Service processing method and device, equipment and storage medium thereof

Abstract

The embodiment of the invention belongs to the technical field of artificial intelligence and data processing, is applied to a car insurance renewal scheme making and pushing scene, and relates to a service processing method, device and equipment and a storage medium thereof. Classifying and sorting the multi-dimensional service data to obtain use conditions corresponding to services of all service dimensions; respectively formulating a service pushing scheme in the next service period for all users in the batch of users; and sending the service pushing scheme to a corresponding user within a preset time period. According to the technical scheme, the service pushing scheme corresponding to the target user in the next service period is jointly generated from the perspective of the group users and the single users in combination with the service data in the current service period, the general scheme making requirement based on the group is met, and the individual scheme making requirement based on the single users is also met.

Description

Technical Field

[0001] The present application relates to the field of artificial intelligence and data processing technology, and is applied to the scenario of formulating and pushing auto insurance renewal plans, and in particular to a service processing method, device, equipment and storage medium thereof. Background Art

[0002] In the rapidly developing digital age, customer experience has become a key factor in corporate competition, especially in the financial services sector, such as the auto insurance industry. With the growing demand for personalized services from consumers, the traditional standardized service model can no longer meet the diverse and refined service expectations of modern customers. Especially in the mid-sale stage of auto insurance, that is, during the renewal period of customers, how to provide caring and attractive services is not only related to customer satisfaction, but also directly affects the renewal rate and the long-term profitability of the company.

[0003] Therefore, different insurance companies have adopted the method of adding additional services to improve customer stickiness, for example, recommending or issuing service discount cards. However, traditional customer service distribution strategies during auto insurance sales rely more on experience judgment and market research, which often leads to the service recommendation plan being out of touch with the actual needs of customers and making it impossible to construct reasonable service recommendation plans for customers. Summary of the invention

[0004] The purpose of the embodiments of the present application is to propose a service processing method, device, equipment and storage medium thereof to solve the problem that the existing service recommendation solutions are out of touch with the actual needs of customers and cannot reasonably construct service recommendation solutions for customers.

[0005] In order to solve the above technical problems, the embodiment of the present application provides a service processing method, which adopts the following technical solutions:

[0006] A service processing method comprises the following steps:

[0007] Obtain multi-dimensional service data generated by batch users in the current service cycle;

[0008] Classify and sort the multi-dimensional service data according to the service dimensions and user identifiers to obtain service data corresponding to each user in each service dimension;

[0009] Based on the service data corresponding to each user in each service dimension, statistics of the service conditions corresponding to all service dimensions are performed to obtain the usage conditions corresponding to the services in all service dimensions;

[0010] Based on the usage of services in all service dimensions, respectively, a service push plan for the next service cycle is formulated for all users in the batch of users;

[0011] The service push plans corresponding to all users in the batch of users are sent to the corresponding users within a preset time limit, wherein the preset time limit includes a time limit pre-set according to service requirements.

[0012] Furthermore, the step of classifying and arranging the multi-dimensional service data according to the service dimensions and user identifiers to obtain the service data corresponding to each user in each service dimension specifically includes:

[0013] Preliminarily classifying and arranging the multi-dimensional service data according to the service dimension to obtain a preliminary classification and arranging result based on the service dimension;

[0014] Perform secondary classification and sorting on the preliminary classification and sorting results according to the user identifier to obtain secondary classification and sorting results based on the service dimension and the user identifier;

[0015] The secondary classification and sorting results are set as the service data corresponding to each user in each service dimension.

[0016] Furthermore, the step of preliminarily classifying and arranging the multi-dimensional service data according to the service dimension to obtain a preliminary classification and arranging result based on the service dimension specifically includes:

[0017] Obtain the car wash service data generated by batch users in the current car insurance underwriting cycle, and cluster them into a preset first cluster to obtain the preliminary classification and sorting results corresponding to the car wash service dimension;

[0018] Obtain the refueling service data generated by batch users in the current auto insurance underwriting cycle, and cluster them into the preset second cluster, to obtain the preliminary classification and sorting results corresponding to the refueling service dimension;

[0019] Obtain maintenance service data generated by batch users during the current auto insurance underwriting period, and cluster them into a preset third cluster to obtain a preliminary classification and sorting result corresponding to the maintenance service dimension;

[0020] Obtaining the car beauty service data generated by batch users in the current car insurance underwriting cycle, and clustering them into the preset fourth cluster, to obtain the preliminary classification and sorting results corresponding to the car beauty service dimension;

[0021] Acquire the vehicle decoration accessories purchase data generated by batch users in the current vehicle insurance underwriting period, and cluster them into the preset fifth cluster, so as to obtain the preliminary classification and sorting results corresponding to the vehicle decoration accessories purchase dimension;

[0022] The vehicle rescue service data generated by batch users in the current vehicle insurance underwriting cycle is obtained, and clustered into the preset sixth cluster to obtain the preliminary classification and sorting results corresponding to the vehicle rescue service dimension.

[0023] Furthermore, the step of performing secondary classification and sorting on the preliminary classification and sorting results according to the user identifier to obtain the secondary classification and sorting results based on the service dimension and the user identifier specifically includes:

[0024] Perform secondary classification and sorting of the preliminary classification and sorting results corresponding to the car wash service dimension according to the user identifier to obtain the car wash service data of each user in the current car insurance underwriting period;

[0025] Perform secondary classification and sorting of the preliminary classification and sorting results corresponding to the refueling service dimension according to the user identifier to obtain the refueling service data of each user in the current motor insurance underwriting period;

[0026] Perform secondary classification and sorting of the preliminary classification and sorting results corresponding to the maintenance service dimension according to the user identifier to obtain the maintenance service data of each user in the current motor insurance underwriting period;

[0027] Perform secondary classification and sorting of the preliminary classification and sorting results corresponding to the automobile beauty service dimension according to the user identifier to obtain automobile beauty service data of each user in the current automobile insurance underwriting period;

[0028] Perform secondary classification and sorting of the preliminary classification and sorting results corresponding to the vehicle decoration accessories purchase dimension according to the user identifier to obtain the vehicle decoration accessories purchase data of each user in the current vehicle insurance underwriting period;

[0029] The preliminary classification and sorting results corresponding to the vehicle rescue service dimension are secondary classified and sorted according to the user identification to obtain the vehicle rescue service data of each user in the current motor insurance underwriting period.

[0030] Furthermore, the step of performing service situation statistics corresponding to all service dimensions based on the service data corresponding to each user in each service dimension, and obtaining the usage situation corresponding to the services in all service dimensions, specifically includes:

[0031] According to the service data corresponding to each user in each service dimension, the number of times each user uses the service in each service dimension is counted;

[0032] Based on the service usage times of each user in each service dimension, the total service usage times of the same user in all service dimensions are calculated by summing them up;

[0033] Based on the service usage times of each user in each service dimension and the total service usage times of the same user in all service dimensions, the service preference weights corresponding to the same user in all service dimensions are calculated by using a ratio method;

[0034] Based on the number of service usages corresponding to each user in each service dimension, the average number of service usages corresponding to all users in different service dimensions is calculated by cumulative averaging.

[0035] Further, after executing the step of calculating the average number of service usages corresponding to different service dimensions by all users by using a cumulative average method based on the number of service usages corresponding to each user in each service dimension, the method further includes:

[0036] Based on the service usage times of each user in each service dimension and the average service usage times of all users in different service dimensions, a comparison method is used to determine whether the service usage times of each user in each service dimension exceeds the average service usage times of the corresponding service dimension;

[0037] Combined with the judgment result, the service usage times corresponding to each user in each service dimension are distinguished and marked using a preset distinction strategy, wherein the preset distinction strategy includes:

[0038] If the number of service uses corresponding to the target service dimension by the current user exceeds the average number of service uses in the target service dimension, the number of service uses corresponding to the target service dimension by the current user is marked with a first distinguishing color; if the number of service uses corresponding to the target service dimension by the current user does not exceed the average number of service uses in the target service dimension, the number of service uses corresponding to the target service dimension by the current user is marked with a second distinguishing color, or,

[0039] If the number of service uses corresponding to the target service dimension by the current user exceeds the average number of service uses of the target service dimension, a first distinguishing tag is used to distinguish and mark the number of service uses corresponding to the target service dimension by the current user; if the number of service uses corresponding to the target service dimension by the current user does not exceed the average number of service uses of the target service dimension, a second distinguishing tag is used to distinguish and mark the number of service uses corresponding to the target service dimension by the current user.

[0040] Furthermore, before executing the step of formulating service push plans for the next service cycle for all users in the batch of users based on the usage conditions corresponding to the services in all service dimensions, the method further includes:

[0041] According to the preset service nature classification form, the mandatory service dimension and the non-mandatory service dimension are identified from all service dimensions, wherein the mandatory service dimension includes vehicle rescue service, and the non-mandatory service dimension includes car washing service, refueling service, maintenance service, car beauty service, and purchase of vehicle decoration accessories;

[0042] The step of formulating service push plans for the next service cycle for all users in the batch of users based on the usage conditions of the services in all service dimensions includes:

[0043] According to the usage of services in all service dimensions, identifying whether the number of service usages corresponding to the mandatory service dimension by the same user exceeds the average number of service usages in the mandatory service dimension;

[0044] If the number of service usages corresponding to the mandatory service dimension of the current user exceeds the average number of service usages of the mandatory service dimension, then the target proportion of service usages is increased on the basis of the preset service planning number to obtain the total number of service plannings of the mandatory service dimension;

[0045] If the number of service usages corresponding to the mandatory service dimension of the current user does not exceed the average number of service usages of the mandatory service dimension, the preset service planning number is set as the total number of service plannings of the mandatory service dimension;

[0046] According to the usage of services in all service dimensions, the service preference weights corresponding to all non-mandatory service dimensions of the same user are identified;

[0047] If the service preference weights corresponding to all non-mandatory service dimensions of the current user are not zero, then the service planning times corresponding to all non-mandatory service dimensions in the next service cycle are calculated by multiplication based on the service preference weights and the total number of service recommendations preset in the next service cycle;

[0048] If the current user has a service preference weight of zero corresponding to at least one non-mandatory service dimension, then all non-mandatory service dimensions with a service preference weight of zero are identified, and the number of service plans for all non-mandatory service dimensions with a service preference weight of zero in the next service cycle is set to zero, and all non-mandatory service dimensions with a service preference weight of non-zero are identified, and the number of service plans corresponding to all non-mandatory service dimensions with a service preference weight of non-zero in the next service cycle are calculated by multiplication based on the service preference weight and the total number of service recommendations preset in the next service cycle;

[0049] According to the total number of service plans corresponding to the current user in the mandatory service dimension and the number of service plans corresponding to the current user in all non-mandatory service dimensions, a service push plan for the next service cycle is formulated for the current user.

[0050] In order to solve the above technical problems, the embodiment of the present application also provides a service processing device, which adopts the following technical solution:

[0051] A service processing device, comprising:

[0052] The service data acquisition module is used to acquire the multi-dimensional service data generated by batch users in the current service cycle;

[0053] A service data classification module, used to classify and sort the multi-dimensional service data according to the service dimensions and user identifiers, and obtain the service data corresponding to each user in each service dimension;

[0054] A service usage statistics module is used to perform service statistics corresponding to all service dimensions based on the service data corresponding to each user in each service dimension, and obtain the usage corresponding to the services in all service dimensions;

[0055] A service push plan formulation module, used to formulate service push plans for the next service cycle for all users in the batch of users based on the usage of services in all service dimensions;

[0056] The service push plan sending module is used to send the service push plans corresponding to all users in the batch of users to the corresponding users within a preset time limit, wherein the preset time limit includes a time limit pre-set according to service requirements.

[0057] In order to solve the above technical problems, the embodiment of the present application further provides a computer device, which adopts the following technical solution:

[0058] A computer device includes a memory and a processor, wherein the memory stores computer-readable instructions, and the processor implements the steps of the service processing method described above when executing the computer-readable instructions.

[0059] In order to solve the above technical problems, the embodiment of the present application further provides a computer-readable storage medium, which adopts the following technical solution:

[0060] A computer-readable storage medium stores computer-readable instructions, which, when executed by a processor, implement the steps of the service processing method described above.

[0061] Compared with the prior art, the embodiments of the present application have the following beneficial effects:

[0062] The service processing method described in the embodiment of the present application obtains the multi-dimensional service data generated by batch users in the current service cycle; classifies and organizes the multi-dimensional service data to obtain the usage of services corresponding to all service dimensions; and formulates a service push plan for the next service cycle for all users in the batch of users; and sends the service push plan to the corresponding users within a preset time limit. It realizes the combination of service data in this service cycle, and jointly generates the service push plan corresponding to the target user in the next service cycle from the perspective of group users and individual users, which not only meets the requirements for formulating common plans based on groups, but also meets the requirements for formulating personalized plans based on individual users. BRIEF DESCRIPTION OF THE DRAWINGS

[0063] In order to more clearly illustrate the scheme in the present application, a brief introduction is given below to the drawings required for use in the description of the embodiments of the present application. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0064] Figure 1 is an exemplary system architecture diagram to which the present application may be applied;

[0065] Figure 2 is a flow chart of an embodiment of a service processing method according to the present application;

[0066] Figure 3 yes Figure 2 A flowchart of a specific embodiment of step 202 is shown;

[0067] Figure 4 yes Figure 2 A flowchart of a specific embodiment of step 203 is shown;

[0068] Figure 5 is a structural diagram of an embodiment of a service processing device according to the present application;

[0069] Figure 6 It is a structural diagram of an embodiment of a computer device according to the present application. DETAILED DESCRIPTION

[0070] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by technicians in the technical field of the present application; the terms used in the specification of the application herein are only for the purpose of describing specific embodiments and are not intended to limit the present application; the terms "including" and "having" and any variations thereof in the specification and claims of the present application and the above-mentioned drawings are intended to cover non-exclusive inclusions. The terms "first", "second", etc. in the specification and claims of the present application or the above-mentioned drawings are used to distinguish different objects, not to describe a specific order.

[0071] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0072] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the accompanying drawings.

[0073] like Figure 1 As shown, the system architecture 100 may include a terminal device 101, a network 102 and a server 103. The terminal device 101 may be a laptop 1011, a tablet computer 1012 or a mobile phone 1013. The network 102 is used to provide a medium for a communication link between the terminal device 101 and the server 103. The network 102 may include various connection types, such as wired, wireless communication links or optical fiber cables.

[0074] The user can use the terminal device 101 to interact with the server 103 through the network 102 to receive or send messages, etc. Various communication client applications can be installed on the terminal device 101, such as web browser applications, shopping applications, search applications, instant messaging tools, email clients, social platform software, etc.

[0075] The terminal device 101 can be any electronic device with a display screen and supporting web browsing. In addition to a laptop computer 1011, a tablet computer 1012 or a mobile phone 1013, the terminal device 101 can also be an e-book reader, an MP3 player (Moving Picture Experts Group Audio Layer III), an MP4 (Moving Picture Experts Group Audio Layer IV), a laptop computer, a desktop computer, etc.

[0076] The server 103 may be a server that provides various services, such as a background server that provides support for a web page displayed on the terminal device 101 .

[0077] It should be noted that the service processing method provided in the embodiment of the present application is generally executed by a server, and accordingly, the service processing device is generally set in the server.

[0078] It should be understood that Figure 1 The number of terminal devices, networks and servers in the embodiment is only for illustration. Any number of terminal devices, networks and servers may be provided according to implementation requirements.

[0079] Continue to refer Figure 2 , shows a flow chart of an embodiment of a service processing method according to the present application. The service processing method comprises the following steps:

[0080] Step 201, obtaining multi-dimensional service data generated by batch users in the current service cycle.

[0081] In this embodiment, the current service cycle includes the current motor insurance underwriting cycle, and the step of obtaining the multi-dimensional service data generated by batch users in the current service cycle specifically includes: obtaining the multi-dimensional service data generated by batch users in the current motor insurance underwriting cycle, wherein the multi-dimensional service data includes car wash service data, refueling service data, maintenance service data, car beauty service data, vehicle decoration accessories purchase data and vehicle rescue service data.

[0082] By acquiring the multi-dimensional service data generated by batch users in the current service cycle, it is possible to formulate and adjust the service plans for the multi-dimensional services involved in the next service cycle for the target users in combination with the multi-dimensional service data generated in the current service cycle. Especially in the auto insurance renewal scenario, when the auto insurance is renewed, in order to increase the purchasing intention of the auto insurance renewal users, it is often necessary to formulate certain vehicle service plans when designing the renewal plan. It is possible to formulate and adjust the service plans for the multi-dimensional services involved in the next auto insurance underwriting cycle for the target users in combination with the multi-dimensional service data generated in the current auto insurance underwriting cycle.

[0083] Step 202: classify and sort the multi-dimensional service data according to the service dimensions and user identifiers to obtain the service data corresponding to each user in each service dimension.

[0084] By classifying and arranging the multi-dimensional service data corresponding to the batch of users, the service data corresponding to each user in each service dimension is obtained, so as to jointly formulate and adjust service plans from both group and individual perspectives.

[0085] Step 203, based on the service data corresponding to each user in each service dimension, statistics of the service conditions corresponding to all service dimensions are performed to obtain the usage conditions corresponding to the services in all service dimensions.

[0086] By counting the service conditions corresponding to all service dimensions, we can obtain the usage conditions of the services in all service dimensions, and convert the service data into numerical values ​​for the purpose of computer processing and reference for subsequent service plan formulation.

[0087] Step 204: based on the usage of services in all service dimensions, respectively, formulate service push plans for the next service cycle for all users in the batch of users.

[0088] Step 205: Send the service push plans corresponding to all users in the batch of users to the corresponding users within a preset time limit, wherein the preset time limit includes a time limit pre-set according to service requirements.

[0089] Specifically, the preset time limit is, for example, the time limit between the current time and the start time of the next motor insurance underwriting cycle when renewing motor insurance.

[0090] Through the usage of services in all service dimensions, service push plans for the next service cycle are formulated for all users in the batch of users, and the service push plans corresponding to all users in the batch of users are sent to the corresponding users within a preset time limit, thereby combining the service data in this service cycle and jointly generating the service push plans corresponding to the target users in the next service cycle from the perspectives of group users and individual users, which not only meets the requirements for formulating common plans based on groups, but also meets the requirements for formulating personalized plans based on individuals. Especially in the scenario of auto insurance renewal, it is possible to formulate and adjust service plans for the multi-dimensional services involved in the next auto insurance underwriting cycle for the target users in combination with the multi-dimensional service data generated in the current auto insurance underwriting cycle.

[0091] In this embodiment, the multi-dimensional service data generated by batch users in the current service cycle is obtained; the multi-dimensional service data is classified and sorted to obtain the usage of services in all service dimensions; and a service push plan for the next service cycle is formulated for all users in the batch of users; and the service push plan is sent to the corresponding users within a preset time limit. The service data in this service cycle is combined to jointly generate the service push plan corresponding to the target user in the next service cycle from the perspective of group users and individual users, which not only meets the requirements for formulating common plans based on groups, but also meets the requirements for formulating personalized plans based on individual users.

[0092] Continue to refer Figure 3 , in some optional implementations, Figure 3 yes Figure 2 The flowchart of a specific embodiment of step 202 shown includes the following steps:

[0093] Step 301, preliminarily classifying and arranging the multi-dimensional service data according to the service dimension to obtain a preliminary classification and arranging result based on the service dimension;

[0094] Step 302, performing secondary classification and sorting on the preliminary classification and sorting results according to the user identifier, to obtain secondary classification and sorting results based on the service dimension and the user identifier;

[0095] Step 303: Set the secondary classification and sorting results as the service data corresponding to each user in each service dimension.

[0096] By classifying and arranging the multi-dimensional service data corresponding to the batch of users, the service data corresponding to each user in each service dimension is obtained, so as to formulate and adjust the service plan from an individual perspective.

[0097] In this embodiment, the step of performing preliminary classification and sorting of the multi-dimensional service data according to the service dimension to obtain preliminary classification and sorting results based on the service dimension specifically includes: obtaining the car wash service data generated by the batch of users in the current auto insurance underwriting cycle, and clustering them into a preset first clustering cluster, to obtain the preliminary classification and sorting results corresponding to the car wash service dimension; obtaining the refueling service data generated by the batch of users in the current auto insurance underwriting cycle, and clustering them into a preset second clustering cluster, to obtain the preliminary classification and sorting results corresponding to the refueling service dimension; obtaining the maintenance service data generated by the batch of users in the current auto insurance underwriting cycle, and clustering them into a preset third clustering cluster. , and obtain the preliminary classification and sorting results corresponding to the maintenance service dimension; obtain the car beauty service data generated by batch users in the current car insurance underwriting period, and cluster them into the preset fourth cluster, and obtain the preliminary classification and sorting results corresponding to the car beauty service dimension; obtain the car decoration accessories purchase data generated by batch users in the current car insurance underwriting period, and cluster them into the preset fifth cluster, and obtain the preliminary classification and sorting results corresponding to the car decoration accessories purchase dimension; obtain the vehicle rescue service data generated by batch users in the current car insurance underwriting period, and cluster them into the preset sixth cluster, and obtain the preliminary classification and sorting results corresponding to the vehicle rescue service dimension.

[0098] In essence, the above steps can be understood as sorting out the service data corresponding to different service dimensions, for example: clustering the car wash service data into the preset first clustering cluster, and obtaining all the car wash service data generated by the batch users in the current auto insurance underwriting period. By analogy, clustering the refueling service data into the preset second clustering cluster, and obtaining all the refueling service data generated by the batch users in the current auto insurance underwriting period; clustering the maintenance service data into the preset third clustering cluster, and obtaining all the maintenance service data generated by the batch users in the current auto insurance underwriting period; clustering the car beauty service data into the preset fourth clustering cluster, and obtaining all the car beauty service data generated by the batch users in the current auto insurance underwriting period; clustering the car decoration accessories purchase data into the preset fifth clustering cluster, and obtaining all the car decoration accessories purchase data generated by the batch users in the current auto insurance underwriting period; and clustering the vehicle rescue service data into the preset sixth clustering cluster, and obtaining all the vehicle rescue service data generated by the batch users in the current auto insurance underwriting period. Through the above preliminary classification and organization, secondary classification and organization can be carried out on this basis to obtain the service data corresponding to each user in each service dimension.

[0099] In this embodiment, the step of performing secondary classification and sorting on the preliminary classification and sorting results according to the user identification to obtain the secondary classification and sorting results based on the service dimension and the user identification specifically includes: performing secondary classification and sorting on the preliminary classification and sorting results corresponding to the car wash service dimension according to the user identification to obtain the car wash service data of each user in the current auto insurance underwriting cycle; performing secondary classification and sorting on the preliminary classification and sorting results corresponding to the refueling service dimension according to the user identification to obtain the refueling service data of each user in the current auto insurance underwriting cycle; performing secondary classification and sorting on the preliminary classification and sorting results corresponding to the maintenance service dimension according to the user identification , obtain the maintenance service data of each user within the current auto insurance underwriting period; perform secondary classification and sorting on the preliminary classification and sorting results corresponding to the automobile beauty service dimension according to the user identification, and obtain the automobile beauty service data of each user within the current auto insurance underwriting period; perform secondary classification and sorting on the preliminary classification and sorting results corresponding to the vehicle decoration accessories purchase dimension according to the user identification, and obtain the vehicle decoration accessories purchase data of each user within the current auto insurance underwriting period; perform secondary classification and sorting on the preliminary classification and sorting results corresponding to the vehicle rescue service dimension according to the user identification, and obtain the vehicle rescue service data of each user within the current auto insurance underwriting period.

[0100] In essence, the above steps are secondary classification and sorting based on the preliminary classification and sorting, and the car wash service data, refueling service data, maintenance service data, car beauty service data, vehicle decoration and accessories purchase data and vehicle rescue service data of each user in the current auto insurance underwriting period are obtained, wherein the service data includes the number of services, the price of each service, discounts, service time, etc. Correspondingly, when the service dimension is the vehicle decoration and accessories purchase data, the corresponding service data is the number of purchases, the price of each purchase, discounts, purchase time, etc. By classifying and sorting the multi-dimensional service data corresponding to the batch users, the service data corresponding to each user in each service dimension is obtained, so as to formulate and adjust the service plan from an individual perspective.

[0101] Continue to refer Figure 4 , in some optional implementations, Figure 4 yes Figure 2 The flowchart of a specific embodiment of step 203 shown includes the following steps:

[0102] Step 401, according to the service data corresponding to each user in each service dimension, the service usage times corresponding to each user in each service dimension are counted;

[0103] Specifically, assuming that the batch of users includes 5 users, the user identifiers are user1, user2, user3, user4 and user5, and the service dimensions include six service dimensions: car wash service data, refueling service data, maintenance service data, car beauty service data, vehicle decoration accessories purchase data and vehicle rescue service data. The service times of the six service dimensions corresponding to user1 are {50, 30, 5, 2, 10, 1}, the service times of the six service dimensions corresponding to user2 are {20, 20, 4, 2, 3, 0}, the service times of the six service dimensions corresponding to user3 are {35, 10, 4, 1, 8, 1}, the service times of the six service dimensions corresponding to user4 are {40, 20, 2, 4, 5, 1} and the service times of the six service dimensions corresponding to user5 are {15, 10, 1, 0, 3, 0}.

[0104] Step 402, based on the service usage times of each user in each service dimension, the total service usage times of the same user in all service dimensions are calculated by summing up.

[0105] Continuing with the above embodiment, step 402 can be understood as:

[0106] Get the total number of times user1, user2, user3, user4, and user5 use the car wash service data, that is, 50+20+35+40+15=160;

[0107] Get the total number of times that users user1, user2, user3, user4, and user5 use the refueling service data, that is, 30+20+10+20+10=90;

[0108] Get the total number of service usages corresponding to users user1, user2, user3, user4, and user5 in the maintenance service data, that is, 5+4+4+2+1=16;

[0109] Get the total number of times that users user1, user2, user3, user4, and user5 use the corresponding services in the car beauty service data, that is, 2+2+1+4+0=9;

[0110] Obtain the total number of purchases and uses corresponding to the vehicle decoration accessories purchase data of users user1, user2, user3, user4, and user5, that is, 10+3+8+5+3=29;

[0111] The total number of service usages corresponding to users user1, user2, user3, user4, and user5 in the vehicle rescue service data is obtained, that is, 1+0+1+1+0=3.

[0112] Step 403, based on the service usage times of each user in each service dimension and the total service usage times of the same user in all service dimensions, the service preference weights corresponding to the same user in all service dimensions are calculated by using a ratio method;

[0113] Continuing with the above embodiment, step 403 can be understood as:

[0114] According to the service times of user 1 in these six service dimensions {50, 30, 5, 2, 10, 1}, the service preference weights corresponding to user 1 in the six service dimensions of car wash service data, refueling service data, maintenance service data, car beauty service data, car decoration accessories purchase data and vehicle rescue service data are calculated respectively. The specific calculation method is: Among them, A is 50, 30, 5, 2, 10, and 1 respectively, and B is the sum of 50+30+5+2+10+1. Similarly, the service preference weights of users user2, user3, user4, and user5 in the six service dimensions of car wash service data, refueling service data, maintenance service data, car beauty service data, vehicle decoration accessories purchase data, and vehicle rescue service data can also be calculated.

[0115] Step 404, based on the service usage times of each user in each service dimension, the average service usage times of all users in different service dimensions are calculated by cumulative averaging.

[0116] Continuing with the above embodiment, step 404 can be understood as:

[0117] After obtaining the total number of service usages corresponding to the car wash service data of users user1, user2, user3, user4 and user5, that is, 50+20+35+40+15=160, the average value is calculated according to the number of users, that is, 160 divided by 5 equals 32, and 32 is used as the average number of service usages corresponding to the car wash service data of all users; similarly, the average number of service usages corresponding to the refueling service data, maintenance service data, car beauty service data, vehicle decoration accessories purchase data and vehicle rescue service data of all users can also be calculated.

[0118] By counting the service conditions corresponding to all service dimensions, we can obtain the usage conditions of the services in all service dimensions, and convert the service data into numerical values ​​for the purpose of computer processing and reference for subsequent service plan formulation.

[0119] In this embodiment, after executing the step of calculating the average number of service uses corresponding to all users in different service dimensions by cumulative averaging based on the number of service uses corresponding to each user in each service dimension, the method further includes: judging whether the number of service uses corresponding to each user in each service dimension exceeds the average number of service uses of the corresponding service dimension by comparing the number of service uses corresponding to each user in each service dimension and the average number of service uses corresponding to all users in different service dimensions; and combining the judgment result, using a preset distinction strategy to perform distinction marking processing on the number of service uses corresponding to each user in each service dimension.

[0120] Among them, the preset distinction strategy includes: if the number of service uses corresponding to the target service dimension of the current user exceeds the average number of service uses of the target service dimension, the first distinction color is used to distinguish and mark the number of service uses corresponding to the target service dimension of the current user; if the number of service uses corresponding to the target service dimension of the current user does not exceed the average number of service uses of the target service dimension, the second distinction color is used to distinguish and mark the number of service uses corresponding to the target service dimension of the current user; or, if the number of service uses corresponding to the target service dimension of the current user exceeds the average number of service uses of the target service dimension, the first distinction label is used to distinguish and mark the number of service uses corresponding to the target service dimension of the current user; if the number of service uses corresponding to the target service dimension of the current user does not exceed the average number of service uses of the target service dimension, the second distinction label is used to distinguish and mark the number of service uses corresponding to the target service dimension of the current user.

[0121] By adopting a comparative method, it is determined whether the number of service uses corresponding to each user in each service dimension exceeds the average number of service uses in the corresponding service dimension. Combined with the judgment result, the preset distinction strategy is used to distinguish and mark the number of service uses corresponding to each user in each service dimension. In this way, users who use the service more often and users who use the service less often under the same service dimension can be distinguished, so as to facilitate the subsequent formulation and adjustment of service plans based on the individual usage times.

[0122] In this embodiment, before executing the step of formulating service push plans for the next service cycle for all users in the batch of users based on the usage corresponding to the services of all service dimensions, the method also includes: dividing the form according to the preset service nature, identifying mandatory service dimensions and non-mandatory service dimensions from all service dimensions, wherein the mandatory service dimensions include vehicle rescue services, and the non-mandatory service dimensions include car wash services, refueling services, maintenance services, car beauty services, and purchase of vehicle decorative accessories.

[0123] In essence, it can be understood that the mandatory service dimension refers to the mandatory additional services when underwriting auto insurance, such as: vehicle rescue services, and another example is the auto insurance claims service, vehicle and vessel tax payment and other service dimensions. The non-mandatory service dimension can be understood as the additional services established by insurance companies in order to increase user recognition of the company's business, such as: the car wash service, that is, if the company underwrites auto insurance, 40 free car washes will be provided within the one-year underwriting period, and other such service activities.

[0124] In this embodiment, the step of formulating service push plans for the next service cycle for all users in the batch of users based on the usage conditions corresponding to the services in all service dimensions, that is, step 204, specifically includes:

[0125] According to the usage of services in all service dimensions, identifying whether the number of service usages corresponding to the mandatory service dimension by the same user exceeds the average number of service usages in the mandatory service dimension;

[0126] If the number of service usages corresponding to the mandatory service dimension of the current user exceeds the average number of service usages of the mandatory service dimension, then the target proportion of service usages is increased on the basis of the preset service planning number to obtain the total number of service plannings of the mandatory service dimension;

[0127] If the number of service usages corresponding to the mandatory service dimension of the current user does not exceed the average number of service usages of the mandatory service dimension, the preset service planning number is set as the total number of service plannings of the mandatory service dimension;

[0128] According to the usage of services in all service dimensions, the service preference weights corresponding to all non-mandatory service dimensions of the same user are identified;

[0129] If the service preference weights corresponding to all non-mandatory service dimensions of the current user are not zero, then the service planning times corresponding to all non-mandatory service dimensions in the next service cycle are calculated by multiplication based on the service preference weights and the total number of service recommendations preset in the next service cycle;

[0130] If the current user has a service preference weight of zero corresponding to at least one non-mandatory service dimension, then all non-mandatory service dimensions with a service preference weight of zero are identified, and the number of service plans for all non-mandatory service dimensions with a service preference weight of zero in the next service cycle is set to zero, and all non-mandatory service dimensions with a service preference weight of non-zero are identified, and the number of service plans corresponding to all non-mandatory service dimensions with a service preference weight of non-zero in the next service cycle are calculated by multiplication based on the service preference weight and the total number of service recommendations preset in the next service cycle;

[0131] According to the total number of service plans corresponding to the current user in the mandatory service dimension and the number of service plans corresponding to the current user in all non-mandatory service dimensions, a service push plan for the next service cycle is formulated for the current user.

[0132] Through the usage conditions of services in all service dimensions, service push plans for the next service cycle are formulated for all users in the batch of users, and the service push plans corresponding to all users in the batch of users are sent to corresponding users within a preset time limit. This realizes the combination of service data in this service cycle, and the joint generation of service push plans corresponding to target users in the next service cycle from the perspectives of group users and individual users, which not only meets the requirements for formulating common plans based on groups, but also meets the requirements for formulating personalized plans based on individuals.

[0133] This application obtains the multi-dimensional service data generated by batch users in the current service cycle; classifies and organizes the multi-dimensional service data to obtain the usage of services in all service dimensions; and formulates service push plans for the next service cycle for all users in the batch; and sends the service push plans to the corresponding users within a preset time limit. It realizes the combination of service data in this service cycle, and jointly generates the service push plan corresponding to the target user in the next service cycle from the perspective of group users and individual users, which not only meets the requirements for formulating common plans based on groups, but also meets the requirements for formulating personalized plans based on individual users.

[0134] The embodiments of the present application can acquire and process relevant data based on artificial intelligence technology. Among them, artificial intelligence (AI) is the theory, method, technology and application system that uses digital computers or machines controlled by digital computers to simulate, extend and expand human intelligence, perceive the environment, acquire knowledge and use knowledge to obtain the best results.

[0135] AI basic technologies generally include sensors, dedicated AI chips, cloud computing, distributed storage, big data processing technology, operation / interaction systems, mechatronics, etc. AI software technologies mainly include computer vision technology, robotics technology, biometrics technology, speech processing technology, natural language processing technology, and machine learning / deep learning.

[0136] In the embodiment of the present application, the multi-dimensional service data generated by batch users in the current service cycle is obtained; the multi-dimensional service data is classified and sorted to obtain the usage of services in all service dimensions; and a service push plan for the next service cycle is formulated for all users in the batch of users; and the service push plan is sent to the corresponding user within a preset time limit. The service data in this service cycle is combined to jointly generate the service push plan corresponding to the target user in the next service cycle from the perspective of group users and individual users, which not only meets the requirements for formulating common plans based on groups, but also meets the requirements for formulating personalized plans based on individual users.

[0137] Further references Figure 5 , as a response to the above Figure 2 In order to realize the method shown in the figure, the present application provides an embodiment of a service processing device, and the device embodiment is Figure 2 Corresponding to the method embodiment shown, the device can be specifically applied to various electronic devices.

[0138] like Figure 5 As shown, the service processing device 500 described in this embodiment includes: a service data acquisition module 501, a service data classification module 502, a service usage statistics module 503, a service push plan formulation module 504 and a service push plan sending module 505. Among them:

[0139] The service data acquisition module 501 is used to acquire the multi-dimensional service data generated by batch users in the current service cycle;

[0140] A service data classification module 502 is used to classify and sort the multi-dimensional service data according to the service dimensions and user identifiers, and obtain the service data corresponding to each user in each service dimension;

[0141] The service usage statistics module 503 is used to perform service statistics corresponding to all service dimensions based on the service data corresponding to each user in each service dimension, and obtain the usage corresponding to the services in all service dimensions;

[0142] A service push plan formulation module 504 is used to formulate service push plans for the next service cycle for all users in the batch of users based on the usage of the services in all service dimensions;

[0143] The service push plan sending module 505 is used to send the service push plans corresponding to all users in the batch of users to the corresponding users within a preset time limit, wherein the preset time limit includes a time limit pre-set according to service requirements.

[0144] This application obtains the multi-dimensional service data generated by batch users in the current service cycle; classifies and organizes the multi-dimensional service data to obtain the usage of services in all service dimensions; and formulates service push plans for the next service cycle for all users in the batch; and sends the service push plans to the corresponding users within a preset time limit. It realizes the combination of service data in this service cycle, and jointly generates the service push plan corresponding to the target user in the next service cycle from the perspective of group users and individual users, which not only meets the requirements for formulating common plans based on groups, but also meets the requirements for formulating personalized plans based on individual users.

[0145] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through computer-readable instructions, and the computer-readable instructions can be stored in a computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, the aforementioned storage medium can be a non-volatile storage medium such as a disk, an optical disk, a read-only memory (ROM), or a random access memory (RAM).

[0146] It should be understood that, although the steps in the flowchart of the accompanying drawings are displayed in sequence as indicated by the arrows, these steps are not necessarily executed in sequence in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least a part of the steps in the flowchart of the accompanying drawings may include multiple sub-steps or multiple stages, and these sub-steps or stages are not necessarily executed at the same time, but can be executed at different times, and their execution order is not necessarily sequential, but can be executed in turn or alternately with other steps or at least a part of the sub-steps or stages of other steps.

[0147] To solve the above technical problems, the present application also provides a computer device. Figure 6 , Figure 6 This is a basic structural block diagram of the computer device in this embodiment.

[0148] The computer device 6 includes a memory 6a, a processor 6b, and a network interface 6c which are interconnected through a system bus. It should be noted that: Figure 6 Only a computer device 6 having a component memory 6a, a processor 6b, and a network interface 6c is shown, but it should be understood that it is not required to implement all the components shown, and more or fewer components may be implemented instead. Among them, those skilled in the art can understand that the computer device here is a device that can automatically perform numerical calculations and / or information processing according to pre-set or stored instructions, and its hardware includes but is not limited to a microprocessor, an application specific integrated circuit (ASIC), a field programmable gate array (FPGA), a digital processor (DSP), an embedded device, etc.

[0149] The computer device may be a computing device such as a desktop computer, a notebook, a PDA, a cloud server, etc. The computer device may interact with a user through a keyboard, a mouse, a remote controller, a touch pad, or a voice control device.

[0150] The memory 6a includes at least one type of readable storage medium, and the readable storage medium includes flash memory, hard disk, multimedia card, card-type memory (for example, SD or DX memory, etc.), random access memory (RAM), static random access memory (SRAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), programmable read-only memory (PROM), magnetic memory, magnetic disk, optical disk, etc. In some embodiments, the memory 6a can be an internal storage unit of the computer device 6, such as a hard disk or memory of the computer device 6. In other embodiments, the memory 6a can also be an external storage device of the computer device 6, such as a plug-in hard disk equipped on the computer device 6, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (FlashCard), etc. Of course, the memory 6a can also include both the internal storage unit of the computer device 6 and its external storage device. In this embodiment, the memory 6a is generally used to store the operating system and various application software installed on the computer device 6, such as a computer-readable instruction of a service processing method, etc. In addition, the memory 6a can also be used to temporarily store various types of data that have been output or are to be output.

[0151] The processor 6b may be a central processing unit (CPU), a controller, a microcontroller, a microprocessor, or other data processing chips in some embodiments. The processor 6b is generally used to control the overall operation of the computer device 6. In this embodiment, the processor 6b is used to run the computer-readable instructions stored in the memory 6a or process data, such as computer-readable instructions for running the service processing method.

[0152] The network interface 6c may include a wireless network interface or a wired network interface. The network interface 6c is generally used to establish a communication connection between the computer device 6 and other electronic devices.

[0153] The computer device proposed in this embodiment belongs to the field of artificial intelligence and data processing technology, and is applied to the scenario of formulating and pushing auto insurance renewal plans. This application obtains the multi-dimensional service data generated by batch users in the current service cycle; classifies and organizes the multi-dimensional service data to obtain the usage conditions corresponding to the services of all service dimensions; and formulates a service push plan for the next service cycle for all users in the batch of users; and sends the service push plan to the corresponding users within a preset time limit. It realizes the combination of service data in this service cycle, and jointly generates the service push plan corresponding to the target user in the next service cycle from the perspective of group users and individual users, which not only meets the requirements for formulating common plans based on groups, but also meets the requirements for formulating personalized plans based on individuals.

[0154] The present application also provides another implementation, namely, providing a computer-readable storage medium, wherein the computer-readable storage medium stores computer-readable instructions, and the computer-readable instructions can be executed by a processor to enable the processor to perform the steps of the service processing method as described above.

[0155] The computer-readable storage medium proposed in this embodiment belongs to the field of artificial intelligence and data processing technology, and is applied to the scenario of formulating and pushing auto insurance renewal plans. This application obtains the multi-dimensional service data generated by batch users in the current service cycle; classifies and organizes the multi-dimensional service data to obtain the usage conditions corresponding to the services of all service dimensions; and formulates a service push plan for the next service cycle for all users in the batch of users; and sends the service push plan to the corresponding users within a preset time limit. It realizes the combination of service data in this service cycle, and jointly generates the service push plan corresponding to the target user in the next service cycle from the perspective of group users and individual users, which not only meets the requirements for formulating common plans based on groups, but also meets the requirements for formulating personalized plans based on individuals.

[0156] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), and includes a number of instructions for a terminal device (which can be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in each embodiment of the present application.

[0157] Obviously, the embodiments described above are only some embodiments of the present application, rather than all embodiments. The preferred embodiments of the present application are given in the accompanying drawings, but they do not limit the patent scope of the present application. The present application can be implemented in many different forms. On the contrary, the purpose of providing these embodiments is to make the understanding of the disclosure of the present application more thorough and comprehensive. Although the present application is described in detail with reference to the aforementioned embodiments, for those skilled in the art, it is still possible to modify the technical solutions recorded in the aforementioned specific implementation methods, or to perform equivalent replacement of some of the technical features therein. Any equivalent structure made using the contents of the specification and drawings of this application, directly or indirectly used in other related technical fields, is similarly within the scope of patent protection of this application.

Claims

1. A service processing method, characterized in that: The steps include: Obtain multi-dimensional service data generated by batch users in the current service cycle; Classify and sort the multi-dimensional service data according to the service dimensions and user identifiers to obtain service data corresponding to each user in each service dimension; Based on the service data corresponding to each user in each service dimension, statistics of the service conditions corresponding to all service dimensions are performed to obtain the usage conditions corresponding to the services in all service dimensions; Based on the usage of services in all service dimensions, respectively, a service push plan for the next service cycle is formulated for all users in the batch of users; The service push plans corresponding to all users in the batch of users are sent to the corresponding users within a preset time limit, wherein the preset time limit includes a time limit pre-set according to service requirements.

2. The service processing method according to claim 1, characterized in that: The step of classifying and arranging the multi-dimensional service data according to the service dimensions and the user identifiers to obtain the service data corresponding to each user in each service dimension specifically includes: Preliminarily classifying and arranging the multi-dimensional service data according to the service dimension to obtain a preliminary classification and arranging result based on the service dimension; Perform secondary classification and sorting on the preliminary classification and sorting results according to the user identifier to obtain secondary classification and sorting results based on the service dimension and the user identifier; The secondary classification and sorting results are set as the service data corresponding to each user in each service dimension.

3. The service processing method according to claim 2, characterized in that: The step of preliminarily classifying and arranging the multi-dimensional service data according to the service dimension to obtain a preliminary classification and arranging result based on the service dimension specifically includes: Obtain the car wash service data generated by batch users in the current car insurance underwriting cycle, and cluster them into a preset first cluster to obtain the preliminary classification and sorting results corresponding to the car wash service dimension; Obtain the refueling service data generated by batch users in the current auto insurance underwriting cycle, and cluster them into the preset second cluster, to obtain the preliminary classification and sorting results corresponding to the refueling service dimension; Obtain maintenance service data generated by batch users during the current auto insurance underwriting period, and cluster them into a preset third cluster to obtain a preliminary classification and sorting result corresponding to the maintenance service dimension; Obtaining the car beauty service data generated by batch users in the current car insurance underwriting cycle, and clustering them into the preset fourth cluster, to obtain the preliminary classification and sorting results corresponding to the car beauty service dimension; Acquire the vehicle decoration accessories purchase data generated by batch users in the current vehicle insurance underwriting period, and cluster them into the preset fifth cluster, so as to obtain the preliminary classification and sorting results corresponding to the vehicle decoration accessories purchase dimension; The vehicle rescue service data generated by batch users in the current vehicle insurance underwriting cycle is obtained, and clustered into the preset sixth cluster to obtain the preliminary classification and sorting results corresponding to the vehicle rescue service dimension.

4. The service processing method according to claim 2, characterized in that: The step of performing secondary classification and sorting on the preliminary classification and sorting results according to the user identifier to obtain the secondary classification and sorting results based on the service dimension and the user identifier specifically includes: Perform secondary classification and sorting of the preliminary classification and sorting results corresponding to the car wash service dimension according to the user identifier to obtain the car wash service data of each user in the current car insurance underwriting period; Perform secondary classification and sorting of the preliminary classification and sorting results corresponding to the refueling service dimension according to the user identifier to obtain the refueling service data of each user in the current motor insurance underwriting period; Perform secondary classification and sorting of the preliminary classification and sorting results corresponding to the maintenance service dimension according to the user identifier to obtain the maintenance service data of each user in the current motor insurance underwriting period; Perform secondary classification and sorting of the preliminary classification and sorting results corresponding to the automobile beauty service dimension according to the user identifier to obtain automobile beauty service data of each user in the current automobile insurance underwriting period; Perform secondary classification and sorting of the preliminary classification and sorting results corresponding to the vehicle decoration accessories purchase dimension according to the user identifier to obtain the vehicle decoration accessories purchase data of each user in the current vehicle insurance underwriting period; The preliminary classification and sorting results corresponding to the vehicle rescue service dimension are secondary classified and sorted according to the user identification to obtain the vehicle rescue service data of each user in the current motor insurance underwriting period.

5. The service processing method according to claim 1, characterized in that: The step of performing service situation statistics corresponding to all service dimensions based on the service data corresponding to each user in each service dimension, and obtaining the usage situation corresponding to the services in all service dimensions specifically includes: According to the service data corresponding to each user in each service dimension, the number of times each user uses the service in each service dimension is counted; Based on the service usage times of each user in each service dimension, the total service usage times of the same user in all service dimensions are calculated by summing them up; Based on the service usage times of each user in each service dimension and the total service usage times of the same user in all service dimensions, the service preference weights corresponding to the same user in all service dimensions are calculated by using a ratio method; Based on the number of service usages corresponding to each user in each service dimension, the average number of service usages corresponding to all users in different service dimensions is calculated by cumulative averaging.

6. The service processing method according to claim 5, characterized in that: After executing the step of calculating the average number of service usages corresponding to different service dimensions by all users in a cumulative average manner based on the number of service usages corresponding to each user in each service dimension, the method further includes: Based on the service usage times of each user in each service dimension and the average service usage times of all users in different service dimensions, a comparison method is used to determine whether the service usage times of each user in each service dimension exceeds the average service usage times of the corresponding service dimension; Combined with the judgment result, the service usage times corresponding to each user in each service dimension are distinguished and marked using a preset distinction strategy, wherein the preset distinction strategy includes: If the number of service uses corresponding to the target service dimension by the current user exceeds the average number of service uses of the target service dimension, the first distinguishing color is used to distinguish the number of service uses corresponding to the target service dimension by the current user; if the number of service uses corresponding to the target service dimension by the current user does not exceed the average number of service uses of the target service dimension, the second distinguishing color is used to distinguish the number of service uses corresponding to the target service dimension by the current user; or, if the number of service uses corresponding to the target service dimension by the current user exceeds the average number of service uses of the target service dimension, the first distinguishing label is used to distinguish the number of service uses corresponding to the target service dimension by the current user; if the number of service uses corresponding to the target service dimension by the current user does not exceed the average number of service uses of the target service dimension, the second distinguishing label is used to distinguish the number of service uses corresponding to the target service dimension by the current user.

7. The service processing method according to claim 1 or 5, characterized in that: Before executing the step of formulating service push plans for the next service cycle for all users in the batch of users based on the usage conditions corresponding to the services in all service dimensions, the method further includes: According to the preset service nature classification form, the mandatory service dimension and the non-mandatory service dimension are identified from all service dimensions, wherein the mandatory service dimension includes vehicle rescue service, and the non-mandatory service dimension includes car washing service, refueling service, maintenance service, car beauty service, and purchase of vehicle decoration accessories; The step of formulating service push plans for the next service cycle for all users in the batch of users based on the usage conditions of the services in all service dimensions includes: According to the usage of services in all service dimensions, identifying whether the number of service usages corresponding to the mandatory service dimension by the same user exceeds the average number of service usages in the mandatory service dimension; If the number of service usages corresponding to the mandatory service dimension of the current user exceeds the average number of service usages of the mandatory service dimension, then the target proportion of service usages is increased on the basis of the preset service planning number to obtain the total number of service plannings of the mandatory service dimension; If the number of service usages corresponding to the mandatory service dimension of the current user does not exceed the average number of service usages of the mandatory service dimension, the preset service planning number is set as the total number of service plannings of the mandatory service dimension; According to the usage of services in all service dimensions, the service preference weights corresponding to all non-mandatory service dimensions of the same user are identified; If the service preference weights corresponding to all non-mandatory service dimensions of the current user are not zero, then the service planning times corresponding to all non-mandatory service dimensions in the next service cycle are calculated by multiplication based on the service preference weights and the total number of service recommendations preset in the next service cycle; If the current user has a service preference weight of zero corresponding to at least one non-mandatory service dimension, then all non-mandatory service dimensions with a service preference weight of zero are identified, and the number of service plans for all non-mandatory service dimensions with a service preference weight of zero in the next service cycle is set to zero, and all non-mandatory service dimensions with a service preference weight of non-zero are identified, and the number of service plans corresponding to all non-mandatory service dimensions with a service preference weight of non-zero in the next service cycle are calculated by multiplication based on the service preference weight and the total number of service recommendations preset in the next service cycle; According to the total number of service plans corresponding to the current user in the mandatory service dimension and the number of service plans corresponding to the current user in all non-mandatory service dimensions, a service push plan for the next service cycle is formulated for the current user.

8. A service processing device, characterized in that: include: The service data acquisition module is used to acquire the multi-dimensional service data generated by batch users in the current service cycle; A service data classification module, used to classify and sort the multi-dimensional service data according to the service dimensions and user identifiers, and obtain the service data corresponding to each user in each service dimension; A service usage statistics module is used to perform service statistics corresponding to all service dimensions based on the service data corresponding to each user in each service dimension, and obtain the usage corresponding to the services in all service dimensions; A service push plan formulation module, used to formulate service push plans for the next service cycle for all users in the batch of users based on the usage of services in all service dimensions; The service push plan sending module is used to send the service push plans corresponding to all users in the batch of users to the corresponding users within a preset time limit, wherein the preset time limit includes a time limit pre-set according to service requirements.

9. A computer device, characterized in that: The method comprises a memory and a processor, wherein the memory stores computer-readable instructions, and the processor implements the steps of the service processing method according to any one of claims 1 to 7 when executing the computer-readable instructions.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-readable instructions, and when the computer-readable instructions are executed by a processor, the steps of the service processing method according to any one of claims 1 to 7 are implemented.

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