CN114461690A

CN114461690A - Data processing method and device, computing equipment and storage medium

Info

Publication number: CN114461690A
Application number: CN202210114010.2A
Authority: CN
Inventors: 梁雅云
Original assignee: Hangzhou Bizhi Technology Co ltd
Current assignee: Hangzhou Bizhi Technology Co ltd
Priority date: 2022-01-30
Filing date: 2022-01-30
Publication date: 2022-05-10

Abstract

The invention discloses a data processing method, a data processing device, a computing device and a storage medium, wherein the method comprises the following steps: collecting user data of each user in a plurality of service domains, analyzing and fusing the user data, and establishing a corresponding relation between all user identifications of each user in the plurality of service domains and the user universal identity; acquiring a service requirement to be processed of a service end, and disassembling the service requirement to obtain a plurality of service indexes; determining a user atom label according to a plurality of service indexes, and generating a derived label by using the user atom label; and searching a target user with the user label matched with the derived label, acquiring the user general identity of the target user, and correspondingly storing the derived label and the user general identity of the target user. The invention can effectively get through the user full data, and establishes a label system based on the service index of the service requirement to be processed at the service end, thereby helping the service end to find the target user and carry out layered accurate operation.

Description

Data processing method and device, computing equipment and storage medium

Technical Field

The invention relates to the technical field of data analysis, in particular to a data processing method, a data processing device, computing equipment and a storage medium.

Background

The analysis method based on the internet user behaviors can find possible problems in marketing, products and business promotion, modify application product interactive design, improve user experience, realize more precise and accurate product planning and marketing, and enable products to obtain better growth. After the integration, the internet user condition is visualized through the operation model, the internet user condition is processed into a data billboard or a report, the internet users are further classified according to the operation model, and the popularization and the marketing are performed specifically, so that the operation of member loyalty, the operation of member value and the operation of user growth are realized.

The data acquired in the prior art is mainly behavior data for internet products, but for general retail, not only user behavior data is needed, but also user multi-channel behavior, transaction and marketing data are integrated to realize accurate user insight and operation. Secondly, in the prior art, only the problem of the increase of the number of users can be solved through model training data, but the general retail industry needs to solve not only the increase of the number but also the increase of transactions. On the other hand, although the existing model can find out the problem in marketing promotion, the sales of retail cannot be deconstructed, and the sales index cannot be disassembled and associated with the operation action.

Disclosure of Invention

In view of the above, the present invention has been made to provide a data processing method, apparatus, computing device and storage medium that overcome or at least partially address the above-mentioned problems.

According to an aspect of the present invention, there is provided a data processing method including:

collecting user data of each user in a plurality of service domains, analyzing and fusing the user data in the plurality of service domains, and establishing a corresponding relation between all user identifications of each user in the plurality of service domains and the user universal identity;

acquiring a service requirement to be processed of a service end, and disassembling the service requirement to obtain a plurality of service indexes;

determining a user atom label according to a plurality of service indexes, and generating a derived label by using the user atom label;

and searching a target user with a user tag matched with the derived tag, acquiring a user general identity of the target user, and correspondingly storing the derived tag and the user general identity of the target user.

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

the user data fusion module is used for collecting the user data of each user in a plurality of service domains, analyzing and fusing the user data in the plurality of service domains and establishing the corresponding relation between all user identifications of each user in the plurality of service domains and the user universal identity;

the service index disassembling module is used for acquiring a service requirement to be processed of a service end, and disassembling the service requirement to obtain a plurality of service indexes;

the label generation module is used for determining a user atom label according to a plurality of service indexes and generating a derived label by using the user atom label;

and the storage module is used for searching a target user with a user tag matched with the derived tag, acquiring a user general identity of the target user, and correspondingly storing the derived tag and the user general identity of the target user.

According to yet another aspect of the present invention, there is provided a computing device comprising: the system comprises a processor, a memory, a communication interface and a communication bus, wherein the processor, the memory and the communication interface complete mutual communication through the communication bus;

the memory is used for storing at least one executable instruction, and the executable instruction enables the processor to execute the operation corresponding to the data processing method.

According to still another aspect of the present invention, there is provided a computer storage medium having at least one executable instruction stored therein, the executable instruction causing a processor to perform operations corresponding to the data processing method as described above.

According to the invention, the data processing method, the data processing device, the computing equipment and the storage medium are provided, and the method comprises the following steps: collecting user data of each user in a plurality of service domains, analyzing and fusing the user data in the plurality of service domains, and establishing a corresponding relation between all user identifications of each user in the plurality of service domains and the user universal identity; acquiring a service requirement to be processed of a service end, and disassembling the service requirement to obtain a plurality of service indexes; determining a user atom label according to a plurality of service indexes, and generating a derived label by using the user atom label; and searching a target user with the user label matched with the derived label, acquiring the user general identity of the target user, and correspondingly storing the derived label and the user general identity of the target user. The invention can effectively get through the user full data, and establishes a label system based on the service index of the service requirement to be processed at the service end, thereby helping the service end to find the target user and carry out layered accurate operation.

The above description is only an overview of the technical solutions of the present invention, and the present invention can be implemented in accordance with the content of the description so as to make the technical means of the present invention more clearly understood, and the above and other objects, features, and advantages of the present invention will be more clearly understood.

Drawings

Various other advantages and benefits will become apparent to those of ordinary skill in the art upon reading the following detailed description of the preferred embodiments. The drawings are only for purposes of illustrating the preferred embodiments and are not to be construed as limiting the invention. Also, like reference numerals are used to refer to like parts throughout the drawings. In the drawings:

FIG. 1 is a flow chart of a data processing method according to an embodiment of the present invention;

FIG. 2 is an exemplary diagram of industry OneID of a data processing method according to an embodiment of the present invention;

FIG. 3 is a schematic diagram of a user's digital tour illustrating a data processing method according to an embodiment of the present invention;

fig. 4 is a schematic structural diagram of a data processing apparatus according to an embodiment of the present invention;

fig. 5 is a schematic structural diagram of a computing device provided by an embodiment of the present invention.

Detailed Description

Exemplary embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the invention are shown in the drawings, it should be understood that the invention can be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the invention to those skilled in the art.

For the retail industry, the growth and composition of sales is influenced by multiple factors, including retail status, channel, trading and marketing. In the invention, a user data is accessed on line and off line, a plurality of service domain data such as user behaviors, transactions, channels and the like are communicated, a user universal identity (namely OneID) system is constructed, and a user label system is constructed to disassemble service requirements such as sales growth targets and the like from the user perspective.

Fig. 1 shows a flow chart of an embodiment of a data processing method of the present invention, as shown in fig. 1, the method includes the following steps:

step S110: collecting user data of each user in a plurality of service domains, analyzing and fusing the user data in the plurality of service domains, and establishing a corresponding relation between all user identifications of each user in the plurality of service domains and the user universal identity.

In an alternative, the plurality of service domains comprises: a member domain, a transaction domain, and a marketing domain. The method includes the steps of fusing data from a plurality of service domains such as a member domain, a transaction domain, a marketing domain and the like, endowing a globally unique identifier for each user, namely a user universal identity identifier, for replacing identifiers such as member account numbers, mobile phone numbers and the like of each service domain, and getting through users and behaviors thereof in all the service domains.

Fig. 2 is an exemplary diagram of OneID in the industry, and as shown in fig. 2, the OneID technology is that as long as data of each business domain is collected, a big data platform can perform standardization, normalization, data aggregation and other processing of multiple data sources, and completes business object identification and data communication of a member domain, a transaction domain, a marketing domain and the like through an OneID system, solves a data island, establishes an association network relationship of all OneID objects, and forms an enterprise-level association system; the OneID object is comprehensively portrait based on the label, the network relation and the knowledge map, an OneID portrait label is generated, an upper application scene is assisted, and an enterprise-level operation view and operation activities are formed. The member domain (UID) includes information such as a member account, a phone, a name, a wechat account (e.g., wechat OpenID and wechat UnionID); the transaction domain comprises client member grades, a client table, a client detailed table, member interaction data and the like; the marketing domain comprises a customer relationship management system (ECRM), a card center, a customer service center, a research system, advertisement return system information, e-commerce system information and the like. It should be noted that fig. 2 is only one example of OneID relationship shown in the retail industry, and in the field, the contents of the business domains are different based on different business backgrounds.

In the invention, user data of a member domain, such as member ID, mobile phone number, OpenID and the like, can be sent to an OneID platform through simple fusion, OneID is obtained through fusion service, if a universal identity mark of a user exists in an OneID database, the OneID service combines the existing user mark and a newly-transmitted user mark and returns the user mark to the original OneID, and otherwise, a new OneID is generated for the user so as to update the user mark of the user. Wherein the user identification comprises one or more of the following identifications: user identity identification, attribute identification, account identification, equipment identification and behavior identification. Specifically, the user ID is an ID that can accurately determine that the user is a user, such as an ID card ID, a passport ID, a faceID, and the like; the attribute identifier is an attribute of the user, such as a mobile phone number, a name, a gender, and the like, and it should be noted that the attribute identifier of the user may be changed, and therefore the attribute identifier cannot be determined as the same user; the account id includes user account information of some application software (or systems) and a mailbox address of the user, it should be noted that the same user may have multiple account information in the same application software (or system), and when the account id is uniquely bound to the user id, the user id can be determined to be the same user; the device identifier includes an International Mobile Equipment Identity number (IMEI), a local area network Address (MAC Address), and the like, and a plurality of device identifiers can be used by a same user, and when the device identifier and the attribute identifier are frequently associated, the same user can be determined by a large probability; the behavior identification comprises a cookie address, a user IP address, a receiving address and the like, the behavior identification of the same user needs a plurality of characteristics to be determined, the change frequency is high, sequencing can be carried out according to the occurrence probability of the behavior identification, and the user behavior identification is determined.

In an alternative manner, algorithm fusion can also be performed based on basic attributes of members/non-members, social relationships, geographic location attributes, transaction behavior and marketing campaign participation behavior. After being processed by a map-reduce (MapReduce) algorithm or a graph calculation algorithm, entities with completely different identifications may also be fused into one user entity, and similarly, entities with the same identification may also be split into different user entities; when the confidence degrees of all the identifications are the same, a MapReduce or graph calculation algorithm can be selected according to the client environment to complete the OneID fusion. The effect is similar to simple fusion, but OneID mapping can be corrected in batch, and influence caused by data change is eliminated. Specifically, when OneID fusion is performed through graph calculation, whether the users are the same user can be determined according to ID clues, wherein the ID clues comprise strong ID clues and weak ID clues; wherein, the strong ID clue refers to an identity clue that can only point to one ID individual at a large probability, such as ID card ID, passport ID, faceID, fingerprint, IMEI, wechat UnionID, and the like; a weak ID thread refers to an identity thread that may point to multiple ID individuals, such as: name, nickname, MAC address, cookie address, shipping address, etc. The incidence relation during graph calculation comprises an original incidence relation and a logic incidence relation; the original incidence relation refers to the incidence relation among the identity clues directly acquired through an original data source; logical associations refer to associations that are related together by the same identity thread. It should be noted that the association relationship associated by the weak ID clue can be disassociated at any time.

In an optional manner, step S110 further includes: user data for respective users at a plurality of business domains is collected at respective itinerary nodes in the user digital itinerary.

FIG. 3 is a schematic diagram of a user digital itinerary, as shown in FIG. 3, where user data for various users in multiple business domains is collected at various itinerary nodes in the user digital itinerary. Wherein the trip nodes include: adding enterprise Wechat (adding enterprise Wechat), registering (adding member), browsing, collecting, adding purchase and the like, and collecting user data generated by the user at different journey nodes, such as personal information data, business attribute data, interaction buried point data, purchasing behavior data, marketing activity data and the like.

Step S120: and acquiring the service requirement to be processed of the service end, and disassembling the service requirement to obtain a plurality of service indexes.

In an alternative, the plurality of service indicators includes: number of users, average purchase amount, and marketing value.

In this step, under the operation background with the user as the center, the formula of enterprise sales is disassembled to obtain formula (1):

sales yield (CV)^M；(1)

Wherein C is the number of users; v is the average purchase amount; m is the marketing value.

The method comprises the steps of obtaining to-be-processed service requirements of a service end, disassembling the service requirements based on the formula (1), obtaining core operation indexes and operation actions capable of improving C, V, M, and obtaining a plurality of service indexes based on the core operation indexes and the operation actions. For example, if the pending business demand is to promote sales through user operation, the business index may be to determine sales growth source, sales target user, sales priority, and the like.

In the process of disassembling the service indexes from the increase of the number (C) of the users, the core key is to increase the population with consumption and purchase, the population is disassembled from the view of user operation, potential users can be identified through data, for example, through training and learning old customer data, a model is established, similar users are found through a LOOKALIKE model on the whole media, and the similar users are determined as the population which is likely to be consumed and purchased; or the cognitive population is influenced by small-scale advertisement delivery, content grass planting and the like, so that the population which is possibly consumed and purchased is obtained; or carrying out targeted commodity putting on specific interest groups to obtain groups which are likely to be consumed and purchased; or evaluating the value of the user in social contact and marketing, determining consumption increment possibly brought by the user through an existing model, distributing the user to obtain a fission group, determining the fission group as a group which is possibly consumed and purchased, and the like.

When the business index is disassembled from the average purchase amount (V), the business index can be disassembled by analyzing the aspects of life cycle information, penetration promotion information, price promotion information, new product efficiency information and the like; the lifecycle information specifically includes: the user ID is in an active first-purchase state, the user ID is in an active second-purchase state, the user ID is in an active low-frequency state, the user ID is in an active intermediate-frequency state, the user ID is in an active high-frequency state, the user ID is in a deep sleep promoting state and the like; the permeation boost information includes at least: core category permeability, associated category permeability, category user permeability, commodity user permeability and the like; the price boost information includes at least: the method comprises the following steps of increasing the number of commodities of a first shopping cart, purchasing high-value commodities under categories, upgrading and increasing the value through attribute information, supplying new commodities to high-value crowds and the like; the new product efficiency information comprises new product promotion information, new product planning information and the like.

In the process of disassembling the business indexes from the marketing value (M), the business indexes can be disassembled by analyzing the aspects of the reach ability, the marketing value information, the marketing fission information and the like; wherein the touch capability information at least includes: user reach ability, user interaction value, user activity engagement and the like; the marketing value information at least includes: driving the value of the entrance, the value of the sale, the value of the brand volume, and the like; marketing fission information includes at least: marketing fission assessment and fission trees, and the like.

Step S130: and determining a user atom label according to the plurality of service indexes, and generating a derived label by using the user atom label.

In an optional manner, step S130 further includes: adding time dimension, service dimension and/or service definition information to the user atom label to generate a derivative label.

In the step, a user atom label is determined according to a plurality of service indexes, time dimension, service dimension and/or service limiting information are added to the user atom label, and a derived label is generated; for example, by disassembling a service requirement to be processed, obtaining a plurality of service indexes according to life cycle information, determining that a user atom label is user ID information in a plurality of states according to the plurality of service indexes, adding time dimension, service dimension and/or service restriction information to the user atom label, and generating a derivative label; for example, the user ID information in the deep sleep promoting state is extracted, i.e. the derived tag.

Step S140: and searching a target user with the user label matched with the derived label, acquiring the user general identity of the target user, and correspondingly storing the derived label and the user general identity of the target user.

Specifically, a target user with a user tag matched with 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 correspondingly stored.

In an optional manner, the method further includes step S150: and acquiring user identifications of a plurality of service domains corresponding to the user general identification of the target user.

Specifically, this step can obtain the user identities of the user OneID with the target user in the affiliate domain, the transaction domain, and the marketing domain.

In an alternative approach, the user identification includes one or more of the following identifications: user identity identification, attribute identification, account identification, equipment identification, behavior identification and the like.

In an optional manner, the method further includes step S160: and sending the user identifications of the plurality of service domains corresponding to the user general identification of the target user to the service end so that the service end can perform service processing according to the received user identifications.

Specifically, the service end can perform operations such as service advertisement putting or marketing operation according to the received user identification, so that layered accurate operation is realized, and the industry sales growth is effectively driven.

By adopting the method of the embodiment, the user data of each user in a plurality of service domains is collected, the user data in the plurality of service domains is analyzed and fused, and the corresponding relation between all user identifications of each user in the plurality of service domains and the user universal identity is established; acquiring a service requirement to be processed of a service end, and disassembling the service requirement to obtain a plurality of service indexes; determining a user atom label according to a plurality of service indexes, and generating a derived label by using the user atom label; and searching a target user with the user label matched with the derived label, acquiring the user general identity of the target user, and correspondingly storing the derived label and the user general identity of the target user. The method can effectively get through the user total data, and a label system is established based on the service index of the service requirement to be processed by the service end, so that the service end is helped to find the target user, and the service end can carry out operations such as service advertisement putting or marketing operation according to the received user identification, thereby realizing layered accurate operation and effectively driving the industry sales growth.

Fig. 4 shows a schematic structural diagram of an embodiment of a data processing apparatus according to the present invention. As shown in fig. 4, the apparatus includes: the system comprises a user data fusion module 410, a service index dismantling module 420, a label generation module 430, a storage module 440 and a service processing module 450.

The user data fusion module 410 is configured to collect user data of each user in multiple service domains, analyze and fuse the user data in the multiple service domains, and establish a correspondence between all user identifiers of each user in the multiple service domains and the user universal identity identifier.

In an optional manner, the user data fusion module 410 is further configured to: user data for respective users at a plurality of business domains is collected at respective itinerary nodes in the user digital itinerary.

In an alternative, the plurality of service domains comprises: a member domain, a transaction domain, and a marketing domain.

The service index disassembling module 420 is configured to acquire a service requirement to be processed at the service end, and disassemble the service requirement to obtain a plurality of service indexes.

And the tag generation module 430 is configured to determine a user atom tag according to the multiple service indexes, and generate a derivative tag by using the user atom tag.

In an alternative manner, the tag generation module 430 is further configured to: adding time dimension, service dimension and/or service definition information to the user atom label to generate a derivative label.

The storage module 440 is configured to search for a target user whose user tag matches the derivative tag, obtain a user universal identity of the target user, and correspondingly store the derivative tag and the user universal identity of the target user.

In an optional manner, the apparatus further includes a service processing module 450, configured to obtain user identifiers of multiple service domains corresponding to the user universal identity of the target user; and sending the user identifications of the plurality of service domains corresponding to the user general identification of the target user to the service end so that the service end can perform service processing according to the received user identifications.

In an alternative approach, the user identification includes one or more of the following identifications: user identity identification, attribute identification, account identification, equipment identification and behavior identification.

By adopting the device of the embodiment, the user data of each user in a plurality of service domains is collected, the user data in the plurality of service domains is analyzed and fused, and the corresponding relation between all user identifications of each user in the plurality of service domains and the user universal identity is established; acquiring a service requirement to be processed of a service end, and disassembling the service requirement to obtain a plurality of service indexes; determining a user atom label according to a plurality of service indexes, and generating a derived label by using the user atom label; and searching a target user with the user label matched with the derived label, acquiring the user general identity of the target user, and correspondingly storing the derived label and the user general identity of the target user. The device can effectively get through the user's full data, and based on the business index of the business demand to be processed at the business end, a label system is established, thereby helping the business end to find the target user, and the business end can carry out operations such as business advertisement putting or marketing operation according to the received user identification, thereby realizing the layered accurate operation, and effectively driving the industry sale to increase.

An embodiment of the present invention provides a non-volatile computer storage medium, where at least one executable instruction is stored in the computer storage medium, and the computer executable instruction may execute a data processing method in any method embodiment described above.

The executable instructions may be specifically configured to cause the processor to:

and searching a target user with the user label matched with the derived label, acquiring the user general identity of the target user, and correspondingly storing the derived label and the user general identity of the target user.

Fig. 5 is a schematic structural diagram of an embodiment of a computing device according to the present invention, and a specific embodiment of the present invention does not limit a specific implementation of the computing device.

As shown in fig. 5, the computing device may include:

a processor (processor), a Communications Interface (Communications Interface), a memory (memory), and a Communications bus.

Wherein: the processor, the communication interface, and the memory communicate with each other via a communication bus. A communication interface for communicating with network elements of other devices, such as clients or other servers. The processor is configured to execute a program, and may specifically execute relevant steps in the foregoing data processing method embodiment.

In particular, the program may include program code comprising computer operating instructions.

The processor may be a central processing unit CPU or an application Specific Integrated circuit asic or one or more Integrated circuits configured to implement embodiments of the present invention. The server comprises one or more processors, which can be the same type of processor, such as one or more CPUs; or may be different types of processors such as one or more CPUs and one or more ASICs.

And the memory is used for storing programs. The memory may comprise high-speed RAM memory, and may also include non-volatile memory (non-volatile memory), such as at least one disk memory.

The program may specifically be adapted to cause a processor to perform the following operations:

The algorithms or displays presented herein are not inherently related to any particular computer, virtual system, or other apparatus. Various general purpose systems may also be used with the teachings herein. The required structure for constructing such a system is apparent from the description above. In addition, embodiments of the present invention are not directed to any particular programming language. It is appreciated that a variety of programming languages may be used to implement the teachings of the present invention as described herein, and any descriptions of specific languages are provided above to disclose the best mode of the invention.

In the description provided herein, numerous specific details are set forth. It is understood, however, that embodiments of the invention may be practiced without these specific details. In some instances, well-known methods, structures and techniques have not been shown in detail in order not to obscure an understanding of this description.

Similarly, it should be appreciated that in the foregoing description of exemplary embodiments of the invention, various features of the embodiments of the invention are sometimes grouped together in a single embodiment, figure, or description thereof for the purpose of streamlining the invention and aiding in the understanding of one or more of the various inventive aspects. However, the disclosed method should not be interpreted as reflecting an intention that: that the invention as claimed requires more features than are expressly recited in each claim. Rather, as the following claims reflect, inventive aspects lie in less than all features of a single foregoing disclosed embodiment. Thus, the claims following the detailed description are hereby expressly incorporated into this detailed description, with each claim standing on its own as a separate embodiment of this invention.

Those skilled in the art will appreciate that the modules in the device in an embodiment may be adaptively changed and disposed in one or more devices different from the embodiment. The modules or units or components of the embodiments may be combined into one module or unit or component, and furthermore they may be divided into a plurality of sub-modules or sub-units or sub-components. All of the features disclosed in this specification (including any accompanying claims, abstract and drawings), and all of the processes or elements of any method or apparatus so disclosed, may be combined in any combination, except combinations where at least some of such features and/or processes or elements are mutually exclusive. Each feature disclosed in this specification (including any accompanying claims, abstract and drawings) may be replaced by alternative features serving the same, equivalent or similar purpose, unless expressly stated otherwise.

Furthermore, those skilled in the art will appreciate that while some embodiments herein include some features included in other embodiments, rather than other features, combinations of features of different embodiments are meant to be within the scope of the invention and form different embodiments. For example, in the following claims, any of the claimed embodiments may be used in any combination.

The various component embodiments of the invention may be implemented in hardware, or in software modules running on one or more processors, or in a combination thereof. Those skilled in the art will appreciate that a microprocessor or Digital Signal Processor (DSP) may be used in practice to implement some or all of the functionality of some or all of the components according to embodiments of the present invention. The present invention may also be embodied as apparatus or device programs (e.g., computer programs and computer program products) for performing a portion or all of the methods described herein. Such programs implementing the present invention may be stored on computer-readable media or may be in the form of one or more signals. Such a signal may be downloaded from an internet website or provided on a carrier signal or in any other form.

It should be noted that the above-mentioned embodiments illustrate rather than limit the invention, and that those skilled in the art will be able to design alternative embodiments without departing from the scope of the appended claims. In the claims, any reference signs placed between parentheses shall not be construed as limiting the claim. The word "comprising" does not exclude the presence of elements or steps not listed in a claim. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The invention may be implemented by means of hardware comprising several distinct elements, and by means of a suitably programmed computer. In the unit claims enumerating several means, several of these means may be embodied by one and the same item of hardware. The usage of the words first, second and third, etcetera do not indicate any ordering. These words may be interpreted as names. The steps in the above embodiments should not be construed as limiting the order of execution unless specified otherwise.

Claims

1. A data processing method, comprising:

and searching a target user with a user label matched with the derived label, acquiring a user universal identity of the target user, and correspondingly storing the derived label and the user universal identity of the target user.

2. The method of claim 1, wherein after the storing the derived label and the user universal identity of the target user, the method further comprises:

acquiring user identifications of a plurality of service domains corresponding to the user general identification of the target user;

and sending the user identifications of the plurality of service domains corresponding to the user general identification of the target user to the service end so that the service end can perform service processing according to the received user identification.

3. The method of claim 2, wherein collecting user data for each user in a plurality of service domains further comprises:

user data for respective users at a plurality of business domains is collected at respective itinerary nodes in the user digital itinerary.

4. A method according to any of claims 1-3, characterized in that the plurality of service domains comprises: a member domain, a transaction domain, and a marketing domain.

5. The method of claim 4, wherein the plurality of traffic indicators comprises: number of users, average purchase amount, and marketing value.

6. The method of claim 5, wherein the generating a derivative label using the user atomic label further comprises:

and adding time dimension, service dimension and/or service definition information to the user atom label to generate a derivative label.

7. A method as claimed in any one of claims 1 to 6, wherein the user identity comprises one or more of: user identity identification, attribute identification, account identification, equipment identification and behavior identification.

8. A data processing apparatus, comprising:

9. A computing device, comprising: the system comprises a processor, a memory, a communication interface and a communication bus, wherein the processor, the memory and the communication interface complete mutual communication through the communication bus;

the memory is used for storing at least one executable instruction, and the executable instruction causes the processor to execute the operation corresponding to the data processing method according to any one of claims 1-7.

10. A computer storage medium having at least one executable instruction stored therein, the executable instruction causing a processor to perform operations corresponding to the data processing method according to any one of claims 1 to 7.