Client management system based on marketing

Abstract

The invention discloses a marketing-based customer management system, which relates to the technical field of customer management and comprises a customer information acquisition module, a product information acquisition module, a transaction information acquisition module, a customer consumption recording module, a customer consumption calculation module, a customer value information module and the like. Value levels of customers to enterprises are evaluated from multiple aspects of basic information, transaction information, profit data, profit rate data, consumption data and the like of consumption products of the customers, so that the enterprises can select proper service schemes to serve the customers, and a similarity matrix is constructed based on different optimal customer value data; a similarity loss function is constructed by combining the mean square error of the distance from the customer value data to each piece of optimal customer value data, so that even if the searched optimal customer value data is different from the actual optimal customer value data, the optimal customer value data can be close to the actual optimal customer value data as much as possible; and the value grade classification precision of the customer value data can be greatly improved.

Description

Technical Field

[0001] The present invention relates to the technical field of customer management, and particularly to a marketing-based customer management system. Background Art

[0002] Existing customer management systems are usually based on the construction of customer portraits to understand customer needs in order to customize better services for customers. For example, the prior art with the publication number CN118822670A discloses a company customer management system based on customer portraits, which relates to the technical field of customer management and includes a customer information acquisition module, a classification and integration analysis module, and a portrait precise analysis module; the customer information acquisition module is used to acquire customer information; the classification and integration analysis module is used to classify and integrate and analyze customer data information, including analyzing customer levels and differentiating and analyzing customer purchase psychology and purchase attitudes; the portrait precise analysis module is used to construct customer portraits and improve the accuracy of customer portraits; this system improves the accuracy of customer portraits and also provides valuable data support for enterprises, helping enterprises achieve more accurate market positioning and marketing strategies.

[0003] However, there are still some problems with the customer management systems in the current market. Although the existing systems can provide some data support, they fail to deeply explore and analyze the actual value of customers to the enterprise. For example, the current systems lack the analysis of the value of customers to the enterprise. Due to the lack of an effective customer value evaluation mechanism, enterprises often fall into blindness when allocating limited energy and resources. Some customers with low or even no value occupy a large amount of service resources of the enterprise, while the truly high-value customers fail to receive sufficient attention and personalized services. This not only leads to a waste of enterprise resources but also affects the improvement of customer satisfaction, and may further weaken the market competitiveness of the enterprise. Summary of the Invention

[0004] The purpose of the present invention is to provide a marketing-based customer management system to solve the above deficiencies in the prior art.

[0005] To achieve the above purpose, the present invention provides the following technical solution: A marketing-based customer management system, including a customer information acquisition module, a product information acquisition module, a transaction information acquisition module, a customer consumption record module, a customer consumption calculation module, a customer value information module, a customer level evaluation module, and a customer management module;

[0006] The customer information acquisition module is used to acquire basic customer information, and the basic customer information includes customer name, customer identification code, customer address, and customer contact information. Among them, the customer name, customer address, and customer contact information can be obtained through information registration methods, and a unique customer identification code is generated for different customer individuals;

[0007] The product information acquisition module is used to acquire the basic product information, and the basic product information includes product name, product identification code, product cost price, product guiding price, and product inventory;

[0008] The transaction information acquisition module is used to acquire transaction information, and the transaction information includes transaction customer identification code, transaction product identification code, transaction quantity, and transaction price;

[0009] The customer consumption record module is used to perform character matching processing based on the basic product information and transaction information to construct the customer consumption history data of different customers;

[0010] The customer consumption calculation module is used to calculate based on the customer consumption history data to obtain customer consumption data, and the customer consumption data includes customer consumption amount, customer profit, and customer profit margin;

[0011] The customer value information module is used to construct customer value data based on the customer consumption history data and customer consumption data;

[0012] The customer value information module is further used to perform customer value level marking processing based on the customer value data to construct value level customer value data;

[0013] The customer level evaluation module is used to perform search processing based on the value level customer value data and customer value data to generate customer level evaluation data;

[0014] The customer management module is used to edit different customer service plans based on the customer level evaluation data, and construct customer management data based on the customer value data, customer level evaluation data, and customer service plan data.

[0015] Furthermore, the product information acquisition module is used to acquire the basic product information, and the basic product information includes product name, product identification code, product cost price, product guiding price, and product inventory, including the following steps:

[0016] S1. Acquire the basic product information and construct the basic product information set A = (a 1 , …, a o , …, a p ), o = 1, 2, 3, …, p, where a o represents the oth type of basic product information data, and p represents the maximum number of categories of basic product information.

[0017] Furthermore, the transaction information acquisition module is used to acquire transaction information, and the transaction information includes transaction customer identification code, transaction product identification code, transaction quantity, and transaction price, including the following steps:

[0018] S2. Obtain transaction information through transaction records, and construct a transaction information set B = (b 1 , …, b n , …, b m ), where n = 1, 2, 3, …, m, and b n is the nth type of transaction information, and m is the maximum number of transaction information categories.

[0019] Furthermore, the customer consumption record module is used to perform character matching processing based on product basic information and transaction information, and construct customer consumption history data of different customers, including the following steps:

[0020] S3. After performing character matching and combination processing based on the product basic information set A and the transaction information set B, construct a customer consumption history data set C = (c 1 , …, c q , …, c w ), where q = 1, 2, 3, …, w, and c q represents the qth customer consumption history data, w is the maximum number of customers, C = (A, B), and c q = (A q , B q ), A q represents the basic information of the consumption products of the qth customer, and B q represents the transaction information of the qth customer.

[0021] Furthermore, the customer consumption calculation module is used to calculate based on the customer consumption history data to obtain customer consumption data, including the following steps:

[0022] S41. Calculate the customer profit based on the customer consumption history data set C, and construct a customer profit data set D′ = (d′ 1 , …, d′ q , …, d′ w ), where d′ q represents the qth customer profit data;

[0023] S42. Calculate the customer profit margin based on the customer consumption history data set C, and construct a customer profit margin data set D″ = (d″ 1 , …, d″ q , …, d″ w ), where d″ q represents the qth customer profit margin data;

[0024] S43. Calculate the customer consumption amount based on the customer consumption history data set C, and construct a customer consumption amount data set D″′ = (d″′ 1 , …, d″′ q , …, d″′ w), d″′ represents the consumption amount data of the q-th customer;

[0025] S44. Combine the customer profit data set D′, the customer profit margin data set D″, and the customer consumption amount data set D″′ to obtain the customer consumption data D = (d 1 , …, d q , …, d w ), d q = (d′ q , d″ q , d″′ q ) represents the consumption data of the q-th customer.

[0026] Furthermore, the customer value information module is used to construct customer value data based on the customer consumption history data and the customer consumption data; the customer value information module is also used to perform customer value level annotation processing based on the customer value data to construct value level customer value data, including the following steps:

[0027] S51. Combine the customer consumption history data C and the customer consumption data D to construct the customer value data set E = (e 1 , …, e q , …, e w ), where e q = (c q , d q ) represents the customer value data of the q-th customer;

[0028] S52. Perform customer value level annotation on the customer value data e q , and classify the customer value data e q according to the annotated customer value level to construct the value level customer value data set F = (f 1 ,..., f j ,..., f k ), j = 1, 2, 3, …, k, where f j is the customer value data of the j-th value level, and k is the maximum number of customer value level categories, including the following steps:

[0029] S5201. Perform standardization processing on the customer value data set E to obtain the standardized customer value data set E′. Further standardization processing includes dimensionality reduction of E and mapping E to the [0, 1] interval;

[0030] S5202. Initialize and select the radius r and the selection space density ρ;

[0031] S5203. Randomly select a customer value data e q in the standardized customer value data set E′ as the search point;

[0032] S5204. Draw a search circle with the search point as the center and r as the radius;

[0033] S5205. Determine whether the number of customer value data in the search circle is greater than ρ;

[0034] S5206. If so, update the customer value data in the search circle that is not the search point to the search point, and return to step 04;

[0035] S5207. If not, mark all the customer value data within the current search circles as one category;

[0036] S5208. Determine whether the number of customer value data in the category is greater than ρ;

[0037] S5209. If not, mark the customer value data in the said category as abnormal data;

[0038] S5210. Determine whether each customer value data e in the standardized set E′ of customer value data q has been used as a search point;

[0039] S5211. If not, randomly select an unused customer value data e in the standardized set E′ of customer value data q as the search point, and return to step 04;

[0040] S5212. If so, output the customer value data of each obtained category, map the customer value data to the set k customer value levels according to the marked categories, and construct a value level customer value data set F = (f 1 , …, f j , …, f k ), where j = 1, 2, 3, …, k, and f j is the customer value data of the jth value level, k is the maximum number of customer value level categories, and each customer value level can be mapped to one or more categories of customer value data, f j = (e q1 , …, e q2 ), 1 ≤ e q1 ≤ e q ≤ e q2 ≤ e w , where q1 represents the q1th customer and q2 represents the q2th customer.

[0041] Furthermore, the customer level evaluation module is used to perform search processing based on the value level customer value data and the customer value data to generate customer level evaluation data, including the following steps:

[0042] S61. Search for the best customer value data e' in the customer value data f of the value level j to minimize the distance between the best customer value data e' in the value level and each customer value data e j，q in the customer value data f of the value level; j，q j in the customer value data f of the value level; q The distance is minimized;

[0043] S62. Based on different best customer value data e', j，q construct a similarity matrix, and combine the mean square error of the distance between the customer value data e q and each best customer value data e' j，q to construct a similarity loss function S;

[0044] S63. Search in the set F of customer value data of the value level for the best customer value data e' that matches the customer value data e q and minimizes the loss function S, and construct a level evaluation data G, i.e., G = (g j，q , …, g 1 , …, g j , …, g k ), where g j represents the j-th type of level evaluation data and g j = e' j，q . When searching, the gradient descent method can be used to find the e' that minimizes the loss function S j，q .

[0045] Furthermore, the customer management module is used to edit different customer service plans based on the customer level evaluation data, and construct customer management data based on the customer value data, customer level evaluation data, and customer service plan data, including the following steps:

[0046] S71. Edit different customer service plans based on the customer level evaluation data G, and construct customer service data H that corresponds one-to-one with the level evaluation data G, H = (h 1 , …, h j , …, h k ), where h j is the customer service data corresponding to the level evaluation data g j ;

[0047] S72. Collect and combine the customer value data set E, the customer level evaluation data G, and the customer service data H to construct customer management data R = (E, G, H);

[0048] ​S73. Manage data by customer. Generate corresponding customer evaluation data G according to the customer value data set E, and perform service management for the corresponding customers based on the customer service data H corresponding to the customer level evaluation data G. The corresponding customers are obtained by character matching search of the customer service data H and the basic customer information. For example, there is a customer value data e q , according to e q Generate the corresponding customer level evaluation data g j , then select the customer service data h j corresponding to the customer level evaluation data g j to provide customer service for e q corresponding customers.

[0049] 1. Compared with the prior art, a customer management system based on marketing provided by the present invention can evaluate the value level of customers to the enterprise from multiple aspects such as the basic information, transaction information, profit data, profit rate data, and consumption data of the products consumed by the customers by setting a customer information acquisition module, a product information acquisition module, a transaction information acquisition module, a customer consumption record module, a customer consumption calculation module, a customer value information module, a customer level evaluation module, and a customer management module, so that the enterprise can select a suitable service plan to serve the customers, which is beneficial for the enterprise to use limited service resources on high-value customers.

[0050] 2. Compared with the prior art, a customer management system based on marketing provided by the present invention constructs a similarity matrix based on different optimal customer value data, and combines the mean square error of the distance from the customer value data to each optimal customer value data to construct a similarity loss function by setting a customer information acquisition module, a product information acquisition module, a transaction information acquisition module, a customer consumption record module, a customer consumption calculation module, a customer value information module, a customer level evaluation module, and a customer management module. Even if the searched optimal customer value data is different from the actual optimal customer value data, it will be as close as possible to the actual optimal customer value data, which can greatly improve the accuracy of value level classification for customer value data.

[0051] 3. Compared with the prior art, a customer management system based on marketing provided by the present invention can cluster the characteristics of customer value data by setting a customer information acquisition module, a product information acquisition module, a transaction information acquisition module, a customer consumption record module, a customer consumption calculation module, a customer value information module, a customer level evaluation module, and a customer management module to obtain multiple characteristic categories of customer value data, and then judge the actual value of the customers corresponding to the customer value data of each category, and map the obtained different categories of customer value data to the set k categories of customer value levels, which can more clearly reflect the characteristics of the customer value data corresponding to the customers of each value level. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments recorded in the present invention. For those of ordinary skill in the art, other drawings can also be obtained based on these drawings.

[0053] Figure 1 It is a system structure block diagram provided by an embodiment of the present invention;

[0054] Figure 2 It is a system implementation step diagram provided by an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0055] In order to enable those skilled in the art to better understand the technical solutions of the present invention, the following will further introduce the present invention in detail in conjunction with the drawings.

[0056] In the description of the present invention, it should be understood that the terms "first" and "second" are only used for descriptive purposes and cannot be construed as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include one or more of the described features. In the description of the present invention, "a plurality" means two or more unless otherwise specifically defined. In addition, the terms "installation", "connection", and "connection" should be understood in a broad sense. For example, it may be a fixed connection, a detachable connection, or an integral connection; it may be a mechanical connection or an electrical connection; it may be directly connected or indirectly connected through an intermediate medium, and it may be the internal communication of two components. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0057] In the following, the exemplary embodiments will be more fully described with reference to the drawings, but the exemplary embodiments may be embodied in different forms and should not be construed as limited to the embodiments set forth herein. On the contrary, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

[0058] Without conflict, the various embodiments of the present disclosure and the features in the embodiments may be combined with each other.

[0059] As used herein, the term "and / or" includes any and all combinations of one or more of the associated listed items.

[0060] The terms used in this document are only for describing specific embodiments and are not intended to limit the present disclosure. As used herein, the singular forms "a" and "the" are also intended to include the plural forms, unless the context clearly indicates otherwise. It will also be understood that when the terms "comprising" and / or "consisting of" are used in this specification, the specified features, wholes, steps, operations, elements, and / or components are present, but the presence or addition of one or more other features, wholes, steps, operations, elements, components, and / or their groups is not excluded.

[0061] Please refer to Figure 1 - Figure 2 A marketing-based customer management system, comprising a customer information acquisition module, a product information acquisition module, a transaction information acquisition module, a customer consumption record module, a customer consumption calculation module, a customer value information module, a customer level evaluation module, and a customer management module;

[0062] The customer information acquisition module is used to acquire basic customer information. The basic customer information includes customer name, customer identification code, customer address, and customer contact information. Among them, the customer name, customer address, customer contact information, etc. can be acquired through information registration, and a unique customer identification code is generated for different customer individuals;

[0063] The product information acquisition module is used to acquire basic product information. The basic product information includes product name, product identification code, product cost price, product guiding price, and product inventory;

[0064] The transaction information acquisition module is used to acquire transaction information. The transaction information includes transaction customer identification code, transaction product identification code, transaction quantity, and transaction price;

[0065] The customer consumption record module is used to perform character matching processing based on the basic product information and transaction information, and construct the customer consumption history data of different customers;

[0066] The customer consumption calculation module is used to calculate based on the customer consumption history data to obtain customer consumption data. The customer consumption data includes customer consumption amount, customer profit, and customer profit margin;

[0067] The customer value information module is used to construct customer value data based on the customer consumption history data and customer consumption data;

[0068] The customer value information module is also used to perform customer value level marking processing based on the customer value data, and construct value level customer value data;

[0069] The customer level evaluation module is used to perform search processing based on the value level customer value data and customer value data, and generate customer level evaluation data;

[0070] The customer management module is used to edit different customer service plans based on customer level evaluation data, and construct customer management data based on customer value data, customer level evaluation data, and customer service plan data.

[0071] Furthermore, the product information acquisition module is used to acquire product basic information, and the product basic information includes product name, product identification code, product cost price, product guiding price, and product inventory quantity, including the following steps:

[0072] S1. Acquire product basic information and construct a product basic information set A = (a 1 , …, a o , …, a p ), o = 1, 2, 3, …, p, where a o represents the o-th type of product basic information data, and p represents the maximum number of categories of product basic information;

[0073] Furthermore, S1 also includes the following steps:

[0074] Acquire customer basic information, and the customer basic information includes customer name, customer identification code, customer address, and customer contact information. Among them, the customer name, customer address, and customer contact information can be obtained through information registration, and a unique customer identification code is generated for different customer individuals.

[0075] Furthermore, the transaction information acquisition module is used to acquire transaction information, and the transaction information includes transaction customer identification code, transaction product identification code, transaction quantity, and transaction price, including the following steps:

[0076] S2. Acquire transaction information through transaction records and construct a transaction information set B = (b 1 , …, b n , …, b m ), n = 1, 2, 3, …, m, where b n is the n-th type of transaction information, and m is the maximum number of categories of transaction information.

[0077] Furthermore, the customer consumption record module is used to perform character matching processing based on product basic information and transaction information, and construct customer consumption history data of different customers, including the following steps:

[0078] S3. Perform character matching and combination processing based on the product basic information set A and the transaction information set B, and construct a customer consumption history data set C = (c 1 , …, c q , …, c w ), q = 1, 2, 3, …, w, where c q represents the q-th customer consumption history data, w is the maximum number of customers, C = (A, B), cq =(A q , B q ), A q represents the basic information of the consumer products of the q-th customer, and B q represents the transaction information of the q-th customer.

[0079] Furthermore, the customer consumption calculation module is used to calculate based on the customer consumption historical data to obtain customer consumption data, including the following steps:

[0080] S41. Calculate the customer profit based on the customer consumption historical data set C, and construct the customer profit data set D' = (d' 1 , …, d' q , …, d' w ), where d' q represents the q-th customer profit data;

[0081] S42. Calculate the customer profit margin based on the customer consumption historical data set C, and construct the customer profit margin data set D'' = (d'' 1 , …, d'' q , …, d'' w ), where d'' q represents the q-th customer profit margin data;

[0082] S43. Calculate the customer consumption amount based on the customer consumption historical data set C, and construct the customer consumption amount data set D''' = (d''' 1 , …, d''' q , …, d''' w ), where d''' represents the q-th customer consumption amount data;

[0083] S44. Combine the customer profit data set D', the customer profit margin data set D'' and the customer consumption amount data set D''' to obtain the customer consumption data D = (d 1 , …, d q , …, d w ), where d q =(d' q , d'' q , d''' q ) represents the q-th customer consumption data.

[0084] Furthermore, the customer value information module is used to construct customer value data based on the customer consumption historical data and the customer consumption data; the customer value information module is also used to perform customer value level annotation processing based on the customer value data to construct value level customer value data, including the following steps:

[0085] S51. Combine the customer consumption history data C and the customer consumption data D to construct a customer value data set E = (e 1 , …, e q , …, e w ), where e q = (c q , d q ) represents the q-th customer value data;

[0086] S52. Label the customer value level of the customer value data e q , and classify the customer value data e q according to the labeled customer value level to construct a value-level customer value data set F = (f 1 , …, f j , …, f k ), j = 1, 2, 3, …, k, where f j is the customer value data of the j-th value level, and k is the maximum number of customer value level categories, including the following steps:

[0087] S5201. Perform standardization processing on the customer value data set E to obtain a standardized customer value data set E′. Further standardization processing includes dimensionality reduction of E and mapping E to the interval [0, 1];

[0088] S5202. Initialize the selection radius r and the selection space density ρ;

[0089] S5203. Randomly select a customer value data e q in the standardized customer value data set E′ as the search point;

[0090] S5204. Draw a search circle with the search point as the center and r as the radius;

[0091] S5205. Determine whether the number of customer value data in the search circle is greater than ρ;

[0092] S5206. If so, update the customer value data in the search circle that is not the search point to the search point, and return to step 04;

[0093] S5207. If not, mark all the customer value data in the search circle at this time as one category;

[0094] S5208. Determine whether the number of customer value data in the category is greater than ρ;

[0095] S5209. If not, mark the customer value data in the category as abnormal data;

[0096] S5210. Determine whether each piece of customer value data e in the standardized set E' of customer value data has been used as a search point; q If not, randomly select an unused piece of customer value data e from the standardized set E' of customer value data

[0097] as a search point and return to step 04; q If so, output the customer value data of each category obtained, map the customer value data to the set k-class customer value levels according to the marked categories, and construct a value-level customer value data set F = (f

[0098] ,..., f 1 , …, f j , …, f k ), where j = 1, 2, 3, …, k, and f j is the customer value data of the j-th value level, k is the maximum number of customer value level categories, and each customer value level can be mapped to one or more categories of customer value data. f j = (e q1 , …, e q2 ), where 1 ≤ e q1 ≤ e q ≤ e q2 ≤ e w , q1 represents the q1-th customer, and q2 represents the q2-th customer.

[0099] Through the above embodiments, the characteristics of customer value data can be clustered to obtain multiple characteristic categories of customer value data, and then the actual value of the customers corresponding to the customer value data of each category can be judged. Mapping the obtained customer value data of different categories to the set k-class customer value levels can more clearly reflect the characteristics of the customer value data corresponding to the customers of each value level.

[0100] Furthermore, the customer level evaluation module is used to perform search processing based on the value-level customer value data and the customer value data to generate customer level evaluation data, including the following steps:

[0101] Search for the best customer value data e' of the value level in the value-level customer value data f j such that the distance from the best customer value data e' of the value level to each piece of customer value data e j，q in the value-level customer value data f j，q is the smallest; j Based on different best customer value data e' q construct a similarity matrix, combined with the customer value data e

[0102] j，q q ​​to each optimal customer value data e′ j，q The mean squared error of the distances is used to construct a similarity loss function S:

[0103]

[0104] where, represents the predicted optimal customer value data, α is a control parameter with a value in (0, 1), e′ j，q，λ respectively represent and the λ-th dimensional data of e′ j，q , ψ represents that the optimal customer value data has at most ψ dimensional data;

[0105] Search for the optimal customer value data e′ q in the value level customer value data set F that matches the customer value data e j，q and minimizes the loss function S, and construct the level evaluation data G, that is, G = (g 1 , …, g j …, g k ), where g j represents the j-th type of level evaluation data and g j = e′ j，q . When searching, the gradient descent method can be used to find the e′ j，q that minimizes the loss function S.

[0106] Through the above embodiments, even if the searched optimal customer value data e′ j，q is different from the actual optimal customer value data e′ j，q , it will be as close as possible to the actual optimal customer value data e′ j，q , which can greatly improve the accuracy of classifying the customer value data e q into value levels.

[0107] Furthermore, the customer management module is used to edit different customer service plans based on the customer level evaluation data, and construct customer management data based on the customer value data, customer level evaluation data, and customer service plan data, including the following steps:

[0108] Edit different customer service plans based on the customer level evaluation data G, and construct customer service data H that corresponds one-to-one with the level evaluation data G, H = (h 1 , …, h j …, h k ), where h j is the customer service data corresponding to the level evaluation data g j ;

[0109] Collect and combine the customer value data set E, the customer level evaluation data G, and the customer service data H to construct the customer management data R = (E, G, H).

[0110] Generate the corresponding customer evaluation data G according to the customer value data set E in the customer management data R, and perform service management on the corresponding customers based on the customer service data H corresponding to the customer level evaluation data G. The corresponding customers are obtained by character matching search of the customer service data H and the customer basic information. For example, there is a customer value data e q , according to e q Generate the corresponding customer level evaluation data g j , then select the customer service data h j corresponding to the customer level evaluation data g j to provide customer service for e q corresponding customers. Further, the customer basic information of the corresponding customers can be retrieved through character matching search of the customer identification code.

[0111] Only some exemplary embodiments of the present invention are described by way of illustration above. Undoubtedly, for those of ordinary skill in the art, the described embodiments can be modified in various different ways without departing from the spirit and scope of the present invention. Therefore, the above drawings and descriptions are illustrative in nature and should not be construed as limiting the protection scope of the claims of the present invention.

Claims

1. A customer management system based on marketing, characterized by: It includes customer information acquisition module, product information acquisition module, transaction information acquisition module, customer consumption record module, customer consumption calculation module, customer value information module, customer grade evaluation module and customer management module; The customer information acquisition module is used to acquire basic customer information; The product information acquisition module is used to acquire basic product information; The transaction information acquisition module is used to acquire transaction information; The customer consumption record module is used to perform character matching processing based on basic product information and transaction information to construct customer consumption history data of different customers; The customer consumption calculation module is used to calculate based on the customer consumption history data to obtain customer consumption data, wherein the customer consumption data includes customer profit data, customer profit rate data, and customer consumption amount data; The customer value information module is used to construct customer value data based on the customer consumption history data and customer consumption data, and to perform customer value grade labeling processing based on the customer value data to construct value grade customer value data; The customer grade evaluation module is used to perform search processing based on the value grade customer value data and customer value data to generate customer grade evaluation data; The customer management module is used to edit different customer service plans based on customer grade evaluation data, and to construct customer management data based on customer value data, customer grade evaluation data and customer service plan data.

2. A marketing-based customer management system according to claim 1, characterized in that: The product information acquisition module is used to acquire basic product information, which includes product name, product identification code, product cost price, product guide price, and product inventory, and includes the following steps: S1. Obtain basic product information and construct a product basic information set A = (a1, ..., a o , …, a p ), o = 1, 2, 3, ..., p, where a o represents the basic information data of the oth category of products, and p represents the maximum number of categories of basic product information.

3. A marketing-based customer management system according to claim 2, characterized in that: The transaction information acquisition module is used to acquire transaction information, wherein the transaction information includes a transaction customer identification code, a transaction product identification code, a transaction quantity, and a transaction price, and includes the following steps: S2. Obtain transaction information through transaction records and construct a transaction information set B = (b1, ..., b n , …, b m ), n = 1, 2, 3, ..., m, where b n is the nth category of transaction information, and m is the maximum number of categories of transaction information.

4. A marketing-based customer management system according to claim 3, characterized in that: The customer consumption record module is used to perform character matching processing based on product basic information and transaction information to construct customer consumption history data of different customers, including the following steps: S3: Based on the product basic information set A and the transaction information set B, character matching and combination processing are performed to construct a customer consumption history data set C = (c1, ..., c q , …, c w ), q=1,2,3,…,w, where c q represents the consumption history data of the qth customer, and w is the maximum number of customers.

5. A marketing-based customer management system according to claim 4, characterized in that: The customer consumption calculation module is used to calculate based on the customer consumption history data to obtain customer consumption data, including the following steps: S41. Calculate customer profit based on customer consumption history data set C and construct customer profit data set D′=(d′1,…,d′ q ,…,d′ w ), d′ q represents the profit data of the qth customer; S42. Calculate customer profit margin based on customer consumption history data set C, and construct customer profit margin data set D″=(d″1, …, d″ q ,…,d″ w ), d″ q represents the profit margin data of the qth customer; S43. Calculate the customer's consumption amount based on the customer's consumption history data set C, and construct a customer consumption amount data set D″′=(d″′1,…,d″′ q ,…,d″′ w ), d″′ represents the consumption amount data of the qth customer; S44, combining the customer profit data set D′, the customer profit rate data set D″ and the customer consumption amount data set D″′ to obtain customer consumption data D=(d1, …, d q , …, d w ), d q =(d′ q ,d″ q ,d″′ q ) represents the consumption data of the qth customer.

6. A marketing-based customer management system according to claim 5, characterized in that: The customer value information module is used to construct customer value data based on the customer consumption history data and customer consumption data; the customer value information module is also used to perform customer value grade labeling processing based on the customer value data to construct value grade customer value data, including the following steps: S51, based on the customer consumption history data C and the customer consumption data D, construct a customer value data set E = (e1, ..., e q ,…,e w ), where e q =(c q ,d q ) represents the qth customer value data; S52. Customer value data q Mark the customer value level and sort the customer value data according to the marked customer value level q Perform classification processing and construct a value-level customer value data set F = (f1, ..., f j , ..., f k ), j = 1, 2, 3, ..., k, where f j is the customer value data of the jth value level, k is the maximum number of customer value level categories, including the following steps: S5201, standardize the customer value data set E to obtain a customer value data standardized set E′; S5202, initializing the selected radius r and the selected space density ρ; S5203. Randomly select a customer value data e from the standardized set of customer value data E′. q As a search point; S5204, draw a search circle with the search point as the center and r as the radius; S5205, determining whether the number of customer value data in the search circle is greater than ρ; S5206, if yes, then update the customer value data of the non-search point in the search circle to the search point, and return to step 04; S5207, if not, then mark all customer value data in the search circle as one category; S5208, judging whether the number of customer value data in the category is greater than ρ; S5209, if not, marking the customer value data in the category as abnormal data; S5210, determine the customer value data e in the standardized set of customer value data E' q Whether they are all considered as past search points; S5211. If not, randomly select an unselected customer value data e from the standardized customer value data set E′. q As the search point, return to step 04; S5212: If yes, then output the obtained customer value data of each category, map the customer value data to the set k customer value levels according to the marked categories, and construct a value level customer value data set F = (f1, ..., f j , …, f k ), j = 1, 2, 3, ..., k, where f j is the customer value data of the jth value level, and k is the maximum number of customer value level categories.

7. A marketing-based customer management system according to claim 6, characterized in that: The customer grade evaluation module is used to perform search processing based on the value grade customer value data and customer value data to generate customer grade evaluation data, including the following steps: S61, in the value level customer value data f j Search for the best customer value data in value ranking e′ j，q , making the value level the best customer value data e′ j，q To value level customer value data f j Customer value data q The distance is the smallest; S62, based on different optimal customer value data e′ j，q Construct a similarity matrix and combine it with customer value data q To each optimal customer value data e′ j，q The mean square error of the distance is used to construct the similarity loss function S; S63, searching for the customer value data set F that matches the customer value data e q The best customer value data e′ that matches and minimizes the loss function S j，q , and construct the grade evaluation data G.

8. A marketing-based customer management system according to claim 7, characterized in that: The customer management module is used to edit different customer service plans based on customer grade evaluation data, and to construct customer management data based on customer value data, customer grade evaluation data and customer service plan data, including the following steps: S71, edit different customer service plans based on the customer grade evaluation data G, and construct customer service data H corresponding to the grade evaluation data G, H = (h1, ..., h j …,h k ); S72, collect and combine the customer value data set E, the customer rating evaluation data G and the customer service data H to construct the customer management data R = (E, G, H); S73. Generate corresponding customer evaluation data G according to the customer management data R and the customer value data set E, and perform service management on the corresponding customer based on the customer service data H corresponding to the customer grade evaluation data G. The corresponding customer is obtained by performing character matching search on the customer service data H and the customer's basic information.

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