Data processing method, device and equipment and readable storage medium
By dynamically combining multiple non-mobile phone number identifications from customers with mobile phone numbers as the core identifiers, the problem that data integration in the existing technology is difficult to meet cross-platform and cross-device scenarios, and the unity of customer identification and data integrity are achieved.
Patent Information
- Application Number
- CN202510006399.2
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-01-02
- Publication Date
- 2025-05-02
AI Technical Summary
Existing data integration solutions are difficult to meet the unified management needs of customer information in complex cross-platform, cross-device, and cross-application scenarios, resulting in poor data integrity.
By dynamically combining multiple non-mobile phone number identifications for customers with mobile phone number as the core identifier, the unified customer identification across platforms and devices is achieved. The specific steps include obtaining the pending behavior data, determining whether to associate the mobile phone number identifier, and if associated, it is used as the core identifier to judge the association relationship, and merging and processing to generate the customer identifier.
By achieving the unity of customer identification, the integrity of data is improved and the customer information management needs in complex scenarios are met.
Smart Images
Figure CN119917514A_ABST
Abstract
Description
Technical Field
[0001] The present application relates to the field of data processing technology, and in particular to a data processing method, device, equipment and readable storage medium. Background Art
[0002] With the rapid development of Internet technology, various applications and WeChat mini-programs have been developed. In order to facilitate users, applications and WeChat mini-programs can often handle the same business. In order to support customer behavior analysis across business systems, data integration becomes particularly important.
[0003] Existing data integration solutions usually use a single identifier to associate customer data, which makes it difficult to meet the needs of unified management of customer information in complex cross-platform, cross-device, and cross-application scenarios, resulting in poor integrity of the integrated data.
[0004] Therefore, how to improve the integrity of data is an issue that technical personnel in this field need to solve urgently. Summary of the invention
[0005] Based on the above problems, the present application provides a data processing method, apparatus, device and readable storage medium. By using the mobile phone number as the core identifier and dynamically merging the customer's multiple non-mobile phone number identifiers, the customer identification is unified across platforms and devices, thereby improving the integrity of the data.
[0006] In a first aspect, an embodiment of the present application provides a data processing method, the method comprising:
[0007] Obtaining the behavior data to be processed; each piece of the behavior data to be processed is associated with a corresponding specific identifier; the specific identifier includes one or more of a mobile phone number identifier and a non-mobile phone number identifier;
[0008] If the behavior data to be processed is associated with the mobile phone number identifier, the mobile phone number identifier is used as the core identifier, and the association relationship is determined based on the specific identifier;
[0009] If a mobile phone number corresponding to the core identifier corresponds to a unique non-mobile phone number identifier, the core identifier and the non-mobile phone number identifier are merged to generate a customer identifier;
[0010] The behavior data to be processed is integrated and output based on the customer identification.
[0011] Optionally, the method further includes:
[0012] If the behavior data to be processed is not associated with the mobile phone number identifier, the behavior data to be processed will be isolated and notified for manual confirmation.
[0013] Optionally, the method further includes:
[0014] If a mobile phone number corresponding to the core identifier corresponds to at least two non-mobile phone number identifiers, frequency evaluation is performed on different non-mobile phone number identifiers, and a first identifier state is determined;
[0015] The non-mobile phone number identifier whose first identifier status is active is merged with the core identifier to generate a customer identifier.
[0016] Optionally, the performing frequency evaluation on different non-mobile phone number identifiers and determining the first identifier state includes:
[0017] Determine the usage frequency of each non-mobile phone number identifier corresponding to a mobile phone number corresponding to the core identifier;
[0018] Setting the non-mobile phone number identifier with the highest frequency of use as active;
[0019] The non-mobile phone number identifier that is not used most frequently is set to an isolated state.
[0020] Optionally, the non-mobile phone number identifier includes: a customer number;
[0021] The method further comprises:
[0022] If at least two mobile phone numbers corresponding to the core identifier correspond to the same customer number, a frequency assessment is performed on each mobile phone number corresponding to the customer number, and a second identifier status is determined;
[0023] The core identifier corresponding to the mobile phone number whose second identifier status is active is merged with the customer number to generate a customer identifier.
[0024] Optionally, the non-mobile phone number identifier includes: device ID and WeChat UnionId;
[0025] The method further comprises:
[0026] If at least two mobile phone numbers corresponding to the core identifier correspond to the same device ID and / or WeChat UnionId, the behavior data to be processed corresponding to each mobile phone number will be isolated.
[0027] Optionally, the method further includes:
[0028] Detecting the identification status of the mobile phone number identification and the non-mobile phone number identification;
[0029] The customer identification is updated according to the identification status.
[0030] In a second aspect, an embodiment of the present application provides a data processing device, including:
[0031] An acquisition module is used to acquire the behavior data to be processed; each piece of the behavior data to be processed is associated with a corresponding specific identifier; the specific identifier includes one or more of a mobile phone number identifier and a non-mobile phone number identifier;
[0032] A judgment module, used for, when the behavior data to be processed is associated with the mobile phone number identifier, using the mobile phone number identifier as a core identifier and performing an association judgment based on the specific identifier;
[0033] A first merging module, configured to merge the core identifier with the non-mobile number identifier to generate a customer identifier when the mobile number corresponding to the core identifier corresponds to the unique non-mobile number identifier;
[0034] An integration module is used to integrate and output the behavior data to be processed based on the customer identification.
[0035] In a third aspect, an embodiment of the present application provides a data processing device, including:
[0036] Memory for storing computer programs;
[0037] A processor is used to implement the steps of the data processing method as described above when executing the computer program.
[0038] In a fourth aspect, an embodiment of the present application provides a readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the data processing method described above are implemented.
[0039] It can be seen from the above technical solutions that compared with the prior art, the present application has the following advantages:
[0040] This application first obtains the behavior data to be processed. Among them, each piece of behavior data to be processed is associated with a corresponding specific identifier, and the specific identifier includes one or more of a mobile phone number identifier and a non-mobile phone number identifier. If the behavior data to be processed is associated with a mobile phone number identifier, the mobile phone number identifier is used as the core identifier, and the association relationship is judged based on the specific identifier. If a mobile phone number corresponding to the core identifier corresponds to a unique non-mobile phone number identifier, the core identifier and the non-mobile phone number identifier are merged to generate a customer identifier. Finally, the behavior data to be processed is integrated and output based on the customer identifier. In this way, by taking the mobile phone number as the core identifier and dynamically merging the customer's multiple non-mobile phone number identifiers, the unification of customer identifiers across platforms and devices is achieved, thereby improving the integrity of the data. BRIEF DESCRIPTION OF THE DRAWINGS
[0041] Figure 1A schematic diagram of the structure of a customer identification merging business model provided in an embodiment of the present application;
[0042] Figure 2 A flowchart of a data processing method provided in an embodiment of the present application;
[0043] Figure 3 A flowchart of an execution logic provided by an embodiment of the present application;
[0044] Figure 4 A schematic diagram of the structure of a data processing device provided in an embodiment of the present application. DETAILED DESCRIPTION
[0045] As mentioned above, existing data integration solutions are prone to problems with low integrity of integrated data. Specifically, existing solutions usually rely on a single identifier to associate customer data, which makes it difficult to meet the needs of unified management of customer information in complex cross-platform, cross-device, and cross-application scenarios. Under the existing methods, relying solely on a single identifier for data association often results in the loss of important behavioral data of customers in the potential customer stage. Before a customer formally registers or binds a mobile phone number, the access, browsing, and interaction behaviors in many channels are difficult to attribute to a unified customer ID. These behavioral data are of great value to companies in analyzing customer potential and conducting precision marketing, and are difficult to meet the company's needs for comprehensive integration of customer data.
[0046] In order to solve the above problems, an embodiment of the present application provides a data processing method, which first obtains the behavior data to be processed. Each piece of behavior data to be processed is associated with a corresponding specific identifier, and the specific identifier includes one or more of a mobile phone number identifier and a non-mobile phone number identifier. If the behavior data to be processed is associated with a mobile phone number identifier, the mobile phone number identifier is used as the core identifier, and the association relationship is judged based on the specific identifier. If a mobile phone number corresponding to the core identifier corresponds to a unique non-mobile phone number identifier, the core identifier and the non-mobile phone number identifier are merged to generate a customer identifier. Finally, the behavior data to be processed is integrated and output based on the customer identifier.
[0047] In this way, by using the mobile phone number as the core identifier and dynamically merging the customer's various non-mobile phone number identifiers, the customer identification is unified across platforms and devices, thereby improving the integrity of the data.
[0048] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant laws, regulations and standards of relevant countries and regions.
[0049] It should be noted that the data processing method, device, equipment and readable storage medium provided by the present application can be applied to the field of data processing technology. The above is only an example and does not limit the application field of the data processing method, device, equipment and readable storage medium provided by the present application.
[0050] In order to make the purpose, technical solution and advantages of the embodiments of the present application clearer, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.
[0051] Figure 1 A schematic diagram of a customer identification merging business model provided in an embodiment of the present application. Figure 1 As shown, the customer identification merging business model consists of a customer behavior data source, a system function module, and a unified customer identification module. The model merges multiple customer identifications into a unified identification through a core ID, and integrates all relevant customer data based on this merged identification. Among them, customer behavior data includes: embedded point operation behavior data (recording specific operations of customers in the application, such as clicks, browsing, logins, etc., to provide basic data for customer behavior analysis) and scenario customer acquisition retention data (covering customer information retention in various marketing activities and advertising scenarios). System functions include: core ID merging (for example, merging other identifications with mobile phone numbers as the core), active status setting (based on frequency of use), isolation mechanism (to avoid accidental merging), and manual confirmation (identification confirmation). The unified customer identification can be a mobile phone number, device ID, or WeChat ID, etc. The integrated customer data can be cross-application, cross-device, and cross-business, ensuring the integrity of the data.
[0052] Figure 2 A flowchart of a data processing method provided in an embodiment of the present application. Figure 1 As shown, a data processing method provided in an embodiment of the present application may include:
[0053] S201: Obtaining behavior data to be processed; each piece of the behavior data to be processed is associated with a corresponding specific identifier; the specific identifier includes one or more of a mobile phone number identifier and a non-mobile phone number identifier.
[0054] In practical applications, the customer behavior data source contains a variety of interaction data of customers in different scenarios. The data processing device provided in the embodiment of the present application is intended to merge the data in the data source according to different customers. Specifically, the system collects different identification data and imports them into the system to form a customer behavior data source. The data processing device needs to obtain the behavior data to be processed from the customer behavior data source, and the behavior data to be processed includes the point-of-use operation behavior data and the scene customer acquisition retention data. Each piece of behavior data to be processed is associated with a specific identifier (specific identifier), such as a mobile phone number, WeChat UnionId, device ID, etc. These identifiers provide a basis for subsequent merging. For example, customer A handles a business through a mobile phone APP. If the customer associates the mobile phone number when logging into the APP, then the specific identifier associated with the behavior data "customer A handles the business" should have the mobile phone number and the device ID; if the customer does not associate the mobile phone number when logging into the APP, then the specific identifier associated with the behavior data "customer A handles the business" should only have the device ID. In order to better support the data processing logic, the embodiment of the present application designs a table structure. Specifically, the basic information and ownership relationship of each identifier are recorded in the `guid_mapping` main table, and all identifiers under the same customer are uniformly managed through fields. The fields may include the unique ID of each identifier, the core mobile phone number ID to which it belongs, the identifier type, the original coding value, the logical deletion flag, the creation time of the record, and the last modification time. The `guid_related_ids` association table is used to manage the association relationship between identifiers, track the association between various identifiers and core mobile phone numbers, and support dynamic updates and isolation control. Fields may include the mobile phone number ID, other identifier IDs associated with the mobile phone number ID, the frequency of associated use, the associated status, the record creation time, and the time when the status was last updated. In addition, the query and update performance can be improved based on the sub-table logic, and indexes can be established on the main table and the associated table to support quick query of ownership relationships.
[0055] S202: If the behavior data to be processed is associated with the mobile phone number identifier, the mobile phone number identifier is used as a core identifier, and an association relationship judgment is performed based on the specific identifier.
[0056] In practical applications, mobile phone numbers generally require real-name registration, so they can be considered to be uniquely corresponding to customers, that is, one customer corresponds to one mobile phone number. In this regard, the data processing device provided in the embodiment of the present application first needs to determine whether the behavior data to be processed is associated with a mobile phone number identifier. If so, the mobile phone number identifier is used as the core identifier to determine the association relationship between the subsequent mobile phone number identifier and the non-mobile phone number identifier based on the specific identifier.
[0057] S203: If a mobile phone number corresponding to the core identifier corresponds to the unique non-mobile phone number identifier, the core identifier and the non-mobile phone number identifier are merged to generate a customer identifier.
[0058] In actual applications, the mobile phone number can be used as the core identifier, and all relevant identifiers under the same customer can be integrated through dynamic data matching to form a unified customer identifier. For example, if the mobile phone number identifier in the specific identifier corresponding to the pending behavior data 1 is 13811111111, and the non-mobile phone number identifier is A; the mobile phone number identifier in the specific identifier corresponding to the pending behavior data 2 is 13811111111, and the non-mobile phone number identifier is A; the mobile phone number identifier in the specific identifier corresponding to the pending behavior data 3 is 13811111111, and the non-mobile phone number identifier is A; the mobile phone number identifier in the specific identifier corresponding to the pending behavior data 4 is 13822222222, and the non-mobile phone number identifier is B. Among them, taking the mobile phone number identifier as the core identifier, it can be obtained that the mobile phone number "13811111111" corresponding to the core identifier uniquely corresponds to the non-mobile phone number identifier A, and the mobile phone number "13822222222" corresponding to the core identifier uniquely corresponds to the non-mobile phone number identifier B. In this way, the core identifier 13811111111 and the non-mobile phone number identifier A are merged to obtain a customer identifier, and the core identifier 13822222222 and the non-mobile phone number identifier B are merged to obtain another customer identifier. These two customer identifiers correspond to two different customers independently. In addition, non-mobile phone number identifiers can include WeChat openid, WeChat unionId, and device ID. When a user uses the same mobile phone number to associate multiple identifiers in different occasions, the system needs to merge these identifiers into one customer identifier. For example, when the user reports behavior data for the first time, data 1 is associated with mobile phone number 13811111111, WeChat openid1 and WeChat unionId1. The data processing device will identify and merge the mobile phone number 13811111111 with WeChat openid1 and WeChat unionId1. When the behavior data is reported for the second time, data 2 is associated with mobile phone number 13811111111 and device ID1. Since no new WeChat openid and WeChat unionId are involved, device ID1 is the same as WeChat openid1 and WeChat unionId1, and is also the unique non-mobile phone number identifier corresponding to mobile phone number 13811111111. The data processing device will identify and merge the mobile phone number 13811111111 with device ID1, WeChat openid1 and WeChat unionId1.
[0059] S204: Integrate and output the behavior data to be processed based on the customer identification.
[0060] In practical applications, the uniformity of customer behavior data is crucial for accurate profiling and analysis. Through multi-identity dynamic association technology, all identifiers under the same customer are merged into one core identifier, thereby building a unified customer identifier. Through the customer identifier, data from different platforms can be integrated and output, breaking down data silos and providing data support for subsequent customer identification, profiling and accurate services.
[0061] In addition, since the association situations of the behavior data to be processed are not the same, the embodiment of the present application can illustrate a possible association situation.
[0062] In one embodiment, the method further comprises:
[0063] If the behavior data to be processed is not associated with the mobile phone number identifier, the behavior data to be processed will be isolated and notified for manual confirmation.
[0064] In actual applications, it can be stipulated that a mobile phone number (mobile phone number identifier) uniquely corresponds to a customer, but a non-mobile phone number identifier may correspond to multiple customers. Therefore, in order to avoid the mis-merging of identifiers corresponding to different customers, the embodiment of the present application introduces an anti-mis-merging mechanism, sets up isolation control and manual confirmation mechanisms, and isolates the behavior data to be processed when it is not associated with a mobile phone number identifier to prevent mis-merging, and notifies and waits for subsequent data updates or manual confirmation processes.
[0065] In addition, since the association situations of the behavior data to be processed are not the same, the embodiment of the present application can illustrate a possible association situation.
[0066] In one case, if a mobile phone number corresponding to the core identifier corresponds to at least two non-mobile phone number identifiers, a frequency evaluation is performed on different non-mobile phone number identifiers, and a first identifier state is determined;
[0067] The non-mobile phone number identifier whose first identifier status is active is merged with the core identifier to generate a customer identifier.
[0068] In actual applications, if a mobile phone number corresponding to a core identifier corresponds to at least two non-mobile phone number identifiers, it means that the same customer has behavioral data on different devices or platforms. At this time, it is necessary to conduct a frequency assessment on each non-mobile phone number identifier (determine the frequency of use of each non-mobile phone number identifier by the customer), and determine the status corresponding to each non-mobile phone number identifier, that is, determine the first identification status. The first identification status includes an active state (active) and an isolated state (isolated). The data processing aims to merge commonly used identifiers to ensure the accuracy of the merger. Therefore, the data processing device needs to merge the active non-mobile phone number identifier with the core identifier to generate a customer identifier.
[0069] In addition, since the frequency evaluation methods are different, the embodiment of the present application can illustrate a possible evaluation method.
[0070] In one case,
[0071] The step of performing frequency evaluation on different non-mobile phone number identifiers and determining a first identifier state includes:
[0072] Determine the usage frequency of each non-mobile phone number identifier corresponding to a mobile phone number corresponding to the core identifier;
[0073] Setting the non-mobile phone number identifier with the highest frequency of use as active;
[0074] The non-mobile phone number identifier that is not used most frequently is set to an isolated state.
[0075] In actual applications, the frequency evaluation process is based on a mobile phone number corresponding to the core identifier, and evaluates the usage frequency of each non-mobile phone number identifier corresponding to it, and then determines the identification status of each non-mobile phone number identifier corresponding to the mobile phone number. For example, customer A used a mobile phone number 13811111111 corresponding to the core identifier to handle a business once on a device with device ID A, and handled business twice on a device with device ID B. The frequency evaluation process shows that the user uses the device with device ID B most frequently, so the device with device ID B is set to "active" status, and the device with device ID A is set to "isolated" status to avoid data conflicts. In addition, if the usage frequency of each non-mobile phone number identifier is the same, they are all set to active status.
[0076] In addition, since different non-mobile phone number identifiers correspond to different association methods, the embodiment of the present application can illustrate a possible association situation.
[0077] In one case, the non-mobile phone number identifier includes: a customer number;
[0078] The method further comprises:
[0079] If at least two mobile phone numbers corresponding to the core identifier correspond to the same customer number, a frequency assessment is performed on each mobile phone number corresponding to the customer number, and a second identifier status is determined;
[0080] The core identifier corresponding to the mobile phone number whose second identifier status is active is merged with the customer number to generate a customer identifier.
[0081] In actual applications, a non-mobile phone number identifier can be a customer number. If the behavior data to be processed is associated with a customer number, the system will treat the customer number as a unique identifier generated based on the ID card to ensure that it is associated with a unique mobile phone number. Therefore, when it is detected that a customer number is associated with multiple mobile phone numbers, that is, when at least two mobile phone numbers corresponding to the core identifier correspond to the same customer number, the mobile phone number with the highest frequency will be retained first, and the other mobile phone numbers will be set to an isolated state to prevent accidental merging. Specifically, when a customer number corresponds to multiple mobile phone numbers, the data processing device performs a frequency evaluation on each mobile phone number and determines the second identification state corresponding to each mobile phone number. For example, customer A used a mobile phone number 13811111111 corresponding to the core identifier to handle a business on a device with device ID A and associated it with customer number A. He then used another mobile phone number 138222222222 to handle two businesses on a device with device ID A and associated them with customer number A. The frequency evaluation process shows that the user uses mobile phone number 138222222222 most frequently, so the core identifier corresponding to mobile phone number 138222222222 is set to "active", and the core identifier corresponding to mobile phone number 13811111111 is set to "isolated", and the active mobile phone number 13822222222 is merged with customer number A to avoid data conflicts and ensure that the customer number is associated with a unique mobile phone number. In addition, the core identifier determined to be in isolation status needs to wait for manual confirmation. If the mobile phone number 13811111111 is manually confirmed as the unique associated mobile phone number of customer number A, the core identifier corresponding to the mobile phone number 13822222222 will be set to the "isolated" status, and the core identifier corresponding to the mobile phone number 13811111111 will be set to the "active" status for data update, and the active mobile phone number 13811111111 will be merged with customer number A to avoid data conflicts.
[0082] In addition, since different non-mobile phone number identifiers correspond to different association methods, the embodiment of the present application can illustrate a possible association situation.
[0083] In one case, the non-mobile phone number identifier includes: device ID and WeChat UnionId;
[0084] The method further comprises:
[0085] If at least two mobile phone numbers corresponding to the core identifier correspond to the same device ID and / or WeChat UnionId, the behavior data to be processed corresponding to each mobile phone number will be isolated.
[0086] In actual applications, non-mobile phone number identifiers can be device IDs and WeChat UnionIds. When the same identifier (device ID and / or the WeChat UnionId) is associated with different mobile phone numbers, the system needs to isolate the corresponding data to prevent the occurrence of erroneous merging. For example, when the user's first behavioral data is reported, data 3 is associated with mobile phone number 13822222222 with WeChat openid2 and WeChat unionId2, and the data processing device will identify and merge the mobile phone number 13822222222 with WeChat openid2 and WeChat unionId2. When the second behavioral data is reported, data 4 is associated with mobile phone number 13833333333 with WeChat openid2 and WeChat unionId2. At this time, the association of different mobile phone numbers is detected, and the data processing device will set the association of mobile phone number 13833333333 to an isolated state, thereby isolating data 3 and data 4, and waiting for manual confirmation.
[0087] In addition, since the updating methods of the identification status are not the same, the embodiment of the present application can illustrate a possible updating method.
[0088] In one embodiment, the method further comprises:
[0089] Detecting the identification status of the mobile phone number identification and the non-mobile phone number identification;
[0090] The customer identification is updated according to the identification status.
[0091] In actual applications, the data processing device will count the usage frequency of each identifier in the guid_related_ids table, determine the usage frequency of the associated identifier through the usage_count field, and set the associated identifier with the highest usage frequency to the active state (active) to ensure that the primary identifier selection reflects the customer's primary identity information. The data processing device will regularly detect and update the frequency data and active status, and update the customer identifier according to the identifier status to ensure the dynamic accuracy and consistency of data merging.
[0092] Figure 3 A flowchart of an execution logic provided in an embodiment of the present application. Figure 3As shown, the system collects data and initially records each piece of data through the main table and the associated table. The data processing device first determines whether each piece of behavior data to be processed is associated with a mobile phone number. If not, the record is set to an isolated state, waiting for update or manual confirmation. If the behavior data to be processed is associated with a mobile phone number, it is determined whether it is associated with a customer number. If the customer number is not associated, it continues to determine whether there are multiple identifiers associated with the same mobile phone number. If the customer number is associated, it is determined whether multiple mobile phone numbers are associated. If it is determined otherwise, the customer number is associated with the first mobile phone number to ensure uniqueness, and then it is determined whether there are multiple identifiers associated with the same mobile phone number; if it is determined to be yes, it is determined whether the unique relationship is automatically confirmed. If it is determined to be yes, the customer number is set to be associated with the mobile phone number with the highest frequency. If it is determined to be otherwise, the manual confirmation process is entered, and then it is determined whether there are multiple identifiers associated with the same mobile phone number. If there are multiple identifiers associated with the same mobile phone number, the frequency evaluation process will be entered. Depending on whether a frequency evaluation is required, the identifier with the highest frequency will be set to active or kept active. If there are no multiple identifiers associated with the same mobile phone number, the unique identifier status will be set to active, and then it will be determined whether multiple mobile phone numbers are detected to be associated with the same non-mobile phone number identifier. If the test result is yes, it will be set to isolation status and wait for manual confirmation. If the test result is no, it will continue to merge and merge the identifiers under the core identifier to determine whether the main table needs to be updated. If an update is required, the main table will be updated. If an update is not required, the current status of the main table will be maintained, and the final data will be integrated and output to generate a unified customer identifier to support subsequent customer profiling and analysis.
[0093] To summarize, the present application first obtains the behavior data to be processed. Among them, each piece of behavior data to be processed is associated with a corresponding specific identifier, and the specific identifier includes one or more of a mobile phone number identifier and a non-mobile phone number identifier. If the behavior data to be processed is associated with a mobile phone number identifier, the mobile phone number identifier is used as the core identifier, and the association relationship is judged based on the specific identifier. If a mobile phone number corresponding to the core identifier corresponds to a unique non-mobile phone number identifier, the core identifier and the non-mobile phone number identifier are merged to generate a customer identifier. Finally, the behavior data to be processed is integrated and output based on the customer identifier. In this way, by taking the mobile phone number as the core identifier and dynamically merging the customer's multiple non-mobile phone number identifiers, the unification of customer identifiers across platforms and devices is achieved, thereby improving the integrity of the data.
[0094] Figure 4 A schematic diagram of the structure of a data processing device provided in an embodiment of the present application. Figure 4 As shown, the data processing device 400 provided in the embodiment of the present application includes:
[0095] Acquisition module 401, used to acquire the behavior data to be processed; each piece of the behavior data to be processed is associated with a corresponding specific identifier; the specific identifier includes one or more of a mobile phone number identifier and a non-mobile phone number identifier;
[0096] The judgment module 402 is used for, when the behavior data to be processed is associated with the mobile phone number identifier, using the mobile phone number identifier as a core identifier and performing an association judgment based on the specific identifier;
[0097] A first merging module 403 is used to merge the core identifier with the non-mobile number identifier to generate a customer identifier when the mobile number corresponding to the core identifier corresponds to the unique non-mobile number identifier;
[0098] The integration module 404 is used to integrate and output the behavior data to be processed based on the customer identification.
[0099] As an implementation manner, regarding how to process the behavior data to be processed, the data processing device 400 further includes: a first isolation module;
[0100] The first isolation module is used to isolate the behavior data to be processed and notify manual confirmation when the behavior data to be processed is not associated with the mobile phone number identifier.
[0101] As an implementation method, regarding how to perform identity merging, the data processing device 400 further includes: a frequency evaluation module and a second merging module;
[0102] A frequency evaluation module, configured to perform frequency evaluation on different non-mobile number identifiers and determine a first identifier state when a mobile number corresponding to the core identifier corresponds to at least two non-mobile number identifiers;
[0103] The second merging module is used to merge the non-mobile phone number identifier whose first identifier status is active with the core identifier and generate a customer identifier.
[0104] As an implementation manner, with respect to how to determine the first identification state, the frequency evaluation module is specifically used to:
[0105] Determine the usage frequency of each non-mobile phone number identifier corresponding to a mobile phone number corresponding to the core identifier;
[0106] Setting the non-mobile phone number identifier with the highest frequency of use as active;
[0107] The non-mobile phone number identifier that is not used most frequently is set to an isolated state.
[0108] As an implementation mode, the non-mobile phone number identifier includes: a customer number; with respect to how to merge the identifiers, the data processing device 400 further includes: a third merging module;
[0109] A third merging module is used to perform frequency evaluation on each mobile phone number corresponding to the customer number and determine the second identification state when at least two mobile phone numbers corresponding to the core identification correspond to the same customer number;
[0110] The core identifier corresponding to the mobile phone number whose second identifier status is active is merged with the customer number to generate a customer identifier.
[0111] As an implementation method, the non-mobile phone number identifier includes: device ID and WeChat UnionId; Regarding how to process the behavior data to be processed, the data processing device 400 further includes: a second isolation module;
[0112] The second isolation module is used to isolate the to-be-processed behavior data corresponding to each mobile phone number when at least two mobile phone numbers corresponding to the core identifier correspond to the same device ID and / or WeChat UnionId.
[0113] As an implementation method, regarding how to update the customer identification, the data processing device 400 further includes: an updating module;
[0114] An updating module, used to detect the identification status of the mobile phone number identification and the non-mobile phone number identification;
[0115] The customer identification is updated according to the identification status.
[0116] To summarize, the present application first obtains the behavior data to be processed. Among them, each piece of behavior data to be processed is associated with a corresponding specific identifier, and the specific identifier includes one or more of a mobile phone number identifier and a non-mobile phone number identifier. If the behavior data to be processed is associated with a mobile phone number identifier, the mobile phone number identifier is used as the core identifier, and the association relationship is judged based on the specific identifier. If a mobile phone number corresponding to the core identifier corresponds to a unique non-mobile phone number identifier, the core identifier and the non-mobile phone number identifier are merged to generate a customer identifier. Finally, the behavior data to be processed is integrated and output based on the customer identifier. In this way, by taking the mobile phone number as the core identifier and dynamically merging the customer's multiple non-mobile phone number identifiers, the unification of customer identifiers across platforms and devices is achieved, thereby improving the integrity of the data.
[0117] In addition, the present application also provides a data processing device, including:
[0118] Memory for storing computer programs;
[0119] A processor is used to implement the steps of the data processing method as described above when executing the computer program.
[0120] In addition, the present application also provides a readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the data processing method described above are implemented.
[0121] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present application. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to the embodiments shown herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.
Claims
1. A data processing method, characterized in that: The method comprises: Obtaining the behavior data to be processed; each piece of the behavior data to be processed is associated with a corresponding specific identifier; the specific identifier includes one or more of a mobile phone number identifier and a non-mobile phone number identifier; If the behavior data to be processed is associated with the mobile phone number identifier, the mobile phone number identifier is used as the core identifier, and the association relationship is determined based on the specific identifier; If a mobile phone number corresponding to the core identifier corresponds to a unique non-mobile phone number identifier, the core identifier and the non-mobile phone number identifier are merged to generate a customer identifier; The behavior data to be processed is integrated and output based on the customer identification.
2. The method according to claim 1, characterized in that: The method further comprises: If the behavior data to be processed is not associated with the mobile phone number identifier, the behavior data to be processed will be isolated and notified for manual confirmation.
3. The method according to claim 1, characterized in that The method further comprises: If a mobile phone number corresponding to the core identifier corresponds to at least two non-mobile phone number identifiers, frequency evaluation is performed on different non-mobile phone number identifiers, and a first identifier state is determined; The non-mobile phone number identifier whose first identifier status is active is merged with the core identifier to generate a customer identifier.
4. The method according to claim 3, characterized in that The step of performing frequency evaluation on different non-mobile phone number identifiers and determining a first identifier state includes: Determine the usage frequency of each non-mobile phone number identifier corresponding to a mobile phone number corresponding to the core identifier; Setting the non-mobile phone number identifier with the highest frequency of use as active; The non-mobile phone number identifier that is not used most frequently is set to an isolated state.
5. The method according to claim 1, characterized in that The non-mobile phone number identifier includes: customer number; The method further comprises: If at least two mobile phone numbers corresponding to the core identifier correspond to the same customer number, a frequency assessment is performed on each mobile phone number corresponding to the customer number, and a second identifier status is determined; The core identifier corresponding to the mobile phone number whose second identifier status is active is merged with the customer number to generate a customer identifier.
6. The method according to claim 1, characterized in that The non-mobile phone number identifier includes: device ID and WeChat UnionId; The method further comprises: If at least two mobile phone numbers corresponding to the core identifier correspond to the same device ID and / or WeChat UnionId, the behavior data to be processed corresponding to each mobile phone number will be isolated.
7. The method according to claim 1, characterized in that The method further comprises: Detecting the identification status of the mobile phone number identification and the non-mobile phone number identification; The customer identification is updated according to the identification status.
8. A data processing device, characterized in that: include: An acquisition module is used to acquire the behavior data to be processed; each piece of the behavior data to be processed is associated with a corresponding specific identifier; the specific identifier includes one or more of a mobile phone number identifier and a non-mobile phone number identifier; A judgment module, used for, when the behavior data to be processed is associated with the mobile phone number identifier, using the mobile phone number identifier as a core identifier and performing an association judgment based on the specific identifier; A first merging module, configured to merge the core identifier with the non-mobile number identifier to generate a customer identifier when the mobile number corresponding to the core identifier corresponds to the unique non-mobile number identifier; An integration module is used to integrate and output the behavior data to be processed based on the customer identification.
9. A data processing device, characterized in that: include: Memory for storing computer programs; A processor, configured to implement the steps of the data processing method according to any one of claims 1 to 7 when executing the computer program.
10. A readable storage medium, characterized in that: The readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the data processing method according to any one of claims 1 to 7 are implemented.