Data processing method, device, computing device and storage medium

Abstract

The present invention discloses a data processing method, apparatus, computing device and storage medium, which comprises: collecting user data of each user in multiple business domains, analyzing and integrating the user data, establishing a corresponding relationship between all user identifiers of each user in multiple business domains and user universal identity identifiers; obtaining the pending business needs of the business end, disassembling the business needs, and obtaining multiple business indicators; determining user atomic tags based on the multiple business indicators, and generating derived tags using the user atomic tags; searching for target users whose user tags match the derived tags, obtaining the target user's user universal identity identifier, and correspondingly storing the derived tags and the target user's user universal identity identifier. The present invention can effectively connect all user data, establish a tag system based on the business indicators of the pending business needs of the business end, thereby helping the business end to discover target users and conduct layered and precise operations.

Description

Technical Field

[0001] The present invention relates to the field of data analysis technology, and in particular to a data processing method, apparatus, computing device and storage medium. Background Art

[0002] Analytical methods based on internet user behavior can identify potential issues in marketing, product, and business promotion, modify application product interaction design, enhance user experience, and achieve more refined and precise product planning and marketing, thereby achieving better product growth. Existing methods for analyzing internet user behavior are generally based on internet user growth methods. They collect online user behavior through tracking points and then clean, process, and integrate user behavior data with order, membership, and other data. After integration, the internet user situation is visualized through operational models and processed into data dashboards or reports. Based on the operational models, internet users are further categorized and targeted for promotion and marketing to achieve member loyalty, member value, and user growth.

[0003] Existing technologies primarily capture behavioral data for internet products. However, for general retail, accurate user insights and operations require not only user behavioral data but also the integration of multi-channel user behavior, transaction data, and marketing data. Furthermore, existing technologies, using model training data, can only address user growth, but the general retail industry needs to address both user growth and transaction growth. Furthermore, while existing models can identify marketing and promotion issues, they cannot deconstruct retail sales, breaking down sales metrics and linking them to operational actions. Summary of the Invention

[0004] In view of the above problems, the present invention is proposed to provide a data processing method, apparatus, computing device and storage medium that overcome the above problems or at least partially solve the above problems.

[0005] According to one aspect of the present invention, there is provided a data processing method, comprising:

[0006] Collect user data of each user in multiple business domains, analyze and integrate the user data in multiple business domains, and establish a correspondence between all user identifiers of each user in multiple business domains and the user's universal identity identifier;

[0007] Obtaining pending business requirements from the business side, breaking down the business requirements, and obtaining multiple business indicators;

[0008] Determine a user atomic tag based on multiple business indicators, and generate a derived tag using the user atomic tag;

[0009] A target user whose user tag matches the derived tag is searched, a universal user identity identifier of the target user is obtained, and the derived tag and the universal user identity identifier of the target user are stored in correspondence.

[0010] According to another aspect of the present invention, there is provided a data processing apparatus, comprising:

[0011] The user data fusion module is used to collect user data of each user in multiple business domains, analyze and fuse the user data in multiple business domains, and establish a corresponding relationship between all user identifiers of each user in multiple business domains and the user's universal identity identifier;

[0012] A business indicator decomposition module is used to obtain pending business requirements from the business end, decompose the business requirements, and obtain multiple business indicators;

[0013] A tag generation module, configured to determine a user atomic tag based on multiple business indicators and generate a derived tag using the user atomic tag;

[0014] The storage module is used to search for a target user whose user tag matches the derived tag, obtain the universal user identity of the target user, and store the derived tag and the universal user identity of the target user in correspondence.

[0015] According to another aspect of the present invention, there is provided a computing device, comprising: a processor, a memory, a communication interface, and a communication bus, wherein the processor, the memory, and the communication interface communicate with each other via the communication bus;

[0016] The memory is used to store at least one executable instruction, and the executable instruction enables the processor to execute an operation corresponding to the above-mentioned data processing method.

[0017] According to another aspect of the present invention, a computer storage medium is provided, wherein the storage medium stores at least one executable instruction, and the executable instruction enables a processor to execute an operation corresponding to the above-mentioned data processing method.

[0018] According to a data processing method, device, computing device and storage medium of the present invention, the method includes: collecting user data of each user in multiple business domains, analyzing and integrating the user data in multiple business domains, establishing a correspondence between all user identifiers of each user in multiple business domains and user universal identity identifiers; obtaining the business needs to be processed on the business side, disassembling the business needs, and obtaining multiple business indicators; determining user atomic tags based on multiple business indicators, and generating derived tags using user atomic tags; searching for target users whose user tags match the derived tags, obtaining the user universal identity identifier of the target user, and correspondingly storing the derived tags and the user universal identity identifier of the target user. The present invention can effectively connect the full amount of user data, establish a tag system based on the business indicators of the business needs to be processed on the business side, thereby helping the business side to discover target users and conduct layered and precise operations.

[0019] The above description is only an overview of the technical solution of the present invention. In order to more clearly understand the technical means of the present invention, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are specifically listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Various other advantages and benefits will become apparent to those skilled in the art upon reading the detailed description of the preferred embodiment below. The accompanying drawings are for illustration purposes only and are not to be considered as limiting the present invention. The same reference symbols are used throughout the drawings to represent the same components. In the drawings:

[0021] Figure 1 A flow chart of a data processing method provided by an embodiment of the present invention is shown;

[0022] Figure 2 An industry OneID example diagram showing a data processing method provided by an embodiment of the present invention;

[0023] Figure 3 A schematic diagram of a user digital journey of a data processing method provided by an embodiment of the present invention is shown;

[0024] Figure 4 A schematic structural diagram of a data processing device provided by an embodiment of the present invention is shown;

[0025] Figure 5 A schematic structural diagram of a computing device provided by an embodiment of the present invention is shown. DETAILED DESCRIPTION

[0026] Exemplary embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present invention are shown in the accompanying drawings, it should be understood that the present invention can be implemented in various forms and should not be limited by the embodiments set forth herein. Rather, these embodiments are provided to enable a more thorough understanding of the present invention and to fully convey the scope of the present invention to those skilled in the art.

[0027] For the general retail industry, sales growth and structure are influenced by multiple factors, including retail formats, channels, transactions, and marketing. This invention connects multiple business domains, such as user behavior, transactions, and channels, by accessing offline and online user data. This allows us to build a universal user identity (i.e., OneID) system. By building a user tagging system, we can analyze business needs, such as sales growth targets, from the user's perspective.

[0028] Figure 1 A flow chart of an embodiment of a data processing method of the present invention is shown as follows: Figure 1 As shown, the method includes the following steps:

[0029] Step S110: collecting user data of each user in multiple business domains, analyzing and integrating the user data in multiple business domains, and establishing a correspondence between all user identifiers of each user in multiple business domains and the user's universal identity identifier.

[0030] In one optional approach, multiple business domains include: membership domain, transaction domain, and marketing domain. By integrating data from these domains, each user is assigned a globally unique identifier, known as a universal user identity. This identifier replaces identifiers such as membership accounts and mobile phone numbers across various business domains, connecting users and their behaviors across all business domains.

[0031] Figure 2 This is an example of an industry OneID diagram, such as Figure 2As shown, OneID technology means that as long as the data of each business domain is collected, the big data platform can perform standardization, normalization, data aggregation and other processing of multiple data sources, and complete the identification and data connection of business objects such as member domain, transaction domain and marketing domain through the OneID system, solve the data island, establish the associated network relationship of all OneID objects, and form an enterprise-level association system; conduct a comprehensive portrait of OneID objects based on tags, network relationships and knowledge graphs, generate OneID portrait tags, assist upper-level application scenarios, and form enterprise-level operation views and operation activities. Among them, the member domain (User Identification, UID) includes member account, phone number, name, WeChat account (such as WeChat OpenID and WeChat UnionID) and other information; the transaction domain includes customer membership level, customer table, customer detail table, member interaction data, etc.; the marketing domain includes customer relationship management system (ECRM), card and coupon center, customer service center, survey system, advertising return system information and e-commerce system information, etc. It should be noted that, Figure 2 This is just one example of a OneID relationship in the general retail industry. In this field, the content of each business domain is different based on different business backgrounds.

[0032] In the present invention, user data in the member domain, such as member ID, mobile phone number, and OpenID, can be sent to the OneID platform through simple fusion. A OneID is then obtained through the fusion service. If the user's universal identity already exists in the OneID database, the OneID service merges the existing user ID with the newly received user ID and returns the original OneID. Otherwise, a new OneID is generated for the user, thereby updating the user's user ID. The user ID includes one or more of the following: user identity, attribute, account, device, and behavior. Specifically, the user identity identifier is an identifier that can accurately determine that a user is a single user, such as an ID card, passport ID, and faceID. The attribute identifier is a user's attribute, such as mobile phone number, name, and gender. It should be noted that since the user's attribute identifier may change, the attribute identifier cannot be used to determine the same user. The account identifier includes user account information of some application software (or system) and the user's email address. It should be noted that the same user can have multiple account information in the same application software (or system). When the account identifier is uniquely bound to the user identity identifier, it can be determined that they are the same user. The device identifier includes the International Mobile Equipment Identity number (IMEI) and the local area network address (MAC address). The same user can have multiple device identifiers. When the device identifier and the attribute identifier are frequently associated, it is highly likely that they are the same user. The behavior identifier includes the cookie address, user IP address, and delivery address. The behavior identifier of the same user requires multiple features to determine and changes frequently. The behavior identifier can be sorted according to the probability of occurrence to determine the user behavior identifier.

[0033] Alternatively, algorithm fusion can be performed based on basic member / non-member attributes, social relationships, location, transaction behavior, and marketing campaign participation. After processing using a MapReduce or graph computing algorithm, entities with completely different identifiers can be merged into a single user entity. Similarly, entities with the same identifier can be split into separate user entities. When all identifiers have the same confidence, MapReduce or graph computing algorithms can be selected based on the customer's environment to complete OneID fusion. The effect is similar to simple fusion, but OneID mappings can be corrected in batches to eliminate the impact of data changes. Specifically, when OneID fusion is performed through graph computing, ID clues can be used to determine whether the user is the same. ID clues include strong and weak ID clues. Strong ID clues refer to identity clues that are likely to only point to a single ID individual, such as ID cards, passport IDs, faceIDs, fingerprints, IMEIs, and WeChat UnionIDs. Weak ID clues refer to identity clues that can point to multiple ID individuals, such as names, nicknames, MAC addresses, cookie addresses, and shipping addresses. The relationships used in graph calculations include raw relationships and logical relationships. Raw relationships refer to relationships between identity clues collected directly from the original data source, while logical relationships refer to relationships linked by the same identity clue. It should be noted that relationships linked by weak ID clues can be disassociated at any time.

[0034] In an optional manner, step S110 further includes: collecting user data of each user in multiple business domains at each journey node in the user's digital journey.

[0035] Figure 3 A diagram of the user's digital journey, such as Figure 3 As shown in the figure, at each node in the user's digital journey, user data from multiple business domains is collected. Journey nodes include adding WeChat for Business, registering for membership, browsing, adding to favorites, and adding to cart. The user data generated at these nodes includes personal information, business attribute data, interaction tracking data, purchasing behavior data, and marketing activity data.

[0036] Step S120: Obtain the pending business requirements of the business end, decompose the business requirements, and obtain multiple business indicators.

[0037] In one optional approach, the multiple business indicators include: number of users, average purchase amount, and marketing value.

[0038] In this step, under the user-centered operation background, the enterprise sales volume formula is decomposed to obtain formula (1):

[0039] Sales volume = CV M ;(1)

[0040] Among them, C is the number of users; V is the average purchase amount; M is the marketing value.

[0041] Obtain pending business needs from the business side, decompose them based on formula (1), and obtain core operational indicators and operational actions that can improve C, V, and M. Based on these core operational indicators and operational actions, multiple business indicators are obtained. For example, if the pending business need is to increase sales through user management, then the business indicators can include determining the source of sales growth, target sales users, and sales priorities.

[0042] In the process of breaking down business indicators from the growth of the number of users (C), the core key is to increase the number of people who are likely to consume and purchase. From the perspective of user operation, potential users can be identified through data. For example, by training and learning old customer data and building models, similar users can be found through the LOOKALIKE model on all media, and similar users can be identified as people who are likely to consume and purchase; or small-scale advertising, content seeding, etc. can be used to influence the cognitive population and obtain people who are likely to consume and purchase; or targeted products can be delivered to people with specific interests and obtain people who are likely to consume and purchase; or the value of users in social and marketing can be evaluated, and the consumption increase that they may bring can be determined through existing models, so that the fission population can be obtained through distribution by the user, and the fission population can be identified as people who are likely to consume and purchase, etc.

[0043] When breaking down business indicators from the perspective of average purchase amount (V), the breakdown can be carried out by analyzing life cycle information, penetration improvement information, price improvement information and new product effectiveness information; among them, life cycle information specifically includes: the user ID is in an active first-purchase state, the user ID is in an active repeat purchase state, the user ID is in an active low-frequency state, the user ID is in an active medium-frequency state, the user ID is in an active high-frequency state and the user ID is in a dormant activation state, etc.; penetration improvement information at least includes: core category penetration rate, related category penetration rate, category user penetration rate and product user penetration rate, etc.; price improvement information at least includes: an increase in the number of items in the first shopping cart, purchases of high-value items under the category, value enhancement through attribute information upgrades and the supply of new products for high-value groups, etc.; new product effectiveness information includes new product promotion information and new product planning information, etc.

[0044] In the process of decomposing business indicators from the perspective of marketing value (M), the decomposition can be carried out by analyzing the reach capability, marketing value information and marketing fission information. Among them, the reach capability information at least includes: user reach capability, user interaction value and user activity participation, etc.; the marketing value information at least includes: the value of driving membership, the value of driving sales and the value of brand voice, etc.; the marketing fission information at least includes: marketing fission evaluation and fission tree, etc.

[0045] Step S130: determining a user atomic tag according to multiple business indicators, and generating a derived tag using the user atomic tag.

[0046] In an optional manner, step S130 further includes: adding a time dimension, a business dimension and / or business limitation information to the user atomic tag to generate a derived tag.

[0047] In this step, the user atomic tag is determined based on multiple business indicators, and the time dimension, business dimension and / or business limitation information are added to the user atomic tag to generate a derived tag; for example, by disassembling the business needs to be processed, multiple business indicators are obtained based on the life cycle information, and then the user atomic tag can be determined to be user ID information in multiple states based on the multiple business indicators, and the time dimension, business dimension and / or business limitation information are added to the user atomic tag to generate a derived tag; for example, the user ID information in the dormant and activation state is extracted, which is the derived tag.

[0048] Step S140: searching for a target user whose user tag matches the derived tag, obtaining the universal user identity identifier of the target user, and storing the derived tag and the universal user identity identifier of the target user in correspondence.

[0049] Specifically, the target user whose user tag matches the derived tag is searched, the user OneID of the target user is obtained, and the derived tag and the user OneID of the target user are stored in correspondence.

[0050] In an optional manner, the method further includes step S150: acquiring user identifiers of multiple business domains corresponding to the universal user identity identifier of the target user.

[0051] Specifically, this step can obtain the user identification of the target user's user OneID in the member domain, transaction domain, and marketing domain.

[0052] In an optional manner, the user identifier includes one or more of the following identifiers: user identity identifier, attribute identifier, account identifier, device identifier, behavior identifier, etc.

[0053] In an optional manner, the method further includes step S160: sending user identifiers of multiple business domains corresponding to the universal user identity identifier of the target user to the business end, so that the business end performs business processing according to the received user identifiers.

[0054] Specifically, the business side can carry out business advertising or marketing operations based on the received user ID, thereby achieving layered and precise operations and effectively driving industry sales growth.

[0055] The method of this embodiment is adopted to collect user data of each user in multiple business domains, analyze and integrate the user data in multiple business domains, and establish a corresponding relationship between all user identifiers of each user in multiple business domains and the user's universal identity identifier; obtain the pending business needs of the business end, disassemble the business needs, and obtain multiple business indicators; determine the user atomic label based on multiple business indicators, and use the user atomic label to generate a derived label; find the target user whose user label matches the derived label, obtain the target user's user universal identity identifier, and store the derived label and the target user's user universal identity identifier in correspondence. This method can effectively connect the full amount of user data, establish a label system based on the business indicators of the pending business needs of the business end, thereby helping the business end to find target users. The business end can perform business advertising or marketing operations based on the received user identifier, thereby realizing layered and precise operations and effectively driving industry sales growth.

[0056] Figure 4 FIG. 1 shows a schematic diagram of the structure of a data processing device according to an embodiment of the present invention. Figure 4 As shown, the device includes: a user data fusion module 410, a service indicator decomposition module 420, a label generation module 430, a storage module 440 and a service processing module 450.

[0057] The user data fusion module 410 is used to collect user data of each user in multiple business domains, analyze and fuse the user data in multiple business domains, and establish a correspondence between all user identifiers of each user in multiple business domains and the user's universal identity identifier.

[0058] In an optional manner, the user data fusion module 410 is further configured to collect user data of each user in multiple business domains at each journey node in the user's digital journey.

[0059] In an optional manner, the multiple business domains include: a membership domain, a transaction domain, and a marketing domain.

[0060] In one optional approach, the multiple business indicators include: number of users, average purchase amount, and marketing value.

[0061] The business indicator decomposition module 420 is used to obtain the business requirements to be processed from the business end, decompose the business requirements, and obtain multiple business indicators.

[0062] The tag generation module 430 is configured to determine a user atomic tag according to multiple business indicators and generate a derived tag using the user atomic tag.

[0063] In an optional manner, the tag generation module 430 is further configured to add a time dimension, a business dimension and / or business definition information to the user atomic tag to generate a derived tag.

[0064] The storage module 440 is configured to search for a target user whose user tag matches the derived tag, obtain the universal user identity of the target user, and store the derived tag and the universal user identity of the target user in correspondence.

[0065] In an optional manner, the device also includes a business processing module 450, which is used to obtain user identifiers of multiple business domains corresponding to the user universal identity identifier of the target user; and send the user identifiers of multiple business domains corresponding to the user universal identity identifier of the target user to the business end, so that the business end performs business processing based on the received user identifiers.

[0066] In an optional manner, the user identifier includes one or more of the following identifiers: user identity identifier, attribute identifier, account identifier, device identifier, and behavior identifier.

[0067] The device of this embodiment collects user data of each user in multiple business domains, analyzes and integrates the user data in multiple business domains, and establishes a corresponding relationship between all user identifiers of each user in multiple business domains and the user's universal identity identifier; obtains the pending business needs of the business end, decomposes the business needs, and obtains multiple business indicators; determines the user atomic label based on multiple business indicators, and generates a derived label using the user atomic label; searches for the target user whose user label matches the derived label, obtains the target user's universal identity identifier, and stores the derived label and the target user's universal identity identifier in correspondence. This device can effectively connect all user data, establish a label system based on the business indicators of the pending business needs of the business end, and thus help the business end find target users. The business end can perform business advertising or marketing operations based on the received user identifier, thereby achieving layered and precise operations and effectively driving industry sales growth.

[0068] An embodiment of the present invention provides a non-volatile computer storage medium, wherein the computer storage medium stores at least one executable instruction, and the computer executable instruction can execute a data processing method in any of the above method embodiments.

[0069] The executable instructions can be used to cause the processor to perform the following operations:

[0070] Collect user data of each user in multiple business domains, analyze and integrate the user data in multiple business domains, and establish a correspondence between all user identifiers of each user in multiple business domains and the user's universal identity identifier;

[0071] Obtain pending business requirements from the business side, break them down, and obtain multiple business indicators;

[0072] Determine user atomic tags based on multiple business indicators and use them to generate derived tags.

[0073] A target user whose user tag matches the derived tag is found, a universal user identity identifier of the target user is obtained, and the derived tag and the universal user identity identifier of the target user are stored in correspondence.

[0074] Figure 5 The schematic diagram of the structure of the computing device embodiment of the present invention is shown. The specific embodiment of the present invention does not limit the specific implementation of the computing device.

[0075] like Figure 5 As shown, the computing device may include:

[0076] Processor, Communications Interface, Memory, and Communication Bus.

[0077] The processor, communication interface, and memory communicate with each other via a communication bus. The communication interface is used to communicate with other devices, such as clients or other server network elements. The processor is used to execute programs, specifically, the steps described in the aforementioned data processing method embodiment.

[0078] Specifically, the program may include program codes including computer operation instructions.

[0079] The processor may be a central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present invention. The one or more processors included in the server may be processors of the same type, such as one or more CPUs, or processors of different types, such as one or more CPUs and one or more ASICs.

[0080] Memory is used to store programs. The memory may include high-speed RAM memory, and may also include non-volatile memory (non-volatile memory), such as at least one disk storage.

[0081] The program can be specifically used to cause the processor to perform the following operations:

[0082] Collect user data of each user in multiple business domains, analyze and integrate the user data in multiple business domains, and establish a correspondence between all user identifiers of each user in multiple business domains and the user's universal identity identifier;

[0083] Obtain pending business requirements from the business side, break them down, and obtain multiple business indicators;

[0084] Determine user atomic tags based on multiple business indicators and use them to generate derived tags.

[0085] A target user whose user tag matches the derived tag is found, a universal user identity identifier of the target user is obtained, and the derived tag and the universal user identity identifier of the target user are stored in correspondence.

[0086] The algorithm or demonstration provided here are not inherently relevant to any particular computer, virtual system or other equipment. Various general-purpose systems can also be used together with the teachings based on this. According to the above description, it is obvious that the structure required for constructing this type of system. In addition, the embodiment of the present invention is not directed to any specific programming language yet. It should be understood that various programming languages ​​can be utilized to realize the content of the present invention described here, and the above description of specific languages ​​is for disclosing the best mode of the present invention.

[0087] In the description provided herein, numerous specific details are described. However, it is understood that embodiments of the present invention may be practiced without these specific details. In some instances, well-known methods, structures, and techniques are not shown in detail so as not to obscure the understanding of this description.

[0088] Similarly, it should be understood that in order to streamline the present invention and aid in understanding one or more of the various inventive aspects, in the above description of exemplary embodiments of the invention, various features of the embodiments of the invention are sometimes grouped together into a single embodiment, figure, or description thereof. However, this disclosed method should not be interpreted as reflecting an intention that the claimed invention requires more features than are expressly recited in each claim. Rather, as reflected in the claims below, inventive aspects lie in less than all the features of the individual embodiments disclosed above. Accordingly, the claims that follow the detailed description are hereby expressly incorporated into this detailed description, with each claim standing on its own as a separate embodiment of the invention.

[0089] Those skilled in the art will appreciate that the modules in the devices in the embodiments may be adaptively changed and arranged in one or more devices different from the embodiments. The modules or units or components in the embodiments may be combined into one module or unit or component, and in addition may be divided into multiple submodules or subunits or subcomponents. All features disclosed in this specification (including the accompanying claims, abstracts and drawings) and all processes or units of any method or device disclosed herein may be combined in any combination, except that at least some of such features and / or processes or units are mutually exclusive. Unless expressly stated otherwise, each feature disclosed in this specification (including the accompanying claims, abstracts and drawings) may be replaced by an alternative feature providing the same, equivalent or similar purpose.

[0090] Furthermore, those skilled in the art will appreciate that although some embodiments herein include certain features included in other embodiments but not other features, combinations of features from different embodiments are intended to be within the scope of the present invention and to form different embodiments. For example, in the claims below, any of the claimed embodiments may be used in any combination.

[0091] The various component embodiments of the present invention can be implemented in hardware, or in software modules running on one or more processors, or in a combination thereof. It will be appreciated by those skilled in the art that a microprocessor or digital signal processor (DSP) can be used in practice to implement some or all of the functions of some or all of the components according to an embodiment of the present invention. The present invention can also be implemented as a device or apparatus program (e.g., a computer program and a computer program product) for executing a part or all of the methods described herein. Such a program implementing the present invention can be stored on a computer-readable medium, or can have the form of one or more signals. Such a signal can be downloaded from an Internet website, or provided on a carrier signal, or provided in any other form.

[0092] It should be noted that the above embodiments illustrate rather than limit the invention, and that alternative embodiments may be devised by a person skilled in the art without departing from the scope of the appended claims. In the claims, any reference signs placed between brackets should not be construed as limiting the claims. The word "comprising" does not exclude the presence of elements or steps not listed in the claims. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The present invention may be implemented by means of hardware comprising several different elements and by means of appropriately programmed computers. In a unit claim enumerating several means, several of these means may be embodied by the same item of hardware. The use of the words first, second, and third etc. does not indicate any order. These words may be interpreted as names. The steps in the above embodiments should not be understood as limiting the order of execution unless otherwise specified.

Claims

1. A data processing method, characterized in that: include: Collect user data of each user in multiple business domains, analyze and integrate the user data in multiple business domains, and establish a correspondence between all user identifiers of each user in multiple business domains and the user's universal identity identifier; Obtaining pending business requirements from the business side, breaking down the business requirements, and obtaining multiple business indicators; Determine a user atomic tag based on multiple business indicators, and generate a derived tag using the user atomic tag; Searching for a target user whose user tag matches the derived tag, obtaining a universal user identity identifier of the target user, and storing the derived tag and the universal user identity identifier of the target user in correspondence; The decomposing of the business requirements to obtain multiple business indicators further includes: Based on formula (1), the business needs are decomposed to obtain core operating indicators and operating actions for increasing the number of users, average purchase amount and marketing value. Based on the core operating indicators and operating actions, multiple business indicators are obtained; formula (1) is: Sales volume = CV M ;(1) Where C is the number of users; V is the average purchase amount; M is the marketing value; The step of generating a derived tag using the user atomic tag further includes: A time dimension, a business dimension and / or business limitation information are added to the user atomic tag to generate a derived tag.

2. The method according to claim 1, characterized in that After storing the derived tag and the universal user identity of the target user in correspondence, the method further includes: Obtaining user identifiers of multiple business domains corresponding to the universal user identity identifier of the target user; The user identifiers of multiple service domains corresponding to the universal user identity identifier of the target user are sent to the service end, so that the service end performs service processing according to the received user identifiers.

3. The method according to claim 2, characterized in that The collecting of user data of each user in multiple service domains further includes: At each journey node in the user's digital journey, collect user data from each user in multiple business domains.

4. The method according to any one of claims 1 to 3, characterized in that Multiple business domains include: membership domain, transaction domain and marketing domain.

5. The method according to any one of claims 1 to 3, characterized in that The user identifier includes one or more of the following identifiers: user identity identifier, attribute identifier, account identifier, device identifier, and behavior identifier.

6. A data processing device, characterized in that: include: The user data fusion module is used to collect user data of each user in multiple business domains, analyze and fuse the user data in multiple business domains, and establish a corresponding relationship between all user identifiers of each user in multiple business domains and the user's universal identity identifier; A business indicator decomposition module is used to obtain pending business requirements from the business end, decompose the business requirements, and obtain multiple business indicators; A tag generation module, configured to determine a user atomic tag based on multiple business indicators and generate a derived tag using the user atomic tag; a storage module, configured to search for a target user whose user tag matches the derived tag, obtain the universal user identity identifier of the target user, and store the derived tag and the universal user identity identifier of the target user in correspondence; The business indicator decomposition module is further used to: Based on formula (1), the business needs are decomposed to obtain core operating indicators and operating actions for increasing the number of users, average purchase amount and marketing value. Based on the core operating indicators and operating actions, multiple business indicators are obtained; formula (1) is: Sales volume = CV M ;(1) Where C is the number of users; V is the average purchase amount; M is the marketing value; The tag generation module is further configured to add a time dimension, a business dimension and / or business limitation information to the user atomic tag to generate a derived tag.

7. A computing device, characterized in that include: A processor, a memory, a communication interface, and a communication bus, wherein the processor, the memory, and the communication interface communicate with each other via the communication bus; The memory is used to store at least one executable instruction, and the executable instruction enables the processor to execute an operation corresponding to the data processing method according to any one of claims 1 to 5.

8. A computer storage medium, characterized in that The storage medium stores at least one executable instruction, and the executable instruction enables the processor to execute an operation corresponding to the data processing method according to any one of claims 1 to 5.

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