Information pushing method based on cloud tenant classification

Abstract

The invention discloses an information pushing method based on cloud tenant classification, and relates to the technical field of informatization and automation. Comprising the following steps: step 1, classifying cloud tenant recharging modes, and obtaining related data of each cloud tenant about recharging mode preference and arrearage degree; step 2, according to the related data obtained in the step 1, respectively constructing a recharging mode preference degree classification model and an arrearage degree classification model; 3, according to the recharge mode preference degree classification model and the arrearage degree classification model, subdividing the types of the cloud tenants from the two dimensions of the recharge mode preference and the arrearage degree; and 4, respectively formulating different recharging service information for pushing from four aspects of a pushing group, a pushing period, a pushing content and a pushing channel aiming at different types of cloud tenants after subdivision.

Description

Technical Field

[0001] The present invention discloses an information push method based on cloud tenant classification, and relates to the technical field of informatization and automation. Background Art

[0002] With the rapid development of my country's cloud computing industry, cloud tenants' demands for production and service efficiency in the cloud computing industry are constantly increasing. The push service business for recharge service information in the cloud computing industry has developed rapidly. However, the existing recharge service information push method still has the following shortcomings:

[0003] (1) The existing recharge service information push includes two types of information push: recharge reminder and arrears reminder. The push recipients need to be manually selected, which is highly subjective, arbitrary, and time-determined. The existing relevant management measures do not have relevant provisions for this.

[0004] (2) The existing methods do not clearly specify the specific time, number and frequency of push notifications for various types of recharge service information, resulting in users receiving multiple text messages a day or receiving text messages every day, which can easily lead to "over-service" and reduce users' perception of information push services.

[0005] (3) The existing method uses a unified information template for all cloud tenants. The information content is relatively simple and lacks specificity. The information only serves as a notification and it is difficult to guide users through channels. Summary of the invention

[0006] In view of the problems of the prior art, the present invention provides an information push method based on cloud tenant classification, which can reduce the total amount of recharge service information pushed, guide the recharge method of cloud tenants, and improve the accuracy of recharge service information push.

[0007] The specific scheme proposed by the present invention is:

[0008] The present invention provides an information push method based on cloud tenant classification, comprising:

[0009] Step 1: Classify the recharge methods of cloud tenants and obtain relevant data on each cloud tenant's recharge method preference and arrears level;

[0010] Step 2: Based on the relevant data obtained in step 1, a classification model of the recharge method preference and a classification model of the arrears degree are constructed respectively;

[0011] Step 3: Based on the recharge method preference classification model and the arrears degree classification model, the cloud tenant types are segmented from the two dimensions of recharge method preference and arrears degree;

[0012] Step 4: For different types of cloud tenants, formulate different recharge service information for push based on four aspects: push group, push cycle, push content and push channel.

[0013] Furthermore, in step 1 of the information push method based on cloud tenant classification, the cloud tenant recharge methods are classified, including: the recharge methods are divided into three categories:

[0014] Recharge method: Cloud tenants do not need to recharge by themselves, and recharge by a third-party agent;

[0015] Online banking recharge method: Cloud tenants use the recharge platform to complete the recharge through online payment;

[0016] Offline remittance method: The cloud tenant transfers the recharge amount to the platform's public account, and the platform's professionals complete the recharge of the user's account.

[0017] Furthermore, the data related to the recharge method preference in step 1 of the information push method based on cloud tenant classification includes: the type of recharge method used within a preset time, the recharge amount, and the recharge time. Based on the data related to the recharge method preference, the number of times each type of recharge method is used, the recharge ratio, and the average recharge duration index are calculated respectively;

[0018] The data related to the degree of arrears include: the bill amount between two recharges within a preset time, the amount of arrears each time, and the duration of arrears for each recharge.

[0019] Based on the above-mentioned data on the degree of arrears, the total arrears ratio, total number of arrears, total arrears amount, and total arrears duration of cloud tenants are calculated respectively.

[0020] Furthermore, the recharge method preference degree classification model constructed in step 2 of the information push method based on cloud tenant classification includes: determining the recharge method preference type of each cloud tenant according to the recharge method preference related data,

[0021] The classification setting R1 is the preference category for agency recharge methods, R2 is the preference category for online banking recharge methods, and R3 is the preference category for offline remittance methods;

[0022] The input indicators of the recharge method preference classification model are obtained, including: the number of times the agent recharge method is used X1, the recharge ratio of the agent recharge method X2, the average recharge time of the deduction method X3, the number of times the online banking recharge method is used X4, the recharge ratio of the online banking recharge method X5, the average recharge time of the online banking recharge method X6, the number of times the offline remittance method is used X7, the recharge ratio of the offline remittance method X8, and the average recharge time of the offline remittance method X9.

[0023] Furthermore, in step 3 of the information push method based on cloud tenant classification, cloud tenant types are subdivided based on recharge method preference according to the recharge method preference classification model, including:

[0024] Calculate (X1+X2-X3), (X4+X5-X6), and (X7+X8-X9) respectively to obtain the preference data of each category of cloud tenants.

[0025] Compare the recharge method preference data of each cloud tenant (X1+X2-X3), (X4+X5-X6), and (X7+X8-X9). When (X1+X2-X3) is the largest, it is classified as R1, when (X4+X5-X6) is the largest, it is classified as R2, and when (X7+X8-X9) is the largest, it is classified as R3. When they are equal, they are classified in the priority order of R1>R2>R3.

[0026] Furthermore, the arrears degree classification model constructed in step 2 of the information push method based on cloud tenant classification includes: judging the arrears degree of each cloud tenant through relevant data of the arrears degree;

[0027] Set A1 as heavy arrears, A2 as moderate arrears, and A3 as no arrears;

[0028] The input indicators of the arrears degree classification model are obtained, and the input indicators include: total arrears ratio Y1, total arrears times Y2, total arrears amount Y3, and total arrears duration Y4.

[0029] Furthermore, in step 3 of the information push method based on cloud tenant classification, cloud tenant types are subdivided according to the arrears degree classification model, including: setting an arrears degree classification measurement value M according to the operation situation;

[0030] Calculate the arrears data Y of each cloud tenant during the last five recharges, the formula is Y=Y1+Y2+Y3+Y4;

[0031] Compare Y with M. When Y>=M, the degree of arrears is A1; when M>Y>0, the degree of arrears is A2; when Y=0, the degree of arrears is A3.

[0032] The present invention also provides an information push device based on cloud tenant classification, including a recharge data collection module, a model management module, a cloud tenant classification module and an information push module.

[0033] The recharge data collection module classifies the recharge methods of cloud tenants and obtains relevant data on each cloud tenant's recharge method preference and arrears level;

[0034] The model management module constructs a recharge method preference classification model and a debt degree classification model based on the relevant data obtained;

[0035] The cloud tenant classification module subdivides the cloud tenant types based on the recharge method preference and arrears degree classification models respectively;

[0036] The information push module formulates different recharge service information for push according to the different types of cloud tenants after segmentation, from four aspects: push group, push cycle, push content and push channel.

[0037] The benefits of the present invention are:

[0038] (1) This method accurately segments users by establishing a classification model based on their recharge method preferences and the degree of arrears, and then configures the recharge service information push strategy based on the characteristics of each user group. The pushed information is more practical, saves push costs, and improves information push efficiency.

[0039] (2) Based on the analysis of recharge big data of various user segments, this method can configure the recharge service information of each user segment from four dimensions, namely, push group, push cycle, push content and push method, so as to improve the relevance of the information to the user segment and improve the accuracy of the recharge service information push. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 It is a schematic flow chart of the method of the present invention. DETAILED DESCRIPTION

[0041] The present invention is further described below in conjunction with the accompanying drawings and specific embodiments so that those skilled in the art can better understand the present invention and implement it, but the embodiments are not intended to limit the present invention.

[0042] Example 1

[0043] The present invention provides an information push method based on cloud tenant classification, comprising:

[0044] Step 1: Classify the recharge methods of cloud tenants and obtain relevant data on each cloud tenant's recharge method preference and degree of arrears.

[0045] The cloud tenant recharge methods are classified into three categories:

[0046] Recharge method: Cloud tenants do not need to recharge by themselves, and recharge by a third-party agent;

[0047] Online banking recharge method: Cloud tenants use the recharge platform to complete the recharge through online payment;

[0048] Offline remittance method: The cloud tenant transfers the recharge amount to the platform's public account, and the platform's professionals complete the recharge of the user's account.

[0049] The data related to the recharge method preference in step 1 may further include: the type of recharge method used within a preset time, the recharge amount, and the recharge time. Based on the data related to the recharge method preference, the number of times each type of recharge method is used, the recharge ratio, and the average recharge duration index are calculated. For example, the type of recharge method and the recharge amount used within the last five recharges.

[0050] The data related to the degree of arrears may further include: the bill amount during two recharges within a preset time, the amount of arrears each time, and the duration of arrears for each recharge.

[0051] Based on the above data on the degree of arrears, the total arrears ratio, total number of arrears, total arrears amount, and total arrears duration of cloud tenants are calculated. For example, the bill amount during two recharges within the last five recharges, the arrears amount each time, and the duration of arrears for each recharge.

[0052] Step 2: Based on the relevant data obtained in step 1, construct a classification model for the recharge method preference and a classification model for the degree of arrears respectively.

[0053] The recharge method preference classification model constructed includes: determining the recharge method preference type of each cloud tenant based on the recharge method preference related data,

[0054] The classification setting R1 is the preference category for agency recharge methods, R2 is the preference category for online banking recharge methods, and R3 is the preference category for offline remittance methods;

[0055] The input indicators of the recharge method preference classification model are obtained, including: the number of times the agent recharge method is used X1, the recharge ratio of the agent recharge method X2, the average recharge time of the deduction method X3, the number of times the online banking recharge method is used X4, the recharge ratio of the online banking recharge method X5, the average recharge time of the online banking recharge method X6, the number of times the offline remittance method is used X7, the recharge ratio of the offline remittance method X8, and the average recharge time of the offline remittance method X9.

[0056] The arrears classification model constructed includes: judging the arrears degree of each cloud tenant through the relevant data of arrears degree;

[0057] Set A1 as heavy arrears, A2 as moderate arrears, and A3 as no arrears;

[0058] The input indicators of the arrears degree classification model are obtained, and the input indicators include: total arrears ratio Y1, total arrears times Y2, total arrears amount Y3, and total arrears duration Y4.

[0059] Step 3: Based on the recharge method preference classification model and the arrears degree classification model, the cloud tenant types are subdivided from the two dimensions of recharge method preference and arrears degree.

[0060] The classification model based on the recharge method preference can be used to segment cloud tenant types based on recharge method preference, including:

[0061] Calculate (X1+X2-X3), (X4+X5-X6), and (X7+X8-X9) respectively to obtain the preference data of each category of cloud tenants.

[0062] Compare the recharge method preference data of each cloud tenant (X1+X2-X3), (X4+X5-X6), and (X7+X8-X9). When (X1+X2-X3) is the largest, it is classified as R1, when (X4+X5-X6) is the largest, it is classified as R2, and when (X7+X8-X9) is the largest, it is classified as R3. When they are equal, they are classified in the priority order of R1>R2>R3.

[0063] When cloud tenant types are segmented according to the arrears degree classification model, the method includes: setting an arrears degree classification measurement value M according to the operation situation;

[0064] Calculate the arrears data Y of each cloud tenant during the last five recharges, the formula is Y=Y1+Y2+Y3+Y4;

[0065] Compare Y with M. When Y>=M, the degree of arrears is A1; when M>Y>0, the degree of arrears is A2; when Y=0, the degree of arrears is A3.

[0066] Step 4: For different types of cloud tenants, formulate different recharge service information for push from four aspects: push group, push cycle, push content and push channel. Specifically, you can set the account change notification, recharge reminder and overdue payment notification of the recharge service information.

[0067] Example 2

[0068] The present invention also provides an information push device based on cloud tenant classification, including a recharge data collection module, a model management module, a cloud tenant classification module and an information push module.

[0069] The recharge data collection module classifies the recharge methods of cloud tenants and obtains relevant data on each cloud tenant's recharge method preference and arrears level;

[0070] The model management module constructs a recharge method preference classification model and a debt degree classification model based on the relevant data obtained;

[0071] The cloud tenant classification module subdivides the cloud tenant types based on the recharge method preference and arrears degree classification models respectively;

[0072] The information push module formulates different recharge service information for push according to the different types of cloud tenants after segmentation, from four aspects: push group, push cycle, push content and push channel.

[0073] As the information interaction and execution process between the modules of the above-mentioned device are based on the same concept as the embodiment of the method of the present invention, the specific contents can be found in the description of the embodiment of the method of the present invention and will not be repeated here.

[0074] Likewise, the benefits of the device of the present invention are:

[0075] According to the recharge method preference and the degree of arrears, users are accurately segmented by establishing a classification model, and then the recharge service information push strategy is configured according to the characteristics of each user group. The push information is more practical, saves push costs, and improves information push efficiency.

[0076] Based on the recharge big data analysis of various user segments, the recharge service information of each user segment can be configured from four dimensions, namely, push group, push cycle, push content and push method, to improve the fit between the information and the user segment and improve the accuracy of the recharge service information push.

[0077] It should be noted that not all steps and modules in the above-mentioned processes and device structures are necessary, and some steps or modules can be ignored according to actual needs. The execution order of each step is not fixed and can be adjusted as needed. The system structure described in the above-mentioned embodiments can be a physical structure or a logical structure, that is, some modules may be implemented by the same physical entity, or some modules may be implemented by multiple physical entities, or some components in multiple independent devices may be implemented together.

[0078] The above-described embodiments are only preferred embodiments for fully illustrating the present invention, and the protection scope of the present invention is not limited thereto. Equivalent substitutions or changes made by those skilled in the art based on the present invention are within the protection scope of the present invention. The protection scope of the present invention shall be subject to the claims.

Claims

1. A method for pushing information based on cloud tenant classification, characterized in that include: Step 1: Classify the recharge methods of cloud tenants and obtain relevant data on each cloud tenant's recharge method preference and arrears level; Step 2: Based on the relevant data obtained in step 1, a classification model of the recharge method preference and a classification model of the arrears degree are constructed respectively; Step 3: Based on the recharge method preference classification model and the arrears degree classification model, the cloud tenant types are segmented from the two dimensions of recharge method preference and arrears degree; Step 4: For different types of cloud tenants, formulate different recharge service information for push based on four aspects: push group, push cycle, push content and push channel.

2. According to claim 1, the information push method based on cloud tenant classification is characterized by: In step 1, the cloud tenant recharge methods are classified, including: the recharge methods are divided into three categories: Recharge method: Cloud tenants do not need to recharge by themselves, and recharge by a third-party agent; Online banking recharge method: Cloud tenants use the recharge platform to complete the recharge through online payment; Offline remittance method: The cloud tenant transfers the recharge amount to the platform's public account, and the platform's professionals complete the recharge of the user's account.

3. The information push method based on cloud tenant classification according to claim 1 is characterized in that The data related to the recharge method preference in step 1 include: the type of recharge method used within a preset time, the recharge amount, and the recharge time. Based on the data related to the recharge method preference, the number of times each type of recharge method is used, the recharge ratio, and the average recharge duration index are calculated respectively; The data related to the degree of arrears include: the bill amount between two recharges within a preset time, the amount of arrears each time, and the duration of arrears for each recharge. Based on the above-mentioned data on the degree of arrears, the total arrears ratio, total number of arrears, total arrears amount, and total arrears duration of cloud tenants are calculated respectively.

4. The information push method based on cloud tenant classification according to claim 1 is characterized in that The recharge method preference classification model constructed in step 2 includes: determining the recharge method preference type of each cloud tenant according to the recharge method preference related data, The classification setting R1 is the preference category for agency recharge methods, R2 is the preference category for online banking recharge methods, and R3 is the preference category for offline remittance methods; The input indicators of the recharge method preference classification model are obtained, including: the number of times the agent recharge method is used X1, the recharge ratio of the agent recharge method X2, the average recharge time of the deduction method X3, the number of times the online banking recharge method is used X4, the recharge ratio of the online banking recharge method X5, the average recharge time of the online banking recharge method X6, the number of times the offline remittance method is used X7, the recharge ratio of the offline remittance method X8, and the average recharge time of the offline remittance method X9.

5. The information push method based on cloud tenant classification according to claim 4 is characterized in that In step 3, the cloud tenant types are segmented according to the recharge method preference classification model based on the recharge method preference, including: Calculate (X1+X2-X3), (X4+X5-X6), and (X7+X8-X9) respectively to obtain the preference data of each category of cloud tenants. Compare the recharge method preference data of each cloud tenant (X1+X2-X3), (X4+X5-X6), and (X7+X8-X9). When (X1+X2-X3) is the largest, it is classified as R1, when (X4+X5-X6) is the largest, it is classified as R2, and when (X7+X8-X9) is the largest, it is classified as R3. When they are equal, they are classified in the priority order of R1>R2>R3.

6. The information push method based on cloud tenant classification according to claim 1 is characterized in that The arrears degree classification model constructed in step 2 includes: judging the arrears degree of each cloud tenant through relevant data of the arrears degree; Set A1 as heavy arrears, A2 as moderate arrears, and A3 as no arrears; The input indicators of the arrears degree classification model are obtained, and the input indicators include: total arrears ratio Y1, total arrears times Y2, total arrears amount Y3, and total arrears duration Y4.

7. The information push method based on cloud tenant classification according to claim 6 is characterized by: In step 3, the cloud tenant types are subdivided according to the arrears degree classification model, including: setting the arrears degree classification measurement value M according to the operation situation; Calculate the arrears data Y of each cloud tenant during the last five recharges, the formula is Y=Y1+Y2+Y3+Y4; Compare Y with M. When Y>=M, the degree of arrears is A1; when M>Y>0, the degree of arrears is A2; when Y=0, the degree of arrears is A3.

8. An information push device based on cloud tenant classification, characterized in that It includes recharge data collection module, model management module, cloud tenant classification module and information push module. The recharge data collection module classifies the recharge methods of cloud tenants and obtains relevant data on each cloud tenant's recharge method preference and arrears level; The model management module constructs a recharge method preference classification model and a debt degree classification model based on the relevant data obtained; The cloud tenant classification module subdivides the cloud tenant types based on the recharge method preference and arrears degree classification models respectively; The information push module formulates different recharge service information for push according to the different types of cloud tenants after segmentation, from four aspects: push group, push cycle, push content and push channel.

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