactive service is judged and corresponding optimization measures are taken.

[0012] Optionally, in the AI-based customer service intelligent interaction system described in this application, collecting the target customer's attribute information and behavior trajectory information, and processing to obtain the customer information profile, includes: Collect target customers' attribute information and behavior trajectory information; The attribute information includes age, gender, region and spending capacity; The behavior trajectory information includes historical purchase records, consultation frequency, question type, and channel preference; Based on the age, gender, region and spending capacity, combined with the historical purchase records, consultation frequency, question type and channel preference, a profile description is performed to obtain a customer information profile.

[0013] Optionally, in the AI-based customer service intelligent interaction system described in the present application, extracting the personalized demand information of the target customer based on the customer information portrait includes: Extracting personalized demand information based on the customer information portrait; The personalized demand information includes product function requirements, service category requirements and product after-sales requirements.

[0014] In a third aspect, the present application also provides a computer-readable storage medium, which stores an AI-based customer service intelligent interaction method program. When the AI-based customer service intelligent interaction method program is executed by a processor, the steps of the AI-based customer service intelligent interaction method as described in any one of the above items are implemented.

[0015] From the above, it can be seen that the AI-based customer service intelligent interaction method, system and medium provided by this application collect the attribute information and behavior trajectory information of the target customers, and process them to obtain customer information portraits, extract the personalized demand information of the target customers based on the customer information portraits, perform intelligent interactive services based on the personalized demand information, monitor the interactive service process in real time, and collect service status parameters. It determines whether manual customer service transfer is required based on the service status parameters, monitors the intelligent interactive services within a preset time period, and extracts service indicator data. It performs quantitative evaluation and processing based on the service indicator data to obtain the service reliability coefficient, and judges the reliability of the intelligent interactive service and takes corresponding optimization measures, thereby realizing AI-based customer service intelligent interaction technology.

[0016] Other features and advantages of the present application will be described in the following description, and in part will become apparent from the description, or understood by practicing the embodiments of the present application. The objectives and other advantages of the present application can be achieved and obtained through the structures particularly pointed out in the written description and the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following is a brief introduction to the drawings required for use in the embodiments of the present application. It should be understood that the following drawings only show certain embodiments of the present application and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other relevant drawings can be obtained based on these drawings without creative work.

[0018] Figure 1A flowchart of the AI-based customer service intelligent interaction method provided in an embodiment of the present application; Figure 2 A flowchart of obtaining a customer information profile for the AI-based customer service intelligent interaction method provided in an embodiment of the present application; Figure 3 A flowchart of collecting service status parameters for the AI-based customer service intelligent interaction method provided in an embodiment of the present application; Figure 4 A flowchart of the AI-based customer service intelligent interaction method provided in an embodiment of the present application for determining whether manual customer service transfer is required. DETAILED DESCRIPTION

[0019] The technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all of the embodiments. The components of the embodiments of the present application generally described and shown in the drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the application for protection, but merely represents the selected embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without making creative work fall within the scope of protection of the present application.

[0020] It should be noted that similar reference numerals and letters represent similar items in the following drawings. Therefore, once an item is defined in one drawing, it does not need to be further defined or explained in subsequent drawings. At the same time, in the description of this application, the terms "first", "second", etc. are only used to distinguish the description and should not be understood as indicating or implying relative importance.

[0021] Please refer to Figure 1 , Figure 1 This is a flow chart of an AI-based customer service intelligent interaction method in some embodiments of the present application. The AI-based customer service intelligent interaction method is used in a terminal device, such as a computer, a mobile phone terminal, etc. The AI-based customer service intelligent interaction method includes the following steps: S11. Collect the target customer's attribute information and behavior trajectory information, and process it to obtain a customer information profile; S12. Extracting personalized demand information of the target customer based on the customer information portrait; S13. Execute intelligent interactive services based on the personalized demand information, monitor the interactive service process in real time, and collect service status parameters; S14. Determine whether manual customer service transfer is required based on the service status parameters; S15. Monitoring the intelligent interactive service within a preset time period and extracting service indicator data; S16. Perform quantitative evaluation processing based on the service indicator data to obtain a service reliability coefficient, determine the reliability of the intelligent interactive service, and take corresponding optimization measures.

[0022] It should be noted that under the wave of digital services, AI-based customer service intelligent interaction technology is data-driven at its core to build a complete service closed loop. First, the system collects target customer attribute information through multiple source channels, such as static labels such as age, gender, region, and consumption capacity. At the same time, it tracks customer behavior on platforms such as APP and official websites, including historical purchase records, consultation frequency, question types, and channel preferences. It uses big data analysis and machine learning algorithms to clean, cluster, and extract features from the original data, and builds a customer information portrait that depicts customer information and purchase preference information, accurately depicting customer preferences and potential needs. Based on the portrait analysis, it mines personalized needs through customer consultation texts and drives the generation of intelligent interaction modules. Customized service solutions. During the service process, the system collects problem complexity, customer emotional tension, problem-solving satisfaction, service response efficiency, and service duration status parameters in real time. When customers ask questions repeatedly or the emotional index is abnormal, the manual customer service transfer mechanism is automatically triggered. In addition, the system periodically extracts indicator data such as accuracy, efficiency, satisfaction, and stability, and calculates the service reliability coefficient based on the AI ​​service reliability evaluation model. If the coefficient is lower than the threshold, the accuracy and stability of intelligent interactive services are continuously improved through measures such as optimizing the model, updating the knowledge graph, and adjusting the service strategy, thereby realizing AI-based customer service intelligent interaction technology.

[0023] Please refer to Figure 2 , Figure 2 This is a flow chart of obtaining a customer information profile for an AI-based customer service intelligent interaction method in some embodiments of the present application. According to an embodiment of the present invention, the process of collecting target customer attribute information and behavior trajectory information and processing to obtain a customer information profile includes: S21. Collecting target customer attribute information and behavior trajectory information; S22. The attribute information includes age, gender, region, and spending capacity; S23, the behavior trajectory information includes historical purchase records, consultation frequency, question type and channel preference; S24. Based on the age, gender, region and spending capacity, combined with the historical purchase records, consultation frequency, question type and channel preference, a profile description process is performed to obtain a customer information profile.

[0024] It should be noted that the attribute information and behavioral trajectory information of target customers are collected comprehensively; in terms of attribute information, the customer's age, gender, region and consumption capacity are accurately obtained, among which age divides different life cycle needs, gender distinguishes differences in consumption preferences, region is combined with local market characteristics, and consumption capacity directly reflects the level of purchasing power; the collection of behavioral trajectory information focuses more on capturing dynamic data, among which historical purchase records reflect consumption frequency and category preferences; consultation frequency reflects customer stickiness, and high-frequency consulting customers are often potential high-value users; question types can identify product pain points and service needs; channel preferences clarify customer contact habits, such as the use tendency of different channels such as APP, official website, and telephone; based on the above information, clustering algorithms are used to mine the characteristics of similar customer groups to generate customer labels, and then combined with the target customer information to generate a structured customer information portrait that describes the target customer attributes and personalized information, so as to describe the target customer's attributes and purchasing behavior.

[0025] According to an embodiment of the present invention, extracting the personalized demand information of the target customer based on the customer information portrait includes: Extracting personalized demand information based on the customer information portrait; The personalized demand information includes product function requirements, service category requirements and product after-sales requirements.

[0026] It should be noted that the personalized demand information of target customers is obtained by extracting features based on customer information portraits; by deeply mining the attributes and behavioral data in the customer portraits; on the one hand, historical purchase records and consultation content are analyzed to judge customers' needs for product functions, such as the pursuit of high performance or emphasis on cost-effectiveness; on the other hand, the demand keywords, feedback, and notes of consultation, after-sales, and communication are combined to capture customers' needs for service categories; personalized demand information includes product function requirements, service category requirements, and product after-sales requirements. This information can provide precise guidance for subsequent intelligent interactive services.

[0027] Please refer to Figure 3 , Figure 3 This is a flow chart of collecting service status parameters for an AI-based customer service intelligent interaction method in some embodiments of the present application. According to an embodiment of the present invention, executing intelligent interactive services based on the personalized demand information, monitoring the interactive service process in real time, and collecting service status parameters include: S31, performing matching processing through a preset demand strategy library according to the product function requirements, service category requirements, and product after-sales requirements to obtain an adaptation demand strategy; S32. Execute intelligent interactive services according to the adaptation demand strategy; S33. Real-time monitoring of the interactive service process and collection of service status parameters; S34. The service status parameters include problem complexity, customer emotional tension, problem resolution satisfaction, service response efficiency, and service duration.

[0028] It should be noted that based on the extracted product function requirements, service category requirements and product after-sales requirements, they are input into the preset demand strategy library for precise matching; among them, the strategy library adopts a combination of rule engine and machine learning, and has built-in massive scenario-based strategy templates; for example, for customers who pursue high-performance product function preferences, the introduction strategy that highlights the technical advantages is automatically matched; for customers who pay attention to service warmth, a friendly and patient communication strategy is selected to generate an adaptation demand strategy; based on the adaptation strategy, the intelligent interactive service responds to customer inquiries immediately; at the same time, the system monitors the entire interaction process in real time, uses natural language processing technology to analyze the semantics of the problem and judge the complexity of the problem; uses emotion recognition algorithms to capture customer emotional tension; grasps problem-solving satisfaction through task progress tracking; monitors the service response efficiency and service provision time of manual customer service, and provides real-time and accurate data support for subsequent service optimization and manual transfer decisions by collecting service status parameters.

[0029] Please refer to Figure 4 , Figure 4 This is a flow chart of an AI-based customer service intelligent interaction method in some embodiments of the present application for determining whether manual customer service transfer is required. According to an embodiment of the present invention, determining whether manual customer service transfer is required based on the service status parameter includes: S41. Processing the problem complexity, customer emotional tension, problem resolution satisfaction, service response efficiency, and service duration using a preset transfer mechanism evaluation model to obtain a service transfer evaluation coefficient; S42: comparing the service transfer assessment coefficient with a preset service transfer assessment threshold, and determining whether manual customer service transfer is required based on the comparison result; S43. If the service transfer evaluation coefficient is less than a preset service transfer evaluation threshold, manual customer service transfer is not required. S44. If the service transfer evaluation coefficient is greater than or equal to the preset service transfer evaluation threshold, manual customer service transfer needs to be performed.

[0030] It should be noted that the service transfer assessment coefficient is obtained by processing the problem complexity, customer emotional tension, problem solving satisfaction, service response efficiency and service time through the preset transfer mechanism assessment model. Among them, the transfer mechanism assessment model is a neural network model. The initialized transfer mechanism assessment model is trained based on the problem complexity, customer emotional tension, problem solving satisfaction, service response efficiency and service time of a large number of historical product service record samples to obtain a trained transfer mechanism assessment model, which is then compared with the preset service transfer assessment threshold. According to the comparison result, it is determined whether manual customer service transfer is required; if the service transfer assessment coefficient is less than the preset service transfer assessment threshold, manual customer service transfer is not required. If the service transfer assessment coefficient is greater than or equal to the preset service transfer assessment threshold, manual customer service transfer is required. Through this processing method, accurate transfer of manual service and intelligent service is ensured.

[0031] According to an embodiment of the present invention, monitoring the intelligent interactive service within a preset time period and extracting service indicator data includes: Monitoring the intelligent interactive service within a preset time period and extracting service index data, including accuracy index data, efficiency index data, satisfaction index data, and stability index data; The accuracy index data includes question answering accuracy and intent recognition accuracy; The efficiency indicator data includes average response time and average problem resolution time; The satisfaction index data includes customer satisfaction and net promoter score; The stability index data includes system failure rate and result consistency.

[0032] It should be noted that the intelligent interactive services within the preset time period are monitored and service indicator data are extracted, including accuracy indicator data, efficiency indicator data, satisfaction indicator data and stability indicator data; among them, the accuracy indicator data includes question answering accuracy and intent recognition accuracy; among them, the question answering accuracy rate measures the proportion of AI correctly answering customer questions, that is, the ratio of the number of correctly answered questions to the total number of questions; the intent recognition accuracy rate calculates the ratio of AI accurately identifying customer intentions; the efficiency indicator data includes average response time and average problem solving time; among them, the average response time refers to the average time from the AI ​​receiving the customer question to giving the answer; Problem resolution time refers to the total time recorded from the time a customer raises a problem to the time the problem is finally resolved, including the processing time after AI automatic resolution and manual intervention; satisfaction index data includes customer satisfaction and net promoter score; among them, customer satisfaction with AI services is collected through questionnaires, online ratings, etc., and customers are asked whether they are willing to recommend the AI ​​customer service to others. The net promoter score is calculated by calculating the difference between the proportion of recommenders and the proportion of detractors; stability index data includes system failure rate and result consistency; among them, the system failure rate refers to the statistical number of times or duration of failures in the AI ​​system within a certain period of time, and result consistency refers to whether the answers given by AI are consistent under the same or similar input conditions. The stability of AI answers is observed by repeatedly testing the same questions.

[0033] According to an embodiment of the present invention, the further embodiment includes: The quantitative evaluation process is performed based on the service indicator data to obtain a service reliability coefficient, and the reliability of the intelligent interactive service is determined and corresponding optimization measures are taken, specifically including: A service reliability coefficient is obtained by performing a quantitative evaluation based on the accuracy index data, efficiency index data, satisfaction index data, and stability index data using a preset AI service reliability evaluation model; Comparing the service reliability coefficient with a preset service reliability threshold, and determining whether the reliability of the intelligent interactive service meets the requirements based on the comparison result; If the service reliability coefficient is greater than a preset service reliability threshold, the reliability of the intelligent interactive service meets the requirements; If the service reliability coefficient is less than or equal to the preset service reliability threshold, the reliability of the intelligent interactive service does not meet the requirements and corresponding optimization measures need to be taken.

[0034] It should be noted that the accuracy index data, efficiency index data, satisfaction index data and stability index data are quantitatively evaluated by a preset AI service reliability evaluation model to obtain a service reliability coefficient. The AI ​​service reliability evaluation model is a neural network model, which is initialized by training an AI service reliability evaluation model based on a large amount of historical accuracy index data, efficiency index data, satisfaction index data and stability index data to obtain a trained AI service reliability evaluation model, which is compared with a preset service reliability threshold. According to the comparison result, it is judged whether the reliability of the intelligent interactive service meets the requirements. If the service reliability coefficient is greater than the preset service reliability threshold, it indicates that the reliability of the intelligent interactive service meets the requirements and no optimization is required. If the service reliability coefficient is less than or equal to the preset service reliability threshold, it indicates that the reliability of the intelligent interactive service does not meet the requirements and corresponding optimization measures need to be taken.

[0035] In a second aspect, the present invention further discloses an AI-based customer service intelligent interaction system, comprising a memory and a processor, wherein the memory includes an AI-based customer service intelligent interaction method program, and when the AI-based customer service intelligent interaction method program is executed by the processor, the following steps are implemented: Collect target customers' attribute information and behavior trajectory information, and process them to obtain customer information portraits; Extracting personalized demand information of the target customer based on the customer information portrait; Execute intelligent interactive services based on the personalized demand information, monitor the interactive service process in real time, and collect service status parameters; Determine whether manual customer service transfer is required based on the service status parameters; Monitoring the intelligent interactive service within a preset time period and extracting service indicator data; A quantitative evaluation process is performed based on the service indicator data to obtain a service reliability coefficient, and the reliability of the intelligent interactive service is judged and corresponding optimization measures are taken.

[0036] It should be noted that under the wave of digital services, AI-based customer service intelligent interaction technology is data-driven at its core to build a complete service closed loop. First, the system collects target customer attribute information through multiple source channels, such as static labels such as age, gender, region, and consumption capacity. At the same time, it tracks customer behavior on platforms such as APP and official websites, including historical purchase records, consultation frequency, question types, and channel preferences. It uses big data analysis and machine learning algorithms to clean, cluster, and extract features from the original data, and builds a customer information portrait that depicts customer information and purchase preference information, accurately depicting customer preferences and potential needs. Based on the portrait analysis, it mines personalized needs through customer consultation texts and drives the generation of intelligent interaction modules. Customized service solutions. During the service process, the system collects problem complexity, customer emotional tension, problem-solving satisfaction, service response efficiency, and service duration status parameters in real time. When customers ask questions repeatedly or the emotional index is abnormal, the manual customer service transfer mechanism is automatically triggered. In addition, the system periodically extracts indicator data such as accuracy, efficiency, satisfaction, and stability, and calculates the service reliability coefficient based on the AI ​​service reliability evaluation model. If the coefficient is lower than the threshold, the accuracy and stability of intelligent interactive services are continuously improved through measures such as optimizing the model, updating the knowledge graph, and adjusting the service strategy, thereby realizing AI-based customer service intelligent interaction technology.

[0037] According to an embodiment of the present invention, the step of collecting target customer attribute information and behavior trajectory information and processing to obtain a customer information profile includes: Collect target customers' attribute information and behavior trajectory information; The attribute information includes age, gender, region and spending capacity; The behavior trajectory information includes historical purchase records, consultation frequency, question type, and channel preference; Based on the age, gender, region and spending capacity, combined with the historical purchase records, consultation frequency, question type and channel preference, a profile description is performed to obtain a customer information profile.

[0038] It should be noted that the attribute information and behavioral trajectory information of target customers are collected comprehensively; in terms of attribute information, the customer's age, gender, region and consumption capacity are accurately obtained, among which age divides different life cycle needs, gender distinguishes differences in consumption preferences, region is combined with local market characteristics, and consumption capacity directly reflects the level of purchasing power; the collection of behavioral trajectory information focuses more on capturing dynamic data, among which historical purchase records reflect consumption frequency and category preferences; consultation frequency reflects customer stickiness, and high-frequency consulting customers are often potential high-value users; question types can identify product pain points and service needs; channel preferences clarify customer contact habits, such as the use tendency of different channels such as APP, official website, and telephone; based on the above information, clustering algorithms are used to mine the characteristics of similar customer groups to generate customer labels, and then combined with the target customer information to generate a structured customer information portrait that describes the target customer attributes and personalized information, so as to describe the target customer's attributes and purchasing behavior.

[0039] According to an embodiment of the present invention, extracting the personalized demand information of the target customer based on the customer information portrait includes: Extracting personalized demand information based on the customer information portrait; The personalized demand information includes product function requirements, service category requirements and product after-sales requirements.

[0040] It should be noted that the personalized demand information of target customers is obtained by extracting features based on customer information portraits; by deeply mining the attributes and behavioral data in the customer portraits; on the one hand, historical purchase records and consultation content are analyzed to judge customers' needs for product functions, such as the pursuit of high performance or emphasis on cost-effectiveness; on the other hand, the demand keywords, feedback, and notes of consultation, after-sales, and communication are combined to capture customers' needs for service categories; personalized demand information includes product function requirements, service category requirements, and product after-sales requirements. This information can provide precise guidance for subsequent intelligent interactive services.

[0041] According to an embodiment of the present invention, executing intelligent interactive services based on the personalized demand information, monitoring the interactive service process in real time, and collecting service status parameters include: According to the product function requirements, service category requirements and product after-sales requirements, matching is performed through the preset demand strategy library to obtain an adaptation demand strategy; Executing intelligent interactive services according to the adaptation demand strategy; Monitor the interactive service process in real time and collect service status parameters; The service status parameters include problem complexity, customer emotional tension, problem resolution satisfaction, service response efficiency, and service duration.

[0042] It should be noted that based on the extracted product function requirements, service category requirements and product after-sales requirements, they are input into the preset demand strategy library for precise matching; among them, the strategy library adopts a combination of rule engine and machine learning, and has built-in massive scenario-based strategy templates; for example, for customers who pursue high-performance product function preferences, the introduction strategy that highlights the technical advantages is automatically matched; for customers who pay attention to service warmth, a friendly and patient communication strategy is selected to generate an adaptation demand strategy; based on the adaptation strategy, the intelligent interactive service responds to customer inquiries immediately; at the same time, the system monitors the entire interaction process in real time, uses natural language processing technology to analyze the semantics of the problem and judge the complexity of the problem; uses emotion recognition algorithms to capture customer emotional tension; grasps problem-solving satisfaction through task progress tracking; monitors the service response efficiency and service provision time of manual customer service, and provides real-time and accurate data support for subsequent service optimization and manual transfer decisions by collecting service status parameters.

[0043] According to an embodiment of the present invention, determining whether manual customer service transfer is required based on the service status parameter includes: The service transfer evaluation coefficient is obtained by processing the problem complexity, customer emotional tension, problem resolution satisfaction, service response efficiency and service time through a preset transfer mechanism evaluation model; comparing the service transfer assessment coefficient with a preset service transfer assessment threshold, and determining whether manual customer service transfer is required based on the comparison result; If the service transfer evaluation coefficient is less than the preset service transfer evaluation threshold, manual customer service transfer is not required; If the service transfer evaluation coefficient is greater than or equal to the preset service transfer evaluation threshold, manual customer service transfer needs to be performed.

[0044] It should be noted that the service transfer assessment coefficient is obtained by processing the problem complexity, customer emotional tension, problem solving satisfaction, service response efficiency and service time through the preset transfer mechanism assessment model. Among them, the transfer mechanism assessment model is a neural network model. The initialized transfer mechanism assessment model is trained based on the problem complexity, customer emotional tension, problem solving satisfaction, service response efficiency and service time of a large number of historical product service record samples to obtain a trained transfer mechanism assessment model, which is then compared with the preset service transfer assessment threshold. According to the comparison result, it is determined whether manual customer service transfer is required; if the service transfer assessment coefficient is less than the preset service transfer assessment threshold, manual customer service transfer is not required. If the service transfer assessment coefficient is greater than or equal to the preset service transfer assessment threshold, manual customer service transfer is required. Through this processing method, accurate transfer of manual service and intelligent service is ensured.

[0045] According to an embodiment of the present invention, monitoring the intelligent interactive service within a preset time period and extracting service indicator data includes: Monitoring the intelligent interactive service within a preset time period and extracting service index data, including accuracy index data, efficiency index data, satisfaction index data, and stability index data; The accuracy index data includes question answering accuracy and intent recognition accuracy; The efficiency indicator data includes average response time and average problem resolution time; The satisfaction index data includes customer satisfaction and net promoter score; The stability index data includes system failure rate and result consistency.

[0046] It should be noted that the intelligent interactive services within the preset time period are monitored and service indicator data are extracted, including accuracy indicator data, efficiency indicator data, satisfaction indicator data and stability indicator data; among them, the accuracy indicator data includes question answering accuracy and intent recognition accuracy; among them, the question answering accuracy rate measures the proportion of AI correctly answering customer questions, that is, the ratio of the number of correctly answered questions to the total number of questions; the intent recognition accuracy rate calculates the ratio of AI accurately identifying customer intentions; the efficiency indicator data includes average response time and average problem solving time; among them, the average response time refers to the average time from the AI ​​receiving the customer question to giving the answer; Problem resolution time refers to the total time recorded from the time a customer raises a problem to the time the problem is finally resolved, including the processing time after AI automatic resolution and manual intervention; satisfaction index data includes customer satisfaction and net promoter score; among them, customer satisfaction with AI services is collected through questionnaires, online ratings, etc., and customers are asked whether they are willing to recommend the AI ​​customer service to others. The net promoter score is calculated by calculating the difference between the proportion of recommenders and the proportion of detractors; stability index data includes system failure rate and result consistency; among them, the system failure rate refers to the statistical number of times or duration of failures in the AI ​​system within a certain period of time, and result consistency refers to whether the answers given by AI are consistent under the same or similar input conditions. The stability of AI answers is observed by repeatedly testing the same questions.

[0047] According to an embodiment of the present invention, the further embodiment includes: The quantitative evaluation process is performed based on the service indicator data to obtain a service reliability coefficient, and the reliability of the intelligent interactive service is determined and corresponding optimization measures are taken, specifically including: A service reliability coefficient is obtained by performing a quantitative evaluation based on the accuracy index data, efficiency index data, satisfaction index data, and stability index data using a preset AI service reliability evaluation model; Comparing the service reliability coefficient with a preset service reliability threshold, and determining whether the reliability of the intelligent interactive service meets the requirements based on the comparison result; If the service reliability coefficient is greater than a preset service reliability threshold, the reliability of the intelligent interactive service meets the requirements; If the service reliability coefficient is less than or equal to the preset service reliability threshold, the reliability of the intelligent interactive service does not meet the requirements and corresponding optimization measures need to be taken.

[0048] It should be noted that the accuracy index data, efficiency index data, satisfaction index data and stability index data are quantitatively evaluated by a preset AI service reliability evaluation model to obtain a service reliability coefficient. The AI ​​service reliability evaluation model is a neural network model, which is initialized by training an AI service reliability evaluation model based on a large amount of historical accuracy index data, efficiency index data, satisfaction index data and stability index data to obtain a trained AI service reliability evaluation model, which is compared with a preset service reliability threshold. According to the comparison result, it is judged whether the reliability of the intelligent interactive service meets the requirements. If the service reliability coefficient is greater than the preset service reliability threshold, it indicates that the reliability of the intelligent interactive service meets the requirements and no optimization is required. If the service reliability coefficient is less than or equal to the preset service reliability threshold, it indicates that the reliability of the intelligent interactive service does not meet the requirements and corresponding optimization measures need to be taken.

[0049] The third aspect of the present invention provides a readable storage medium, which stores an AI-based customer service intelligent interaction method program. When the AI-based customer service intelligent interaction method program is executed by a processor, the steps of the AI-based customer service intelligent interaction method as described in any one of the above items are implemented.

[0050] The AI-based customer service intelligent interaction method, system and medium disclosed in the present invention collect attribute information and behavior trajectory information of target customers, and process them to obtain customer information portraits, extract personalized demand information of target customers based on the customer information portraits, perform intelligent interactive services based on the personalized demand information, monitor the interactive service process in real time, and collect service status parameters. It determines whether manual customer service transfer is required based on the service status parameters, monitors intelligent interactive services within a preset time period, and extracts service indicator data. It performs quantitative evaluation processing based on the service indicator data to obtain a service reliability coefficient, and determines the reliability of the intelligent interactive service and takes corresponding optimization measures, thereby realizing AI-based customer service intelligent interaction technology.

[0051] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are merely schematic. For example, the division of the units is merely a logical function division. In actual implementation, there may be other division methods, such as: multiple units or components can be combined, or can be integrated into another system, or some features can be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the components shown or discussed can be through some interfaces, and the indirect coupling or communication connection of the devices or units can be electrical, mechanical or other forms.

[0052] The units described above as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units; they may be located in one place or distributed across multiple network units; some or all of the units may be selected according to actual needs to achieve the purpose of the scheme of this embodiment.

[0053] In addition, all functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may be separately used as a unit, or two or more units may be integrated into one unit; the above-mentioned integrated units may be implemented in the form of hardware or in the form of hardware plus software functional units.

[0054] Those skilled in the art will appreciate that all or part of the steps of the above-mentioned method embodiments may be implemented by hardware related to program instructions, and the aforementioned program may be stored in a readable storage medium. When the program is executed, the program executes the steps of the above-mentioned method embodiments. The aforementioned storage medium includes various media that can store program codes, such as mobile storage devices, read-only memories (ROMs), random access memories (RAMs), magnetic disks, or optical disks.

[0055] Alternatively, if the integrated units described above are implemented as software functional modules and sold or used as standalone products, they can also be stored on a readable storage medium. Based on this understanding, the technical solutions of the embodiments of the present invention, or the portion that contributes to the prior art, can be embodied in the form of a software product. This software product, stored on a storage medium, includes instructions for enabling a computer device (such as a personal computer, server, or network device) to execute all or part of the methods described in the various embodiments of the present invention. The aforementioned storage media include various media capable of storing program code, such as removable storage devices, ROM, RAM, magnetic disks, or optical disks.

Claims

1. An AI-based intelligent customer service interaction method, characterized by: The following steps are involved: Collect target customers' attribute information and behavior trajectory information, and process them to obtain customer information portraits; Extracting personalized demand information of the target customer based on the customer information portrait; Execute intelligent interactive services based on the personalized demand information, monitor the interactive service process in real time, and collect service status parameters; Determine whether manual customer service transfer is required based on the service status parameters; Monitoring the intelligent interactive service within a preset time period and extracting service indicator data; A quantitative evaluation process is performed based on the service indicator data to obtain a service reliability coefficient, and the reliability of the intelligent interactive service is judged and corresponding optimization measures are taken.

2. The AI-based customer service intelligent interaction method according to claim 1, characterized in that: The collection of target customer attribute information and behavior trajectory information, and processing to obtain customer information profiles, includes: Collect target customers' attribute information and behavior trajectory information; The attribute information includes age, gender, region and spending capacity; The behavior trajectory information includes historical purchase records, consultation frequency, question type, and channel preference; Based on the age, gender, region and spending capacity, combined with the historical purchase records, consultation frequency, question type and channel preference, a profile description is performed to obtain a customer information profile.

3. The AI-based customer service intelligent interaction method according to claim 2, characterized in that: The extracting of the target customer's personalized demand information based on the customer information portrait includes: Extracting personalized demand information based on the customer information portrait; The personalized demand information includes product function requirements, service category requirements and product after-sales requirements.

4. The AI-based customer service intelligent interaction method according to claim 3, characterized in that: The executing of intelligent interactive services based on the personalized demand information, real-time monitoring of the interactive service process, and collection of service status parameters include: According to the product function requirements, service category requirements and product after-sales requirements, matching is performed through the preset demand strategy library to obtain an adaptation demand strategy; Executing intelligent interactive services according to the adaptation demand strategy; Monitor the interactive service process in real time and collect service status parameters; The service status parameters include problem complexity, customer emotional tension, problem resolution satisfaction, service response efficiency, and service duration.

5. The AI-based customer service intelligent interaction method according to claim 4 is characterized in that: The determining whether manual customer service transfer is required according to the service status parameter includes: The service transfer evaluation coefficient is obtained by processing the problem complexity, customer emotional tension, problem resolution satisfaction, service response efficiency and service time through a preset transfer mechanism evaluation model; comparing the service transfer assessment coefficient with a preset service transfer assessment threshold, and determining whether manual customer service transfer is required based on the comparison result; If the service transfer evaluation coefficient is less than the preset service transfer evaluation threshold, manual customer service transfer is not required; If the service transfer evaluation coefficient is greater than or equal to the preset service transfer evaluation threshold, manual customer service transfer needs to be performed.

6. The AI-based customer service intelligent interaction method according to claim 5, characterized in that: The monitoring of the intelligent interactive service within a preset time period and extracting service indicator data includes: Monitoring the intelligent interactive service within a preset time period and extracting service index data, including accuracy index data, efficiency index data, satisfaction index data, and stability index data; The accuracy index data includes question answering accuracy and intent recognition accuracy; The efficiency indicator data includes average response time and average problem resolution time; The satisfaction index data includes customer satisfaction and net promoter score; The stability index data includes system failure rate and result consistency.

7. AI-based customer service intelligent interaction system, characterized by: The system includes: a memory and a processor, wherein the memory includes a program of an AI-based customer service intelligent interaction method, and when the program of the AI-based customer service intelligent interaction method is executed by the processor, the following steps are implemented: Collect target customers' attribute information and behavior trajectory information, and process them to obtain customer information portraits; Extracting personalized demand information of the target customer based on the customer information portrait; Execute intelligent interactive services based on the personalized demand information, monitor the interactive service process in real time, and collect service status parameters; Determine whether manual customer service transfer is required based on the service status parameters; Monitoring the intelligent interactive service within a preset time period and extracting service indicator data; A quantitative evaluation process is performed based on the service indicator data to obtain a service reliability coefficient, and the reliability of the intelligent interactive service is judged and corresponding optimization measures are taken.

8. The AI-based customer service intelligent interactive system according to claim 7, characterized in that: The collection of target customer attribute information and behavior trajectory information, and processing to obtain customer information profiles, includes: Collect target customers' attribute information and behavior trajectory information; The attribute information includes age, gender, region and spending capacity; The behavior trajectory information includes historical purchase records, consultation frequency, question type, and channel preference; Based on the age, gender, region and spending capacity, combined with the historical purchase records, consultation frequency, question type and channel preference, a profile description is performed to obtain a customer information profile.

9. The AI-based customer service intelligent interactive system according to claim 8, characterized in that: The extracting of the target customer's personalized demand information based on the customer information portrait includes: Extracting personalized demand information based on the customer information portrait; The personalized demand information includes product function requirements, service category requirements and product after-sales requirements.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium includes an AI-based customer service intelligent interaction method program. When the AI-based customer service intelligent interaction method program is executed by a processor, the steps of the AI-based customer service intelligent interaction method as described in any one of claims 1 to 6 are implemented.

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