Telecommunications subscriber differentiation marketing method and apparatus

Abstract

The application relates to the computer technical field and provides a telecommunication user differentiation marketing method and device. The method comprises the following steps: clustering telecommunication users into a preset number of clustering clusters according to first feature data, second feature data and third feature data; after adjusting the preset number, returning to the step of clustering the telecommunication users into the preset number of clustering clusters according to the first feature data, the second feature data and the third feature data; if the clustering clusters satisfy specific conditions, obtaining a final number of the clustering clusters; and setting a differentiated marketing frequency for the final number of the clustering clusters. The telecommunication user differentiation marketing method and device can avoid setting specific marketing rules for single telecommunication users, fully explore the common points among the telecommunication users, realize unified management of the same type of telecommunication users, and thus improve marketing accuracy and marketing efficiency.

Description

Technical Field

[0001] This application relates to the field of computer technology, specifically to a method and apparatus for differentiated marketing to telecommunications users. Background Technology

[0002] Telecommunications users have different consumption behavior characteristics. These characteristics have both similarities and differences. When setting marketing rules for telecommunications users, it is necessary to match the consumption behavior characteristics of each telecommunications user in order to provide targeted marketing strategies and achieve better marketing results.

[0003] On the one hand, the number of telecommunications users is enormous, and it is impractical to set marketing rules based on the consumption behavior characteristics of each user. This is time-consuming and labor-intensive, and does not meet the efficiency requirements of actual business scenarios. On the other hand, telecommunications users share common consumption behavior characteristics. If differentiated marketing rules are adopted for telecommunications users with many commonalities, it will sever the commonalities among telecommunications users, making it impossible to conduct unified marketing management for these users and reducing marketing accuracy and efficiency. Summary of the Invention

[0004] This application provides a method and apparatus for differentiated marketing to telecommunications users, which solves the technical problems that traditional methods do not meet the efficiency requirements of actual business scenarios and cannot perform unified marketing management of telecommunications users, thus reducing marketing accuracy and efficiency.

[0005] In a first aspect, embodiments of this application provide a method for differentiated marketing to telecommunications users, including:

[0006] Based on the first feature data, the second feature data, and the third feature data, telecommunications users are clustered into a preset number of clusters; the first feature data is the reciprocal of the interval between the current time and the last time the telecommunications user recharged; the second feature data is the number of times the telecommunications user has recharged within the past six months; and the third feature data is the total amount of telecommunications recharges made by the telecommunications user within the past six months.

[0007] After adjusting the preset number, return to the step of clustering telecommunications users into a preset number of clusters based on the first feature data, the second feature data, and the third feature data;

[0008] If the clusters meet certain conditions, the final number of clusters is obtained; the specific conditions are set based on the overall sum of squared distances between the clusters and the profile coefficients of the telecommunications users in the clusters.

[0009] Differentiated marketing frequencies are set for the final number of clusters.

[0010] In one embodiment, obtaining the final number of clusters if the clusters satisfy a specific condition includes:

[0011] If the sum of squared distances of the clusters obtained after adjusting the preset number reaches the minimum value, then the number of clusters obtained after this adjustment is determined as the first number;

[0012] If the contour coefficients of all telecommunications users in the clusters obtained after the adjustment of the first quantity are greater than the coefficient threshold, then the number of clusters obtained after this adjustment is determined as the final number of clusters.

[0013] In one embodiment, the sum of squared distances of the clusters obtained after adjusting the preset number is based on the following steps:

[0014] The sum of squared intra-cluster distances of any cluster is obtained by calculating the sum of Euclidean distances between all telecommunications users in any cluster and the cluster center of any cluster after the preset quantity adjustment.

[0015] The sum of the squared intra-cluster distances of all clusters obtained after adjusting the preset number is obtained by summing the squared intra-cluster distances of all clusters obtained after adjusting the preset number.

[0016] In one embodiment, the profile coefficients of all telecommunications users in the cluster obtained after the first quantity adjustment are obtained based on the following steps:

[0017] Calculate the average distance between any telecommunications user in any cluster and other telecommunications users in any cluster within the clusters obtained after the first quantity adjustment, and obtain the first average value;

[0018] Calculate the average distance between any telecommunications user and any other telecommunications user in any cluster outside of any given cluster to obtain a second average value;

[0019] The minimum value of all second average values ​​is determined as the third average value. Based on the first average value and the third average value, the profile coefficient of any telecommunications user is obtained.

[0020] In one embodiment, setting differentiated marketing frequencies for the final number of clusters includes:

[0021] Based on the cluster core characteristic data of each cluster in the final number of clusters, differentiated marketing frequencies are set.

[0022] In one embodiment, setting differentiated marketing frequencies based on the cluster core characteristic data of each cluster in the final number of clusters includes:

[0023] If, in the final number of clusters, the first feature data of the cluster center of any cluster is greater than the reciprocal of the duration threshold, the second feature data is greater than the recharge number threshold, and the third feature data is greater than the total recharge amount threshold, then the telecommunications user in the determined cluster is identified as an important value user, and a first marketing frequency is set for the important value user.

[0024] If, in the final number of clusters, the first feature data of the cluster center of any cluster is less than or equal to the reciprocal duration threshold, the second feature data is greater than the recharge count threshold, and the third feature data is greater than the total recharge amount threshold, then the telecommunications user in the determined cluster is identified as an important retention user, and a first marketing frequency is set for the important retention user.

[0025] If, in the final number of clusters, the first feature data of the cluster center of any cluster is greater than the reciprocal of the duration threshold, the second feature data is less than or equal to the recharge count threshold, and the third feature data is greater than the total recharge amount threshold, then the telecommunications user in the determined cluster is identified as an important development user, and a first marketing frequency is set for the important development user.

[0026] If, in the final number of clusters, the first feature data of the cluster center is less than or equal to the reciprocal duration threshold, the second feature data is less than or equal to the number of recharges threshold, and the third feature data is greater than the total recharge amount threshold, then the telecommunications users in the determined clusters are identified as important retention users, and a first marketing frequency is set for the important retention users.

[0027] In one embodiment, setting differentiated marketing frequencies based on the cluster core characteristic data of each cluster in the final number of clusters includes:

[0028] If, in the final number of clusters, the first feature data of the cluster center of any cluster is greater than the reciprocal of the duration threshold, the second feature data is greater than the recharge count threshold, and the third feature data is less than or equal to the total recharge amount threshold, then the telecommunications user in the determined cluster is identified as a general value user, and a second marketing frequency is set for the general value user.

[0029] If, in the final number of clusters, the first feature data of the cluster center of any cluster is greater than the reciprocal of the duration threshold, the second feature data is less than or equal to the recharge number threshold, and the third feature data is less than or equal to the total recharge amount threshold, then the telecommunications user in the determined cluster is identified as a general development user, and a third marketing frequency is set for the general development user.

[0030] If, in the final number of clusters, the first feature data of the cluster center of any cluster is less than or equal to the reciprocal duration threshold, the second feature data is greater than the recharge count threshold, and the third feature data is less than or equal to the total recharge amount threshold, then the telecommunications user in the determined cluster is identified as a general retention user, and a first marketing frequency is set for the general retention user.

[0031] If, in the final number of clusters, the first feature data of the cluster center of any cluster is less than or equal to the reciprocal duration threshold, the second feature data is less than or equal to the number of recharges threshold, and the third feature data is less than or equal to the total recharge amount threshold, then the telecommunications user in the determined cluster is identified as a general retention user, and a third marketing frequency is set for the general retention user.

[0032] The first marketing frequency is greater than the second marketing frequency, and the first marketing frequency is less than the third marketing frequency.

[0033] Secondly, embodiments of this application provide a telecommunications user differentiated marketing device, comprising:

[0034] The clustering module is used to: cluster telecommunications users into a preset number of clusters based on first feature data, second feature data, and third feature data; the first feature data is the reciprocal of the interval between the current time and the last time the telecommunications user recharged, the second feature data is the number of times the telecommunications user recharged within six months from the current time, and the third feature data is the total amount of telecommunications recharged within six months from the current time.

[0035] The clustering quantity adjustment module is used to: adjust the preset quantity and then return to the step of clustering telecommunications users into a preset number of clusters based on the first feature data, the second feature data, and the third feature data;

[0036] The cluster number determination module is used to: if the clusters meet specific conditions, then obtain the final number of clusters; the specific conditions are set based on the overall sum of squared distances of the clusters and the profile coefficients of the telecommunications users in the clusters;

[0037] The marketing frequency setting module is used to set differentiated marketing frequencies for the final number of clusters.

[0038] Thirdly, embodiments of this application provide an electronic device, including a processor and a memory storing a computer program, wherein the processor executes the program to implement the steps of the telecommunications user differentiated marketing method described in the first aspect.

[0039] Fourthly, embodiments of this application provide a computer program product, including a computer program that, when executed by a processor, implements the steps of the telecommunications user differentiated marketing method described in the first aspect.

[0040] The telecommunications user differentiated marketing method and apparatus provided in this application clusters telecommunications users into a preset number of clusters based on first feature data, second feature data, and third feature data. After adjusting the preset number, it returns to the step of clustering telecommunications users into a preset number of clusters based on the first feature data, second feature data, and third feature data. If the clusters meet specific conditions, the final number of clusters is obtained, and differentiated marketing frequencies are set for the final number of clusters. By clustering telecom users based on multiple feature data, and adjusting the number of clusters based on the overall sum of squared distances between clusters and the silhouette coefficients of telecom users within clusters, the final number of clusters results in a high degree of similarity among telecom users within each cluster across multiple feature dimensions, while the similarity between telecom users within each cluster and those outside the clusters across multiple feature dimensions is low. This improves the accuracy of grouping massive numbers of telecom users, allows for differentiated marketing frequency settings for each group, avoids setting specific marketing rules for individual telecom users, and fully explores the commonalities among telecom users, achieving unified management of similar telecom users, thereby improving marketing accuracy and efficiency. Attached Figure Description

[0041] To more clearly illustrate the technical solutions in this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0042] Figure 1 This is one of the flowcharts illustrating the telecommunications user differentiation marketing method provided in the embodiments of this application;

[0043] Figure 2 This is a second flowchart illustrating the telecommunications user differentiation marketing method provided in the embodiments of this application;

[0044] Figure 3 This is a schematic diagram of the structure of the telecommunications user differentiated marketing device provided in the embodiments of this application;

[0045] Figure 4 This is a schematic diagram of the structure of the electronic device provided in the embodiments of this application. Detailed Implementation

[0046] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions of this application will be clearly and completely described below with reference to the accompanying drawings of the embodiments. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0047] Figure 1 This is one of the flowcharts illustrating the telecommunications user differentiated marketing method provided in this application embodiment. (Refer to...) Figure 1 This application provides a method for differentiated marketing to telecommunications users, which may include:

[0048] 101. Based on the first feature data, the second feature data, and the third feature data, the telecommunications users are clustered into a preset number of clusters;

[0049] The first feature data is the reciprocal of the interval between the current time and the last time the telecom user recharged; the second feature data is the number of times the telecom user recharged within the past six months; and the third feature data is the total amount of telecom recharged within the past six months.

[0050] 102. After adjusting the preset quantity, return to step 101;

[0051] 103. If the clusters meet certain conditions, the final number of clusters can be obtained;

[0052] The specific conditions are set based on the overall sum of squared distances between clusters and the profile coefficients of telecommunications users in the clusters;

[0053] 104. Set differentiated marketing frequencies for the final number of clusters.

[0054] In step 101, the preset quantity can be set according to actual needs, and there is no limit here.

[0055] In step 102, the telecommunications users are re-clustered based on the first feature data, the second feature data, and the third feature data after the preset number is adjusted, so that the number of clusters is the adjusted number. For example, if the preset number is 5, in step 101 the telecommunications users are first clustered into 5 clusters, and in step 102 the preset number is adjusted to 6, and the telecommunications users are re-clustered into 6 clusters.

[0056] In step 104, different marketing frequencies are set for each cluster in the final number of clusters to reflect differentiated marketing strategies.

[0057] The differentiated marketing method for telecommunications users provided in this embodiment clusters telecommunications users into a preset number of clusters based on first, second, and third feature data. After adjusting the preset number, it returns to the step of clustering telecommunications users into a preset number of clusters based on the first, second, and third feature data. If the clusters meet specific conditions, the final number of clusters is obtained, and differentiated marketing frequencies are set for the final number of clusters. Because telecommunications users are clustered based on multiple feature data, and the number of clusters is adjusted based on the overall sum of squared distances between clusters and the silhouette coefficients of telecommunications users in the clusters, the final number of clusters results in telecommunications users within each cluster having high similarity across multiple feature dimensions, and telecommunications users within each cluster having low similarity across multiple feature dimensions compared to telecommunications users in clusters outside the cluster. This improves the accuracy of grouping massive numbers of telecommunications users and allows for differentiated marketing frequency settings for each group, avoiding the setting of specific marketing rules for individual telecommunications users. It also fully explores the commonalities among telecommunications users, achieving unified management of similar telecommunications users, thereby improving marketing accuracy and efficiency.

[0058] Figure 2 This is the second flowchart illustrating the telecommunications user differentiated marketing method provided in this application embodiment. (Refer to...) Figure 2 In one embodiment, if the clusters meet certain conditions, the final number of clusters is obtained, which may include:

[0059] 201. If the sum of squared distances of the clusters obtained after adjusting the preset number reaches the minimum value, then the number of clusters obtained after this adjustment is determined as the first number.

[0060] 202. Adjust the first quantity. If the contour coefficients of all telecommunications users in the clusters obtained after the adjustment of the first quantity are greater than the coefficient threshold, then the number of clusters obtained after this adjustment is determined as the final number of clusters.

[0061] In step 201, the sum of squared distances of the clusters obtained after adjusting the preset number can be obtained based on the following steps:

[0062] 201a. Calculate the sum of Euclidean distances between all telecommunications users in any cluster and the cluster center of the cluster after the preset quantity adjustment, and obtain the sum of squared intra-cluster distances of the cluster.

[0063] 201b. Sum the squared intra-cluster distances of all clusters obtained after adjusting the preset number to obtain the overall squared distance of the clusters obtained after adjusting the preset number.

[0064] For a given cluster, the smaller the sum of the distances from all telecommunications users within it to the cluster center (i.e., the smaller the sum of squared intra-cluster distances), the more similar the telecommunications users in that cluster are considered, and the smaller the intra-cluster differences are. By adding up the sum of squared intra-cluster distances of all clusters, we obtain the overall sum of squared distances. The smaller the overall sum of squared distances, the more similar the telecommunications users are within each cluster, and the better the clustering effect.

[0065] In fact, the process of adjusting the preset number is the process of adjusting the cluster center position of the clusters. During this process, the sum of squared distances of all clusters becomes smaller and smaller. When the sum of squared distances of all clusters reaches the minimum value, the cluster center no longer changes. Then, the number of clusters at this time is determined as the first number.

[0066] In step 202, the profile coefficients of all telecom users in the cluster obtained after the first quantity adjustment can be obtained based on the following steps:

[0067] 202a. Calculate the average distance between any telecommunications user in any cluster and other telecommunications users in the cluster obtained after the first quantity adjustment, and obtain the first average value;

[0068] 202b. Calculate the average distance between the telecommunications user and telecommunications users in any other cluster outside the current cluster, and obtain the second average distance.

[0069] 202c. Determine the minimum value of all second averages as the third average. Based on the first average and the third average, obtain the profile coefficient of the telecommunications user.

[0070] In steps 202b to 202c, for example, after the first quantity adjustment, four clusters A, B, C, and D are obtained. If the telecommunications user is in cluster A, the average distance between the telecommunications user and all telecommunications users in cluster B is calculated to obtain the first second average. Similarly, the average distance between the telecommunications user and all telecommunications users in cluster C is calculated to obtain the second second average. Similarly, the average distance between the telecommunications user and all telecommunications users in cluster D is calculated to obtain the third second average. The minimum value among these three second averages is determined as the third average.

[0071] The profile coefficient of this telecommunications user can be calculated using the following formula:

[0072]

[0073] Where S is the profile coefficient of the telecommunications user, b is the third average value, and a is the first average value.

[0074] The silhouette coefficient ranges from -1 to 1. A value closer to 1 indicates that the user is more similar to other users in their own cluster and less similar to users in other clusters. When the user is more similar to users outside their cluster, the silhouette coefficient is negative. A silhouette coefficient of 0 indicates that the users in clusters b and a have the same similarity, meaning the two clusters should ideally be grouped into one.

[0075] Therefore, the selection of coefficient thresholds should follow the principle of being close to 1 in order to improve clustering accuracy.

[0076] This embodiment evaluates the clustering effect of clusters based on the overall sum of squared distances of clusters and the profile coefficients of telecommunications users obtained after adjusting the preset number, and determines the number of clusters with the best clustering effect as the final number, so that the clustering accuracy of the final number of clusters is greatly improved.

[0077] In one embodiment, setting differentiated marketing frequencies for the final number of clusters may include:

[0078] If, in the final number of clusters, the first characteristic data of the cluster center of any cluster is greater than the reciprocal of the duration threshold, the second characteristic data is greater than the recharge number threshold, and the third characteristic data is greater than the total recharge amount threshold, then the telecommunications users in that cluster are identified as important value users, and a first marketing frequency is set for important value users, and a large customer marketing strategy is adopted.

[0079] If, in the final number of clusters, the first characteristic data of the cluster center is less than or equal to the reciprocal duration threshold, the second characteristic data is greater than the recharge number threshold, and the third characteristic data is greater than the total recharge amount threshold, then the telecom users in that cluster are identified as important retention users, and a first marketing frequency is set for important retention users to guide user consumption.

[0080] If, in the final number of clusters, the first characteristic data of the cluster center is greater than the reciprocal of the duration threshold, the second characteristic data is less than or equal to the recharge number threshold, and the third characteristic data is greater than the total recharge amount threshold, then the telecommunications users in that cluster are identified as important development users, and a first marketing frequency is set for important development users to stabilize daily consumption.

[0081] If, in the final number of clusters, the first characteristic data of the cluster center is less than or equal to the reciprocal duration threshold, the second characteristic data is less than or equal to the number of recharges threshold, and the third characteristic data is greater than the total recharge amount threshold, then the telecom users in that cluster are identified as important retention users, and a first marketing frequency is set for important retention users to increase the discounts in order to focus on retention.

[0082] If, in the final number of clusters, the first feature data of the cluster center is greater than the reciprocal of the duration threshold, the second feature data is greater than the recharge number threshold, and the third feature data is less than or equal to the total recharge amount threshold, then the telecommunications users in that cluster are identified as general value users, and a second marketing frequency is set for general value users to primarily boost the consumption of users with low average income.

[0083] If, in the final number of clusters, the first feature data of the cluster center is greater than the reciprocal of the duration threshold, the second feature data is less than or equal to the number of recharges threshold, and the third feature data is less than or equal to the total recharge amount threshold, then the telecommunications users in that cluster are identified as general development users, and a third marketing frequency is set for general development users to increase new user consumption and consumption frequency.

[0084] If, in the final number of clusters, the first characteristic data of the cluster center of any cluster is less than or equal to the reciprocal duration threshold, the second characteristic data is greater than the recharge number threshold, and the third characteristic data is less than or equal to the total recharge amount threshold, then the telecom users in that cluster are identified as general retention users, and a first marketing frequency is set for general retention users, and free benefit packages are given to cultivate consumption habits.

[0085] If, in the final number of clusters, the first feature data of the cluster center is less than or equal to the reciprocal duration threshold, the second feature data is less than or equal to the number of recharges threshold, and the third feature data is less than or equal to the total recharge amount threshold, then the telecommunications users in that cluster are identified as general retention users, and a third marketing frequency is set for general retention users to periodically recall lost users.

[0086] The first marketing frequency is greater than the second marketing frequency, and the first marketing frequency is less than the third marketing frequency. The first marketing frequency can be set as medium frequency, the second marketing frequency as low frequency, and the third marketing frequency as high frequency.

[0087] In addition to classifying telecom users in clusters based on the inverse duration threshold, the number of recharges threshold, and the total recharge amount threshold, it is also possible to perform comparison operator calculations or logical operator calculations on multiple feature data of the cluster core, and classify telecom users based on the calculation results. This is not limited here.

[0088] This embodiment improves user lifecycle management and marketing accuracy by setting differentiated marketing frequencies based on the comparison results of the cluster core feature data of each cluster in the final number of clusters with the threshold.

[0089] The telecommunications user differentiation marketing device provided in the embodiments of this application will be described below. The telecommunications user differentiation marketing device described below can be referred to in correspondence with the telecommunications user differentiation marketing method described above.

[0090] Figure 3 This is a schematic diagram of the structure of the telecommunications user differentiated marketing device provided in an embodiment of this application. (Refer to...) Figure 3 This application provides a telecommunications user differentiated marketing device, which may include:

[0091] Clustering module 301 is used to: cluster telecommunications users into a preset number of clusters based on first feature data, second feature data and third feature data; the first feature data is the reciprocal of the interval between the current time of the telecommunications user and the last time of telecommunications recharge, the second feature data is the number of times the telecommunications user has recharged within six months from the current time, and the third feature data is the total amount of telecommunications recharges by the telecommunications user within six months from the current time.

[0092] The clustering quantity adjustment module 302 is used to: after adjusting the preset quantity, return to the step of clustering telecommunications users into a preset number of clusters based on the first feature data, the second feature data, and the third feature data;

[0093] The cluster number determination module 303 is used to: if the clusters meet specific conditions, then obtain the final number of clusters; the specific conditions are set based on the overall sum of squared distances of the clusters and the profile coefficients of the telecommunications users in the clusters;

[0094] The marketing frequency setting module 304 is used to set differentiated marketing frequencies for the final number of clusters.

[0095] The telecommunications user differentiated marketing device provided in this embodiment clusters telecommunications users into a preset number of clusters based on first, second, and third feature data. After adjusting the preset number, it returns to the step of clustering telecommunications users into a preset number of clusters based on the first, second, and third feature data. If the clusters meet specific conditions, the final number of clusters is obtained, and differentiated marketing frequencies are set for the final number of clusters. Because telecommunications users are clustered based on multiple feature data, and the number of clusters is adjusted based on the overall sum of squared distances between clusters and the silhouette coefficients of telecommunications users in the clusters, the telecommunications users within each cluster have high similarity in multiple feature dimensions, and the telecommunications users within each cluster have low similarity in multiple feature dimensions compared to the telecommunications users in the clusters outside the clusters. This improves the accuracy of grouping massive numbers of telecommunications users and allows for differentiated marketing frequency settings for each group, avoiding the setting of specific marketing rules for individual telecommunications users. It also fully explores the commonalities among telecommunications users, achieving unified management of similar telecommunications users, thereby improving marketing accuracy and efficiency.

[0096] In one embodiment, the cluster number determination module 303 is specifically used for:

[0097] If the sum of squared distances of the clusters obtained after adjusting the preset number reaches the minimum value, then the number of clusters obtained after this adjustment is determined as the first number;

[0098] If the contour coefficients of all telecommunications users in the clusters obtained after the adjustment of the first quantity are greater than the coefficient threshold, then the number of clusters obtained after this adjustment is determined as the final number of clusters.

[0099] In one embodiment, the cluster number determination module 303 is specifically used for:

[0100] The sum of squared intra-cluster distances of any cluster is obtained by calculating the sum of Euclidean distances between all telecommunications users in any cluster and the cluster center of any cluster after the preset quantity adjustment.

[0101] The sum of the squared intra-cluster distances of all clusters obtained after adjusting the preset number is obtained by summing the squared intra-cluster distances of all clusters obtained after adjusting the preset number.

[0102] In one embodiment, the cluster number determination module 303 is specifically used for:

[0103] Calculate the average distance between any telecommunications user in any cluster and other telecommunications users in any cluster within the clusters obtained after the first quantity adjustment, and obtain the first average value;

[0104] Calculate the average distance between any telecommunications user and any other telecommunications user in any cluster outside of any given cluster to obtain a second average value;

[0105] The minimum value of all second average values ​​is determined as the third average value. Based on the first average value and the third average value, the profile coefficient of any telecommunications user is obtained.

[0106] In one embodiment, the marketing frequency setting module 304 is specifically used for:

[0107] Based on the cluster core characteristic data of each cluster in the final number of clusters, differentiated marketing frequencies are set.

[0108] In one embodiment, the marketing frequency setting module 304 is specifically used for:

[0109] If, in the final number of clusters, the first feature data of the cluster center of any cluster is greater than the reciprocal of the duration threshold, the second feature data is greater than the recharge number threshold, and the third feature data is greater than the total recharge amount threshold, then the telecommunications user in the determined cluster is identified as an important value user, and a first marketing frequency is set for the important value user.

[0110] If, in the final number of clusters, the first feature data of the cluster center of any cluster is less than or equal to the reciprocal duration threshold, the second feature data is greater than the recharge count threshold, and the third feature data is greater than the total recharge amount threshold, then the telecommunications user in the determined cluster is identified as an important retention user, and a first marketing frequency is set for the important retention user.

[0111] If, in the final number of clusters, the first feature data of the cluster center of any cluster is greater than the reciprocal of the duration threshold, the second feature data is less than or equal to the recharge count threshold, and the third feature data is greater than the total recharge amount threshold, then the telecommunications user in the determined cluster is identified as an important development user, and a first marketing frequency is set for the important development user.

[0112] If, in the final number of clusters, the first feature data of the cluster center is less than or equal to the reciprocal duration threshold, the second feature data is less than or equal to the number of recharges threshold, and the third feature data is greater than the total recharge amount threshold, then the telecommunications users in the determined clusters are identified as important retention users, and a first marketing frequency is set for the important retention users.

[0113] In one embodiment, the marketing frequency setting module 304 is specifically used for:

[0114] If, in the final number of clusters, the first feature data of the cluster center of any cluster is greater than the reciprocal of the duration threshold, the second feature data is greater than the recharge count threshold, and the third feature data is less than or equal to the total recharge amount threshold, then the telecommunications user in the determined cluster is identified as a general value user, and a second marketing frequency is set for the general value user.

[0115] If, in the final number of clusters, the first feature data of the cluster center of any cluster is greater than the reciprocal of the duration threshold, the second feature data is less than or equal to the recharge number threshold, and the third feature data is less than or equal to the total recharge amount threshold, then the telecommunications user in the determined cluster is identified as a general development user, and a third marketing frequency is set for the general development user.

[0116] If, in the final number of clusters, the first feature data of the cluster center of any cluster is less than or equal to the reciprocal duration threshold, the second feature data is greater than the recharge count threshold, and the third feature data is less than or equal to the total recharge amount threshold, then the telecommunications user in the determined cluster is identified as a general retention user, and a first marketing frequency is set for the general retention user.

[0117] If, in the final number of clusters, the first feature data of the cluster center of any cluster is less than or equal to the reciprocal duration threshold, the second feature data is less than or equal to the number of recharges threshold, and the third feature data is less than or equal to the total recharge amount threshold, then the telecommunications user in the determined cluster is identified as a general retention user, and a third marketing frequency is set for the general retention user.

[0118] The first marketing frequency is greater than the second marketing frequency, and the first marketing frequency is less than the third marketing frequency.

[0119] Figure 4 An example is a schematic diagram of the physical structure of an electronic device, such as... Figure 4 As shown, the electronic device may include: a processor 410, a communication interface 420, a memory 430, and a communication bus 440, wherein the processor 410, the communication interface 420, and the memory 430 communicate with each other via the communication bus 440. The processor 410 can call a computer program in the memory 430 to execute steps of a telecommunications user differentiated marketing method, such as:

[0120] Based on the first feature data, the second feature data, and the third feature data, telecommunications users are clustered into a preset number of clusters; the first feature data is the reciprocal of the interval between the current time and the last time the telecommunications user recharged; the second feature data is the number of times the telecommunications user has recharged within the past six months; and the third feature data is the total amount of telecommunications recharges made by the telecommunications user within the past six months.

[0121] After adjusting the preset number, return to the step of clustering telecommunications users into a preset number of clusters based on the first feature data, the second feature data, and the third feature data;

[0122] If the clusters meet certain conditions, the final number of clusters is obtained; the specific conditions are set based on the overall sum of squared distances between the clusters and the profile coefficients of the telecommunications users in the clusters.

[0123] Differentiated marketing frequencies are set for the final number of clusters.

[0124] Furthermore, the logical instructions in the aforementioned memory 430 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0125] On the other hand, this application also provides a computer program product, which includes a computer program that can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can perform the steps of the telecommunications user differentiated marketing method provided in the above embodiments, such as including:

[0126] Based on the first feature data, the second feature data, and the third feature data, telecommunications users are clustered into a preset number of clusters; the first feature data is the reciprocal of the interval between the current time and the last time the telecommunications user recharged; the second feature data is the number of times the telecommunications user has recharged within the past six months; and the third feature data is the total amount of telecommunications recharges made by the telecommunications user within the past six months.

[0127] After adjusting the preset number, return to the step of clustering telecommunications users into a preset number of clusters based on the first feature data, the second feature data, and the third feature data;

[0128] If the clusters meet certain conditions, the final number of clusters is obtained; the specific conditions are set based on the overall sum of squared distances between the clusters and the profile coefficients of the telecommunications users in the clusters.

[0129] Differentiated marketing frequencies are set for the final number of clusters.

[0130] On the other hand, embodiments of this application also provide a processor-readable storage medium storing a computer program for causing a processor to perform the steps of the methods provided in the above embodiments, such as including:

[0131] Based on the first feature data, the second feature data, and the third feature data, telecommunications users are clustered into a preset number of clusters; the first feature data is the reciprocal of the interval between the current time and the last time the telecommunications user recharged; the second feature data is the number of times the telecommunications user has recharged within the past six months; and the third feature data is the total amount of telecommunications recharges made by the telecommunications user within the past six months.

[0132] After adjusting the preset number, return to the step of clustering telecommunications users into a preset number of clusters based on the first feature data, the second feature data, and the third feature data;

[0133] If the clusters meet certain conditions, the final number of clusters is obtained; the specific conditions are set based on the overall sum of squared distances between the clusters and the profile coefficients of the telecommunications users in the clusters.

[0134] Differentiated marketing frequencies are set for the final number of clusters.

[0135] The processor-readable storage medium can be any available medium or data storage device that the processor can access, including but not limited to magnetic memory (e.g., floppy disk, hard disk, magnetic tape, magneto-optical disk (MO)), optical memory (e.g., CD, DVD, BD, HVD), and semiconductor memory (e.g., ROM, EPROM, EEPROM, non-volatile memory (NAND FLASH), solid-state drive (SSD)).

[0136] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0137] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0138] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. A method for differentiated marketing to telecommunications users, characterized in that, include: Based on the first feature data, the second feature data, and the third feature data, telecommunications users are clustered into a preset number of clusters; the first feature data is the reciprocal of the interval between the current time and the last time the telecommunications user recharged; the second feature data is the number of times the telecommunications user has recharged within the past six months; and the third feature data is the total amount of telecommunications recharges made by the telecommunications user within the past six months. After adjusting the preset number, return to the step of clustering telecommunications users into a preset number of clusters based on the first feature data, the second feature data, and the third feature data; If the sum of squared distances of the clusters obtained after adjusting the preset number reaches the minimum value, then the number of clusters obtained after this adjustment is determined as the first number; If the contour coefficients of all telecommunications users in the clusters obtained after the adjustment of the first quantity are greater than the coefficient threshold, then the number of clusters obtained after this adjustment is determined as the final number of clusters. Differentiated marketing frequencies are set for the final number of clusters; The sum of squared distances of the clusters obtained after adjusting the preset number is based on the following steps: The sum of squared intra-cluster distances of any cluster is obtained by calculating the sum of Euclidean distances between all telecommunications users in any cluster and the cluster center of any cluster after the preset quantity adjustment. The sum of the squared intra-cluster distances of all clusters obtained after adjusting the preset number is obtained by summing the squared intra-cluster distances of all clusters obtained after adjusting the preset number.

2. The telecommunications user differentiated marketing method according to claim 1, characterized in that, The profile coefficients of all telecommunications users in the cluster obtained after the first quantity adjustment are based on the following steps: Calculate the average distance between any telecommunications user in any cluster and other telecommunications users in any cluster within the clusters obtained after the first quantity adjustment, and obtain the first average value; Calculate the average distance between any telecommunications user and any other telecommunications user in any cluster outside of any given cluster to obtain a second average value; The minimum value of all second average values ​​is determined as the third average value. Based on the first average value and the third average value, the profile coefficient of any telecommunications user is obtained.

3. The telecommunications user differentiated marketing method according to claim 1, characterized in that, Setting differentiated marketing frequencies for the final number of clusters includes: Based on the cluster core characteristic data of each cluster in the final number of clusters, differentiated marketing frequencies are set.

4. The telecommunications user differentiated marketing method according to claim 3, characterized in that, The step of setting differentiated marketing frequencies based on the cluster core characteristic data of each cluster in the final number of clusters includes: If, in the final number of clusters, the first feature data of the cluster center of any cluster is greater than the reciprocal of the duration threshold, the second feature data is greater than the recharge number threshold, and the third feature data is greater than the total recharge amount threshold, then the telecommunications user in the determined cluster is identified as an important value user, and a first marketing frequency is set for the important value user. If, in the final number of clusters, the first feature data of the cluster center of any cluster is less than or equal to the reciprocal duration threshold, the second feature data is greater than the recharge count threshold, and the third feature data is greater than the total recharge amount threshold, then the telecommunications user in the determined cluster is identified as an important retention user, and a first marketing frequency is set for the important retention user. If, in the final number of clusters, the first feature data of the cluster center of any cluster is greater than the reciprocal of the duration threshold, the second feature data is less than or equal to the recharge count threshold, and the third feature data is greater than the total recharge amount threshold, then the telecommunications user in the determined cluster is identified as an important development user, and a first marketing frequency is set for the important development user. If, in the final number of clusters, the first feature data of the cluster center is less than or equal to the reciprocal duration threshold, the second feature data is less than or equal to the number of recharges threshold, and the third feature data is greater than the total recharge amount threshold, then the telecommunications users in the determined clusters are identified as important retention users, and a first marketing frequency is set for the important retention users.

5. The telecommunications user differentiated marketing method according to claim 3, characterized in that, The step of setting differentiated marketing frequencies based on the cluster core characteristic data of each cluster in the final number of clusters includes: If, in the final number of clusters, the first feature data of the cluster center of any cluster is greater than the reciprocal of the duration threshold, the second feature data is greater than the recharge count threshold, and the third feature data is less than or equal to the total recharge amount threshold, then the telecommunications user in the determined cluster is identified as a general value user, and a second marketing frequency is set for the general value user. If, in the final number of clusters, the first feature data of the cluster center of any cluster is greater than the reciprocal of the duration threshold, the second feature data is less than or equal to the recharge number threshold, and the third feature data is less than or equal to the total recharge amount threshold, then the telecommunications user in the determined cluster is identified as a general development user, and a third marketing frequency is set for the general development user. If, in the final number of clusters, the first feature data of the cluster center of any cluster is less than or equal to the reciprocal duration threshold, the second feature data is greater than the recharge count threshold, and the third feature data is less than or equal to the total recharge amount threshold, then the telecommunications user in the determined cluster is identified as a general retention user, and a first marketing frequency is set for the general retention user. If, in the final number of clusters, the first feature data of the cluster center of any cluster is less than or equal to the reciprocal duration threshold, the second feature data is less than or equal to the number of recharges threshold, and the third feature data is less than or equal to the total recharge amount threshold, then the telecommunications user in the determined cluster is identified as a general retention user, and a third marketing frequency is set for the general retention user. The first marketing frequency is greater than the second marketing frequency, and the first marketing frequency is less than the third marketing frequency.

6. A telecommunications user differentiated marketing device, characterized in that, The method for implementing the telecommunications user differentiated marketing method of claim 1 includes: The clustering module is used to: cluster telecommunications users into a preset number of clusters based on first feature data, second feature data, and third feature data; the first feature data is the reciprocal of the interval between the current time and the last time the telecommunications user recharged, the second feature data is the number of times the telecommunications user recharged within six months from the current time, and the third feature data is the total amount of telecommunications recharged within six months from the current time. The clustering quantity adjustment module is used to: adjust the preset quantity and then return to the step of clustering telecommunications users into a preset number of clusters based on the first feature data, the second feature data, and the third feature data; The cluster number determination module is used to: if the clusters meet specific conditions, then obtain the final number of clusters; the specific conditions are set based on the overall sum of squared distances of the clusters and the profile coefficients of the telecommunications users in the clusters; The marketing frequency setting module is used to set differentiated marketing frequencies for the final number of clusters.

7. An electronic device comprising a processor and a memory storing a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the telecommunications user differentiated marketing method according to any one of claims 1 to 5.

8. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the telecommunications user differentiation marketing method according to any one of claims 1 to 5.

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