Data processing method and device, electronic equipment, storage medium and program product

Abstract

The invention provides a data processing method and device, electronic equipment, a storage medium and a program product. The method comprises the following steps: determining a plurality of objects served by a first customer service, and determining the number of times that the first customer service serves each object; based on the number of times, grouping the plurality of objects to obtain a plurality of object groups; determining a customer service identification program of each object group, and dynamically constructing a tree structure for indicating a relationship between the first customer service and the plurality of second customer services based on the first customer service and the plurality of second customer services; and traversing a plurality of second customer services in the tree structure by adopting a customer service identification program corresponding to the object group, and identifying a third customer service corresponding to the object group from the plurality of second customer services. And deleting the plurality of objects from the service list of the first customer service, and distributing the objects in each object group to the service list of the corresponding third customer service. According to the invention, the accuracy of data processing can be effectively improved.

Description

Technical Field

[0001] The present application relates to the field of computer technology, and in particular to a data processing method, device, electronic device, storage medium, and program product. Background Art

[0002] With the rapid development and popularization of the Internet, customer service systems, such as online customer service systems, are systems in which customer service personnel provide customer service to users by using instant messaging. They play an important role in the business activities of enterprises. Customer service systems are service windows that closely connect enterprises and users.

[0003] In related technologies, the transfer of services usually involves directly transferring the object's services to idle customer service staff. However, due to the lack of overall planning for the entire customer service team, the accuracy of data processing is poor. Summary of the Invention

[0004] The embodiments of the present application provide a data processing method, device, electronic device, computer-readable storage medium, and computer program product, which can effectively improve the accuracy of data processing.

[0005] The technical solution of the embodiment of the present application is implemented as follows:

[0006] The present invention provides a data processing method, including:

[0007] Determine a plurality of objects served by the first customer service, and determine the number of times the first customer service serves each of the objects;

[0008] Grouping the multiple objects based on the number of times to obtain multiple object groups;

[0009] Determine a customer service identification program corresponding to each of the object groups, and dynamically construct a tree structure indicating a relationship between the first customer service and the plurality of second customer services based on the first customer service and the plurality of second customer services;

[0010] For each of the object groups, using a customer service identification program corresponding to the object group, traverse the plurality of second customer services in the tree structure, and identify a third customer service corresponding to the object group from the plurality of second customer services;

[0011] The multiple objects are deleted from the service list of the first customer service, and the objects in each object group are respectively assigned to the corresponding service list of the third customer service, where the service list is used to trigger service for the objects in the service request.

[0012] An embodiment of the present application provides a data processing device, including:

[0013] A first determining module is configured to determine a plurality of objects served by the first customer service, and determine the number of times the first customer service serves each of the objects;

[0014] a grouping module, configured to group the plurality of objects based on the number of times to obtain a plurality of object groups;

[0015] a second determination module configured to determine a customer service identification program corresponding to each of the object groups, and dynamically construct a tree structure indicating a relationship between the first customer service and the plurality of second customer services based on the first customer service and the plurality of second customer services; and for each of the object groups, using the customer service identification program corresponding to the object group, traverse the plurality of second customer services in the tree structure to identify a third customer service corresponding to the object group from the plurality of second customer services;

[0016] A transfer module is used to delete the multiple objects from the service list of the first customer service, and to assign the objects in each object group to the corresponding service list of the third customer service, wherein the service list is used to trigger service for the objects in the service request.

[0017] An embodiment of the present application provides an electronic device, including:

[0018] a memory for storing computer-executable instructions or computer programs;

[0019] The processor is used to implement the data processing method provided in the embodiment of the present application when executing the computer-executable instructions or computer programs stored in the memory.

[0020] An embodiment of the present application provides a computer-readable storage medium storing computer-executable instructions for causing a processor to execute the instructions to implement the data processing method provided in the embodiment of the present application.

[0021] An embodiment of the present application provides a computer program product, which includes a computer program or computer-executable instructions stored in a computer-readable storage medium. A processor of an electronic device reads the computer-executable instructions from the computer-readable storage medium and executes the computer-executable instructions, causing the electronic device to perform the data processing method described in the embodiment of the present application.

[0022] The embodiments of the present application have the following beneficial effects:

[0023] By counting the multiple objects served by the first customer service representative and the number of times each object was served, detailed data on customer service workload can be obtained. Objects are then grouped based on the number of times they were served, forming multiple object groups. This step allows objects with similar service needs to be identified and categorized, facilitating subsequent customer service assignments. For each object group, a customer service identification program is determined, and a tree structure is dynamically constructed based on the first customer service representative and multiple second customer service representatives to indicate the relationships between them. This ensures the rational allocation and utilization of customer service resources, enabling flexible organization and management of customer service resources while also clearly demonstrating the hierarchical relationships and collaboration patterns between customer service representatives through the tree structure. Furthermore, the customer service identification program corresponding to the object group is used to traverse the multiple second customer service representatives in the tree structure, identifying the third customer service representative corresponding to the object group from the multiple second customer service representatives. The third customer service representative that matches the object group is accurately identified, ensuring compatibility between the customer service representative and the service object, avoiding resource waste and service mismatch. Multiple objects are deleted from the service list of the first customer service, and the objects in each object group are respectively assigned to the service list of the corresponding third customer service. The service list is used to trigger service for the objects in the service request, thereby realizing the reasonable diversion of customer service resources, avoiding excessive burden on the first customer service, and ensuring that each object can receive timely and effective service. Since data processing is based on the accurate assessment of customer service capabilities and object needs, the accuracy of data processing is effectively improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 Schematic diagram of the data processing system provided in the embodiment of the present application;

[0025] Figure 2 is a schematic diagram of the structure of an electronic device for transferring services provided in an embodiment of the present application;

[0026] Figure 3 Schematic diagram of the data processing method provided in the embodiment of the present application;

[0027] Figure 4 This is a schematic diagram of the principle of the data processing method provided in the embodiment of the present application Figure 1 ;

[0028] Figure 5 This is a schematic diagram of the principle of the data processing method provided in the embodiment of the present application Figure 2 ;

[0029] Figure 6 This is a schematic diagram of the principle of the data processing method provided in the embodiment of the present application Figure 3 ;

[0030] Figure 7 It is a structural diagram of the tree structure provided in the embodiment of the present application. DETAILED DESCRIPTION

[0031] In order to make the purpose, technical solutions and advantages of this application clearer, the application will be further described in detail below with reference to the accompanying drawings. The described embodiments should not be regarded as limiting this application. All other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application.

[0032] In the following description, reference is made to “some embodiments”, which describes a subset of all possible embodiments, but it will be understood that “some embodiments” may be the same subset or different subsets of all possible embodiments and may be combined with each other without conflict.

[0033] In the following description, the terms "first\second\third" involved are merely used to distinguish similar objects and do not represent a specific ordering of the objects. It can be understood that "first\second\third" can be interchanged with a specific order or sequence where permitted, so that the embodiments of the present application described herein can be implemented in an order other than that illustrated or described herein.

[0034] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which this application pertains. The terms used herein are for the purpose of describing the embodiments of this application only and are not intended to limit this application.

[0035] Before further explaining the embodiments of the present application in detail, the nouns and terms involved in the embodiments of the present application are explained. The nouns and terms involved in the embodiments of the present application are subject to the following interpretations.

[0036] 1) Customer Service: This refers to the department within an organization that provides customer service, specifically the services and support needed to meet customer needs and improve customer satisfaction. Customer service can involve communication via phone, email, online chat, or on-site contact, with the goal of helping customers resolve questions, provide information, handle complaints, and offer technical support. Core customer service functions include: Answering inquiries: Providing information about products or services and helping customers understand how to use or operate them. Handling complaints: Listening to customer complaints, taking steps to resolve issues, and striving to prevent similar problems from recurring. Technical support: Providing assistance to customers experiencing technical issues, including troubleshooting and repair instructions. Order processing: Assisting customers with order placement and handling returns and exchanges. After-sales service: Providing follow-up support after a product or service purchase to ensure customer satisfaction and maintain relationships. Caring: Proactively contacting customers to understand product usage and provide personalized service and advice. Customer service serves as a bridge between companies and their customers and is crucial for maintaining customer relationships, enhancing brands, and fostering customer loyalty. With the development of the Internet and social media, the forms of customer service are also constantly evolving, including but not limited to online chatbots, social media customer service, mobile application support, etc.

[0037] 2) Tree structure: This refers to the structure and composition of the department responsible for providing customer service within a company or organization. This structure typically includes multiple levels and roles to ensure efficient customer service operations.

[0038] 3) Organizational Hierarchy: This refers to the hierarchical structure of different levels and functions within an organization. It defines the authority, responsibilities, and decision-making processes within the organization. Within this tree structure, there is typically a clear division of responsibilities and reporting lines between different levels to ensure the organization's efficient operation. Senior management is responsible for setting strategy and direction, middle management is responsible for execution and oversight, grassroots management is responsible for day-to-day operations, frontline employees are responsible for direct customer service, and support and auxiliary staff provide necessary support services. This hierarchical structure helps clarify responsibilities, improve efficiency, and promote the stable development of the organization.

[0039] 4) Service Transfer: In the customer service field, service transfer refers to the process of transferring customer service requests or issues from one customer service representative or department to another. The goal of service transfer is to ensure that customer issues are resolved in the most efficient and professional manner, while also allocating customer service resources and improving overall customer service efficiency and quality. To achieve this goal, customer service centers typically establish a comprehensive data transfer process and standard operating procedures, including clear transfer conditions, responsibilities, and communication methods, as well as ensuring accurate information delivery and continuity of the customer experience.

[0040] During the implementation of the embodiments of this application, the applicant discovered that the related technology has the following problems:

[0041] In related technologies, the transfer of services usually involves directly transferring the object's services to idle customer service staff. However, due to the lack of overall planning for the entire customer service team, the accuracy of data processing is poor.

[0042] The embodiments of the present application provide a data processing method, apparatus, electronic device, computer-readable storage medium, and computer program product, which can effectively improve the accuracy of data processing. The following describes an exemplary application of the data processing system provided by the embodiments of the present application.

[0043] See also Figure 1 , Figure 1 It is a schematic diagram of the architecture of the data processing system 100 provided in an embodiment of the present application. The terminal (terminal 400 is shown as an example) is connected to the server 200 via the network 300. The network 300 can be a wide area network or a local area network, or a combination of the two.

[0044] The terminal 400 is used for the user to use the client 410, and the tree structure is displayed on the graphical interface 410-1 (graphic interface 410-1 is shown as an example). The terminal 400 and the server 200 are connected to each other via a wired or wireless network.

[0045] In some embodiments, the server 200 can be an independent physical server, or a server cluster or business system composed of multiple physical servers, or a cloud server that provides cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, content delivery networks (CDN), and basic cloud computing services such as big data and artificial intelligence platforms. The terminal 400 can be a smart phone, a tablet computer, a laptop computer, a desktop computer, a smart speaker, a smart TV, a smart watch, a car terminal, etc., but is not limited to this. The electronic device provided in the embodiment of the present application can be implemented as a terminal or as a server. The terminal and the server can be directly or indirectly connected via wired or wireless communication, which is not limited in the embodiment of the present application.

[0046] In some embodiments, the server 200 determines multiple objects served by the first customer service, and determines the number of times the objects are served. Based on the number, the multiple objects are grouped to obtain multiple object groups, and a customer service identification program and a tree structure are determined for each object group. For each object group, based on the tree structure, a corresponding customer service identification program is used to determine the third customer service corresponding to the object group from multiple second customer services, and the third customer service is sent to the terminal 400. The terminal 400 transfers the service of each object in the object group from the first customer service to the third customer service.

[0047] In other embodiments, the terminal 400 determines multiple objects served by the first customer service, and determines the number of times the objects are served. Based on the number, the multiple objects are grouped to obtain multiple object groups, and a customer service identification program and a tree structure are determined for each object group. For each object group, based on the tree structure, a corresponding customer service identification program is used to determine a third customer service corresponding to the object group from multiple second customer services, and the third customer service is sent to the server 200. The server 200 transfers the service of each object in the object group from the first customer service to the third customer service.

[0048] In other embodiments, the embodiments of the present application can be implemented with the help of cloud technology. Cloud technology refers to a hosting technology that unifies a series of resources such as hardware, software, and network within a wide area network or local area network to realize data calculation, storage, processing, and sharing.

[0049] Cloud technology is a general term for network, information, integration, management platform, and application technologies used in the cloud computing business model. It can form a resource pool that can be used flexibly and conveniently on demand. Cloud computing technology will become a key support. The backend services of technical network systems require a large amount of computing and storage resources.

[0050] See also Figure 2 , Figure 2 : is a structural diagram of an electronic device 500 for transferring services provided in an embodiment of the present application, wherein: Figure 2 The electronic device 500 shown may be Figure 1 The server 200 or the terminal 400 in Figure 2 The electronic device 500 shown includes: at least one processor 430, a memory 450, and at least one network interface 420. The various components in the electronic device 500 are coupled together via a bus system 440. It is understood that the bus system 440 is used to achieve connection and communication between these components. In addition to including a data bus, the bus system 440 also includes a power bus, a control bus, and a status signal bus. However, for the sake of clarity, the bus system 440 is not described in detail. Figure 2 Various buses are labeled as bus system 440 .

[0051] The processor 430 can be an integrated circuit chip with signal processing capabilities, such as a general-purpose processor, a digital signal processor (DSP), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc., where the general-purpose processor can be a microprocessor or any conventional processor, etc.

[0052] The memory 450 may be removable, non-removable, or a combination thereof. Exemplary hardware devices include solid-state memory, hard drives, optical drives, etc. The memory 450 may optionally include one or more storage devices that are physically remote from the processor 430.

[0053] The memory 450 includes volatile memory or non-volatile memory, or may include both volatile and non-volatile memory. The non-volatile memory may be a read-only memory (ROM), and the volatile memory may be a random access memory (RAM). The memory 450 described in the embodiments of the present application is intended to include any suitable type of memory.

[0054] In some embodiments, the memory 450 can store data to support various operations, examples of which include programs, modules, and data structures, or a subset or superset thereof, as exemplified below.

[0055] Operating system 451, including system programs for processing various basic system services and performing hardware-related tasks, such as the framework layer, core library layer, and driver layer, which are used to implement various basic services and process hardware-based tasks;

[0056] The network communication module 452 is used to reach other electronic devices via one or more (wired or wireless) network interfaces 420. Exemplary network interfaces 420 include: Bluetooth, Wireless Fidelity (WiFi), and Universal Serial Bus (USB).

[0057] In some embodiments, the data processing device provided in the embodiments of the present application can be implemented in software. Figure 2 The data processing device 455 stored in the memory 450 is shown. This device can be software in the form of a program or plug-in, and includes the following software modules: a first determination module 4551, a grouping module 4552, a second determination module 4553, and a transfer module 4554. These modules are logical and can be arbitrarily combined or further separated according to the functions they implement. The functions of each module will be described below.

[0058] In other embodiments, the data processing device provided in the embodiments of the present application can be implemented in hardware. As an example, the data processing device provided in the embodiments of the present application can be a processor in the form of a hardware decoding processor, which is programmed to execute the data processing method provided in the embodiments of the present application. For example, the processor in the form of a hardware decoding processor can adopt one or more application-specific integrated circuits (ASICs), DSPs, programmable logic devices (PLDs), complex programmable logic devices (CPLDs), field programmable gate arrays (FPGAs), or other electronic components.

[0059] In some embodiments, the terminal or server can implement the data processing method provided in the embodiment of the present application by running a computer program or computer executable instructions. For example, the computer program can be a native program (e.g., a dedicated data processing program) or a software module in the operating system, for example, a data processing module that can be embedded in any program (such as an instant messaging client, a photo album program, an electronic map client, a navigation client); for example, it can be a local (Native) application (APP, Application), that is, a program that needs to be installed in the operating system to run. In short, the above-mentioned computer program can be any form of application, module or plug-in.

[0060] The data processing method provided in the embodiments of the present application will be explained in combination with the exemplary application and implementation of the server or terminal provided in the embodiments of the present application.

[0061] See also Figure 3 , Figure 3 This is a flow chart of the data processing method provided in the embodiment of the present application, which will be combined with Figure 3 Steps 101 to 105 are shown for illustration. The data processing method provided in the embodiment of the present application can be implemented by a server or a terminal alone, or by a server and a terminal in collaboration. The following description will be made using the example of implementation by a server alone.

[0062] In step 101, a plurality of objects served by a first customer service is determined, and the number of times the first customer service serves each of the objects is determined.

[0063] In some embodiments, it is necessary to clarify the target of customer service. In most cases, the target of customer service is users or customers. These users may interact with customer service through telephone, online chat, email or other channels. Based on business needs and the nature of customer service, the targets can be further classified. For example, if the customer service service is for after-sales support of a product, the targets can be users of different products; if the customer service service is for corporate customers, the targets can be companies of different sizes or different industries. Information related to each target is collected through the customer service system or other data recording tools. This information may include the user's ID, contact information, type of service request, etc.

[0064] In some embodiments, a specific time range is defined for statistics, such as a day, week, month, or year. The choice of time range depends on the purpose of the analysis and business needs. Interaction records for each subject with the customer service within the specified time range are extracted from the customer service system. These records may include the start and end time of each service, as well as the service content. Each subject's interaction records are counted, and the number of interactions with the customer service within the specified time range is calculated. This can be achieved using simple counting methods, such as counting the number of interaction records for each subject. By counting the number of service visits for each subject, the distribution of service visits can be analyzed. For example, the average or median service visits can be calculated, or the subjects with the highest and lowest service visits can be identified. By analyzing service visits, subjects requiring frequent customer service support can be identified. These subjects may be high-value customers or may have product or service issues requiring improvement. Based on the distribution of service visits, customer service resource allocation can be optimized. For example, more efficient self-service can be provided or requests can be prioritized for subjects with high service visits. By analyzing service visits, potential service issues or customer demand patterns can be identified, allowing actions to improve service quality, such as optimizing product design, improving service processes, or providing additional training.

[0065] As an example, let's assume we are an e-commerce company, and our customer service targets users who purchase products. We need to determine the number of interactions each user has with customer service within a month. Customer service targets users who purchase products, and each user has a unique user ID. We select a one-month timeframe for statistics. We extract all user interaction records for the month from the customer service system, including user ID, interaction time, and interaction content. We count each user's interaction records and calculate the number of interactions each user has with customer service within a month. Analysis of the statistical results reveals that some users have significantly higher service visits than others. These users may be high-value customers, or they may be experiencing frequent product issues and require further attention.

[0066] In step 102, the multiple objects are grouped based on the number of times to obtain multiple object groups.

[0067] In some embodiments, an object group refers to a subset formed by categorizing and combining a group of objects based on a specific frequency or condition. The frequency here may refer to a metric or frequency of occurrence, such as object similarity, number of occurrences, or attribute value thresholds. By grouping these objects based on a preset frequency or rule, members of each object group can be made to have similar characteristics or meet specific conditions.

[0068] In some embodiments, the above-mentioned grouping of the multiple objects based on the number of times to obtain multiple object groups can be achieved in the following manner: determining multiple preset number intervals, and the service feedback of the objects with a number greater than zero for the first customer service; determining the target number interval to which the number of times of each object belongs from the multiple preset number intervals; grouping the multiple objects based on the target number interval and the service feedback to obtain multiple object groups.

[0069] In some embodiments, it is necessary to define multiple preset frequency intervals based on business needs and actual customer interaction patterns. These intervals are used to categorize customers based on the number of interactions they have with customer service. For example, the following frequency intervals can be set: 0-5 times, 6-10 times, 11-20 times, and 21 times or more. Interval divisions can be determined based on historical data, business goals, or industry standards. For example, if the majority of customer interactions occur between 0 and 10 times, this range can be broken down into smaller intervals for more precise analysis. For each customer who interacts with customer service (i.e., with a frequency greater than zero), feedback on the customer service is collected. Service feedback can include satisfaction scores, specific opinions or suggestions, and problem-solving efficiency. Service feedback can be quantitative (e.g., a satisfaction score of 1-5) or qualitative (e.g., a customer's written review). This feedback information is crucial for subsequent grouping and customer service improvements. Each customer is assigned to a preset frequency interval based on the number of interactions they have with customer service. For example, if a customer interacts with customer service eight times during the statistical period, they will be assigned to the "6-10 times" interval. Record the range to which each object belongs for subsequent analysis and grouping operations. When grouping, consider not only the number of interactions of the object, but also its service feedback. For example, two customers may both belong to the "6-10 times" range, but one customer's service feedback is very positive, while the other customer's service feedback is relatively negative. Develop grouping criteria based on business needs and analysis objectives. For example, customers can be divided into the following groups: High-value customer group: customers with a high number of interactions and positive service feedback. Potential high-value customer group: customers with a high number of interactions but neutral service feedback. Customer group that needs attention: customers with a high number of interactions but negative service feedback. Ordinary customer group: customers with a low number of interactions and neutral or positive service feedback. Low-value customer group: customers with a low number of interactions and negative service feedback.

[0070] In some embodiments, targeted service strategies are developed based on the characteristics of different customer groups. For example, for high-value customers, better services or exclusive offers can be provided; for customers requiring attention, proactive contact can be made to understand their issues and improve service. This grouping allows for more efficient allocation of customer service resources, prioritizing the needs of high-value and potential high-value customers. Grouping criteria and service strategies are regularly reassessed to continuously optimize customer service based on customer dynamics and new feedback.

[0071] As an example, we collected customer satisfaction scores (1-5 points) as service feedback. Based on the number of customer interactions and service feedback, we divided customers into the following groups: High-value customer group: customers with 11-20 interactions and a satisfaction score of 4-5 points. Potential high-value customer group: customers with 6-10 interactions and a satisfaction score of 3-4 points. Customers who need attention: customers with 11-20 interactions but a satisfaction score of 1-2 points. Ordinary customer group: customers with 0-5 interactions and a satisfaction score of 3-5 points. Low-value customer group: customers with 0-5 interactions and a satisfaction score of 1-2 points.

[0072] By defining multiple preset frequency intervals, customers can be categorized according to the frequency of their interactions with customer service. This classification method effectively identifies customer groups with varying levels of activity. Furthermore, incorporating service feedback from customers with frequency greater than zero further enriches the dimensions of customer grouping, enabling grouping not only based on interaction frequency but also taking into account customer satisfaction and experience with the service. This approach more comprehensively reflects a customer's actual needs and potential value. For example, customers with frequent interactions and positive feedback can be identified as high-value customers and accorded more attention and resources. Conversely, customers with frequent interactions but negative feedback can be identified as requiring service improvement, allowing targeted measures to improve customer satisfaction.

[0073] In some embodiments, the above-mentioned determination of the target number interval to which the number of times each object belongs from multiple preset number intervals can be achieved in the following manner: performing the following processing for each of the objects separately: comparing the number of times the first customer service serves the object with each of the number intervals respectively, and obtaining a second comparison result for each of the number intervals; if the second comparison result of the number interval indicates that the number of times the first customer service serves the object is within the number interval, then determining the number interval as the target number interval to which the number of times the object belongs.

[0074] In some embodiments, the following process is performed for each subject to extract the subject's interaction count: First, the number of interactions between each subject and the first customer service service is extracted from the customer service system or data records. These numbers are calculated based on the interaction records of each subject with the customer service service within a specific time period.

[0075] In some embodiments, frequency intervals are defined: Based on business needs and actual customer interaction patterns, multiple preset frequency intervals can be defined. For example, the following frequency intervals can be set: 0-5 times; 6-10 times; 11-20 times; and 21 times or more. For each customer, the number of interactions with the customer service provider is compared with each of the above frequency intervals to determine whether the number falls within a certain interval. If the number of interactions with the customer service provider falls within a certain interval, the interval is determined as the target frequency interval for the customer service provider. The interval to which each customer service provider belongs is recorded for subsequent analysis and grouping. Suppose we have three customers, A, B, and C. Their number of interactions with the customer service provider during the statistical period is: Customer A: 8 times; Customer B: 15 times; Customer C: 3 times. Customer A's 8 interactions fall within the 6-10 interval, so their target frequency interval is 6-10 times. Customer B's 15 interactions fall within the 11-20 interval, so their target frequency interval is 11-20 times. Customer C's three interactions fall within the "0-5 times" range, so his target number range is 0-5 times.

[0076] By defining multiple preset frequency intervals, a clear and quantifiable standard for customer classification is provided. These intervals can be flexibly set based on historical data or business needs, ensuring the scientific and practical nature of the classification. Secondly, by comparing each customer's interaction count against these intervals, the customer's interval can be precisely identified. This one-to-one matching process avoids ambiguity in classification and improves the accuracy and efficiency of data processing. Finally, after determining the frequency interval for each customer, the company can use these intervals for more refined customer management and service optimization. For example, customers with a high frequency of interactions can be provided with more personalized services, while those with a low frequency of interactions can be encouraged to increase their activity.

[0077] In some embodiments, the target frequency interval includes a first frequency interval, a second frequency interval, and a third frequency interval, and the subject groups include a first subject group and a second subject group.

[0078] In some embodiments, based on the target number interval and the service feedback, the multiple objects are grouped to obtain multiple object groups, which can be achieved in the following way: clustering the objects belonging to the first number interval and the objects belonging to the second number interval and for which the service feedback is positive feedback to obtain a first object group; clustering the objects belonging to the third number interval and for which the service feedback is positive feedback to obtain a second object group.

[0079] In some embodiments, the target number intervals are: 1st number interval: for example, defined as "6-10 times." 2nd number interval: for example, defined as "11-20 times." 3rd number interval: for example, defined as "21 times or more." Positive feedback: indicates that the customer is highly satisfied with the customer service, such as a satisfaction score of 4-5 points, or the customer clearly expresses satisfaction. Negative feedback: indicates that the customer is less satisfied with the customer service, such as a satisfaction score of 1-2 points, or the customer clearly expresses dissatisfaction.

[0080] In some embodiments, objects belonging to the "first frequency interval" (6-10 times) are screened from all objects. Objects belonging to the "second frequency interval" (11-20 times) and having positive service feedback are screened from all objects. The above-screened objects are merged into a set. Cluster analysis is performed on the objects in this set to obtain a first object group. The purpose of clustering is to group objects with similar characteristics for subsequent analysis and management.

[0081] In some embodiments, objects belonging to the "third number interval" (21 times or more) and having positive service feedback are screened from all objects. Cluster analysis is performed on the screened objects to obtain a second object group. Similarly, the purpose of clustering is to group objects with similar characteristics.

[0082] As an example, suppose we have the following objects and their associated data: Object A: 8 interactions, positive service feedback (satisfaction score of 5). Object B: 12 ​​interactions, positive service feedback (satisfaction score of 4). Object C: 25 interactions, positive service feedback (satisfaction score of 5). Object D: 18 interactions, negative service feedback (satisfaction score of 2). Object E: 6 interactions, negative service feedback (satisfaction score of 1). First object group: Object A (8 interactions, positive feedback) belongs to the "first number interval." Object B (12 interactions, positive feedback) belongs to the "second number interval" and has positive service feedback. Therefore, Objects A and B are clustered into the first object group. Second object group: Object C (25 interactions, positive feedback) belongs to the "third number interval" and has positive service feedback. Therefore, Object C is clustered into the second object group. First object group: These objects have a moderate number of interactions with customer service and good service feedback, and are likely medium-value customers. This group of customers can be targeted with value-added services or further customer relationship management. The second group: These customers have frequent customer service interactions and receive positive feedback, potentially representing high-value customers. This group can be targeted with enhanced services or exclusive offers to enhance customer loyalty.

[0083] By clearly defining frequency intervals and the positive and negative service feedback patterns, this approach provides a multi-dimensional classification basis for grouping customers. First, customers belonging to the first frequency interval are combined with those belonging to the second frequency interval with positive service feedback. This process not only considers customer interaction frequency but also incorporates the key factor of customer satisfaction. This combined approach effectively identifies customer segments with high potential value: those with moderate interaction frequency but satisfactory service experience, and those with high interaction frequency and high satisfaction. By grouping these customers in the first group, companies can provide targeted value-added services or customer loyalty programs to improve customer satisfaction and retention. Second, customers belonging to the third frequency interval with positive service feedback are separately clustered into the second group. This process focuses on identifying high-value customers who interact most frequently with customer service and are highly satisfied with the service. This group typically has a high level of dependence and loyalty to the company's products or services. By grouping them separately, companies can provide them with more personalized services, such as dedicated customer service channels or customized product recommendations, further strengthening customer stickiness and enhancing the customer experience.

[0084] In some embodiments, after determining the target number interval to which the number of times each object belongs from the multiple preset number intervals, the following processing can also be performed: objects whose service feedback is negative feedback, and objects whose number of times is greater than the maximum value of the third number interval, are determined as target objects; and data processing for the target objects is stopped.

[0085] In some embodiments, after completing the division of the object's frequency attribution interval, two types of special objects are further screened out as "target objects:" Objects with negative service feedback: Although these objects have interacted with customer service, their feedback on the service is negative. This may mean that these customers encountered problems during the service process, or were dissatisfied with the customer service's response. Objects with a frequency greater than the maximum value of the third frequency interval: The number of interactions between these objects and customer service is very high, exceeding the preset maximum frequency interval. This may indicate that these customers have frequent service needs, or may repeatedly seek help on certain issues. Background of data processing: In customer service management, "data processing" usually refers to transferring customers from one customer service channel to another, or from one customer service team to another. For example, transferring customers from online customer service to telephone customer service, or from a junior customer service team to a senior customer service team.

[0086] In some embodiments, for objects with negative service feedback: If the customer has already expressed dissatisfaction with the service, frequent data processing may further aggravate the customer's dissatisfaction. Stopping data processing can avoid causing additional trouble to these customers while providing them with a more stable solution. For objects with a number of times greater than the maximum value of the third number interval: These customers have a very high number of interactions with customer service and may require more focused and personalized service. Stopping data processing can ensure that they can continue to interact with the same customer service team or customer service representative, thereby providing a more consistent and efficient service experience.

[0087] As an example, the following intervals are defined: First interval: 0-5; Second interval: 6-10; Third interval: 11-20. Subject A: 8 interactions, positive service feedback. Subject B: 15 interactions, negative service feedback. Subject C: 25 interactions, positive service feedback. Subject D: 3 interactions, negative service feedback. Subject B (15 interactions, negative feedback) and Subject D (3 interactions, negative feedback) are identified as target subjects. Subject C (25 interactions, positive feedback), despite having positive feedback, is also identified as a target subject because its number of interactions exceeds the maximum value of the third interval (20). Because Subjects B and D have negative service feedback, stopping data processing can prevent further exacerbation of their dissatisfaction and provide them with a more stable solution. Because Subject C has a high number of interactions, stopping data processing can ensure that they continue to interact with the same customer service team, providing a more consistent and efficient service experience.

[0088] In this way, categorizing customers by preset frequency intervals effectively distinguishes the frequency of customer interactions with customer service, thereby preliminarily screening high-demand customer groups. Furthermore, customers with negative service feedback and those whose interactions exceed the third maximum interval are identified as target groups. This process not only considers customer interaction frequency but also incorporates customer satisfaction with the service, accurately identifying customers who may be dissatisfied with the service and high-demand customers who frequently seek help. For these target groups, stopping data processing can avoid the degradation of customer experience caused by frequent transfers, reduce customer dissatisfaction, and ensure that high-demand customers receive more consistent and personalized service support.

[0089] In some embodiments, the plurality of second customer service staff include a plurality of fourth customer service staff and a plurality of fifth customer service staff, and the working time of the fourth customer service staff is greater than the working time of the fifth customer service staff.

[0090] In some embodiments, when the object group is the first object group, the fourth customer service corresponding to the object group is determined from the multiple second customer services based on the tree structure and using the corresponding customer service identification program. This can be achieved in the following way: deleting the fifth customer service in the tree structure to obtain the target tree structure of the first object group; and determining the third customer service corresponding to the first object group from the multiple fourth customer services based on the target tree structure of the first object group.

[0091] In some embodiments, multiple second customer service representatives: This is a general set in the customer service team, including customer service personnel of different levels or different experiences. Multiple fourth customer service representatives and multiple fifth customer service representatives: These are two subsets of the second customer service representatives, where the fourth customer service representative has been in office longer than the fifth customer service representative. This means that the fourth customer service representative usually has richer experience or longer service time. The first object group: This is a customer group divided according to customer characteristics (such as service feedback, number of interactions, etc.), and appropriate customer service personnel need to be assigned to serve them.

[0092] In some embodiments, since the fourth customer service representative has been on the job longer and has more experience, it is decided to exclude the fifth customer service representative when selecting a customer service representative for the first object group. All fifth customer service representatives are removed from the tree structure, and only the fourth customer service representative is retained. The organizational structure obtained in this way is called the "target tree structure of the first object group." In the updated organizational structure (which only includes the fourth customer service representative), specific customer service personnel are further selected to serve the first object group. The third customer service representative is selected from the fourth customer service representative, and the specific selection method may be based on a variety of factors, such as: Skill matching: select the customer service representative who is best at handling the needs of the first object group. Workload: select the customer service representative with a lighter current workload to ensure service efficiency. Other business rules: such as shift system, customer service's area of ​​expertise, etc.

[0093] For example, suppose the customer service team has the following agents: A, B, and C (longer tenure); D, E, and F (less tenure). The first customer group is a customer group requiring highly experienced customer service. According to the above method: Step 1: Delete the fifth agents (D, E, and F), resulting in a target tree structure consisting only of the fourth agents (A, B, and C). Step 2: Select a third agent from the fourth agents. Assume that, based on skill matching and workload analysis, agent A is selected as the third agent to serve the first customer group.

[0094] In this way, by distinguishing the tenure of the fourth and fifth customer service representatives, the customer service team is divided into different experience levels, providing a foundation for subsequent precise assignments. The fourth customer service representative, with longer tenure, typically possesses greater experience, stronger problem-solving skills, and a deeper understanding of the business, making them more suitable for handling complex or high-priority customer requests. When the target group is the first target group, removing the fifth customer service representative, with shorter tenure, from the tree structure directly narrows the selection pool, ensuring that subsequent customer service representatives have sufficient experience to address the needs of the first target group. This process not only improves screening efficiency but also reduces service quality issues caused by insufficient customer service experience. Furthermore, by identifying a specific third customer service representative from the fourth customer service representative based on the updated target tree structure, more precise matching can be achieved based on the specific needs of the first target group (such as problem type and urgency). This tiered screening and precise matching approach not only optimizes the utilization of customer service resources, but also improves customer satisfaction, reduces customer wait times and problem resolution time, and thus improves the overall quality and efficiency of customer service.

[0095] In some embodiments, the plurality of second customer service staff include a fourth customer service staff and a fifth customer service staff, and the fourth customer service staff has been in service for a longer period of time than the fifth customer service staff.

[0096] In some embodiments, when the object group is the second object group, the fourth customer service corresponding to the object group is determined from the multiple second customer services based on the tree structure and using the corresponding customer service identification program. This can be achieved in the following way: deleting the fourth customer service in the tree structure to obtain the target tree structure of the second object group; based on the target tree structure of the second object group, determining the third customer service corresponding to the second object group from the multiple fifth customer services.

[0097] In some embodiments, multiple second customer service representatives are a general group within the customer service team, including customer service representatives of different levels or experience levels. A fourth customer service representative and a fifth customer service representative are two subsets of the second customer service representatives, where the fourth customer service representative has been on the job longer than the fifth customer service representative. This means that the fourth customer service representative typically has more experience or has been providing service for a longer time. A second object group is a customer group divided based on customer characteristics (such as service feedback, number of interactions, etc.), to which appropriate customer service representatives need to be assigned.

[0098] In some embodiments, since the second object group may have different demand characteristics (for example, the problem is relatively simple or requires a quick response), it is decided to exclude the experienced fourth customer service and give priority to the fifth customer service. All fourth customer service staff are removed from the tree structure, and only the fifth customer service staff is retained. The organizational structure obtained in this way is called the "target tree structure of the second object group." In the updated organizational structure (including only the fifth customer service), specific customer service staff are further selected to serve the second object group. The third customer service is selected from the fifth customer service, and the specific selection method may be based on a variety of factors, such as: Skill matching: select the customer service who is best at handling the needs of the second object group. Workload: select the customer service with a lighter current workload to ensure service efficiency. Other business rules: such as shift system, customer service area of ​​expertise, etc.

[0099] As an example, assume the following customer service representatives are on the customer service team: Customer Service Representatives A, B, and C (longer tenure and richer experience), Customer Service Representatives D, E, and F (shorter tenure and less experienced). The second customer group is a group of customers who require a quick response but have relatively simple questions. According to the above method: Step 1: Delete the customer service representatives A, B, and C, resulting in a target tree structure consisting only of the customer service representatives D, E, and F. Step 2: Further select a third customer service representative from the customer service representative group. Assume that, based on skill matching and workload analysis, customer service representative D is selected as the third customer service representative to serve the second customer group.

[0100] In this way, by distinguishing the tenure of the fourth and fifth customer service representatives, the customer service team is divided into different experience levels. Since the fourth customer service representative has been on the job longer and has greater experience, they are generally better suited to handling complex or high-priority customer requests. Meanwhile, although the fifth customer service representative has less experience, they may be more familiar with fast-track processes and better suited to handling relatively simple tasks that require a quick response. When the target group is the second target group, by removing the fourth customer service representative from the tree structure, the selection range is directly limited to the fifth customer service representative. This process not only reduces the complexity of the selection but also ensures that the assigned customer service representative can quickly respond to the needs of the second target group. Furthermore, based on the updated target tree structure, the third customer service representative is determined from the fifth customer service representative, enabling more precise matching based on the specific needs of the second target group (such as problem type, urgency, etc.). This hierarchical screening and precise matching approach not only optimizes the utilization efficiency of customer service resources, but also reduces customer wait time and improves problem resolution speed, ultimately achieving a dual optimization of customer experience and enterprise resource utilization.

[0101] In step 103, a customer service identification program for each of the object groups is determined, and a tree structure indicating the relationship between the first customer service and the plurality of second customer services is dynamically constructed based on the first customer service and the plurality of second customer services.

[0102] In some embodiments, the customer service identification program refers to a method of selecting customer service personnel from the customer service team who are suitable for serving a certain group of objects based on specific rules or standards. This selection is usually based on multiple factors, including the customer service experience, skills, current workload, and specific needs of the customer. For example: Selection based on experience: For complex issues or high-value customers, give priority to experienced customer service personnel. Based on skill matching: Select customer service personnel with relevant expertise based on the type of customer problem. Based on workload: Select customer service personnel with a lighter current workload to ensure timeliness of service. Based on customer feedback: Give priority to customer service personnel who have received positive reviews from customers in the past.

[0103] In some embodiments, the tree structure refers to the internal structure and hierarchical relationship of the customer service team, which defines the roles, responsibilities and collaborative relationships between different customer service personnel. Typically, the tree structure divides customer service personnel into different levels or groups based on their experience, skills and responsibilities. For example: First customer service: usually a junior customer service representative who handles common questions and initial customer inquiries. Second customer service: includes higher-level customer service personnel who may have richer experience and a wider range of skills and can handle more complex issues. Fourth customer service and fifth customer service: further subdivided within the second customer service, the fourth customer service has been in office longer and has more experience; the fifth customer service has been in office for a shorter time and has relatively less experience.

[0104] As an example, assume that a company's customer service team is organized as follows: First Customer Service Representative: Responsible for handling common questions and initial inquiries. Second Customer Service Representative: Includes Fourth and Fifth Customer Service Representatives. Fourth Customer Service Representative: Has been in the position for a long time and is experienced, making him suitable for handling complex issues or high-value customers. Fifth Customer Service Representative: Has been in the position for a short time and has less experience, making him suitable for handling simple issues or tasks that require a quick response. When it is necessary to assign a customer service representative to a certain target group, an appropriate customer service representative identification procedure will be selected based on the characteristics and needs of the target group. For example: If the target group is high-value customers with complex issues, the customer service representative identification procedure may prioritize the fourth customer service representative. If the target group is ordinary customers with relatively simple issues, the customer service representative identification procedure may select the fifth customer service representative.

[0105] In some embodiments, the above-mentioned dynamic construction of a tree structure for indicating the relationship between the first customer service and the multiple second customer services based on the first customer service and the multiple second customer services can be achieved in the following manner: performing relationship detection on the first customer service and each of the second customer services to obtain the relationship between the first customer service and each of the second customer services, the relationship being used to indicate whether the service performance of the first customer service is greater than the service performance of the second customer service; based on the relationship, dynamically constructing a tree structure for indicating the relationship between the first customer service and the multiple second customer services.

[0106] In some embodiments, a relationship check is performed between the first customer service representative and each second customer service representative. The purpose of this relationship check is to determine the service performance relationship between the first customer service representative and each second customer service representative. Specifically, this relationship indicates whether the service performance of the first customer service representative exceeds that of a reference customer service representative. The reference customer service representative can be a preset standard customer service representative whose service performance is known and serves as a benchmark for comparison.

[0107] In some embodiments, service performance can be measured using a variety of metrics, such as: Response time: How quickly customer service responds to service requests. Problem resolution rate: The percentage of problems successfully resolved by customer service. Customer satisfaction: Customer satisfaction ratings for customer service. Service duration: The average time it takes for customer service to handle each service request.

[0108] In some embodiments, the root node is the first customer service representative. Child nodes are each second customer service representative. Edge weights are determined based on the relationship R. If R = 1, the edge weight is high, indicating that the first customer service representative's service performance is better than the reference customer service representative, and the second customer service representative can be considered a potential replacement. If R = 0, the edge weight is low, indicating that the first customer service representative's service performance is not better than the reference customer service representative, and the second customer service representative may require further evaluation.

[0109] In some embodiments, the tree structure is constructed dynamically and can be adjusted based on real-time service performance data. For example, if the service performance of a second customer service suddenly improves, its position and weight in the tree can be adjusted accordingly to reflect the latest service performance relationship. After the tree structure is constructed, the second customer service in the tree structure is traversed for each object group using the corresponding customer service identification program. Based on the weights and relationships in the tree structure, the third customer service that best suits the object group is identified. This process ensures that each object group can be assigned the most appropriate customer service, thereby improving service quality and resource utilization efficiency. The dynamic resource management method not only improves the flexibility and adaptability of customer service, but also ensures that service objects can obtain high-quality services, thereby improving the overall customer service level and customer satisfaction.

[0110] In some embodiments, the above-mentioned relationship detection between the first customer service and each of the second customer service to obtain the relationship between the first customer service and each of the second customer service can be achieved in the following manner: performing service performance prediction on the first customer service to obtain the service performance of the first customer service, and performing the following processing for each of the second customer service: performing service performance prediction on the second customer service to obtain the service performance of the second customer service; comparing the service performance of the first customer service with the service performance of the second customer service to obtain the relationship between the first customer service and the second customer service.

[0111] In some embodiments, service performance prediction is crucial for the reasonable allocation of customer service resources by analyzing historical data and real-time data to predict the service performance of customer service representatives in a future period. The service performance prediction for the first customer service representative can be achieved through the following methods: Historical data analysis: Analyze the past service records of the first customer service representative, including indicators such as response time, problem-solving rate, and customer satisfaction. Real-time data monitoring: Monitor the current service status of the first customer service representative, such as the number of service requests being processed currently and response latency. Model prediction: Use machine learning or statistical models to predict the service performance P1 of the first customer service representative based on historical and real-time data.

[0112] Thus, through service performance prediction and comparison of the first customer service representative and each second customer service representative, accurate relationship detection is achieved, providing a scientific basis for the reasonable allocation of customer service resources. The service performance prediction of the first customer service representative obtains its service performance indicators. This process is based on historical data and real-time monitoring, ensuring the accuracy of the prediction results. For each second customer service representative, service performance prediction is also performed to obtain their respective service performance indicators. By comparing the service performance of the first customer service representative and each second customer service representative, the service performance relationship between them can be clarified, that is, whether the service performance of the first customer service representative is better than, equal to, or lower than that of the second customer service representative. The data-driven comparison method avoids the uncertainty of subjective judgment and ensures the objectivity and reliability of relationship detection. The obtained relationship information can be used to construct a customer service hierarchy structure, optimize task allocation, improve customer service efficiency and customer satisfaction, thus significantly enhancing the operational efficiency of the entire customer service system.

[0113] In some embodiments, the above-mentioned multiple second customer service representatives include the jth reference customer service representative, and the relationship includes the jth layer relationship of the jth reference customer service representative, where 1 < j ≤ M, and M is used to indicate the total number of the second customer service representatives.

[0114] In some embodiments, the above-mentioned dynamically constructing a tree structure for indicating the relationship between the first customer service representative and the multiple second customer service representatives based on the relationship can be achieved through the following methods: Based on the first layer relationship between the first customer service representative and the first reference customer service representative, construct the first customer service representative and the first reference customer service representative into the first tree structure; Traverse j and perform the following processing: Based on the jth layer relationship between the first customer service representative and the (j - 1)th tree structure, construct the jth customer service representative and the (j - 1)th tree structure into the jth tree structure; Determine the Mth tree structure as the tree structure for indicating the relationship between the first customer service representative and the multiple second customer service representatives.

[0115] In some embodiments, the service performance of the first customer service is compared with the first reference customer service to obtain the first-level relationship R1. Assume that R1=1 indicates that the service performance of the first customer service is better than the first reference customer service. Assume that R1=0 indicates that the service performance of the first customer service is not better than the first reference customer service. Determine according to R1. If R1=1, the weight of the edge is higher; if R1=0, the weight of the edge is lower. Assume that there are a total of M second customer services, of which the j-th customer service includes reference customer service and ordinary customer service. By traversing j (from 2 to M), the tree structure of each layer is gradually constructed. Compare the service performance of the first customer service and the j-th customer service to obtain the j-th level relationship Rj. Assume that Rj=1 indicates that the service performance of the first customer service is better than the j-th customer service. Assume that Rj=0 indicates that the service performance of the first customer service is not better than the j-th customer service.

[0116] In some embodiments, all nodes in the j-1th tree structure, plus the j-th customer service, are determined according to Rj. If Rj=1, the weight of the edge is higher; if Rj=0, the weight of the edge is lower. Add the j-th customer service to the j-1th tree structure to form a new j-th tree structure. There are 3 second customer services (M=3), of which the first is a reference customer service. Compare the service performance of the first customer service and the first reference customer service to obtain R1. According to the weight of the edges in the tree structure, decide which service objects to assign to which customer services. According to real-time service performance changes, dynamically adjust the tree structure to ensure the rationality of resource allocation. R1=1 (the first customer service is better than the first reference customer service), R2=0 (the first customer service is not better than the second customer service), R3=1 (the first customer service is better than the third customer service).

[0117] In some embodiments, the above-mentioned construction of the first customer service and the first reference customer service into the first tree structure based on the first-level relationship between the first customer service and the first reference customer service can be achieved in the following manner: if the first-level relationship indicates that the service performance of the first customer service is greater than the service performance of the first reference customer service, then the first customer service and the first reference customer service are constructed into the first tree structure with the first customer service as the parent node and the first reference customer service as the child node; if the first-level relationship indicates that the service performance of the first customer service is less than the service performance of the first reference customer service, then the first customer service and the first reference customer service are constructed into the first tree structure with the first reference customer service as the parent node and the first customer service as the child node; if the first-level relationship indicates that the service performance of the first customer service is equal to the service performance of the first reference customer service, then the first reference customer service and the first customer service are constructed into the first tree structure with the first reference customer service and the first customer service as nodes of the same level.

[0118] In some embodiments, service performance predictions are performed on the first customer service and the first reference customer service respectively to obtain their service performance indicators P1 and Pref1. P1 and Pref1 are compared to obtain the first-level relationship R1. The first-level relationship indicates that the service performance of the first customer service is greater than the service performance of the first reference customer service: parent node: first customer service; child node: first reference customer service; tree structure: first customer service as the root node, and the first reference customer service as its child node. The first-level relationship indicates that the service performance of the first customer service is less than the service performance of the first reference customer service: parent node: first reference customer service; child node: first customer service; tree structure: first reference customer service as the root node, and the first customer service as its child node. The first-level relationship indicates that the service performance of the first customer service is equal to the service performance of the first reference customer service: the first customer service and the first reference customer service are nodes of the same level, and they can be placed at the same level, for example, as two child nodes of the root node, or as two independent root nodes.

[0119] In this way, the service performance of the first customer service representative and the first reference customer service representative are compared, and their parent-child or peer-level relationships in the tree structure are determined based on the comparison results. When the first customer service representative's service performance exceeds that of the reference customer service representative, a tree structure is constructed with the first customer service representative as the parent node and the reference customer service representative as the child node. This hierarchical relationship reflects the first customer service representative's superior service performance, enabling them to take on more critical service tasks and manage the reference customer service representative. When the first customer service representative's service performance is lower than that of the reference customer service representative, a tree structure is constructed with the reference customer service representative as the parent node and the first customer service representative as the child node. This demonstrates the reference customer service representative's superior performance and enables them to guide and assist the first customer service representative in improving service quality. When the service performance of the two is equal, the tree structure is constructed with them as nodes at the same level, indicating that they have equal status in service performance and can collaborate to handle service requests. This dynamic construction method based on service performance not only rationally allocates customer service resources based on actual performance differences, but also ensures that each customer service representative is best suited to their role, thereby improving the operational efficiency and service quality of the entire customer service system. It provides a scientific basis for subsequent resource allocation and dynamic adjustment, helping to further optimize the utilization of customer service resources and enhance customer satisfaction.

[0120] In some embodiments, the j-th level relationship mentioned above includes the j-th level sub-relationship corresponding to the j-th customer service and each node in the j-1-th tree structure.

[0121] In some embodiments, based on the j-th layer relationship between the first customer service agent and the (j - 1)-th tree structure, the j-th customer service agent and the (j - 1)-th tree structure are constructed into the j-th tree structure, which can be achieved in the following manner: Determine the j-th layer sub-relationship indicating the same service performance as the j-th customer service agent in the j-th layer relationship as the j-th layer target sub-relationship, and determine the parent node of the node corresponding to the j-th layer target sub-relationship in the (j - 1)-th tree structure as the j-th target node; Construct the node corresponding to the j-th customer service agent as the child node of the j-th target node to obtain the j-th tree structure.

[0122] In some embodiments, the j-th layer relationship is the service performance relationship between the j-th customer service agent and each node in the (j - 1)-th tree structure. The j-th layer sub-relationship is the service performance relationship between the j-th customer service agent and a specific node in the (j - 1)-th tree structure. The j-th tree structure is a tree structure constructed based on the j-th layer relationship, including the j-th customer service agent and all nodes in the (j - 1)-th tree structure. Perform service performance prediction on the j-th customer service agent to obtain Pj. Perform service performance prediction on each node in the (j - 1)-th tree structure to obtain the service performance Pnode of each node. Rj,node = 1 indicates Pj > Pnode; Rj,node = 0 indicates Pj < Pnode; Rj,node = -1 indicates Pj = Pnode. In the j-th layer relationship, find the j-th layer sub-relationship Rj,node = -1 indicating that the service performance of the j-th customer service agent is the same as that of a certain node. Determine the parent node of the node corresponding to the target sub-relationship in the (j - 1)-th tree structure as the j-th target node. Construct the node corresponding to the j-th customer service agent as the child node of the j-th target node to obtain the j-th tree structure.

[0123] In this way, determine the j-th layer sub-relationship in the j-th layer relationship that is the same as the service performance of the j-th customer service agent as the target sub-relationship. Based on the precise comparison of service performance, the accuracy and reliability of the relationship are ensured. Subsequently, determine the parent node of the node corresponding to the target sub-relationship in the (j - 1)-th tree structure as the j-th target node. Utilize the existing tree structure information, avoid repeated calculations and resource waste, and improve the operating efficiency of the system. Finally, construct the node corresponding to the j-th customer service agent as the child node of the j-th target node to form the new j-th tree structure. This dynamic construction method can not only reflect the service performance relationship between customer service agents in real time but also flexibly adjust the tree structure according to actual needs, ensuring that each customer service agent can play its role at its most suitable position. It can allocate customer service resources more reasonably, reduce customer waiting time, improve the problem-solving efficiency, and thus significantly enhance customer satisfaction and enterprise operating efficiency.

[0124] In step 104, for each of the object groups, based on the tree structure, the customer service identification program corresponding to the object group is used to traverse the multiple second customer services in the tree structure, and the third customer service corresponding to the object group is identified from the multiple second customer services.

[0125] In some embodiments, the tree structure includes N organizational levels, each organizational level includes multiple customer service groups, the i-th customer service group in the i-th organizational level includes at least one (i - 1)-th customer service group in the (i - 1)-th organizational level, 1 < i ≤ N, and each first customer service group in the first organizational level includes at least one customer service.

[0126] In some embodiments, the tree structure is a multi-level structure for managing the division of labor and collaboration of the customer service team. It usually includes multiple organizational levels, and each level contains multiple customer service groups. The specific definitions are as follows: N organizational levels: The tree structure is divided into N levels, and each level is responsible for different complexity or types of service tasks. The i-th customer service group in the i-th organizational level: Each organizational level contains multiple customer service groups, and each customer service group is composed of customer service personnel with similar skills or responsibilities. The relationship between levels: The i-th customer service group in the i-th organizational level includes at least one (i - 1)-th customer service group in the (i - 1)-th organizational level (1 < i ≤ N). This means that each high-level customer service group can contain one or more low-level customer service groups, forming a hierarchical nesting relationship. The first organizational level: The bottom organizational level, and each first customer service group includes at least one customer service personnel. These customer service personnel are usually junior customer services handling the most basic service tasks.

[0127] In some embodiments, the object groups are customer groups divided according to customer characteristics (such as demand type, interaction frequency, service feedback, etc.). Each object group may have different service requirements and priorities. To meet these requirements, appropriate customer service personnel need to be selected from the tree structure. The specific steps are as follows: Analyze the characteristics of the object group, for example: Demand complexity: Whether the problems of the object group are complex and require senior customer service to handle. Response speed: Whether the object group requires a quick response. Customer value: Whether the object group contains high-value customers. According to the demand characteristics of the object group, select the most suitable organizational level. For example: If the demand of the object group is complex, preferentially select high-level customer service groups. If the object group requires a quick response, preferentially select low-level customer service groups.

[0128] In some embodiments, in the selected organizational level, further select a specific customer service group. The selection criteria may include: Skill matching: Select the customer service group that is most proficient in handling the requirements of the object group. Workload: Select the customer service group with a lighter current workload to ensure service efficiency. Other business rules: Such as shift systems, the expertise fields of customer services, etc.

[0129] In some embodiments, in a selected customer service group, a specific customer service staff member (the third customer service) is further selected. The selection criteria may include: Experience: Select a customer service with rich experience. Skills: Select a customer service with relevant skills. Workload: Select a customer service with a relatively light current workload.

[0130] In some embodiments, based on the above tree structure, by using the corresponding customer service identification program, to identify the third customer service corresponding to the object group from the multiple second customer services, it can be achieved in the following manner: From the multiple first customer service groups at the first organizational level, determine the first target customer service group where the first customer service is located, and use the corresponding customer service identification program to select the third customer service from the second customer services in the first target customer service group; Based on the number of objects that the second customer services in the first target customer service group can serve, and the total number of objects in the object group, use the customer service identification program corresponding to the object group to select the third customer service from the first reference customer service group and / or the multiple i-th customer service groups at the i-th organizational level.

[0131] In some embodiments, based on the number of objects that the second customer services in the first target customer service group can serve, and the total number of objects in the object group, by using the customer service identification program corresponding to the object group, to select the third customer service from the first reference customer service group and / or the multiple i-th customer service groups at the i-th organizational level, it can be achieved in the following manner: If the number of objects that the second customer services in the first target customer service group can serve is less than the total number of objects in the object group, then use the corresponding customer service identification program to select the third customer service from the first reference customer service group, and the first reference customer service group is the first customer service group different from the first target customer service group among the multiple first customer service groups; If the number of objects that the second customer services in the first reference customer service group can serve is less than the difference between the total number and the number of the already selected third customer services, then traverse i and perform the following processing until the number of the already selected third customer services is equal to the total number: Use the corresponding customer service identification program to select the third customer service from the multiple i-th customer service groups at the i-th organizational level.

[0132] In some embodiments, the definition of the tree structure: The first organizational level: Includes multiple first customer service groups, and each first customer service group includes at least one customer service staff member (the second customer service). The i-th organizational level: Each i-th customer service group includes at least one (i - 1)-th customer service group at the (i - 1)-th organizational level (1 < i ≤ N). The first target customer service group: From the multiple first customer service groups at the first organizational level, determine the customer service group that includes the first customer service. The first reference customer service group: Other first customer service groups different from the first target customer service group.

[0133] In some embodiments, a first target customer service group is identified in the first organizational hierarchy: The first target customer service group is determined by finding a customer service group that includes a first customer service representative from among multiple first customer service groups in the first organizational hierarchy. The first customer service representative is typically a customer service representative who handles basic service tasks. A customer service identification process is implemented to select a second customer service representative from the first target customer service group as the third customer service representative. Selection criteria may include workload, skill matching, and other factors. Customer service capacity is assessed to check whether the number of customers that the second customer service representative in the first target customer service group can serve meets the total number of customers in the customer service group. If capacity is insufficient, if the number of second customer service representatives in the first target customer service group is insufficient to cover all customers in the customer service group, customers are selected from other customer service groups. A first reference customer service group is selected to select another first customer service group from the first organizational hierarchy that is different from the first target customer service group. A customer service identification process is implemented to select a second customer service representative from the first reference customer service group as the third customer service representative to supplement the first target customer service group. A further assessment is performed to check whether the number of customers that the second customer service representative in the first reference customer service group can serve meets the total number of customers in the customer service group.

[0134] In some embodiments, if the number of second agents in the first reference agent group is still insufficient to cover all the subjects in the target group, the organizational structure is traversed upwards, selecting agents from agent groups at higher levels. Layer-by-layer selection: Third agents are selected from multiple i-th agent groups at the i-th organizational level until the number of selected third agents equals the total number of subjects in the target group.

[0135] As an example, assume the following tree structure: Organizational level 1: Customer Service Group 1: Customer Service A and Customer Service B; Customer Service Group 2: Customer Service C and Customer Service D; Organizational level 2: Customer Service Group 3: Customer Service E and Customer Service F (including Customer Service Group 1). Customer Service Group 4: Customer Service G and Customer Service H (including Customer Service Group 2). Organizational level 3: Customer Service Group 5: Customer Service I and Customer Service J (including Customer Service Group 3). Assume that the object group has five objects requiring service.

[0136] Continuing with the previous example, determine the first target customer service group: Customer Service Group 1 (including Customer Service A and Customer Service B). Select the third customer service: Select Customer Service A from Customer Service Group 1 as the third customer service. Examine the customer service capabilities of the first target customer service group. Evaluation: Customer Service Group 1 has two customers (Customer Service A and Customer Service B), but the target group has five customers, which is insufficient to meet the requirements. Select the third customer service from the first reference customer service group. Select Customer Service Group 2 (including Customer Service C and Customer Service D). Select the third customer service: Select Customer Service C from Customer Service Group 2 as the third customer service. Re-evaluate: The number of selected third customers is 2 (Customer Service A and Customer Service C), which is still insufficient to meet the target group's requirement of 5 customers. Select from the second organizational level: Select Customer Service E from Customer Service Group 3 as the third customer service. Select Customer Service G from Customer Service Group 4 as the third customer service. Re-evaluate: The number of selected third customers is 4 (Customer Service A, Customer Service C, Customer Service E, Customer Service G), which is still insufficient to meet the target group's requirement of 5 customers. From the third organizational level, select Customer Service I from the fifth customer service group as the third customer service representative. Final evaluation: Five third customer service representatives have been selected (Customer Service A, Customer Service C, Customer Service E, Customer Service G, and Customer Service I), meeting the five target requirements of the target group.

[0137] In this way, a first target customer service group, containing the first customer service representative, is identified from multiple first customer service groups at the first organizational level, and a third customer service representative is selected from this group. This process utilizes the resources of the grassroots customer service groups and ensures initial service performance. However, if the number of second customers in the first target customer service group is insufficient to meet the total demand of the target group, the method then moves on to the first reference customer service group—a different first customer service group from the first target customer service group—to select a third customer service representative. This step horizontally expands the resource pool, increasing the number of available customers and further improving service coverage. If demand is still not met, the method further traverses customer service groups at higher organizational levels (the i-th organizational level) to select a third customer service representative until the total number of customer service representatives required by the target group is met. This layer-by-layer traversal approach fully utilizes the hierarchical nature of the organizational structure, gradually allocating resources from the grassroots to the top, ensuring that a sufficient number of customer service representatives are allocated to the target group in all circumstances. This not only improves service flexibility and adaptability, but also avoids excessive concentration or waste of resources by dynamically adjusting resource allocation. This maximizes customer demand within limited resources, significantly improving the effectiveness of the customer service system and customer satisfaction.

[0138] In some embodiments, the above-mentioned selection of the third customer service from the multiple i-th customer service groups of the i-th organizational level can be achieved in the following manner: determining the i-th target customer service group where the first customer service is located from the multiple i-th customer service groups of the i-th organizational level; using the corresponding customer service identification program, selecting the third customer service from the i-th reference customer service group, the i-th reference customer service group being the i-th customer service group among the multiple i-th customer service groups that is different from the i-th target customer service group.

[0139] In some embodiments, the i-th organizational level: This is the i-th level in the tree structure, containing multiple i-th customer service groups. Each i-th customer service group is composed of customer service personnel with similar skills or responsibilities. The i-th target customer service group: From the multiple i-th customer service groups in the i-th organizational level, a customer service group that includes the first customer service representative is determined. The first customer service representative is typically a customer service representative who handles basic service tasks or a customer service representative with specific responsibilities in the current level.

[0140] In some embodiments, a customer service identification procedure is used to select a third customer service representative from the i-th target customer service group. The customer service identification procedure involves selecting a suitable customer service representative from the i-th target customer service group based on pre-set rules and criteria. These rules may include: Skill matching: selecting a customer service representative with skills relevant to the needs of the target group; Workload: selecting a customer service representative with a light workload to ensure service efficiency; Experience: selecting a customer service representative with extensive experience to ensure service quality; Selecting a third customer service representative: selecting one or more customer service representatives from the i-th target customer service group as the third customer service representative based on the customer service identification procedure; Assessing customer service capacity: checking whether the number of customers that the second customer service representative in the i-th target customer service group can serve meets the total number of customers in the target group. If capacity is insufficient: if the number of second customer service representatives in the i-th target customer service group is insufficient to cover all customers in the target group, a customer service representative is selected from another customer service group. An i-th reference customer service group is selected from a different customer service group from the i-th target customer service group within the i-th organizational hierarchy. Using the customer service identification procedure: selecting one or more customer service representatives from the i-th reference customer service group based on the same customer service identification procedure as the third customer service representative to supplement the i-th target customer service group. Re-evaluation: Check whether the number of objects that the second customer service in the i-th reference customer service group can serve meets the total number requirement of the object group.

[0141] As an example, assume the following tree structure: First organizational level: Customer Service Group 1: Customer Service A and Customer Service B; Customer Service Group 2: Customer Service C and Customer Service D. Second organizational level: Customer Service Group 3: Customer Service E and Customer Service F (including Customer Service Group 1); Customer Service Group 4: Customer Service G and Customer Service H (including Customer Service Group 2); Third organizational level: Customer Service Group 5: Customer Service I and Customer Service J (including Customer Service Group 3). Determine the second target customer service group. Second target customer service group: From the multiple second customer service groups in the second organizational level, determine the second target customer service group that includes the first customer service representative. Assume that the first customer service representative is in the third customer service group. Select the third customer service representative: Select Customer Service E from the third customer service group as the third customer service representative. Examine the customer service capabilities of the second target customer service group. Evaluation: There are two customers (Customer Service E and Customer Service F) in the third customer service group, but the target group has five targets, which is insufficient to meet the requirements. Select the third customer service representative from the second reference customer service group. Select the second reference customer service group: Select a second customer service group from the second organizational hierarchy, different from the third customer service group, to become the fourth customer service group. Select the third customer service: Select customer service G from the fourth customer service group as the third customer service. Re-evaluate: The number of selected third customer service representatives is three (Customer Service E, Customer Service F, and Customer Service G), which is still insufficient to meet the five target group requirements.

[0142] In this way, the i-th target customer service group, which includes the first customer service representative, is determined from multiple i-th customer service groups at the i-th organizational level. This process ensures coverage of basic service performance. Subsequently, a customer service identification process is used to select a third customer service representative from the i-th target customer service group. This approach is typically based on factors such as the customer service representative's workload and skill matching, ensuring that the selected customer service representative can efficiently and efficiently meet the target group's needs. However, if the customer service capabilities of the i-th target customer service group are insufficient to meet all the needs of the target group, the method then switches to the i-th reference customer service group—an i-th customer service group different from the i-th target customer service group—to select a third customer service representative. This dynamic adjustment mechanism not only expands the resource pool and increases the number of available customers, but also balances the workload across customer service groups by selecting customers from different customer service groups, avoiding excessive concentration or waste of resources. This approach not only improves service flexibility and adaptability, but also optimizes resource allocation to ensure maximum customer satisfaction within limited resources, significantly enhancing the effectiveness of the customer service system and customer satisfaction.

[0143] In step 105, the multiple objects are deleted from the service list of the first customer service, and the objects in each object group are respectively assigned to the corresponding service list of the third customer service, and the service list is used to trigger service for the objects in the service request.

[0144] In some embodiments, object: each individual in the object group, a customer or user who needs service provided by customer service. Service list: a list that records the objects that need to be handled by a specific customer service. Each third customer service has its own service list for managing and serving the customers assigned to them. According to the previously determined third customer service, each object in the object group is assigned to the service list of the corresponding third customer service. This process is usually based on certain rules or standards, such as: Skill matching: assigning objects to the most suitable customer service based on the needs of the object and the skills of the third customer service. Workload: Based on the current workload of the third customer service, assign objects to customer service with lighter workload to ensure service efficiency. Customer value: Based on the importance and value of the object, high-value customers are preferentially assigned to experienced customer service.

[0145] In some embodiments, the service list is not only a tool for assigning objects but also triggers third-party customer service representatives to provide services to objects in the service list. Once objects are assigned to the third-party customer service representative's service list, the third-party customer service representative receives a notification or reminder to begin addressing these objects' needs. The service list helps third-party customer service representatives manage their work, ensuring that each object receives timely and effective service. It can also be used to monitor service progress and quality, facilitating management evaluation and optimization.

[0146] As an example, assume we have the following customer service representatives and objects: Customer Service A is the first customer service representative; Customer Service B and Customer Service C are the third customer service representatives; and the object group contains five objects (User 1, User 2, User 3, User 4, and User 5). Determine the third customer service representative: Based on the customer service identification procedure, select Customer Service B and Customer Service C as the third customer service representatives. Assign objects: Assign User 1 and User 2 to Customer Service B. Assign User 3, User 4, and User 5 to Customer Service C. Update the service list: Add User 1 and User 2 to Customer Service B's service list. Add User 3, User 4, and User 5 to Customer Service C's service list. Customer Service B receives the notification and begins handling the requests of User 1 and User 2. Customer Service C receives the notification and begins handling the requests of User 3, User 4, and User 5.

[0147] In this way, through a clear allocation mechanism, each subject in the subject group is precisely assigned to the corresponding third-party agent. This process ensures a good match between subjects and agents, avoiding the inefficiencies and decreased customer satisfaction that can result from random assignments. The introduction of a service list provides third-party agents with a clear task management tool, enabling them to systematically manage and prioritize their assigned subjects, thereby optimizing workflows and improving service efficiency. Furthermore, the service list's triggering mechanism ensures timely and consistent service, preventing delays or omissions due to busy agent workloads. This approach not only ensures that every subject receives a timely response, but also allows for real-time evaluation of agent performance by monitoring the progress of the service list, further optimizing the allocation of customer service resources. This service list-based transfer and triggering mechanism not only improves service accuracy and efficiency, but also enhances the customer experience, helping companies win customer trust and loyalty in a highly competitive market.

[0148] In this way, by counting the multiple objects served by the first customer service representative and the number of times each object is served, detailed data on the customer service workload can be obtained. Objects are then grouped based on the number of times they are served, forming multiple object groups. This step allows objects with similar service needs to be identified and categorized, facilitating subsequent customer service assignments. For each object group, a customer service identification program is determined, and a tree structure is dynamically constructed based on the first customer service representative and multiple second customer service representatives to indicate the relationship between the first customer service representative and the multiple second customer service representatives. This ensures the rational allocation and utilization of customer service resources, not only enabling flexible organization and management of customer service resources, but also clearly demonstrating the hierarchical relationships and collaboration patterns between customer service representatives through the tree structure. On this basis, the customer service identification program corresponding to the object group is used to traverse the multiple second customer service representatives in the tree structure, identifying the third customer service representative corresponding to the object group from the multiple second customer service representatives. The third customer service representative that matches the object group is accurately identified, ensuring compatibility between the customer service representative and the service object, and avoiding resource waste and service mismatch. Multiple objects are deleted from the service list of the first customer service, and the objects in each object group are respectively assigned to the service list of the corresponding third customer service. The service list is used to trigger service for the objects in the service request, thereby realizing the reasonable diversion of customer service resources, avoiding excessive burden on the first customer service, and ensuring that each object can receive timely and effective service. Since data processing is based on the accurate assessment of customer service capabilities and object needs, the accuracy of data processing is effectively improved.

[0149] Below, an exemplary application of the embodiment of the present application in an actual online customer service application scenario will be described.

[0150] See also Figure 4 , Figure 4 This is a schematic diagram of the principle of the data processing method provided in the embodiment of the present application Figure 1 After receiving the agent's departure message from Kafka, this solution will automatically retrieve all the lists of the departing agent. Subsequently, the queue decision module will divide the lists of this agent into different transfer queues. Then, the list transfer module will match the transfer objects and transfer limits level by level and perform transfer operations, etc. Finally, the transferred agent will be notified.

[0151] See Figure 5 , Figure 5 is a schematic diagram of the principle of the data processing method provided by the embodiment of the present application Figure 2 , the lists of the departing agent will be put into three types of queues: the priority transfer queue, the secondary transfer queue, and the queue to be filtered, according to certain decision rules. The lists in the priority transfer queue have relatively high continuous marketing value and will be preferentially transferred to full-time agents for continuous marketing; the marketing value of the lists in the secondary transfer queue is not very high, and they will be transferred to intern agents for calling practice; the lists in the queue to be filtered are generally lists with too many marketing times and potential complaint risks, and such lists will not be transferred anymore but directly filtered out. Obtain the call records of the lists in the past 30 days. Count the number of calls. If the number of calls = 0, it means that the list has not been marketed yet and has relatively high continuous marketing value, and the list will be directly put into the priority transfer queue. If 0 < the number of calls < T1 (configurable), the list has been called, but the number of calls is not very large. Further analyze the call results. Detect whether the call results contain labels such as swearing, high disgust, and explicit rejection. If so, it means that it is no longer suitable for marketing and put it into the queue to be filtered. If the above labels are not included, put it into the priority transfer queue. If T1 < the number of calls < T2 (configurable), the list has been marketed a certain number of times, but can still be continuously marketed to a certain extent. Then further analyze the call results. Detect whether the call results contain labels such as swearing, high disgust, and explicit rejection. If so, it means that it is no longer suitable for marketing and put it into the queue to be filtered. If the above labels are not included, put it into the secondary transfer queue. If the number of calls >= T (configurable), it means that the list has been marketed too many times. If it is transferred to other agents for marketing, it may cause customer complaints and there is a risk of complaints. Therefore, the list can be directly put into the queue to be filtered.

[0152] In some embodiments, see Figure 6 , Figure 6 is a schematic diagram of the principle of the data processing method provided by the embodiment of the present application Figure 3, the rosters in the priority transfer queue and the secondary transfer queue are transferred to full-time agents and trainee agents, respectively, in a step-by-step matching process. The rosters in the filtering queue are then removed from the queue for filtering. Both the rosters in the priority transfer queue and the secondary transfer queue are transferred according to the following process. The only difference is that the rosters in the priority transfer queue are transferred only to full-time agents, while the rosters in the secondary transfer queue are transferred only to trainee agents.

[0153] In some embodiments, see Figure 7 , Figure 7 It is a structural diagram of the tree structure provided by the embodiment of the present application. According to the organizational structure, priority is given to matching upwards step by step. Priority is given to members of the same group, and then to organizations at the same level as their superior organizations. For example, if Zhang San of Zhang San's group resigns, the list under Zhang San will be transferred to Zhang San 2 and Zhang San 3 in Zhang San's group first; if there are any remaining, they will continue to be transferred to Li Si's group, Wang Wu's group and other members at the same level as Zhang San's group; similarly, if there are any remaining after transferring all the group members under Yongchuan District 1, they will continue to be transferred to Yongchuan District 2, Yongchuan District 3 and other group members, and so on, until the list in the queue is exhausted. Transfer limit. The magnitude of the list that each seat can undertake is limited. In the process of list transfer, the upper limit of the list that the transferred seat can undertake should be fully considered. At the same time, in order to ensure fair competition between groups and between districts and divisions, the magnitude of the transfer list should decrease step by step from bottom to top with the organizational structure, so the transfer limit of each level should be set separately. Assume that the maximum number of lists each agent can handle is T. The organizational structure has 5, 4, 3, 2, and 1 levels from bottom to top, and their corresponding transfer limits are L5, L4, L3, L2, and L1, respectively. The transfer limit relationship is: L5>L4>L3>L2>L1. Therefore, the number of lists that the transferred agent can be assigned can be recorded as: S = Min(Li, (TN))

[0154] Where S is the maximum number of lists that the transferred agent can be assigned, Li is the transfer limit for the agent's organizational structure level, T is the upper limit of the number of lists that the agent can handle, and N is the number of lists the agent currently owns.

[0155] Let's take Zhang San's resignation as an example. Zhang San 2, who is in the same group as Zhang San, is at the lowest level of the entire organizational structure, namely L5. Let L5 = 50, the upper limit of the seat acceptance list size T = 1500, and Zhang San currently has N = 1475 lists under him. Then, the maximum size of the list that Zhang San 2 can be assigned in this round of transfer is: S = Min (50, (1500-1475)) = 25. Similarly, Li Si in Li Si's group is at level L4. Let L4 = 30, and Li Si currently has N = 1300 lists under him. Then, in this round, the maximum size of the list that Li Si can be assigned is: S = Min (30, (1500-1300)) = 30.

[0156] In some embodiments, a transfer is performed. Traverse the members of each level of organization from bottom to top in turn, and query the level of their existing lists. Shuffle the personnel in the organization of the same level (to ensure fairness among members of the organization of the same level), and then calculate the maximum level of the transfer list that each person can be allocated in turn, pull the lists of corresponding levels from the queue in turn, and transfer them until the list in the queue is empty and the transfer process ends. The transferred list will be marked with a transfer list label so that the agent can filter directly according to the label (pass: during the transfer process, the list in the priority transfer queue will only be transferred to the formal seat, and the list in the secondary transfer queue will only be transferred to the intern seat). Treat the lists in the filtered queue, dequeue them in turn, filter out the lists, and no longer market them. After the list transfer is completed, the transferred agent will be notified through a websocket pop-up window that a new xxx transfer list has been added to remind them to pay attention.

[0157] In this way, the fully automatic list transfer greatly improves the transfer speed and saves scheduling labor costs. Through the queue decision module, the list of resigned agents is finely divided according to the number of calls and the effect of the calls, so that they enter different transfer queues according to the specified decision rules, so that the lists of different queues can be handled more reasonably. The lists in the priority queue are marketed to formal agents to increase the probability of loan conversion; the lists in the secondary queue are marketed to trainee agents, who can practice while avoiding affecting the loan issuance of high-quality lists; the filtered queue is no longer transferred for marketing, reducing customer complaints. Through the list queue transfer module, the list of the resigned agent is transferred in sequence by utilizing the organizational structure of the agent and a step-by-step upward matching mechanism. Compared with the method of directly assigning it to a certain person or group, this solution fully guarantees fair competition between groups and between business districts. At the same time, the list of the resigned agent can be given priority to the group, business district, etc. by utilizing the graded transfer limit, so as to reduce the loss of the group or business district caused by the departure of personnel. The scale of the list transferred to each agent is calculated by comprehensively considering the upper limit of the agent's acceptance list and the transfer limit, avoiding the excessive number of lists under the name of a certain agent after the transfer, so that the list can be marketed in a timely manner. By labeling the transferred list and receiving websocket notification reminders, the agent whose list is transferred can easily filter out the transferred list for marketing calls.

[0158] It is understandable that in the embodiments of the present application, when data related to objects is involved and is applied to specific products or technologies, user permission or consent is required, and the collection, use and processing of relevant data must comply with relevant laws, regulations and standards of relevant countries and regions.

[0159] The following continues to describe the exemplary structure of the data processing device 455 provided in the embodiment of the present application implemented as a software module. In some embodiments, such as Figure 2 As shown, the software modules stored in the data processing device 455 of the memory 450 may include: a first determination module, used to determine multiple objects served by the first customer service, and determine the number of times the first customer service serves each of the objects; a grouping module, used to group the multiple objects based on the number of times to obtain multiple object groups; a second determination module, used to determine the customer service identification program corresponding to each of the object groups, and dynamically construct a tree structure for indicating the relationship between the first customer service and the multiple second customer services based on the first customer service and the multiple second customer services; for each of the object groups, using the customer service identification program corresponding to the object group, traverse the multiple second customer services in the tree structure, and identify the third customer service corresponding to the object group from the multiple second customer services; a transfer module, used to delete the multiple objects from the service list of the first customer service, and assign the objects in each of the object groups to the service list of the corresponding third customer service, and the service list is used to trigger service for the objects in the service request.

[0160] In some embodiments, the above-mentioned second determination module is also used to perform relationship detection on the first customer service and each of the second customer service to obtain the relationship between the first customer service and each of the second customer service, and the relationship is used to indicate whether the service performance of the first customer service is greater than the service performance of the second customer service; based on the relationship, a tree structure is dynamically constructed to indicate the relationship between the first customer service and the multiple second customer services.

[0161] In some embodiments, the above-mentioned second determination module is also used to predict the service performance of the first customer service to obtain the service performance of the first customer service, and perform the following processing for each of the second customer service: predict the service performance of the second customer service to obtain the service performance of the second customer service; compare the service performance of the first customer service with the service performance of the second customer service to obtain the relationship between the first customer service and the second customer service.

[0162] In some embodiments, the multiple second customer service representatives include the j-th reference customer service representative, and the relationship includes the j-th layer relationship of the j-th reference customer service representative, where 1 < j ≤ M, and M is used to indicate the total number of the second customer service representatives; the above-mentioned second determination module is further configured to construct the first customer service representative and the first reference customer service representative into the first tree structure based on the first layer relationship between the first customer service representative and the first reference customer service representative; traverse j and perform the following processing: based on the j-th layer relationship between the first customer service representative and the (j - 1)-th tree structure, construct the j-th customer service representative and the (j - 1)-th tree structure into the j-th tree structure; determine the M-th tree structure as the tree structure used to indicate the relationship between the first customer service representative and the multiple second customer service representatives.

[0163] In some embodiments, the above-mentioned second determination module is further configured to, if the first layer relationship indicates that the service performance of the first customer service representative is greater than the service performance of the first reference customer service representative, construct the first customer service representative and the first reference customer service representative into the first tree structure with the first customer service representative as the parent node and the first reference customer service representative as the child node; if the first layer relationship indicates that the service performance of the first customer service representative is less than the service performance of the first reference customer service representative, construct the first customer service representative and the first reference customer service representative into the first tree structure with the first reference customer service representative as the parent node and the first customer service representative as the child node; if the first layer relationship indicates that the service performance of the first customer service representative is equal to the service performance of the first reference customer service representative, construct the first customer service representative and the first reference customer service representative into the first tree structure with the first reference customer service representative and the first customer service representative as nodes at the same level.

[0164] In some embodiments, the j-th layer relationship includes the j-th layer sub-relationships of the j-th customer service representative corresponding to each node in the (j - 1)-th tree structure; the above-mentioned second determination module is further configured to determine the j-th layer sub-relationship indicating the same service performance as the j-th customer service representative in the j-th layer relationship as the j-th layer target sub-relationship, and determine the parent node of the node corresponding to the j-th layer target sub-relationship in the (j - 1)-th tree structure as the j-th target node; construct the node corresponding to the j-th customer service representative as the child node of the j-th target node to obtain the j-th tree structure.

[0165] In some embodiments, the grouping module is further configured to determine multiple preset time intervals, and the service feedback of the object with a positive number of times for the first customer service representative; determine the target time interval to which the number of times of each object belongs from the multiple preset time intervals; group the multiple objects based on the target time interval and the service feedback to obtain multiple object groups.

[0166] In some embodiments, the grouping module is also used to perform the following processing for each of the objects: compare the number of times the first customer service serves the object with each of the number intervals, and obtain a second comparison result for each of the number intervals; if the second comparison result of the number interval indicates that the number of times the first customer service serves the object is within the number interval, then the number interval is determined as the target number interval to which the number of times the object belongs.

[0167] In some embodiments, the target number interval includes a first number interval, a second number interval, and a third number interval, the object group includes a first object group and a second object group, and the grouping module is further used to cluster the objects belonging to the first number interval and the objects belonging to the second number interval and whose service feedback is positive feedback to obtain a first object group; and cluster the objects belonging to the third number interval and whose service feedback is positive feedback to obtain a second object group.

[0168] In some embodiments, the grouping module is further used to determine the objects whose service feedback is negative feedback and the objects whose number of times is greater than the maximum value of the third number interval as target objects; and stop data processing for the target objects.

[0169] In some embodiments, the above-mentioned grouping module is also used to delete the fifth customer service in the tree structure to obtain the target tree structure of the first object group; based on the target tree structure of the first object group, determine the third customer service corresponding to the first object group from the multiple fourth customer services.

[0170] In some embodiments, the multiple second customer service personnel include a fourth customer service personnel and a fifth customer service personnel, and the fourth customer service personnel has been in service longer than the fifth customer service personnel; the above-mentioned grouping module is also used to delete the fourth customer service personnel in the tree structure to obtain the target tree structure of the second object group; based on the target tree structure of the second object group, determine the third customer service personnel corresponding to the second object group from the multiple fifth customer service personnel.

[0171] In some embodiments, the tree structure includes N organizational levels, each organizational level includes a plurality of customer service groups, the ith customer service group in the ith organizational level includes at least one (i - 1)th customer service group in the (i - 1)th organizational level, 1 < i ≤ N, and each first customer service group in the first organizational level includes at least one customer service; the second determination module is further configured to determine the first target customer service group where the first customer service is located from the plurality of first customer service groups in the first organizational level, and select the third customer service from the second customer services in the first target customer service group by using a corresponding customer service identification program; based on the number of objects that the second customer service in the first target customer service group can serve and the total number of objects in the object group, select the third customer service from the first reference customer service group and / or the plurality of ith customer service groups in the ith organizational level by using the customer service identification program corresponding to the object group.

[0172] In some embodiments, the second determination module is further configured to, if the number of objects that the second customer service in the first target customer service group can serve is less than the total number of objects in the object group, select the third customer service from the first reference customer service group by using a corresponding customer service identification program, and the first reference customer service group is the first customer service group different from the first target customer service group among the plurality of first customer service groups; if the number of objects that the second customer service in the first reference customer service group can serve is less than the difference between the total number and the number of the third customer service already selected, traverse i and perform the following processing until the number of the third customer service already selected is equal to the total number: select the third customer service from the plurality of ith customer service groups in the ith organizational level by using a corresponding customer service identification program.

[0173] In some embodiments, the second determination module is further configured to determine the ith target customer service group where the first customer service is located from the plurality of ith customer service groups in the ith organizational level; select the third customer service from the ith reference customer service group by using a corresponding customer service identification program, and the ith reference customer service group is the ith customer service group different from the ith target customer service group among the plurality of ith customer service groups.

[0174] An embodiment of the present application provides a computer program product, which includes a computer program or computer executable instructions, and the computer program or computer executable instructions are stored in a computer-readable storage medium. A processor of an electronic device reads the computer executable instructions from the computer-readable storage medium, and the processor executes the computer executable instructions, so that the electronic device executes the data processing method in the embodiment of the present application described above.

[0175] The embodiment of the present application provides a computer-readable storage medium storing computer-executable instructions, wherein the computer-executable instructions are stored. When the computer-executable instructions are executed by a processor, the processor will execute the data processing method provided by the embodiment of the present application, for example, Figure 3 The data processing method is shown.

[0176] In some embodiments, the computer-readable storage medium may be a memory such as FRAM, ROM, PROM, EPROM, EEPROM, flash memory, magnetic surface storage, optical disk, or CD-ROM; or various electronic devices including one or any combination of the above memories.

[0177] In some embodiments, computer-executable instructions may be in the form of a program, software, software module, script, or code, written in any form of programming language (including compiled or interpreted languages, or declarative or procedural languages), and may be deployed in any form, including as a stand-alone program or as a module, component, subroutine, or other unit suitable for use in a computing environment.

[0178] As an example, computer-executable instructions may, but need not, correspond to a file in a file system, may be stored as part of a file that stores other programs or data, such as, for example, in one or more scripts in a HyperText Markup Language (HTML) document, in a single file dedicated to the program in question, or in multiple coordinating files (e.g., files storing one or more modules, subroutines, or code portions).

[0179] By way of example, computer-executable instructions may be deployed to be executed on one electronic device, or on multiple electronic devices located at one site, or on multiple electronic devices distributed across multiple sites and interconnected by a communication network.

[0180] In summary, the embodiments of the present application have the following beneficial effects:

[0181] (1) By counting the multiple objects served by the first customer service and the number of times each object is served, detailed data on the customer service workload can be obtained. The objects are grouped based on the number of services to form multiple object groups. This step enables objects with similar service needs to be identified and classified, facilitating subsequent customer service allocation. For each object group, its customer service identification program is determined, and based on the first customer service and multiple second customer services, a tree structure is dynamically constructed to indicate the relationship between the first customer service and multiple second customer services, ensuring the reasonable allocation and utilization of customer service resources. Not only does it achieve flexible organization and management of customer service resources, but it also clearly displays the hierarchical relationship and collaboration model between customer services through the tree structure. On this basis, the customer service identification program corresponding to the object group is used to traverse the multiple second customer services in the tree structure, identify the third customer service corresponding to the object group from the multiple second customer services, and accurately identify the third customer service that matches the object group, ensuring the adaptability between the customer service and the service object, and avoiding waste of resources and mismatch of services. Multiple objects are deleted from the service list of the first customer service, and the objects in each object group are respectively assigned to the service list of the corresponding third customer service. The service list is used to trigger service for the objects in the service request, thereby realizing the reasonable diversion of customer service resources, avoiding excessive burden on the first customer service, and ensuring that each object can receive timely and effective service. Since data processing is based on the accurate assessment of customer service capabilities and object needs, the accuracy of data processing is effectively improved.

[0182] (2) By determining multiple preset frequency intervals, customers can be classified according to the frequency of interaction with customer service. This classification method can effectively identify customer groups with different levels of activity. At the same time, combined with the service feedback of objects with a frequency greater than zero, the dimensions of customer grouping are further enriched, so that the grouping is not only based on the frequency of interaction, but also takes into account the customer's satisfaction and experience with the service. This method can more comprehensively reflect the actual needs and potential value of customers. For example, customers who interact frequently and provide positive feedback can be identified as high-value customers and given more attention and resources; while customers who interact frequently but provide negative feedback can be identified as those who need service improvement, and targeted measures can be taken to improve customer satisfaction.

[0183] (3) By defining multiple preset frequency intervals, a clear and quantifiable standard is provided for customer classification. These intervals can be flexibly set according to historical data or business needs, ensuring the scientific and practical nature of the classification. Secondly, by comparing each customer's number of interactions with these intervals one by one, the interval to which the customer belongs can be accurately identified. This one-to-one matching process avoids the ambiguity of classification and improves the accuracy and efficiency of data processing. Finally, after determining the frequency interval to which each customer belongs, the company can carry out more refined customer management and service optimization based on these intervals. For example, for customers with a high number of interactions, more personalized services can be provided; for customers with a low number of interactions, measures can be taken to increase their activity.

[0184] (4) By clearly dividing the frequency intervals and the positive and negative service feedback, a multi-dimensional classification basis is provided for object grouping. First, the objects belonging to the first frequency interval are clustered together with the objects belonging to the second frequency interval with positive service feedback. This process not only takes into account the customer's interaction frequency, but also combines the key factor of customer satisfaction. This combination method can effectively identify customer groups with higher potential value, that is, those customers who are satisfied with the service experience despite moderate interaction frequency, and those customers who have high interaction frequency and good satisfaction. By classifying these customers into the first object group, the company can provide further value-added services or customer loyalty programs in a targeted manner to improve customer satisfaction and promote customer retention. Secondly, the objects belonging to the third frequency interval with positive service feedback are clustered separately into the second object group. This operation focuses on identifying high-value customers who interact most frequently with customer service and are highly satisfied with the service. This group usually has a high degree of dependence and loyalty to the company's products or services. By grouping them separately, the company can provide these customers with more personalized services, such as exclusive customer service channels or customized product recommendations, thereby further enhancing customer stickiness and improving customer experience.

[0185] (5) By classifying customers through preset frequency intervals, it is possible to effectively distinguish the frequency of customer interaction with customer service, thereby preliminarily screening out high-demand customer groups. Furthermore, customers whose service feedback is negative and whose number of interactions exceeds the maximum value of the third frequency interval are identified as target objects. This process not only takes into account the customer's interaction frequency, but also combines the customer's satisfaction with the service, and can accurately identify customers who may be dissatisfied with the service and high-demand customers who frequently seek help. For these target objects, stopping data processing can avoid the decline in customer experience caused by frequent transfers, reduce customer dissatisfaction, and ensure that high-demand customers can receive more consistent and personalized service support.

[0186] (6) By distinguishing the tenure of the fourth and fifth customer service representatives, the customer service team is divided into different experience levels, which provides a basis for subsequent precise allocation. The fourth customer service representative with a longer tenure usually has richer experience, stronger problem-solving skills and deeper business understanding, and is therefore more suitable for handling complex or high-priority customer needs. When the object group is the first object group, by deleting the fifth customer service representative with a shorter tenure from the tree structure, the selection range is directly narrowed, ensuring that the customer service personnel selected subsequently have sufficient experience to meet the needs of the first object group. This process not only improves the screening efficiency, but also reduces the service quality problems caused by insufficient customer service experience. Furthermore, based on the updated target tree structure, the specific third customer service representative is determined from the fourth customer service representative, which can be matched more accurately according to the specific needs of the first object group (such as problem type, urgency, etc.). This hierarchical screening and precise matching method not only optimizes the utilization efficiency of customer service resources, but also improves customer satisfaction, reduces customer waiting time and problem solving time, and thus improves the quality and efficiency of customer service overall.

[0187] (7) By distinguishing the tenure of the fourth and fifth customer service representatives, the customer service team is divided into different experience levels. Since the fourth customer service representative has been on the job longer and has more experience, he is usually more suitable for handling complex or high-priority customer needs; while the fifth customer service representative, although relatively less experienced, may be more familiar with the rapid processing process and is more suitable for handling relatively simple tasks that require a quick response. When the object group is the second object group, by deleting the fourth customer service representative from the tree structure, the selection range is directly limited to the fifth customer service representative. This process not only reduces the complexity of the selection, but also ensures that the assigned customer service representative can quickly respond to the needs of the second object group. Furthermore, based on the updated target tree structure, the third customer service representative is determined from the fifth customer service representative, which can be matched more accurately according to the specific needs of the second object group (such as problem type, urgency, etc.). This hierarchical screening and precise matching method not only optimizes the utilization efficiency of customer service resources, but also reduces customer waiting time and improves the speed of problem resolution, ultimately achieving dual optimization of customer experience and enterprise resource utilization.

[0188] (8) Determine the first target customer service group containing the first customer service from multiple first customer service groups at the first organizational level, and select the third customer service from it. This process utilizes the resources of the grassroots customer service group and ensures the initial service performance. However, if the number of second customer service personnel in the first target customer service group is insufficient to meet the total demand of the target group, the method immediately turns to the first reference customer service group, that is, other first customer service groups different from the first target customer service group, and continues to select the third customer service personnel. This step increases the number of available customer service personnel by horizontally expanding the resource pool, further improving the coverage of the service. If the demand is still not met, the method further selects the third customer service personnel by traversing the customer service groups at a higher organizational level (the i-th organizational level) until the total number demand of the target group is met. This layer-by-layer traversal method fully utilizes the hierarchical nature of the organizational structure, gradually allocating resources from the grassroots to the top, and ensuring that a sufficient number of customer service personnel can be allocated to the target group under any circumstances. It not only improves the flexibility and adaptability of the service, but also avoids excessive concentration or waste of resources by dynamically adjusting resource allocation, thereby maximizing customer demand under limited resource conditions and significantly improving the efficiency and customer satisfaction of the customer service system.

[0189] (9) Determine the i-th target customer service group containing the first customer service from multiple i-th customer service groups at the i-th organizational level. This process ensures the coverage of basic service performance. Subsequently, a customer service identification program is used to select a third customer service from the i-th target customer service group. This method is usually based on factors such as the customer service workload and skill matching, so as to ensure that the selected customer service can efficiently and with high quality meet the needs of the target group. However, if the customer service capabilities of the i-th target customer service group are insufficient to meet all the needs of the target group, the method then turns to the i-th reference customer service group, that is, other i-th customer service groups that are different from the i-th target customer service group, and continues to select a third customer service. This dynamic adjustment mechanism not only expands the resource pool and increases the number of available customer service, but also balances the workload of each customer service group by selecting customer service from different customer service groups, avoiding excessive concentration or waste of resources. This method not only improves the flexibility and adaptability of the service, but also ensures that customer needs are met to the maximum extent under limited resource conditions by optimizing resource allocation, significantly improving the efficiency of the customer service system and customer satisfaction.

[0190] (10) Through a clear allocation mechanism, each object in the object group is accurately assigned to the corresponding third-party customer service. This process ensures the matching degree between the object and the customer service, avoiding low service efficiency and decreased customer satisfaction caused by random allocation. The introduction of the service list provides a clear task management tool for the third-party customer service, allowing the customer service to systematically manage and prioritize the objects assigned to them, thereby optimizing the workflow and improving service efficiency. In addition, the trigger mechanism of the service list ensures the timeliness and continuity of the service, avoiding service delays or omissions caused by the busy work of the customer service staff. In this way, the enterprise can not only ensure that each object can receive a timely response, but also evaluate the customer service performance in real time by monitoring the processing progress of the service list, and further optimize the allocation of customer service resources. This transfer and trigger mechanism based on the service list not only improves the accuracy and efficiency of the service, but also enhances the customer experience, winning the trust and loyalty of customers for the enterprise in the highly competitive market.

[0191] (11) By predicting and comparing the service performance of the first customer service and each second customer service, accurate relationship detection is achieved, providing a scientific basis for the rational allocation of customer service resources. The service performance of the first customer service is predicted and its service performance index is obtained. This process is based on historical data and real-time monitoring, ensuring the accuracy of the prediction results. The service performance prediction is also performed for each second customer service to obtain their respective service performance indicators. By comparing the service performance of the first customer service and each second customer service, the service performance relationship between them can be clarified, that is, whether the service performance of the first customer service is better than, equal to, or lower than that of the second customer service. The data-driven comparison method avoids the uncertainty of subjective judgment and ensures the objectivity and reliability of relationship detection. The obtained relationship information can be used to construct a customer service hierarchy structure, optimize task allocation, improve customer service efficiency and customer satisfaction, and thus significantly improve the operational efficiency of the entire customer service system.

[0192] (12) The service performance of the first customer service and the first reference customer service are compared, and their parent-child relationship or same-level relationship in the tree structure is determined based on the comparison results. When the service performance of the first customer service is greater than that of the reference customer service, a tree structure is constructed with the first customer service as the parent node and the reference customer service as the child node. This hierarchical relationship reflects the advantage of the first customer service in service performance, enabling it to undertake more critical service tasks and manage the reference customer service; when the service performance of the first customer service is less than that of the reference customer service, a tree structure is constructed with the reference customer service as the parent node and the first customer service as the child node. This reflects the performance advantage of the reference customer service, enabling it to guide and assist the first customer service to improve service quality; and when the service performance of the two is equal, they are constructed as nodes of the same level, indicating that they have equal status in service performance and can cooperate with each other to process service requests. This dynamic construction method based on service performance can not only reasonably allocate customer service resources according to actual performance differences, but also ensure that each customer service can play its role in its most suitable position, thereby improving the operating efficiency and service quality of the entire customer service system, providing a scientific basis for subsequent resource allocation and dynamic adjustment, and helping to further optimize the utilization efficiency of customer service resources and improve customer satisfaction.

[0193] (13) The j-th level sub-relationship with the same service performance as the j-th customer service in the j-th level relationship is determined as the target sub-relationship. Based on the precise comparison of service performance, the accuracy and reliability of the relationship are ensured. Subsequently, the parent node of the node corresponding to the target sub-relationship in the j-1-th tree structure is determined as the j-th target node. By utilizing the existing tree structure information, repeated calculations and resource waste are avoided, and the operating efficiency of the system is improved. Finally, the node corresponding to the j-th customer service is constructed as a child node of the j-th target node to form a new j-th tree structure. This dynamic construction method can not only reflect the service performance relationship between customer services in real time, but also flexibly adjust the tree structure according to actual needs to ensure that each customer service can play its role in its most suitable position. It can more reasonably allocate customer service resources, reduce customer waiting time, improve problem solving efficiency, and thus significantly improve customer satisfaction and enterprise operation efficiency.

[0194] The above description is merely an embodiment of the present application and is not intended to limit the scope of protection of the present application. Any modifications, equivalent replacements, and improvements made within the spirit and scope of the present application are included in the scope of protection of the present application.

Claims

1. A data processing method, characterized in that: The method includes: Determine multiple objects served by the first customer service, and determine the number of times the first customer service serves each of the objects; Based on the number of times, group the multiple objects to obtain multiple object groups; Determine the customer service identification program corresponding to each object group, and dynamically construct a tree structure for indicating the relationship between the first customer service and the multiple second customer services based on the first customer service and the multiple second customer services; For each object group, traverse the multiple second customer services in the tree structure using the customer service identification program corresponding to the object group, and identify the third customer service corresponding to the object group from the multiple second customer services; Delete the multiple objects from the service list of the first customer service, and allocate the objects in each object group to the service lists of the corresponding third customer services respectively. The service list is used to trigger services for the objects in the service request.

2. The method according to claim 1, characterized in that The dynamically constructing a tree structure for indicating the relationship between the first customer service and the multiple second customer services based on the first customer service and the multiple second customer services includes: Perform a relationship detection on the first customer service and each second customer service to obtain the relationship between the first customer service and each second customer service respectively. The relationship is used to indicate whether the service performance of the first customer service is greater than that of the second customer service; Based on the relationship, dynamically construct a tree structure for indicating the relationship between the first customer service and the multiple second customer services.

3. The method according to claim 2, characterized in that The performing a relationship detection on the first customer service and each second customer service to obtain the relationship between the first customer service and each second customer service respectively includes: Perform a service performance prediction on the first customer service to obtain the service performance of the first customer service, and perform the following processing for each second customer service respectively: Perform a service performance prediction on the second customer service to obtain the service performance of the second customer service; Compare the service performance of the first customer service and the service performance of the second customer service to obtain the relationship between the first customer service and the second customer service.

4. The method according to claim 2, characterized in that The multiple second customer services include the jth reference customer service, and the relationship includes the jth layer relationship of the jth reference customer service, where 1 < j ≤ M, and M is used to indicate the total number of the second customer services; The dynamically constructing a tree structure for indicating the relationship between the first customer service and the multiple second customer services based on the relationship includes: Based on the first layer relationship between the first customer service and the first reference customer service, construct the first customer service and the first reference customer service into the first tree structure; Traverse j and perform the following processing: Based on the jth layer relationship between the first customer service and the (j - 1)th tree structure, construct the jth customer service and the (j - 1)th tree structure into the jth tree structure; Determine the Mth tree structure as the tree structure for indicating the relationship between the first customer service and the multiple second customer services.

5. The method according to claim 4, characterized in that The constructing the first customer service and the first reference customer service into the first tree structure based on the first layer relationship between the first customer service and the first reference customer service includes: If the first-level relationship indicates that the service performance of the first customer service is greater than the service performance of the first reference customer service, constructing a first tree structure with the first customer service as the parent node and the first reference customer service as the child node; If the first-level relationship indicates that the service performance of the first customer service is lower than the service performance of the first reference customer service, constructing a first tree structure with the first reference customer service as the parent node and the first customer service as the child node; If the first-level relationship indicates that the service performance of the first customer service is equal to the service performance of the first reference customer service, then the first reference customer service and the first customer service are constructed into the first tree structure with the first reference customer service and the first customer service as nodes of the same level.

6. The method according to claim 4, characterized in that The j-th level relationship includes the j-th level sub-relationship corresponding to each node in the j-1-th tree structure and the j-th customer service; The step of constructing the jth customer service and the j-1th tree structure into a jth tree structure based on the jth level relationship between the first customer service and the j-1th tree structure includes: Determine the j-th level sub-relationship in the j-th level relationship that indicates the same service performance as the j-th customer service as the j-th level target sub-relationship, and determine the parent node of the node corresponding to the j-th level target sub-relationship in the j-1-th tree structure as the j-th target node; The node corresponding to the j-th customer service is constructed as a child node of the j-th target node to obtain the j-th tree structure.

7. The method according to claim 1, characterized in that The grouping of the plurality of objects based on the number of times to obtain a plurality of object groups includes: Determine a plurality of preset frequency intervals, and service feedback of the subject to the first customer service representative whose frequency is greater than zero; Determining a target frequency interval to which the frequency of each object belongs from the plurality of preset frequency intervals; The multiple objects are grouped based on the target number interval and the service feedback to obtain multiple object groups.

8. The method according to claim 7, characterized in that Determining the target frequency interval to which the frequency of each object belongs from the plurality of preset frequency intervals includes: The following processing is performed for each of the objects: Compare the number of times the first customer service serves the object with each of the number intervals, respectively, to obtain a second comparison result for each of the number intervals; If the second comparison result of the number intervals indicates that the number of times the first customer service has served the object is within the number interval, the number interval is determined as the target number interval to which the number of times the object has served belongs.

9. The method according to claim 7, characterized in that The target number interval includes a first number interval, a second number interval, and a third number interval; the object group includes a first object group and a second object group; and the grouping of the plurality of objects based on the target number interval and the service feedback to obtain a plurality of object groups includes: Clustering objects belonging to the first frequency interval and objects belonging to the second frequency interval and having positive service feedback to obtain a first object group; Cluster the objects that belong to the third frequency interval and whose service feedback is positive feedback to obtain a second object group.

10. The method according to claim 9, characterized in that After determining the target frequency interval to which each object belongs from the multiple preset frequency intervals, the method further includes: Determine the target objects as the objects with negative service feedback and the objects whose frequency is greater than the maximum value of the third frequency interval. Stop data processing for the target objects.

11. The method according to claim 9, characterized in that The multiple second customer service representatives include multiple fourth customer service representatives and multiple fifth customer service representatives, and the working time of the fourth customer service representatives is greater than that of the fifth customer service representatives. When the object group is the first object group, based on the tree structure, using the corresponding customer service identification program, to determine the fourth customer service representative corresponding to the object group from the multiple second customer service representatives includes: Delete the fifth customer service representatives in the tree structure to obtain the target tree structure of the first object group. Based on the target tree structure of the first object group, determine the third customer service representative corresponding to the first object group from the multiple fourth customer service representatives.

12. The method according to claim 9, characterized in that The multiple second customer service representatives include fourth customer service representatives and fifth customer service representatives, and the working time of the fourth customer service representatives is greater than that of the fifth customer service representatives. When the object group is the second object group, based on the tree structure, using the corresponding customer service identification program, to determine the fourth customer service representative corresponding to the object group from the multiple second customer service representatives includes: Delete the fourth customer service representatives in the tree structure to obtain the target tree structure of the second object group. Based on the target tree structure of the second object group, determine the third customer service representative corresponding to the second object group from the multiple fifth customer service representatives.

13. The method according to claim 1, wherein The tree structure includes N organizational levels, each organizational level includes multiple customer service groups, the i-th customer service group in the i-th organizational level includes at least one (i - 1)-th customer service group in the (i - 1)-th organizational level, 1 < i ≤ N, and each first customer service group in the first organizational level includes at least one customer service representative. Using the customer service identification program corresponding to the object group to traverse the multiple second customer service representatives in the tree structure and identify the third customer service representative corresponding to the object group from the multiple second customer service representatives includes: Determine the first target customer service group where the first customer service representative is located from the multiple first customer service groups in the first organizational level, and use the customer service identification program of the object group to select the third customer service representative from the second customer service representatives in the first target customer service group. Based on the number of objects that the second customer service representatives in the first target customer service group can serve and the total number of objects in the object group, use the customer service identification program corresponding to the object group to select the third customer service representative from the first reference customer service group and / or the multiple i-th customer service groups in the i-th organizational level.

14. The method according to claim 13, wherein: The step of using the customer service identification program corresponding to the object group, based on the number of objects that the second customer service representatives in the first target customer service group can serve and the total number of objects in the object group, to select the third customer service representative from the first reference customer service group and / or the multiple i-th customer service groups in the i-th organizational level includes: If the number of objects that the second customer service representative in the first target customer service group can serve is less than the total number of objects in the object group, then using a corresponding customer service identification procedure to select the third customer service representative from a first reference customer service group, where the first reference customer service group is a first customer service group among the multiple first customer service groups that is different from the first target customer service group; If the number of objects that the second customer service representative in the first reference customer service group can serve is less than the difference between the total number and the number of selected third customer service representatives, then traverse i and perform the following process until the number of selected third customer service representatives equals the total number: The third customer service representative is selected from the i-th customer service groups of the i-th organizational level using a corresponding customer service identification program.

15. The method according to claim 14, characterized in that The selecting the third customer service representative from the plurality of i-th customer service representatives in the i-th organizational level includes: Determine, from the plurality of i-th customer service groups at the i-th organizational level, an i-th target customer service group where the first customer service representative is located; The third customer service representative is selected from an i-th reference customer service group using a corresponding customer service identification program, where the i-th reference customer service group is an i-th customer service group among the multiple i-th customer service groups that is different from the i-th target customer service group.

16. A data processing device, characterized in that: The device comprises: A first determining module is configured to determine a plurality of objects served by the first customer service, and determine the number of times the first customer service serves each of the objects; a grouping module, configured to group the plurality of objects based on the number of times to obtain a plurality of object groups; a second determination module configured to determine a customer service identification program corresponding to each of the object groups, and dynamically construct a tree structure indicating a relationship between the first customer service and the plurality of second customer services based on the first customer service and the plurality of second customer services; and for each of the object groups, using the customer service identification program corresponding to the object group, traverse the plurality of second customer services in the tree structure to identify a third customer service corresponding to the object group from the plurality of second customer services; A transfer module is used to delete the multiple objects from the service list of the first customer service, and to assign the objects in each object group to the corresponding service list of the third customer service, wherein the service list is used to trigger service for the objects in the service request.

17. An electronic device, characterized in that: The electronic device comprises: a memory for storing computer-executable instructions or computer programs; The processor is configured to implement the data processing method according to any one of claims 1 to 15 when executing the computer-executable instructions or computer programs stored in the memory.

18. A computer-readable storage medium storing computer-executable instructions or a computer program, characterized in that: When the computer executable instructions or computer program are executed by a processor, the data processing method according to any one of claims 1 to 15 is implemented.

19. A computer program product comprising a computer program or computer executable instructions, characterized in that When the computer program or computer executable instructions are executed by a processor, the data processing method according to any one of claims 1 to 15 is implemented.

Images