Intelligent scheduling method of intelligent customer service system for cigarette marketing

Abstract

The invention relates to the field of network resource scheduling, in particular to an intelligent scheduling method of an intelligent customer service system for cigarette marketing. The invention provides an intelligent scheduling method of an intelligent customer service system for cigarette marketing. The intelligent scheduling method comprises the following steps: acquiring attribute characteristics of a service request; obtaining state characteristics of all current customer service modules; on the basis of the attribute characteristics of the service request, obtaining the fitness with the service request according to the state characteristics of each customer service module; and based on the execution quotation of each customer service module for the service request, distributing the service request to the customer service module with the lowest execution quotation. According to the invention, customer service resources are dynamically allocated through an intelligent scheduling method, and efficient resource allocation and load balancing are realized by using fitness matching and a bidding mechanism; under a multi-task concurrent scene, optimal allocation is guaranteed through an optimization algorithm, the response speed and the service quality are improved, resource waste is avoided, and the processing capacity of the system in peak hours is improved.

Description

Technical Field

[0001] The invention relates to the field of network resource scheduling, and in particular to an intelligent scheduling method for an intelligent customer service system of cigarette marketing. Background Art

[0002] With the rapid development of the Internet and digital technology, the ways in which consumers obtain information and purchase cigarette products are becoming increasingly diverse, and the importance of online channels is increasing. In the field of cigarette marketing, customers expect to receive timely and professional consultation and services through a variety of digital channels (such as official websites, mobile applications, social media, etc.). This trend requires companies to establish an efficient intelligent customer service system to meet the growing demand for customer service.

[0003] However, the existing intelligent customer service system has obvious deficiencies in resource scheduling and is unable to dynamically adjust the allocation of customer service resources according to the real-time situation and complexity of customer inquiries. During peak periods such as promotional activities and new product launches, the number of customer inquiries increases sharply. The traditional static scheduling method causes customer service personnel to be unable to respond to all customer requests in a timely manner, resulting in customers waiting too long and problems not being solved in a timely manner. This not only affects service efficiency, but also reduces customer satisfaction. During off-peak business periods, customer service resources may be idle, resulting in resource waste and increased operating costs. Therefore, there is an urgent need for a method that can dispatch customer service resources in real time, dynamically, and intelligently to improve the response speed and resource utilization efficiency of the intelligent customer service system. Summary of the invention

[0004] In view of the deficiencies of the prior art and actual application needs, the present invention provides an intelligent scheduling method for an intelligent customer service system for cigarette marketing, aiming to solve the problem of uneven distribution of customer service resources in the prior art.

[0005] In the intelligent scheduling method of the intelligent customer service system for cigarette marketing provided by the present invention, the intelligent customer service system includes a plurality of user ports, a plurality of customer service modules and an intelligent scheduling module, each of the user ports is signal-connected to the intelligent scheduling module for receiving a customer's service request, each of the customer service modules is signal-connected to the intelligent scheduling module for processing at least one service request, and the intelligent scheduling module is used to allocate the service request received by the user port to the corresponding customer service module according to the intelligent scheduling method; when a customer initiates a service request through one of the user ports, the intelligent scheduling method of the intelligent customer service system for cigarette marketing provided by the present invention includes the following steps:

[0006] Obtaining attribute characteristics of the service request;

[0007] Get the status characteristics of all current customer service modules;

[0008] Based on the attribute characteristics of the service request, respectively obtaining the fitness for the service request according to the state characteristics of each customer service module;

[0009] Based on the execution quotation of each customer service module for the service request, the service request is allocated to the customer service module with the lowest execution quotation.

[0010] Furthermore, the characteristic attributes of any service request include urgency, complexity and priority; the status characteristics of any customer service module include skill level, service quality and response efficiency.

[0011] Furthermore, the fitness of any service request and any customer service module is generated through a fitness calculation model.

[0012] Furthermore, any customer service module calculates the execution quotation of any service request through a bidding calculation model.

[0013] Furthermore, the method of allocating the service request to the customer service module with the lowest execution quotation based on the execution quotation of the service request by each customer service module also includes the following steps:

[0014] If there are multiple customer service modules that present the lowest execution quote, the service request will be assigned to the customer service module with the highest fitness.

[0015] Furthermore, the method of allocating the service request to the customer service module with the lowest execution quotation based on the execution quotation of the service request by each customer service module also includes the following steps:

[0016] If there are multiple customer service modules with the highest fitness among multiple customer service modules that present the lowest execution quotes, the service request is randomly assigned to any customer service module with the highest fitness.

[0017] Furthermore, when multiple clients simultaneously initiate service requests through multiple user ports, the following steps are included:

[0018] Acquire attribute feature vectors of a plurality of the service requests, wherein any element in the attribute feature vector is an attribute feature of a service request;

[0019] Obtain the status feature vectors of all current customer service modules, where any element in the litigation status feature vector is the current status feature of a customer service module;

[0020] Based on the attribute feature vector and the state feature vector, a fitness matrix is ​​generated, wherein the fitness matrix includes a plurality of fitness vectors, and any fitness vector includes the fitness of a customer service module and a plurality of service requests;

[0021] Feeding back the fitness vectors of each customer service module and multiple service requests to the corresponding customer service module respectively, and obtaining the execution quotation vectors of each customer service module for the multiple service requests respectively, wherein any element in the execution quotation vector is generated by the customer service module according to its fitness with a service request;

[0022] The execution quotation vectors of each customer service module are aggregated to generate an execution quotation matrix, and based on the execution quotation matrix, a customer service module for executing each service request is selected so that the total execution quotation is minimized.

[0023] Further, the selecting of a customer service module for executing each service request based on the execution quotation matrix so as to minimize the total execution quotation comprises the following steps:

[0024] Construct the minimum objective function of total execution price;

[0025] Solve the minimum objective function of the total execution quotation and obtain the customer service module that executes each service request.

[0026] The intelligent scheduling method of the intelligent customer service system for cigarette marketing provided by the present invention has the following benefits:

[0027] The present invention adjusts the allocation of customer service modules in real time according to the urgency and complexity of service requests, thus avoiding the lag of traditional static scheduling, ensuring rapid response to customer requests during peak hours, improving the flexibility of the system, and optimizing resource utilization efficiency.

[0028] The present invention uses a fitness calculation model to accurately match service requests with the skills, response speed and other status characteristics of the customer service module based on attributes such as complexity and urgency, thereby improving service efficiency, ensuring that complex requests are handled by high-skilled customer service modules, and reducing the probability of simple problems occupying high-skilled customer service modules;

[0029] The present invention is based on a bidding mechanism, comprehensively considers fitness and the current workload of the customer service module to calculate the execution quotation, and then selects the customer service module with the smallest execution quotation to execute the service request, thereby ensuring efficient use of customer service resources and achieving load balancing.

[0030] When multiple customers initiate requests at the same time, the present invention uses the objective function to obtain an allocation plan that minimizes the total execution quotation, so as to ensure the reasonable allocation of customer service resources in high-concurrency scenarios, improve the overall processing efficiency, reduce response delays, optimize resource utilization, and avoid resource waste. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 A schematic diagram of the structure of an intelligent customer service system for cigarette marketing provided by an embodiment of the present invention;

[0032] Figure 2A first flow chart of an intelligent scheduling method for an intelligent customer service system for cigarette marketing provided by an embodiment of the present invention;

[0033] Figure 3 This is a second flow chart of the intelligent scheduling method of the intelligent customer service system for cigarette marketing provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0034] The specific embodiments of the present invention will be described in detail below. It should be noted that the embodiments described here are only for illustration and are not intended to limit the present invention. In the following description, a large number of specific details are set forth in order to provide a thorough understanding of the present invention.

[0035] However, it will be apparent to one of ordinary skill in the art that these specific details need not be employed to practice the present invention. In other instances, well-known circuits, software, or methods are not described in detail to avoid obscuring the present invention.

[0036] In one embodiment, see Figure 1 and Figure 2 , Figure 1 This is a schematic diagram of the structure of the intelligent customer service system for cigarette marketing provided by an embodiment of the present invention. Figure 2 This is a first flow chart of the intelligent scheduling method of the intelligent customer service system for cigarette marketing provided by an embodiment of the present invention.

[0037] like Figure 1 As shown, the intelligent customer service system for cigarette marketing provided by the present invention includes several user ports, several customer service modules and an intelligent scheduling module.

[0038] Furthermore, each of the user ports is connected to the intelligent scheduling module for receiving customer service requests; each of the customer service modules is connected to the intelligent scheduling module for processing at least one service request; the intelligent scheduling module is used to Figure 2 The intelligent scheduling method shown distributes the service requests received by the user port to the corresponding customer service module.

[0039] like Figure 2 As shown, when a customer initiates a service request through a user port, the intelligent scheduling method of the intelligent customer service system for cigarette marketing provided by the embodiment of the present invention includes the following steps:

[0040] S01. Obtain attribute characteristics of the service request.

[0041] Furthermore, the attribute characteristics proposed in the present invention are used to describe the processing requirements of the service request.

[0042] In this embodiment, the attribute characteristics of the service request include urgency, complexity and priority; in one or some other embodiments, the attribute characteristics of the service request also include other requirements such as response time limit.

[0043] Specifically, the urgency is used to measure the key attribute of the time requirement of the service request; the complexity is used to measure the technical difficulty or knowledge depth of the service request processing; and the priority level is used to measure the processing priority of the service request relative to other service requests.

[0044] S02. Obtain status characteristics of all current customer service modules.

[0045] Furthermore, the state characteristics proposed in the present invention are used to describe the current state of the customer service module.

[0046] In this embodiment, the status characteristics of any customer service module include skill level, service quality and response efficiency. In one or more other embodiments, the status characteristics of any customer service module also include other status performances.

[0047] Specifically, the skill level is used to measure the customer service module's ability to handle service requests; the service quality is used to measure the customer service module's historical service performance; and the response efficiency is used to measure the customer service module's average response speed to service requests.

[0048] S03. Based on the attribute characteristics of the service request, the adaptability to the service request is obtained according to the state characteristics of each customer service module.

[0049] Furthermore, the fitness proposed in the present invention is used to measure the matching degree between the customer service module and the service request. It can be understood that the higher the fitness, the more suitable the customer service module is for processing the service request.

[0050] In this embodiment, the urgency, complexity and priority of any service request are quantified as any numerical value of the corresponding part in the following Table 1:

[0051]

[0052]

[0053] Furthermore, the skill level, service quality, and response efficiency of any customer service module are quantified as any value of the corresponding part in the following Table 2:

[0054]

[0055] In one or some other embodiments, various attribute characteristics of the service request and various status characteristics of the customer service module may also be quantified through other rules.

[0056] Furthermore, the fitness of any service request and any customer service module is generated by the following fitness calculation model: Among them, M ij represents the fitness of service request i and customer service module j, C i represents the complexity of service request i, P i represents the priority level of service request i, U i Indicates the urgency of service request i, L j represents the skill level of customer service module j, L min Indicates the minimum quantitative value of skill level, L max Indicates the minimum quantitative value of skill level, E j represents the service quality of customer service module j, E min Indicates the minimum quantitative value of service quality, E max Represents the minimum quantitative value of service quality, R j represents the response efficiency of customer service module j, R min Represents the minimum quantitative value of response efficiency, R max Represents the minimum quantitative value of response efficiency, ω C，L +ω P，E +ω U，R =1,ω C，L >0,ω C，L Represents the fitness weight of the complexity of the service request and the skill level of the customer service module, ω P，E >0,ω P，E Represents the fitness weight of the service request priority and the service quality of the customer service module, ω U，R >0,ω U，R The fitness weight that represents the urgency of the service request and the response efficiency of the customer service module.

[0057] S04. Feedback the fitness of each customer service module with the service request to the corresponding customer service module respectively, and obtain the execution quotation of each customer service module for the service request respectively, any of the execution quotations is generated by the corresponding customer service module according to its fitness with the service request.

[0058] Furthermore, the execution quotation provided by the present invention is used to measure the resource cost of the customer service module in processing the service request. It is understandable that the lower the execution quotation, the lower the resource cost required for the customer service module to process the service request.

[0059] In this embodiment, any execution quotation is generated based on the adaptability of the customer service module and the service request, as well as the workload of the customer service module itself; further, any customer service module calculates the execution quotation of any service request through the following bidding calculation model: Among them, Q ij represents the execution quotation of customer service module j for service request i, M ij represents the fitness of service request i and customer service module j, (O max ) j represents the maximum workload that customer service module j can bear, O j Represents the current workload of customer service module j.

[0060] S05. Based on the execution quotation of each customer service module for the service request, the service request is allocated to the customer service module with the lowest execution quotation.

[0061] Furthermore, if there are multiple customer service modules that present the lowest execution quotation, the service request is allocated to the customer service module with the highest fitness.

[0062] Furthermore, if there are multiple customer service modules that present the lowest execution quote, and multiple customer service modules among these customer service modules have the highest fitness, the service request is randomly assigned to any customer service module with the highest fitness.

[0063] For further information, see Figure 3 , Figure 3 This is a second flow chart of the intelligent scheduling method of the intelligent customer service system for cigarette marketing provided by an embodiment of the present invention. Figure 3 As shown, when multiple customers initiate service requests simultaneously through multiple user ports, based on steps S01 to S05, the intelligent scheduling method of the intelligent customer service system for cigarette marketing provided by the embodiment of the present invention includes the following steps:

[0064] S011. Acquire attribute feature vectors of a plurality of the service requests, wherein any element in the attribute feature vector is an attribute feature of a service request.

[0065] In this embodiment, the attribute feature vector satisfies the following expression model: ((C1, P1, U1), (C2, P2, U2), ...., (C m , P m , U m ), where C1 represents the complexity of service request 1, P1 represents the priority of service request 1, U2 represents the urgency of service request 1, C1 represents the complexity of service request 2, P2 represents the priority of service request 2, U2 represents the urgency of service request 2, C mrepresents the complexity of the service request m, P m represents the priority level of service request m, U m Indicates the urgency of service request m.

[0066] S021. Obtain the status feature vectors of all current customer service modules, where any element in the litigation status feature vector is the current status feature of a customer service module.

[0067] In this embodiment, the state feature vector satisfies the following expression model: ((L1, E1, R1), (L2, E2, R2), ...., (L n , E n , R n ), where L1 represents the skill level of customer service module 1, E1 represents the service quality of customer service module 1, R1 represents the response efficiency of customer service module 1, L2 represents the skill level of customer service module 2, E2 represents the service quality of customer service module 2, R2 represents the response efficiency of customer service module 2, L n Indicates the skill level of customer service module n, E n represents the service quality of customer service module n, R n Represents the response efficiency of customer service module n.

[0068] S031. Generate a fitness matrix based on the attribute feature vector and the state feature vector. The fitness matrix includes multiple fitness vectors. Any fitness vector includes the fitness of a customer service module and multiple service requests.

[0069] Furthermore, the fitness of any service request and any customer service module in step S031 can be obtained through the fitness calculation model provided in step S03.

[0070] In this embodiment, the fitness matrix satisfies the following expression model: Among them, M 11 represents the fitness of service request 1 and customer service module 1, M 1n represents the fitness of service request 1 and customer service module n, M m1 represents the fitness of service request m and customer service module 1, M mn Represents the fitness of service request m and customer service module n.

[0071] It can be understood that the fitness vector corresponding to the customer service module j is: (M 1j , M 2j , ..., M mj ) T , where M 1j represents the fitness of service request 1 and customer service module j, M 2j represents the fitness of service request 2 and customer service module j, Mmj Represents the fitness of service request m and customer service module j.

[0072] S041. Feedback the fitness vectors of each customer service module and multiple service requests to the corresponding customer service modules respectively, and obtain the execution quotation vectors of each customer service module for multiple service requests respectively, wherein any element in the execution quotation vector is generated by the customer service module according to its fitness with a service request.

[0073] Furthermore, the execution quotation of any customer service module for any service request in step S041 can be obtained through the bidding calculation model provided in step S04.

[0074] S051. Summarize the execution quotation vectors of each customer service module to generate an execution quotation matrix, and select a customer service module to execute each service request based on the execution quotation matrix so that the total execution quotation is minimized.

[0075] Further, in order to optimize the customer service resource allocation under multiple service requests, the step S051 described in selecting the customer service module for executing each service request based on the execution quotation matrix so as to minimize the total execution quotation includes the following steps:

[0076] S0511. Construct the minimum objective function of total execution quotation.

[0077] In this embodiment, the total execution price minimum objective function satisfies the following model:

[0078]

[0079] Furthermore, in order to further improve the execution efficiency of a single service request, the total execution quotation minimum objective function also includes the following constraints:

[0080] in, Represents a traversal operation, that is It means that for every j from 1 to n, It is understandable that the constraint condition indicates that any customer service module can only be assigned to at most one service request in any round of allocation.

[0081] S0512. Solve the minimum objective function of the total execution quotation and obtain the customer service module that executes each service request.

[0082] Furthermore, the solution to the minimum objective function of the total execution quotation can be achieved using existing technologies, such as genetic algorithms, which will not be described in detail here.

[0083] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the above embodiments, or replace some or all of the technical features therein with equivalents.

Claims

1. An intelligent scheduling method for an intelligent customer service system for cigarette marketing, the intelligent customer service system comprising a plurality of user ports, a plurality of customer service modules and an intelligent scheduling module, each of the user ports being signal-connected to the intelligent scheduling module for receiving a customer's service request, each of the customer service modules being signal-connected to the intelligent scheduling module for processing at least one service request, the intelligent scheduling module being used to distribute the service request received by the user port to the corresponding customer service module according to the intelligent scheduling method, characterized in that: When a client initiates a service request through a user port, the following steps are included: Obtaining attribute characteristics of the service request; Get the status characteristics of all current customer service modules; Based on the attribute characteristics of the service request, respectively obtaining the fitness for the service request according to the state characteristics of each customer service module; Based on the execution quotation of each customer service module for the service request, the service request is allocated to the customer service module with the lowest execution quotation.

2. The intelligent scheduling method of the intelligent customer service system for cigarette marketing according to claim 1 is characterized in that: The characteristic attributes of any service request include urgency, complexity and priority; the status characteristics of any customer service module include skill level, service quality and response efficiency.

3. The intelligent scheduling method of the intelligent customer service system for cigarette marketing according to claim 2 is characterized in that: The fitness of any service request and any customer service module is generated through the fitness calculation model.

4. The intelligent dispatching method of the intelligent customer service system for cigarette marketing according to claim 1, characterized in that: Any customer service module calculates the execution quotation of any service request through the bidding calculation model.

5. The intelligent scheduling method of the intelligent customer service system for cigarette marketing according to claim 1, wherein the service request is allocated to the customer service module with the lowest execution quotation based on the execution quotation of each customer service module for the service request, and further comprises the following steps: If there are multiple customer service modules that present the lowest execution quote, the service request will be assigned to the customer service module with the highest fitness.

6. The intelligent dispatching method of the intelligent customer service system for cigarette marketing according to claim 5, characterized in that: The method of allocating the service request to the customer service module with the lowest execution quotation based on the execution quotation of the service request by each customer service module also includes the following steps: If there are multiple customer service modules with the highest fitness among multiple customer service modules that present the lowest execution quotes, the service request is randomly assigned to any customer service module with the highest fitness.

7. The intelligent dispatching method of the intelligent customer service system for cigarette marketing according to any one of claims 1 to 6, characterized in that: When multiple clients simultaneously initiate service requests through multiple user ports, the process includes the following steps: Acquire attribute feature vectors of a plurality of the service requests, wherein any element in the attribute feature vector is an attribute feature of a service request; Obtain the status feature vectors of all current customer service modules, where any element in the litigation status feature vector is the current status feature of a customer service module; Based on the attribute feature vector and the state feature vector, a fitness matrix is ​​generated, wherein the fitness matrix includes a plurality of fitness vectors, and any fitness vector includes the fitness of a customer service module and a plurality of service requests; Feeding back the fitness vectors of each customer service module and multiple service requests to the corresponding customer service module respectively, and obtaining the execution quotation vectors of each customer service module for the multiple service requests respectively, wherein any element in the execution quotation vector is generated by the customer service module according to its fitness with a service request; The execution quotation vectors of each customer service module are aggregated to generate an execution quotation matrix, and based on the execution quotation matrix, a customer service module for executing each service request is selected to minimize the total execution quotation.

8. The intelligent dispatching method of the intelligent customer service system for cigarette marketing according to claim 7, characterized in that: The step of selecting a customer service module to execute each service request based on the execution quotation matrix so as to minimize the total execution quotation comprises the following steps: Construct the minimum objective function of total execution price; Solve the minimum objective function of the total execution quotation and obtain the customer service module that executes each service request.

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