Resource allocation method and system applied to customer management data

Abstract

The invention discloses a resource allocation method and system applied to customer management data, and relates to the technical field of customer management, and the method comprises the steps: obtaining the supply efficiency of each resource of all current resource supply sites, and forming a resource supply matrix A; historical demand data of each customer is called; predicting a resource demand prediction value of the customer based on historical demand data of the customer, and constructing a resource demand prediction matrix B of the customer; generating a resource allocation condition based on the resource supply matrix A, generating a plurality of resource allocation schemes based on the resource allocation condition and the resource demand prediction matrix B, and determining resource allocation C under each resource allocation scheme; and each resource supply distribution plan of the resource supply site is carried out through a balanced distribution algorithm. The method has the advantages that the customer data management capability and the resource utilization efficiency of an enterprise are remarkably improved, the resource configuration of the enterprise is greatly optimized, and the operation efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of customer management, and in particular to a resource allocation method and system applied to customer management data. Background Art

[0002] Customer relationship management has become a key tool for companies to maintain their competitive advantage and provide excellent customer service. With the rapid development of big data technology, the amount of customer data accumulated by companies has exploded. How to efficiently manage, analyze and utilize this data and achieve accurate resource allocation has become an urgent problem for companies to solve.

[0003] Traditional customer management models often have problems such as information dispersion, data silos, and uneven resource allocation, which makes it difficult for companies to quickly respond to changes in customer needs and improve customer satisfaction and loyalty. Therefore, designing a scientific and efficient customer management data resource allocation method and system is of great significance for optimizing enterprise resource allocation and improving operational efficiency. Summary of the invention

[0004] In order to solve the above technical problems, a resource allocation method and system for customer management data are provided. This technical solution solves the problems of information dispersion, data silos, and uneven resource allocation in the above-mentioned traditional customer management model, which makes it difficult for enterprises to quickly respond to changes in customer needs and difficult to improve customer satisfaction and loyalty.

[0005] In order to achieve the above purpose, the technical solution adopted by the present invention is: A resource allocation method applied to customer management data, comprising: Obtain the supply efficiency of each resource of all current resource supply sites to form a resource supply matrix A. , where X ij is the supply efficiency of the jth resource of the i-th resource supply site, n is the total number of resource types, and m is the total number of resource supply sites; Retrieve each customer's historical demand data from the customer management database; Based on the customer's historical demand data, predict the customer's resource demand forecast value and build the customer's resource demand forecast matrix B. , where y kj is the resource demand forecast value of the i-th customer for the j-th resource, l is the total number of customers; Based on the resource supply matrix A, generate resource allocation conditions, and generate several resource allocation schemes based on the resource allocation conditions and the resource demand prediction matrix B, and determine the resource allocation C under each resource allocation scheme. , where Z ijis the resource supply demand value of the i-th resource supply station for the j-th resource under the resource allocation scheme; Based on the resource supply matrix A and the resource allocation C under the resource allocation plan, the resource supply allocation planning of each resource supply site is carried out through the balanced allocation algorithm.

[0006] Preferably, the predicting of the resource demand forecast value of the customer based on the customer's historical demand data specifically includes: According to the different types of resource requirements, the customer's historical demand data is classified to obtain the customer's historical demand sample data under each resource type; All historical demand sample data of customers are numbered in order from the earliest to the latest time; Based on the principle of linear fitting, a demand fitting prediction formula is constructed; Substitute all historical demand sample data and numbers into the demand fitting forecast formula to obtain the customer's resource demand forecast value; The demand fitting prediction formula is specifically: ; Where P is the fitting value of green virtual resources of green account, p o The historical demand sample data is numbered o, and a is the total number of historical demand sample data.

[0007] Preferably, generating resource allocation conditions based on the resource supply matrix A specifically includes: Based on the single resource supply efficiency of the resource supply site, a single resource allocation condition is constructed, and all the single resource supply efficiencies of the resource supply site satisfy the single resource allocation condition as the single site restriction condition; All resource supply sites satisfy the single-site constraint as the resource site side condition; Each customer has a corresponding resource supply site as a customer-side condition; Satisfying both the resource site side conditions and the client side conditions will be used as resource allocation conditions; The expression of the single resource allocation condition is: ; In the formula, y qj is the resource demand forecast value for the jth resource of the qth customer assigned to the i-th resource supply site, Ui is the total number of customers assigned to the i-th resource supply site.

[0008] Preferably, the balanced allocation algorithm is specifically: Based on the resource supply matrix A and the resource allocation C under the resource allocation plan, calculate and determine the reasonable allocation index of each resource allocation plan; Filter out the minimum value of the reasonable allocation index and the corresponding resource allocation plan, and use the resource allocation plan as the optimal resource allocation plan; According to the optimal resource allocation plan, the various resources supplied by the resource supply site are allocated to the corresponding customers.

[0009] Preferably, the calculation and determination of the allocation rationality index of each resource allocation scheme based on the resource supply matrix A and the resource allocation C under the resource allocation scheme specifically includes: Based on the resource supply demand value of each resource supply site in the resource allocation C under the resource allocation scheme and the resource supply efficiency of each resource supply site in the resource supply matrix A, the load index of each resource supply site is determined by a load calculation formula; Based on the load index of each resource supply site under the resource allocation plan, the reasonable allocation index of the resource allocation plan is calculated through the balance identification formula; The load calculation formula is specifically: ; F i is the load index of the i-th resource supply site; The equilibrium determination formula is specifically: ; Where H is the reasonable allocation index of the resource allocation scheme.

[0010] Furthermore, a resource allocation system applied to customer management data is proposed, which is used to implement the resource allocation method applied to customer management data as described above, including: A storage module, wherein the storage module is used to store a customer management database; A resource analysis module, which is used to obtain the supply efficiency of various resources of all current resource supply sites and form a resource supply matrix; A demand data analysis module, the demand data analysis module is electrically connected to the storage module, and the demand data analysis module is used to retrieve the historical demand data of each customer from the customer management database, and based on the historical demand data of the customer, predict the resource demand forecast value of the customer, and construct the resource demand forecast matrix of the customer; A resource allocation module, the resource allocation module is electrically connected to the resource analysis module and the demand data analysis module, the resource allocation module is used to generate resource allocation conditions based on the resource supply matrix, and generate several resource allocation schemes based on the resource allocation conditions and the resource demand prediction matrix, and determine the resource allocation under each resource allocation scheme, and based on the resource supply matrix and the resource allocation under the resource allocation scheme, perform various resource supply allocation plans for the resource supply site through a balanced allocation algorithm.

[0011] Optionally, the demand data analysis module includes: A data retrieval unit, the data retrieval unit is used to retrieve the historical demand data of each customer from the customer management database; The prediction unit is used to predict the resource demand prediction value of the customer based on the customer's historical demand data, and to construct the customer's resource demand prediction matrix.

[0012] Optionally, the resource allocation module includes: A scheme generating unit, the scheme generating unit is used to generate resource allocation conditions based on the resource supply matrix, and generate a plurality of resource allocation schemes based on the resource allocation conditions and the resource demand prediction matrix; A scheme evaluation unit, the scheme evaluation unit is used to calculate and determine the allocation rationality index of each resource allocation scheme based on the resource supply matrix and the resource allocation under the resource allocation scheme; A scheme screening unit is used to screen out the minimum value of the reasonable allocation index and the corresponding resource allocation scheme, and use the resource allocation scheme as the optimal resource allocation scheme, and according to the optimal resource allocation scheme, allocate various resource supplies of the resource supply site to the corresponding customers.

[0013] Compared with the prior art, the present invention has the following beneficial effects: The present invention proposes a resource allocation solution for customer management data. By applying big data analysis and artificial intelligence technology to the historical demand data of customers in the customer management database, the customer data is deeply mined and analyzed to obtain the customer's predicted demand data, thereby helping enterprises to quickly understand customer dynamics. Based on the customer's predicted demand data and the company's own resource supply status, the resource allocation solution of the enterprise is dynamically adjusted, which significantly improves the company's customer data management capabilities and resource utilization efficiency, greatly optimizes the company's resource allocation, and improves operational efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 A flow chart of the resource allocation method proposed for this solution applied to customer management data; Figure 2A flow chart of the method for predicting the resource demand forecast value of a customer in this solution; Figure 3 A flow chart of the method for generating resource allocation conditions in this solution; Figure 4 This is a method flow chart of the balanced allocation algorithm in this solution; Figure 5 A flow chart of the method for determining the allocation rationality index of each resource allocation scheme for calculation in this scheme; Figure 6 This is a schematic diagram of the electronic device in this solution; Figure 7 This is a schematic diagram of the computer-readable storage medium structure in this solution. DETAILED DESCRIPTION

[0015] The following description is used to disclose the present invention so that those skilled in the art can implement the present invention. The preferred embodiments described below are only examples, and those skilled in the art may think of other obvious variations.

[0016] Reference Figure 1 As shown, a resource allocation method applied to customer management data includes: Obtain the supply efficiency of each resource of all current resource supply sites to form a resource supply matrix A. , where X ij is the supply efficiency of the jth resource of the i-th resource supply site, n is the total number of resource types, and m is the total number of resource supply sites; Retrieve each customer's historical demand data from the customer management database; Based on the customer's historical demand data, predict the customer's resource demand forecast value and build the customer's resource demand forecast matrix B. , where y kj is the resource demand forecast value of the i-th customer for the j-th resource, l is the total number of customers; Based on the resource supply matrix A, generate resource allocation conditions, and generate several resource allocation schemes based on the resource allocation conditions and the resource demand prediction matrix B, and determine the resource allocation C under each resource allocation scheme. , where Z ij is the resource supply demand value of the i-th resource supply station for the j-th resource under the resource allocation scheme; Based on the resource supply matrix A and the resource allocation C under the resource allocation plan, the resource supply allocation planning of each resource supply site is carried out through the balanced allocation algorithm.

[0017] This solution uses big data analysis and artificial intelligence technology to deeply mine and analyze customer data in the customer management database to obtain customer forecasted demand data, helping companies to quickly understand customer dynamics. Based on the customer forecasted demand data and the company's own resource supply status, the solution dynamically adjusts the company's resource allocation plan, significantly improving the company's customer data management capabilities and resource utilization efficiency.

[0018] Reference Figure 2 As shown in the figure, based on the customer's historical demand data, the predicted resource demand value of the customer specifically includes: According to the different types of resource requirements, the customer's historical demand data is classified to obtain the customer's historical demand sample data under each resource type; All historical demand sample data of customers are numbered in order from the earliest to the latest time; Based on the principle of linear fitting, a demand fitting prediction formula is constructed; Substitute all historical demand sample data and numbers into the demand fitting forecast formula to obtain the customer's resource demand forecast value; The demand fitting prediction formula is as follows: ; Where P is the fitting value of green virtual resources of green account, p o The historical demand sample data is numbered o, and a is the total number of historical demand sample data.

[0019] In this solution, we applied the theoretical basis of linear regression and constructed a demand fitting prediction formula to analyze and predict the future needs of customers. Specifically, we used all the historical demand samples of customers in the historical data to conduct in-depth data analysis to derive the demand trends of customers in the future. This method can help companies quickly grasp the dynamic changes of customers and provide strong pre-guidance for the company's resource allocation. By pre-adapting customer needs in this way, companies can more effectively meet customer expectations, thereby significantly improving customer satisfaction and loyalty.

[0020] Reference Figure 3 As shown, based on the resource supply matrix A, the resource allocation conditions are generated specifically including: Based on the single resource supply efficiency of the resource supply site, a single resource allocation condition is constructed, and all the single resource supply efficiencies of the resource supply site satisfy the single resource allocation condition as the single site restriction condition; All resource supply sites satisfy the single-site constraint as the resource site side condition; Each customer has a corresponding resource supply site as a customer-side condition; Satisfying both the resource site side conditions and the client side conditions will be used as resource allocation conditions; The expression of the single resource allocation condition is: ; In the formula, y qj is the resource demand forecast value for the jth resource of the qth customer assigned to the i-th resource supply site, Ui is the total number of customers assigned to the i-th resource supply site.

[0021] Reference Figure 4 As shown in the figure, the balanced allocation algorithm is specifically as follows: Based on the resource supply matrix A and the resource allocation C under the resource allocation plan, calculate and determine the reasonable allocation index of each resource allocation plan; Filter out the minimum value of the reasonable allocation index and the corresponding resource allocation plan, and use the resource allocation plan as the optimal resource allocation plan; According to the optimal resource allocation plan, the various resources supplied by the resource supply site are allocated to the corresponding customers.

[0022] In the complex process of resource allocation, in order to avoid a single resource supply point from getting into trouble due to overload operation, this solution designs a set of balanced allocation probability strategies. The core of this strategy is to balance the workload of each resource supply point while ensuring that customer needs are met. Through intelligent algorithms, resource allocation can be flexibly adjusted based on real-time data, thereby avoiding overload of resource supply points. This balanced strategy not only ensures the optimization of enterprise resource allocation, but also significantly improves the operating efficiency of resource supply points, making the entire enterprise resource network more efficient and stable.

[0023] Reference Figure 5 As shown, based on the resource supply matrix A and the resource allocation C under the resource allocation scheme, the reasonable allocation index of each resource allocation scheme is calculated and determined, including: Based on the resource supply demand value of each resource supply site in the resource allocation C under the resource allocation scheme and the resource supply efficiency of each resource supply site in the resource supply matrix A, the load index of each resource supply site is determined by a load calculation formula; Based on the load index of each resource supply site under the resource allocation plan, the reasonable allocation index of the resource allocation plan is calculated through the balance identification formula; The load calculation formula is as follows: ; F i is the load index of the i-th resource supply site; The specific equilibrium determination formula is: ; Where H is the reasonable allocation index of the resource allocation scheme.

[0024] In this solution, we use the average of the resource supply ratios of each resource supply site under each solution as an indicator to measure the load of the resource supply site. Specifically, we calculate the supply ratio of each resource supply site on different resources, and then take the average of these ratios to evaluate the load of the site. This average can reflect the relative importance and load level of the resource supply site in the overall resource allocation.

[0025] Furthermore, in order to measure the rationality of the entire resource allocation plan, we introduced the standard deviation of the resource supply site load index as an indicator of allocation rationality. Standard deviation is a concept in statistics, which is used to measure the degree of dispersion of a set of data. Here, the smaller the standard deviation, the smaller the difference between the load indicators of each resource supply site, and the more concentrated the distribution. In other words, the load of each resource supply site is more balanced, and there is no extreme load overload or underload.

[0026] Therefore, when the resource allocation scheme has a smaller allocation rationality index (i.e., the standard deviation of the load index), we can consider that the scheme is more reasonable in resource allocation and can make the load of each resource supply site more balanced. This balanced resource allocation scheme is of great significance for the optimization of enterprise resource allocation, because it can ensure the effective use of resources and avoid resource waste, while also improving the operational efficiency and economic benefits of the entire enterprise.

[0027] Further, based on the same inventive concept as the resource allocation method applied to customer management data, the present solution proposes a resource allocation system applied to customer management data, comprising: A storage module, which is used to store a customer management database; Resource analysis module: The resource analysis module is used to obtain the supply efficiency of various resources of all current resource supply sites and form a resource supply matrix; A demand data analysis module, the demand data analysis module is electrically connected to the storage module, and the demand data analysis module is used to retrieve the historical demand data of each customer from the customer management database, and based on the customer's historical demand data, predict the customer's resource demand forecast value, and build the customer's resource demand forecast matrix; The resource allocation module is electrically connected to the resource analysis module and the demand data analysis module. The resource allocation module is used to generate resource allocation conditions based on the resource supply matrix, and generate several resource allocation plans based on the resource allocation conditions and the resource demand prediction matrix, and determine the resource allocation under each resource allocation plan, and based on the resource supply matrix and the resource allocation under the resource allocation plan, perform various resource supply allocation plans for the resource supply site through a balanced allocation algorithm.

[0028] The demand data analysis module includes: A data retrieval unit, which is used to retrieve historical demand data of each customer from a customer management database; The prediction unit is used to predict the resource demand forecast value of the customer based on the customer's historical demand data and build the customer's resource demand prediction matrix.

[0029] The resource allocation module includes: A scheme generating unit, the scheme generating unit is used to generate resource allocation conditions based on the resource supply matrix, and to generate a plurality of resource allocation schemes based on the resource allocation conditions and the resource demand prediction matrix; A scheme evaluation unit, which is used to calculate and determine the reasonable allocation index of each resource allocation scheme based on the resource supply matrix and the resource allocation under the resource allocation scheme; The scheme screening unit is used to screen out the minimum value of the reasonable allocation index and the corresponding resource allocation scheme, and use the resource allocation scheme as the optimal resource allocation scheme, and according to the optimal resource allocation scheme, allocate various resource supplies of the resource supply site to the corresponding customers.

[0030] The working process of the resource allocation system applied to customer management data is as follows: Step 1: The resource analysis module obtains the supply efficiency of various resources of all current resource supply sites and forms a resource supply matrix; Step 2: The data retrieval unit retrieves the historical demand data of each customer from the customer management database stored in the storage module; Step 3: The forecasting unit forecasts the customer's resource demand forecast value based on the customer's historical demand data, and constructs the customer's resource demand forecast matrix; Step 4: The solution generation unit generates resource allocation conditions based on the resource supply matrix, and generates several resource allocation solutions based on the resource allocation conditions and the resource demand prediction matrix; Step 5: The scheme evaluation unit calculates and determines the reasonable allocation index of each resource allocation scheme based on the resource supply matrix and the resource allocation under the resource allocation scheme; Step 6: The solution screening unit screens out the resource allocation solution corresponding to the minimum value of the reasonable allocation index, takes the resource allocation solution as the optimal resource allocation solution, and allocates the various resource supplies of the resource supply site to the corresponding customers according to the optimal resource allocation solution.

[0031] Furthermore, the method according to the embodiment of the present application can also be performed by Figure 6 The electronic device architecture shown in FIG. Figure 6 As shown, the electronic device 500 may include a bus 501, one or more CPUs 502, a read-only memory (ROM) 503, a random access memory (RAM) 504, a communication port 505 connected to a network, an input / output component 506, a hard disk 507, etc. The storage device in the electronic device 500, such as the ROM 503 or the hard disk 507, may store a resource allocation method for customer management data provided by the present application. The electronic device 500 may also include a user interface 508. Of course, Figure 6 The architecture shown is only exemplary and can be omitted according to actual needs when implementing different devices. Figure 6 One or more components of an electronic device are shown.

[0032] Figure 7 Schematic diagram of a computer-readable storage medium structure provided by an embodiment of the present application. Figure 7 As shown, a computer-readable storage medium 600 according to an embodiment of the present application is shown. Computer-readable instructions are stored on the computer-readable storage medium 600. When the computer-readable instructions are executed by the processor, a resource allocation method for customer management data according to an embodiment of the present application described with reference to the above figures can be executed. The computer-readable storage medium 600 includes, but is not limited to, for example, volatile memory and / or non-volatile memory. Volatile memory may include, for example, random access memory (RAM) and cache memory (cache), etc. Non-volatile memory may include, for example, read-only memory (ROM), hard disk, flash memory, etc.

[0033] In summary, the advantages of the present invention are: significantly improving the customer data management capabilities and resource utilization efficiency of an enterprise, greatly optimizing enterprise resource allocation, and improving operational efficiency.

[0034] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The above embodiments and descriptions only describe the principles of the present invention. The present invention may be subject to various changes and improvements without departing from the spirit and scope of the present invention. These changes and improvements fall within the scope of the present invention. The scope of protection claimed by the present invention is defined by the attached claims and their equivalents.

Claims

1. A resource allocation method applied to customer management data, characterized in that: include: Obtain the supply efficiency of each resource of all current resource supply sites to form a resource supply matrix A. , where X ij is the supply efficiency of the jth resource of the i-th resource supply site, n is the total number of resource types, and m is the total number of resource supply sites; Retrieve each customer's historical demand data from the customer management database; Based on the customer's historical demand data, predict the customer's resource demand forecast value and build the customer's resource demand forecast matrix B. , where y kj is the resource demand forecast value of the i-th customer for the j-th resource, l is the total number of customers; Based on the resource supply matrix A, generate resource allocation conditions, and generate several resource allocation schemes based on the resource allocation conditions and the resource demand prediction matrix B, and determine the resource allocation C under each resource allocation scheme. , where Z ij is the resource supply demand value of the i-th resource supply station for the j-th resource under the resource allocation scheme; Based on the resource supply matrix A and the resource allocation C under the resource allocation plan, the resource supply allocation planning of each resource supply site is carried out through the balanced allocation algorithm.

2. A resource allocation method for customer management data according to claim 1, characterized in that: The predicted resource demand value of the customer based on the customer's historical demand data specifically includes: According to the different types of resource requirements, the customer's historical demand data is classified to obtain the customer's historical demand sample data under each resource type; All historical demand sample data of customers are numbered in order from the earliest to the latest time; Based on the principle of linear fitting, a demand fitting prediction formula is constructed; Substitute all historical demand sample data and numbers into the demand fitting forecast formula to obtain the customer's resource demand forecast value; The demand fitting prediction formula is specifically: ； Where P is the fitting value of green virtual resources of green account, p o The historical demand sample data is numbered o, and a is the total number of historical demand sample data.

3. A resource allocation method for customer management data according to claim 2, characterized in that: The generating of resource allocation conditions based on the resource supply matrix A specifically includes: Based on the single resource supply efficiency of the resource supply site, a single resource allocation condition is constructed, and all the single resource supply efficiencies of the resource supply site satisfy the single resource allocation condition as the single site restriction condition; All resource supply sites satisfy the single-site constraint as the resource site side condition; Each customer has a corresponding resource supply site as a customer-side condition; Satisfying both the resource site side conditions and the client side conditions will be used as resource allocation conditions; The expression of the single resource allocation condition is: ； In the formula, y qj is the resource demand forecast value for the jth resource of the qth customer assigned to the i-th resource supply site, Ui is the total number of customers assigned to the i-th resource supply site.

4. A resource allocation method for customer management data according to claim 3, characterized in that: The balanced allocation algorithm is specifically: Based on the resource supply matrix A and the resource allocation C under the resource allocation plan, calculate and determine the reasonable allocation index of each resource allocation plan; Filter out the minimum value of the reasonable allocation index and the corresponding resource allocation plan, and use the resource allocation plan as the optimal resource allocation plan; According to the optimal resource allocation plan, the various resources supplied by the resource supply site are allocated to the corresponding customers.

5. A resource allocation method for customer management data according to claim 4, characterized in that: The calculation and determination of the reasonable allocation index of each resource allocation scheme based on the resource supply matrix A and the resource allocation C under the resource allocation scheme specifically includes: Based on the resource supply demand value of each resource supply site in the resource allocation C under the resource allocation scheme and the resource supply efficiency of each resource supply site in the resource supply matrix A, the load index of each resource supply site is determined by a load calculation formula; Based on the load index of each resource supply site under the resource allocation plan, the reasonable allocation index of the resource allocation plan is calculated through the balance identification formula; The load calculation formula is specifically: ； F i is the load index of the i-th resource supply site; The equilibrium determination formula is specifically: ； Where H is the reasonable allocation index of the resource allocation scheme.

6. A resource allocation system for customer management data, characterized in that: A method for implementing a resource allocation method for customer management data as claimed in any one of claims 1 to 5, comprising: A storage module, wherein the storage module is used to store a customer management database; A resource analysis module, which is used to obtain the supply efficiency of various resources of all current resource supply sites and form a resource supply matrix; A demand data analysis module, the demand data analysis module is electrically connected to the storage module, and the demand data analysis module is used to retrieve the historical demand data of each customer from the customer management database, and based on the historical demand data of the customer, predict the resource demand forecast value of the customer, and construct the resource demand forecast matrix of the customer; A resource allocation module, the resource allocation module is electrically connected to the resource analysis module and the demand data analysis module, the resource allocation module is used to generate resource allocation conditions based on the resource supply matrix, and generate several resource allocation schemes based on the resource allocation conditions and the resource demand prediction matrix, and determine the resource allocation under each resource allocation scheme, and based on the resource supply matrix and the resource allocation under the resource allocation scheme, perform various resource supply allocation plans for the resource supply site through a balanced allocation algorithm.

7. A resource allocation system for customer management data according to claim 6, characterized in that: The demand data analysis module includes: A data retrieval unit, the data retrieval unit is used to retrieve the historical demand data of each customer from the customer management database; The prediction unit is used to predict the resource demand prediction value of the customer based on the customer's historical demand data, and to construct the customer's resource demand prediction matrix.

8. A resource allocation system for customer management data according to claim 7, characterized in that: The resource allocation module comprises: A scheme generating unit, the scheme generating unit is used to generate resource allocation conditions based on the resource supply matrix, and generate a plurality of resource allocation schemes based on the resource allocation conditions and the resource demand prediction matrix; A scheme evaluation unit, the scheme evaluation unit is used to calculate and determine the allocation rationality index of each resource allocation scheme based on the resource supply matrix and the resource allocation under the resource allocation scheme; A scheme screening unit is used to screen out the minimum value of the reasonable allocation index and the corresponding resource allocation scheme, and use the resource allocation scheme as the optimal resource allocation scheme, and according to the optimal resource allocation scheme, allocate various resource supplies of the resource supply site to the corresponding customers.

9. An electronic device, characterized in that: include: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute a resource allocation method applied to customer management data as described in any one of claims 1-5.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, a resource allocation method for customer management data according to any one of claims 1 to 5 is implemented.

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