Enterprise customer service multi-station collaborative management system and method

Abstract

The invention discloses an enterprise customer service multi-station collaborative management system and method, a data layer ensures data integrity and traceability by constructing various databases and storing customer data, work order information and historical records in a classified manner, a data acquisition interface integrates internal and external data sources, a business logic layer adopts an intelligent work order distribution algorithm, and the business logic layer adopts an intelligent work order distribution algorithm. According to work order characteristics and customer service capability automatic distribution, processing efficiency and quality are improved, customer service satisfaction is enhanced, a unified view is formed through a customer information integration function, customers can be comprehensively understood, an information sharing mechanism promotes team cooperation, service consistency is improved, data statistical analysis and visual display provide visual decision support for a management layer, and the management layer is provided with a management layer. The customer service process is optimized, the system integration and interface management functions realize seamless joint with other business systems, information islands are avoided, the operation efficiency is improved, the application layer provides targeted operation applications, different user role requirements are met, and the intelligent, collaborative and efficient levels of enterprise customer service management are integrally improved.

Description

Technical Field

[0001] The present invention relates to the technical field of enterprise customer service management, and in particular to an enterprise customer service multi-station collaborative management system and method. Background Art

[0002] In today's business operations, customer service plays a vital role in the company's reputation and competitiveness. As the business scale expands, the customer service department of the company often needs to handle a large number of customer inquiries and problem feedback. At present, in the field of enterprise customer service management, the commonly used customer service management software or technology has many shortcomings.

[0003] Many traditional customer service systems only have basic work order flow functions and have extremely limited support for multi-station collaboration. For example, in terms of task allocation among customer service personnel, there is a lack of intelligent and dynamic allocation mechanisms, and work orders are often allocated manually. This is not only inefficient, but also prone to uneven distribution, resulting in some customer service personnel having too much workload while some personnel are idle, seriously affecting the work efficiency of the overall customer service team.

[0004] In addition, some existing systems have defects in customer information integration and sharing. When customer service staff at different workstations handle the same customer issue, they may not be able to obtain the customer's complete historical interaction information in a timely manner, resulting in inconsistent and low-quality services. For example, a customer has previously consulted pre-sales customer service about product details, but when after-sales problems arise, after-sales customer service cannot quickly know the content of the pre-sales communication and requires the customer to repeat it, which can easily lead to customer dissatisfaction.

[0005] At the same time, the existing customer service technology is not perfect in terms of data statistics and analysis functions. It is difficult for enterprises to comprehensively and accurately analyze the data of each link in the customer service workflow through the existing system, such as customer consultation hotspots, customer service response time distribution, problem solving success rate, etc., and it is impossible to provide strong data support for enterprises to optimize customer service processes and improve service quality.

[0006] Furthermore, some existing customer service software has poor compatibility with other internal office systems of the enterprise (such as CRM system, ERP system, etc.), and information cannot be efficiently exchanged, forming "information islands", which hinders the collaboration of the enterprise in the operation and management process, and increases operating costs and management difficulty. Summary of the invention

[0007] In view of this, the present invention proposes an enterprise customer service multi-station collaborative management system and method, which can effectively solve the defects of the prior art such as extremely limited support for multi-station collaboration, inability to timely obtain the customer's complete historical interaction information, difficulty in comprehensively analyzing data from each link in the customer service workflow, and inability to achieve efficient information intercommunication.

[0008] The technical solution of the present invention is achieved in this way:

[0009] An enterprise customer service multi-station collaborative management system, comprising:

[0010] The data layer is used to build different types of databases and data collection interfaces. The different types of databases are used to store data, and the data collection interfaces are used to collect data from various internal systems of the enterprise and external channels.

[0011] Business logic layer, used to realize intelligent work order allocation, customer information integration and sharing, data statistical analysis and visualization, as well as integration and interface management with various internal enterprise systems;

[0012] The application layer is used to provide corresponding operation applications for different user roles, and the operation applications include online customer service applications, work order processing applications and customer service management applications.

[0013] As a further optional solution of the enterprise customer service multi-station collaborative management system, the data layer includes:

[0014] A database module, used to store different types of data, including relational databases and non-relational databases, wherein the relational database is used to store structured data and the non-relational database is used to store unstructured data;

[0015] Data collection interface module, used to collect data from various internal systems of the enterprise and external channels;

[0016] The data backup and recovery module is used to regularly perform full and incremental backups of the database and restore data in the event of system failure or data corruption.

[0017] As a further optional solution of the enterprise customer service multi-station collaborative management system, the business logic layer includes:

[0018] The work order management module is used to realize intelligent allocation and status tracking of work orders based on the intelligent work order allocation algorithm;

[0019] The customer information management module is used to integrate customer information using entity recognition algorithms and use data synchronization technology to achieve real-time sharing of customer information between different workstations and systems;

[0020] Data statistics and analysis module, used to collect and organize various data in the customer service process, use big data processing technology to analyze data, and perform data visualization and customized report generation;

[0021] The system integration and interface management module is used to design general system interface specifications, achieve docking and data interaction with various systems within the enterprise, and use data encryption technology and access permission control mechanisms to ensure interface security.

[0022] As a further optional solution of the enterprise customer service multi-station collaborative management system, the work order management module implements intelligent allocation and status tracking of work orders based on an intelligent work order allocation algorithm, specifically including:

[0023] Use natural language processing technology to conduct in-depth semantic analysis of work order content and extract keywords and problem types from work orders;

[0024] Based on the customer service staff workload prediction model, predict the processing capacity of customer service staff within the preset time;

[0025] According to the keywords and problem types of the work order, as well as the customer service staff's processing capabilities within the preset time, set matching rules with customer service staff, and set weights for each matching rule;

[0026] Calculate the matching degree between each customer service staff and the work order based on the weight and matching rules;

[0027] According to the calculation results of the weighted matching algorithm, the customer service staff with the highest matching degree is selected as the work order assignment object;

[0028] Assigns the ticket to the selected agent and updates the ticket status and the agent's workload.

[0029] As a further optional solution for the enterprise customer service multi-station collaborative management system, the customer information management module integrates customer information using an entity recognition algorithm and uses data synchronization technology to achieve real-time sharing of customer information between different stations and systems, specifically including:

[0030] Using entity recognition algorithms to identify and classify the collected customer information, and identify meaningful entities, including names of people, places, names of organizations, time, and quantity;

[0031] Building a comprehensive view for each customer based on the identified meaningful entities, the comprehensive view including the customer's basic information, interaction history, preference settings, and value assessment;

[0032] The tree-structured data synchronization method allows the comprehensive view of each customer to be shared in real time between different workstations and systems.

[0033] As a further optional solution of the enterprise customer service multi-station collaborative management system, the system also includes:

[0034] The user interface layer is used to provide personalized operation interfaces according to different user roles.

[0035] A multi-station collaborative management method for enterprise customer service, specifically comprising:

[0036] Data layer construction steps: Build different types of databases to store data, and collect data from various internal systems and external channels of the enterprise through data collection interfaces;

[0037] Business logic layer processing steps: intelligent work order allocation, customer information integration and sharing, data statistical analysis and visualization, as well as integration and interface management with various internal enterprise systems are performed at the business logic layer;

[0038] Application layer operation steps: Provide corresponding operation applications for different user roles at the application layer. The operation applications include online customer service applications, work order processing applications, and customer service management applications, allowing each user role to perform corresponding operations according to their respective permissions and needs.

[0039] As a further optional solution of the enterprise customer service multi-station collaborative management method, the method also includes:

[0040] User interface layer personalized configuration steps: Provide a personalized operation interface at the user interface layer according to different user roles.

[0041] A computing device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements any one of the steps of the above-mentioned enterprise customer service multi-station collaborative management method when executing the computer program.

[0042] A computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of any one of the above-mentioned enterprise customer service multi-station collaborative management methods.

[0043] The beneficial effects of the present invention are as follows: the data layer can classify and store a large amount of customer data, work order information, historical records, etc. by constructing different types of databases to ensure the integrity and traceability of the data; the data collection interface can collect data from multiple systems within the enterprise and external channels in real time or regularly to achieve comprehensive data integration and provide a rich data source for the business logic layer; the business logic layer can automatically assign work orders to the most suitable customer service personnel based on the type, urgency, processing difficulty, and current load and professional capabilities of the customer service personnel through an intelligent work order allocation algorithm; this intelligent allocation method effectively reduces errors and delays in manual allocation, improves the efficiency and quality of work order processing, and also improves the satisfaction and work efficiency of customer service personnel; the customer information integration function can integrate customer information from different channels and systems into a unified customer view, which is convenient for customer service personnel to comprehensively Understand customer information. The customer information sharing mechanism ensures that authorized customer service personnel can access and update customer information in real time, promotes information sharing and collaboration among teams, and improves the consistency and satisfaction of customer service. The data statistical analysis and visualization display functions can deeply mine and analyze the data stored in the database, generate key performance indicators and reports, and display the analysis results through visualization tools such as charts and dashboards, providing management with intuitive and easy-to-understand decision support, which helps to optimize customer service processes. The integration and interface management functions with various internal systems of the enterprise ensure that the system can seamlessly connect with other business systems to achieve data sharing and process collaboration. This integration method avoids the creation of information islands and improves the overall operational efficiency and collaboration capabilities of the enterprise. The application layer provides targeted operation applications for different user roles to meet the work needs and operating habits of different roles. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] 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 of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0045] Figure 1 This is a schematic diagram of the composition of an enterprise customer service multi-station collaborative management system of the present invention;

[0046] Figure 2 A flowchart of a method for collaborative management of multiple workstations of customer service of an enterprise according to the present invention;

[0047] Figure 3 The figure is a schematic diagram of the composition of a computing device according to the present invention. DETAILED DESCRIPTION

[0048] The technical solutions in the embodiments of the present invention are described clearly and completely below. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0049] refer to Figures 1 to 3 , an enterprise customer service multi-station collaborative management system, comprising:

[0050] The data layer is used to build different types of databases and data collection interfaces. The different types of databases are used to store data, and the data collection interfaces are used to collect data from various internal systems of the enterprise and external channels.

[0051] Business logic layer, used to realize intelligent work order allocation, customer information integration and sharing, data statistical analysis and visualization, as well as integration and interface management with various internal enterprise systems;

[0052] The application layer is used to provide corresponding operation applications for different user roles, and the operation applications include online customer service applications, work order processing applications and customer service management applications.

[0053] In this embodiment, the data layer can classify and store a large amount of customer data, work order information, historical records, etc. by constructing different types of databases to ensure the integrity and traceability of the data. The data collection interface can collect data from multiple systems within the enterprise and external channels in real time or regularly to achieve comprehensive data integration and provide a rich data source for the business logic layer. The business logic layer can automatically assign work orders to the most suitable customer service personnel based on the type, urgency, processing difficulty, and current load and professional capabilities of the customer service personnel through an intelligent work order allocation algorithm. This intelligent allocation method effectively reduces errors and delays in manual allocation, improves the efficiency and quality of work order processing, and also improves the satisfaction and work efficiency of customer service personnel. The customer information integration function can integrate customer information from different channels and systems into a unified customer view, which is convenient for customer service personnel to fully understand Customer information, the customer information sharing mechanism ensures that authorized customer service personnel can access and update customer information in real time, promotes information sharing and collaboration among teams, and improves the consistency and satisfaction of customer service. The data statistical analysis and visualization display functions can deeply mine and analyze the data stored in the database, generate key performance indicators and reports, and display the analysis results through visualization tools such as charts and dashboards, providing management with intuitive and easy-to-understand decision support, which helps to optimize customer service processes. The integration and interface management functions with various internal systems of the enterprise ensure that the system can seamlessly connect with other business systems to achieve data sharing and process collaboration. This integration method avoids the creation of information islands and improves the overall operational efficiency and collaboration capabilities of the enterprise. The application layer provides targeted operation applications for different user roles to meet the work needs and operating habits of different roles.

[0054] It should be noted that the online customer service application: provides a variety of online customer service channel access methods, such as web chat windows, built-in chat functions in mobile applications, etc., to facilitate real-time communication between customers and customer service personnel. The online customer service application supports the transmission of multiple message formats such as text, pictures, and voice, and has an intelligent customer service assistant function, which can automatically recommend relevant answer words and solutions based on the customer's inquiry content before the customer service personnel reply, thereby improving customer service response speed and service efficiency;

[0055] The work order processing application provides customer service personnel with an operation interface for work order processing, including functions such as work order list display, work order detail viewing, processing opinion filling, and attachment uploading. Customer service personnel can receive and process the work orders assigned to them in the application, view the flow history of the work orders and related customer information, and submit the work orders for review after processing. At the same time, the work order processing application also supports the work order reminder function. When a new work order is assigned or the work order status changes, the customer service personnel are notified in time to process it;

[0056] The customer service management application is mainly aimed at customer service managers, and provides functions such as customer service team management, performance evaluation, and data analysis and viewing. Customer service managers can manage the information of customer service personnel in this application, including personnel information entry, job assignment, skill training records, etc.; by setting performance evaluation indicators (such as work order processing volume, customer satisfaction, response time, etc.), the system automatically calculates the performance scores of customer service personnel and generates performance reports; in addition, customer service managers can also view various data analysis reports generated by the data statistics and analysis module in order to understand the overall work situation of the customer service team, identify problems and formulate improvement measures in a timely manner.

[0057] Preferably, the data layer includes:

[0058] A database module, used to store different types of data, including relational databases and non-relational databases, wherein the relational database is used to store structured data and the non-relational database is used to store unstructured data;

[0059] Data collection interface module, used to collect data from various internal systems of the enterprise and external channels;

[0060] The data backup and recovery module is used to regularly perform full and incremental backups of the database and restore data in the event of system failure or data corruption.

[0061] In this embodiment, the database module includes both relational databases and non-relational databases. This design fully considers the diversity and complexity of data. Relational databases are good at processing structured data and can provide strong data consistency and integrity constraints. They are very suitable for storing customer information, order details and other data that require strict data model support. Non-relational databases are more suitable for storing unstructured data, such as log files, pictures, videos, etc. It can provide higher flexibility and scalability to meet the needs of large data volumes and high concurrent access. Through this combination, the data layer can efficiently store and manage various types of data to meet the needs of different business scenarios; the data acquisition interface module can obtain data from various internal systems of the enterprise (such as ERP, CRM, etc.) and external It collects data comprehensively through various channels (such as social media, email, etc.) to ensure the integrity and accuracy of the data. It also supports real-time or scheduled data collection, and can obtain the latest data in a timely manner according to business needs, providing timely and accurate data support for the business logic layer; the data backup and recovery module regularly performs full and incremental backups of the database to ensure data reliability and security. Full backups can save the complete state of the database at a certain point in time, while incremental backups record changes in the database since the last backup. In the event of system failure or data corruption, the module can quickly restore data, reduce the risk of data loss, and ensure business continuity and stability. In addition, through reasonable backup strategies and management mechanisms, it can also effectively save storage space and reduce backup costs.

[0062] Preferably, the business logic layer includes:

[0063] The work order management module is used to realize intelligent allocation and status tracking of work orders based on the intelligent work order allocation algorithm;

[0064] The customer information management module is used to integrate customer information using entity recognition algorithms and use data synchronization technology to achieve real-time sharing of customer information between different workstations and systems;

[0065] Data statistics and analysis module, used to collect and organize various data in the customer service process, use big data processing technology to analyze data, and perform data visualization and customized report generation;

[0066] The system integration and interface management module is used to design general system interface specifications, achieve docking and data interaction with various systems within the enterprise, and use data encryption technology and access permission control mechanisms to ensure interface security.

[0067] In this embodiment, the work order management module can realize intelligent allocation of work orders according to multiple dimensions such as the skill level of customer service personnel, current workload, and urgency of customer needs through an intelligent work order allocation algorithm. This allocation method not only improves the efficiency of work order processing, but also ensures that customer problems can be solved in a timely and professional manner. At the same time, the module also has a status tracking function, which can record the processing progress and status changes of work orders in real time, provide decision support for management, and optimize customer service workflows; the customer information management module uses an entity recognition algorithm to integrate customer information, effectively avoiding information redundancy and duplication, and improving data consistency and accuracy. Through data synchronization technology, the module can realize real-time sharing of customer information between different workstations and systems, ensuring that customer service personnel can obtain the latest and most comprehensive customer information when handling customer problems. Improved service quality and customer satisfaction; the data statistics and analysis module can collect and organize various data in the customer service process, including call duration, problem resolution rate, customer satisfaction and other key indicators, and use big data processing technology to conduct in-depth analysis of these data, which can reveal the inherent laws and potential problems of customer service work, provide data support for management, and optimize customer service strategies. At the same time, this module also supports data visualization and customized report generation, making data analysis results more intuitive and easy to understand, facilitating management to make scientific decisions; the system integration and interface management module realizes docking and data interaction with various internal systems of the enterprise by designing general system interface specifications, improving the compatibility and scalability of the system, and adopting data encryption technology and access permission control mechanism. This module can ensure the security of interface data transmission and prevent data leakage and illegal access.

[0068] It should be noted that the data statistics and analysis module includes:

[0069] Data collection and organization: Obtain various types of data from the customer service process from the data layer, including work order data, customer interaction data, customer service staff performance data, etc., and organize and classify them according to different analysis dimensions. For example, work order data is classified and counted according to dimensions such as problem type, processing time, and processing results; customer interaction data is analyzed according to dimensions such as customer source, consultation channel, and consultation time;

[0070] Data analysis algorithms and models: Use a variety of data analysis algorithms and models to conduct in-depth analysis of the sorted data. For example, use cluster analysis algorithms to classify customer consultation hot issues and find out the main concerns of different types of customer groups; use time series analysis models to predict the trend of customer service response time so that companies can adjust customer service resource allocation in advance; use association rule mining algorithms to analyze the relationship between customer purchase behavior and consultation issues, and provide a basis for precision marketing;

[0071] Visual display and report generation: The analysis results are displayed on the system interface in the form of intuitive charts (such as bar charts, line charts, pie charts, etc.) and reports, which are convenient for enterprise managers and customer service teams to view and understand. At the same time, the system supports customized generation of data analysis reports according to user needs. The report content includes data summary, analysis results, conclusions and suggestions, etc., which can be sent to relevant personnel regularly or on demand;

[0072] The system integration and interface management module includes:

[0073] Design general system interface specifications, including data format, interface calling method, permission management, etc., so as to connect with other office systems within the enterprise. Develop corresponding adapter interfaces for different types of systems (such as CRM, ERP, etc.) to achieve two-way data transmission and interaction. For example, when connecting with the CRM system, obtain customer sales leads, customer value assessment and other information through the interface, and synchronize customer feedback information and service records generated during the customer service process to the CRM system. When connecting with the ERP system, obtain order status, inventory information and other data, and at the same time feedback the customer's order modification requirements or return information to the ERP system for processing;

[0074] Interface security management: Use data encryption technology (such as SSL / TLS encryption protocol) to encrypt data transmitted by the interface to prevent data leakage; set up access control mechanism to limit access rights to the interface according to different user roles and business needs to ensure the security and stability of the system interface.

[0075] Preferably, the work order management module implements intelligent allocation and status tracking of work orders based on an intelligent work order allocation algorithm, specifically including:

[0076] Use natural language processing technology to conduct in-depth semantic analysis of work order content and extract keywords and problem types from work orders;

[0077] Based on the customer service staff workload prediction model, predict the processing capacity of customer service staff within the preset time;

[0078] According to the keywords and problem types of the work order, as well as the customer service staff's processing capabilities within the preset time, set matching rules with customer service staff, and set weights for each matching rule;

[0079] Calculate the matching degree between each customer service staff and the work order based on the weight and matching rules;

[0080] According to the calculation results of the weighted matching algorithm, the customer service staff with the highest matching degree is selected as the work order assignment object;

[0081] Assigns the ticket to the selected agent and updates the ticket status and the agent's workload.

[0082] In this embodiment, the natural language processing technology is used to perform in-depth semantic analysis on the work order content, and the keywords and problem types of the work order can be accurately extracted. This method avoids the shortcomings of traditional methods based on simple rules or keyword matching, makes the work order allocation more accurate, helps customer service personnel quickly understand and process work orders, and improves work efficiency; the customer service personnel workload prediction model can predict the processing capacity of customer service personnel within a preset time, thereby realizing dynamic monitoring and optimal configuration of customer service resources. Through this prediction, the system can avoid allocating too many work orders to customer service personnel who are already in a high-load state, ensuring that each customer service personnel can efficiently handle work within their own capabilities, avoiding waste and overload of resources; setting matching rules with customer service personnel, and setting weights for each matching rule, so that the system can match work orders based on multiple factors (such as problem type, customer service personnel skills, etc.) This design not only improves the accuracy of matching, but also enables the system to adapt to changes in different business scenarios and customer needs, and enhances the flexibility and adaptability of the system; according to the calculation results of the weighted matching algorithm, the customer service personnel with the highest matching degree are automatically selected as the assignment object of the work order, realizing the automation and intelligence of work order assignment. This allocation method not only reduces manual intervention and improves the allocation efficiency, but also ensures the fairness and rationality of work order allocation, which helps to improve customer satisfaction and the work enthusiasm of customer service personnel; after the work order is assigned to the selected customer service personnel, the system can update the work order status and the workload of the customer service personnel in real time, and realize real-time tracking and monitoring of the work order processing process. This design enables the management to understand the progress of work order processing and the working status of customer service personnel at any time, and improves the transparency and efficiency of management.

[0083] Preferably, the customer information management module integrates customer information using an entity recognition algorithm and uses data synchronization technology to achieve real-time sharing of customer information between different workstations and systems, specifically including:

[0084] Using entity recognition algorithms to identify and classify the collected customer information, and identify meaningful entities, including names of people, places, names of organizations, time, and quantity;

[0085] Building a comprehensive view for each customer based on the identified meaningful entities, the comprehensive view including the customer's basic information, interaction history, preference settings, and value assessment;

[0086] The tree-structured data synchronization method allows the comprehensive view of each customer to be shared in real time between different workstations and systems.

[0087] In this embodiment, the collected customer information is identified and classified through an entity recognition algorithm, and meaningful entities such as names of people, places, names of organizations, time and quantity can be accurately identified. This precise recognition capability ensures the accuracy and completeness of customer information. The identified entity information is integrated into the customer's comprehensive view, making the management of customer information more comprehensive and systematic, which helps customer service personnel to better understand customers and provide more personalized services. The comprehensive view constructed for each customer includes multiple aspects such as the customer's basic information, interaction history, preference settings and value assessment. This design fully considers the diversity and complexity of customer information. The construction of the comprehensive view enables customer service personnel to quickly obtain the customer's complete information and understand the customer's background. and needs, thereby providing more personalized services. At the same time, the comprehensive view also helps companies better evaluate the value of customers and develop more accurate marketing strategies. The tree-structured data synchronization method can ensure that the comprehensive view of each customer is shared in real time between different workstations and systems. The tree structure is used to optimize the data synchronization process, and the speed and stability of data transmission are improved through multi-level data hierarchical management. This real-time synchronization capability enables customer service personnel to obtain the latest customer information at any time, avoiding information lags or inconsistencies. The transparency of data synchronization also helps customer service personnel to collaborate better and improve work efficiency. They can keep abreast of customer information updates on other workstations or systems to ensure consistent and high-quality services for customers.

[0088] It should be noted that the tree-structured data synchronization method shares the comprehensive view of each customer in real time between different workstations and systems. The specific steps include:

[0089] Determine the specific content of the comprehensive customer view that needs to be synchronized, including the customer's basic information, transaction records, service records, etc.;

[0090] According to the hierarchical and logical relationships of the data, a clear tree structure is constructed. In the tree structure, each node represents a data unit or data set, and the nodes are connected through hierarchical relationships;

[0091] Extract the comprehensive customer view data that needs to be synchronized from the data source;

[0092] Arrange the extracted data in a tree structure to ensure that the hierarchical and logical relationships of the data are correct, and perform necessary cleaning and conversion on the data to meet the data format requirements of different workstations and systems;

[0093] Data is synchronized step by step from the top-level node to ensure that the data of each node can be shared in real time between different workstations and systems. During the synchronization process, methods such as text similarity matching can be used to ensure the accuracy and consistency of the data. For mismatched data, manual confirmation and correction can be performed.

[0094] Preferably, the system further comprises:

[0095] The user interface layer is used to provide personalized operation interfaces according to different user roles.

[0096] In this embodiment, personalized operation interfaces are provided according to different user roles (such as customer service personnel, customer service management personnel, customers, etc.). The user interface adopts a responsive design and can adapt to the screen size and resolution of different terminal devices (such as computers, tablets, mobile phones, etc.), so that users can use the system anytime and anywhere; for the operation interface of customer service personnel, attention is paid to the integrity of information display and the convenience of operation. For example, in the work order processing interface, the key information of the work order (such as customer name, problem description, processing time limit, etc.) is highlighted, and quick access to commonly used operation buttons (such as reply, transfer, suspend, etc.) is provided to facilitate customer service personnel to quickly process work orders. In the customer information query interface, customer information is displayed in a list or card layout, which is convenient for customer service personnel to quickly browse and find required information; the customer service management The operating interface for managers focuses on data display and the layout of management functions. For example, in the performance evaluation interface, the performance data comparison of customer service personnel is displayed in the form of charts, which makes it convenient for managers to intuitively understand the differences in the work performance of customer service personnel. In the data analysis interface, it provides viewing entrances for multiple data analysis reports, and supports further screening and drill-down analysis of report data, so that managers can deeply explore the business problems behind the data; the customer interface is designed with simplicity and ease of use as the goal, and pays attention to user experience. For example, the online customer service chat window adopts a simple conversational interface design, and customers can easily enter the consultation content and view the customer service reply. The customer self-service interface provides functional modules such as FAQ, order inquiry, complaint suggestions, etc., which are convenient for customers to solve some common problems by themselves and improve customer satisfaction.

[0097] A multi-station collaborative management method for enterprise customer service, specifically comprising:

[0098] Data layer construction steps: Build different types of databases to store data, and collect data from various internal systems and external channels of the enterprise through data collection interfaces;

[0099] Business logic layer processing steps: intelligent work order allocation, customer information integration and sharing, data statistical analysis and visualization, as well as integration and interface management with various internal enterprise systems are performed at the business logic layer;

[0100] Application layer operation steps: Provide corresponding operation applications for different user roles at the application layer. The operation applications include online customer service applications, work order processing applications, and customer service management applications, allowing each user role to perform corresponding operations according to their respective permissions and needs.

[0101] Preferably, the method further comprises:

[0102] User interface layer personalized configuration steps: Provide a personalized operation interface at the user interface layer according to different user roles.

[0103] A computing device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements any one of the steps of the above-mentioned enterprise customer service multi-station collaborative management method when executing the computer program.

[0104] A computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of any one of the above-mentioned enterprise customer service multi-station collaborative management methods.

[0105] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. An enterprise customer service multi-station collaborative management system, characterized in that: include: The data layer is used to build different types of databases and data collection interfaces. The different types of databases are used to store data, and the data collection interfaces are used to collect data from various internal systems of the enterprise and external channels. Business logic layer, used to realize intelligent work order allocation, customer information integration and sharing, data statistical analysis and visualization, as well as integration and interface management with various internal enterprise systems; The application layer is used to provide corresponding operation applications for different user roles, and the operation applications include online customer service applications, work order processing applications and customer service management applications.

2. According to claim 1, a multi-station collaborative management system for enterprise customer service is characterized in that: The data layer includes: A database module, used to store different types of data, including relational databases and non-relational databases, wherein the relational database is used to store structured data and the non-relational database is used to store unstructured data; Data collection interface module, used to collect data from various internal systems of the enterprise and external channels; The data backup and recovery module is used to regularly perform full and incremental backups of the database and restore data in the event of system failure or data corruption.

3. According to claim 2, a multi-station collaborative management system for enterprise customer service is characterized in that: The business logic layer includes: The work order management module is used to realize intelligent allocation and status tracking of work orders based on the intelligent work order allocation algorithm; The customer information management module is used to integrate customer information using entity recognition algorithms and use data synchronization technology to achieve real-time sharing of customer information between different workstations and systems; Data statistics and analysis module, used to collect and organize various data in the customer service process, use big data processing technology to analyze data, and perform data visualization and customized report generation; The system integration and interface management module is used to design general system interface specifications, achieve docking and data interaction with various systems within the enterprise, and use data encryption technology and access permission control mechanisms to ensure interface security.

4. According to claim 3, a multi-station collaborative management system for enterprise customer service is characterized in that: The work order management module implements intelligent work order allocation and status tracking based on the intelligent work order allocation algorithm, specifically including: Use natural language processing technology to conduct in-depth semantic analysis of work order content and extract keywords and problem types from work orders; Based on the customer service staff workload prediction model, predict the processing capacity of customer service staff within the preset time; According to the keywords and problem types of the work order, as well as the customer service staff's processing capabilities within the preset time, set matching rules with customer service staff, and set weights for each matching rule; Calculate the matching degree between each customer service staff and the work order based on the weight and matching rules; According to the calculation results of the weighted matching algorithm, the customer service staff with the highest matching degree is selected as the work order assignment object; Assigns the ticket to the selected agent and updates the ticket status and the agent's workload.

5. According to claim 4, a multi-station collaborative management system for enterprise customer service is characterized in that: The customer information management module integrates customer information using entity recognition algorithms and uses data synchronization technology to achieve real-time sharing of customer information between different workstations and systems, including: Using entity recognition algorithms to identify and classify the collected customer information, and identify meaningful entities, including names of people, places, names of organizations, time, and quantity; Building a comprehensive view for each customer based on the identified meaningful entities, the comprehensive view including the customer's basic information, interaction history, preference settings, and value assessment; The tree-structured data synchronization method allows the comprehensive view of each customer to be shared in real time between different workstations and systems.

6. According to claim 5, a multi-station collaborative management system for enterprise customer service is characterized in that: The system further comprises: The user interface layer is used to provide personalized operation interfaces according to different user roles.

7. A method for collaborative management of multi-station customer service in an enterprise, characterized in that: Specifically include: Data layer construction steps: Build different types of databases to store data, and collect data from various internal systems and external channels of the enterprise through data collection interfaces; Business logic layer processing steps: intelligent work order allocation, customer information integration and sharing, data statistical analysis and visualization, as well as integration and interface management with various internal enterprise systems are performed at the business logic layer; Application layer operation steps: Provide corresponding operation applications for different user roles at the application layer. The operation applications include online customer service applications, work order processing applications, and customer service management applications, allowing each user role to perform corresponding operations according to their respective permissions and needs.

8. The method for multi-station collaborative management of enterprise customer service according to claim 7, characterized in that: The method further comprises: User interface layer personalized configuration steps: Provide a personalized operation interface at the user interface layer according to different user roles.

9. A computing device, characterized in that It includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the enterprise customer service multi-station collaborative management method described in any one of claims 7-8 are implemented.

10. A computer-readable storage medium, characterized in that: The storage medium stores a computer program, which, when executed by a processor, implements the steps of the enterprise customer service multi-station collaborative management method described in any one of claims 7-8.

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