Behavior attribution method and device, computer equipment, storage medium and program product

Abstract

The invention relates to a behavior attribution method and device, computer equipment, a storage medium and a program product. The method comprises the following steps: acquiring user description data collected during a promotion activity; determining a target user account according to the user description data; the target user account is a user account of an activity crowd conforming to the promotion activity; under the condition of detecting that the target user account triggers the target behavior event, determining promotion activity information of the target behavior event; the target behavior event is a behavior event conforming to a preset trigger event; the promotion activity information is description information of a promotion activity triggered by the target behavior event; and generating a promotion activity effect report according to the target behavior event and the promotion activity information. By adopting the method, the efficiency of behavior attribution analysis can be improved.

Description

Technical Field

[0001] The present application relates to the field of big data technology, and in particular to a behavior attribution method, apparatus, computer equipment, computer-readable storage medium, and computer program product. Background Art

[0002] With the rapid development of Internet technology, the field of digital marketing is facing the challenge of measuring the effectiveness of promotional activities in a multi-channel and multi-touchpoint environment. In order to accurately measure the actual impact of promotional activities on user conversion behavior, behavioral attribution technology is widely used. Behavioral attribution refers to analyzing the user's behavioral data on different promotion channels to determine which promotional activities have played a key role in promoting user conversion and quantify the contribution of each promotional activity. However, traditional behavioral attribution methods often rely on professionals to manually integrate and analyze data during the attribution data collection stage, resulting in low efficiency of behavioral attribution analysis. Summary of the invention

[0003] Based on this, it is necessary to provide a behavior attribution method, apparatus, computer equipment, computer-readable storage medium and computer program product that can improve the efficiency of behavior attribution analysis in response to the above technical problems.

[0004] In a first aspect, the present application provides a behavior attribution method, comprising:

[0005] Obtain user profile data collected during the promotion;

[0006] Determine a target user account according to the user description data; the target user account is a user account that meets the activity group of the promotion activity;

[0007] In the case of detecting that the target user account triggers a target behavior event, determining promotion activity information of the target behavior event; the target behavior event is a behavior event that meets a preset trigger event; the promotion activity information is description information of the promotion activity triggered by the target behavior event;

[0008] Generate a promotion activity effect report based on the target behavior event and the promotion activity information.

[0009] In one embodiment, generating a promotion activity effect report according to the target behavior event and the promotion activity information includes:

[0010] Record at least one of the target behavior events triggered by the target user account within a preset statistical time period and promotion activity information of each of the target behavior events;

[0011] Determining attribution activity information from each piece of promotion activity information according to a priority of each piece of promotion activity information;

[0012] The promotion activity effect report is generated according to the attribution activity information and the target behavior event to which the attribution activity information is attributed.

[0013] In one embodiment, generating the promotion activity effect report according to the attribution activity information and the target behavior event to which the attribution activity information is attributed includes:

[0014] Generate key attribution activity data according to the attribution activity information and the target behavior event to which the attribution activity information is attributed;

[0015] Generate activity exposure data according to other promotion activity information that does not belong to the attribution activity information in each of the promotion activity information, and the target behavior event to which the other promotion activity information belongs;

[0016] Generate the promotion activity effect report based on the key attribution activity data and the activity exposure data.

[0017] In one embodiment, determining a target user account according to the user description data includes:

[0018] In a case where the user behavior represented by the user description data conforms to the preset entity behavior, determining that the user account to which the user description data belongs belongs to the target user account;

[0019] In a case where the user attributes represented by the user description data conform to the preset entity attributes, it is determined that the user account to which the user description data belongs belongs to the target user account.

[0020] In one embodiment, obtaining user description data collected during the promotion activity includes:

[0021] Get the validity period of the promotion activity;

[0022] When the current time is within the validity period of the activity, user description data collected during the promotion activity is obtained.

[0023] In one embodiment, before obtaining the user description data collected during the promotion activity, the method further includes:

[0024] Acquire creation information of the promotion activity; the creation information includes the activity validity period, priority, preset triggering event and activity population of the promotion activity;

[0025] The promotion activity is created according to the creation information.

[0026] In a second aspect, the present application also provides a behavior attribution device, including:

[0027] An acquisition module, used to acquire user description data collected during the promotion activity;

[0028] An account determination module is used to determine a target user account according to the user description data; the target user account is a user account that meets the activity group of the promotion activity;

[0029] An activity determination module, for determining promotion activity information of a target behavior event when detecting that the target user account triggers a target behavior event; the target behavior event is a behavior event that meets a preset trigger event; the promotion activity information is description information of the promotion activity triggered by the target behavior event;

[0030] A generation module is used to generate a promotion activity effect report based on the target behavior event and the promotion activity information.

[0031] In a third aspect, the present application further provides a computer device, comprising a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the above method when executing the computer program.

[0032] In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program implements the steps of the above method when executed by a processor.

[0033] In a fifth aspect, the present application also provides a computer program product, including a computer program, which implements the steps of the above method when executed by a processor.

[0034] The above-mentioned behavior attribution method, device, computer equipment, computer-readable storage medium and computer program product obtain user description data collected during the promotion activity; determine the target user account based on the user description data, wherein the target user account is a user account that meets the activity population of the promotion activity; determine the promotion activity information of the target behavior event when detecting that the target user account triggers the target behavior event, wherein the target behavior event is a behavior event that meets the preset trigger event, wherein the promotion activity information is the description information of the promotion activity triggered by the target behavior event; generate a promotion activity effect report based on the target behavior event and the promotion activity information. By automatically identifying the target user account that meets the promotion activity conditions, the target behavior event triggered by the user is detected in real time, and the promotion activity information associated with it is automatically matched, thereby ensuring the comprehensiveness of data collection and the accuracy of association; in addition, by generating a promotion activity effect report, clear and systematic user behavior and activity association data are provided for subsequent attribution analysis, supporting subsequent promotion effect analysis and optimization decisions. This automated and dynamic data integration and report generation process significantly improves the efficiency and real-time performance of attribution analysis, reduces reliance on professional technical personnel, and enhances the ability to handle complex user behavior paths in a multi-channel, multi-touchpoint environment, providing more accurate and efficient technical support for promotion effectiveness evaluation in the field of digital marketing. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] In order to more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the drawings required for use in the embodiments of the present application or related technical descriptions will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0036] Figure 1 A diagram of an application environment of a behavior attribution method in an embodiment;

[0037] Figure 2 A flowchart of a behavior attribution method in an embodiment;

[0038] Figure 3 is a flow chart of a behavior attribution method in another embodiment;

[0039] Figure 4 is a structural block diagram of a behavior attribution device in one embodiment;

[0040] Figure 5 The figure is a diagram of the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0041] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0042] The behavior attribution method provided in the embodiment of the present application can be applied to Figure 1 In the application environment shown. Among them, the terminal 102 communicates with the server 104 through the network. The data storage system can store the data that the server 104 needs to process. The data storage system can be integrated on the server 104, or it can be placed on the cloud or other network servers. The terminal 102 obtains the user description data collected during the promotion activity; the terminal 102 determines the target user account according to the user description data; the target user account is a user account of the activity group that meets the promotion activity; the terminal 102 determines the promotion activity information of the target behavior event when detecting that the target user account triggers the target behavior event; the target behavior event is a behavior event that meets the preset trigger event; the promotion activity information is the description information of the promotion activity triggered by the target behavior event; the terminal 102 generates a promotion activity effect report based on the target behavior event and the promotion activity information. Among them, the terminal 102 can be, but is not limited to, various personal computers, laptops, smart phones, tablet computers, Internet of Things devices and portable wearable devices. The Internet of Things devices can be smart speakers, smart TVs, smart air conditioners, smart car devices, projection devices, etc. Portable wearable devices can be smart watches, smart bracelets, head-mounted devices, etc. The head mounted device may be a virtual reality (VR) device, an augmented reality (AR) device, smart glasses, etc. The server 104 may be an independent physical server, or a server cluster or distributed system composed of multiple physical servers, or a cloud server providing cloud computing services.

[0043] In an exemplary embodiment, Figure 2 As shown, a behavioral attribution method is provided, which can be applied to Figure 1 The terminal 102 in FIG. 1 is used as an example for explanation, including:

[0044] Step S202, obtaining user description data collected during the promotion activity.

[0045] Among them, promotional activities may include marketing activities pushed to users through digital channels to encourage users to take specific actions such as clicks, registrations, purchases, and sharing. For example, promotional activities may include giving away virtual resources (such as gift packages, coupons, etc.).

[0046] Among them, the period of the promotion activity may include the time period from the start to the end of the promotion activity. During the promotion activity, relevant user description data may be collected. It should be noted that the user description data collected during the promotion activity is not limited to the data that meets the promotion activity triggering conditions, but may also include all data related to the promotion activity, that is, the user description data includes user behavior data collected during the promotion activity that is indirectly related to the promotion activity or has potential value. For example, if it is stipulated that a promotion activity for coupon collection will be pushed only if the user stays on a certain activity page for more than 30 seconds, and the user actually only stays on the activity page for 10 seconds, although the promotion activity triggering conditions are not met, the relevant user description data of the user staying on the activity page will still be collected.

[0047] Among them, user description data may include basic user information such as user account information, account registration time, membership level, user operation information such as clicks, browsing, purchases, searches, sharing, device information such as the client's device identification and operating system, user login time, the time when the user behavior occurs, and the physical location of the location.

[0048] Optionally, the terminal may collect user description data in the following ways: setting tracking points in the user interaction interface of the application to record user operation behaviors in real time as user description data; recording user requests and access paths through server logs as user description data; monitoring user trigger operations on various channels through event monitoring services, such as clicking on advertisements, visiting activity pages, etc., as user description data; capturing and analyzing user description data in real time through a distributed data stream processing framework. The distributed data stream processing framework can efficiently process and analyze real-time data streams, and can realize real-time analysis and processing of user behaviors, thereby improving the accuracy and efficiency of attribution of user-specific behaviors.

[0049] This step can dynamically capture complete user description data during the promotion campaign without manual intervention; it can collect and update user description data in real time, and support real-time and dynamic attribution analysis and promotion effect analysis.

[0050] Step S204: determining the target user account according to the user description data.

[0051] The target user accounts are user accounts that meet the activity population of the promotion activity.

[0052] The terminal can screen out target user accounts that meet the active population of the promotion activity based on user description data and preset active population characteristics.

[0053] Exemplarily, the target user accounts may include newly registered users (e.g., registered for less than 30 days), users who have not been active for a long time (e.g., have not logged in for the past 90 days), etc. For example, newly registered users meet the activity population of the promotion activity "new user registration activity", and the promotion activity may include giving virtual resources to newly registered users to increase the user stickiness of newly registered users; for example, users who have not been active for a long time meet the activity population of the promotion activity "old user recall activity", and the promotion activity may include giving virtual resources to users who have not been active for a long time to encourage them to become active users.

[0054] Exemplarily, the target user account may also include a user account whose device identifier of the client matches the target device identifier, for example, stipulating that certain promotional activities are only applicable to users using a specific brand of mobile phones, or only applicable to users using high-end brand mobile phones.

[0055] Optionally, the distributed data stream processing framework can be used to dynamically screen out target user accounts that meet the activity population of the promotion activity in real time.

[0056] This step can automatically determine the target user accounts that meet the activity population of the promotion activity, improve the pertinence and efficiency of the promotion activity, and reduce the tediousness of operations and manual intervention.

[0057] Step S206, when it is detected that the target user account triggers a target behavior event, determine the promotion activity information of the target behavior event.

[0058] Among them, the preset trigger event can be a promotion activity trigger condition defined when the promotion activity is designed, which is used to identify which behavioral events meet the conditions for triggering the promotion activity. For example, the preset trigger events may include the number of consecutive login days exceeding the threshold, completing account registration, the duration of accessing the interface exceeding the threshold, participating in the game, creating a live broadcast room, entering the live broadcast room, speaking in the live broadcast room, staying in the live broadcast room for a period exceeding the threshold, the login time exceeding the threshold, completing user tasks, joining the anchor fan group, the value of purchased virtual resources exceeding the threshold, the value of consumed virtual resources exceeding the threshold, clicking and accessing the activity interface, etc.

[0059] The target behavior event is a behavior event that meets the preset trigger event. Optionally, the target behavior event can be a behavior event that is triggered during the promotion activity and meets any of the above preset trigger events.

[0060] Among them, the promotion activity information is the description information of the promotion activity triggered by the target behavior event. In the specific implementation, when the target user account is detected to trigger the target behavior event, the corresponding promotion activity can be automatically matched, and the description information of the promotion activity can be extracted as the promotion activity information. Exemplarily, the promotion activity information may include the activity name (such as a new user registration gift), activity rules (such as a coupon for the first registration), activity time (the start and end time of the activity), and activity channel (such as in-application notification, web page advertisement, or SMS notification).

[0061] This step can automatically complete the matching and extraction of behavioral events and promotional activity information, reducing manual intervention and improving operational efficiency; it can realize automatic analysis and processing of user behavior, thereby reducing labor costs and usage thresholds. Even users with non-professional backgrounds can easily get started and realize automated operation and management.

[0062] Step S208: Generate a promotion activity effect report based on the target behavior event and the promotion activity information.

[0063] Among them, the promotion activity effect report is used to integrate and display user behavior data and its associated promotion activity information. The promotion activity effect report may include the matching relationship between the target behavior event and the promotion activity information. For example, a user completed the registration on a certain day, and the associated promotion activity is "New User Registration Gift". The promotion activity effect report can be used as the basic data for subsequent attribution analysis to support operators in analyzing the contribution rate and conversion rate of promotion activities; it helps operators understand the overall situation of user participation in activities so as to formulate more effective marketing strategies.

[0064] Exemplarily, the operator can determine whether a certain promotion campaign is effective by analyzing the promotion campaign effect report. For example, if the promotion campaign effect report records that a target user account that has not logged in for a long time has been pushed a related promotion campaign, if the operator counts that the target user account has logged in again after receiving the promotion campaign, it can be said that the promotion campaign is effective and has a high contribution. That is, the operator can perform attribution analysis based on the promotion campaign effect report to determine which promotion campaigns have an actual impact on user conversion behavior. The above scheme can perform real-time dynamic attribution analysis, based on user description data such as user behavior data and user attribute data, and can process and analyze the user's behavior trajectory on different promotion channels, which will help to accurately measure the contribution of each promotion campaign in the future, and can provide companies with intelligent decision-making suggestions, such as adjusting promotion strategies, optimizing advertising, etc.

[0065] In the above-mentioned behavior attribution method, user description data collected during the promotion activity is obtained; based on the user description data, the target user account is determined, wherein the target user account is a user account that meets the activity population of the promotion activity; in the case of detecting that the target user account triggers a target behavior event, the promotion activity information of the target behavior event is determined, and the target behavior event is a behavior event that meets the preset trigger event, wherein the promotion activity information is the description information of the promotion activity triggered by the target behavior event; based on the target behavior event and the promotion activity information, a promotion activity effect report is generated. By automatically identifying the target user account that meets the promotion activity conditions, the target behavior event triggered by the user is detected in real time, and the promotion activity information associated with it is automatically matched, thereby ensuring the comprehensiveness of data collection and the accuracy of association; in addition, by generating a promotion activity effect report, clear and systematic user behavior and activity association data are provided for subsequent attribution analysis, supporting subsequent promotion effect analysis and optimization decisions. This automated and dynamic data integration and report generation process significantly improves the efficiency and real-time performance of attribution analysis, reduces reliance on professional technical personnel, and enhances the ability to handle complex user behavior paths in a multi-channel, multi-touchpoint environment, providing more accurate and efficient technical support for promotion effectiveness evaluation in the field of digital marketing.

[0066] In another embodiment, a promotion activity effect report is generated based on the target behavior event and the promotion activity information, including: recording at least one target behavior event triggered by the target user account within a preset statistical period and the promotion activity information of each target behavior event; determining attribution activity information from each promotion activity information according to the priority of each promotion activity information; generating a promotion activity effect report based on the attribution activity information and the target behavior event to which the attribution activity information is attributed.

[0067] The preset statistical duration may be a preset time window used to limit the time range of data statistics, such as 1 day, 3 days, 7 days, etc.

[0068] In specific implementations, different types of promotional activities can be assigned different priorities, so the promotional activity information corresponding to different types of promotional activities can also have different priorities. Exemplarily, if the promotional activity information belongs to the conversion type (such as purchase), the priority is the highest; if the promotional activity information belongs to the user recall type or registration incentive type, the priority is the second highest; if the promotional activity information belongs to the simple interaction type (such as click, browse), the priority is the lowest. For example, if the promotional activity corresponding to promotional activity information A is a "purchase conversion activity", such as "buy 100 yuan and get a 20 yuan coupon", then the priority of promotional activity information A is high; if the promotional activity corresponding to promotional activity information B is a "user recall activity", such as "log in for 7 consecutive days to get a gift package", then the priority of promotional activity information B is medium; if the promotional activity corresponding to promotional activity information C is a "click or browse activity", such as "click on an ad to get points", then the priority of promotional activity information C is low.

[0069] In a specific implementation, within the preset statistical time, the target user account may trigger at least one target behavior event, so each target behavior event triggered within the preset statistical time and the corresponding attribution activity information can be recorded. For example, within one day, the user's target behavior event at 9 a.m. is to complete the new account registration, and the corresponding promotion activity information can be the description information of the promotion activity "New user registration to get coupons"; the user's target behavior event at 12 noon is to stay in the live broadcast room for more than 1 hour, and the corresponding promotion activity information can be the description information of the promotion activity "Limited time gift special"; the user's target behavior event at 2 p.m. is to visit the activity page, and the corresponding promotion activity information can be the description information of the promotion activity "Browse to get points".

[0070] In a specific implementation, the terminal determines the attribution activity information from each piece of promotion activity information according to the priority of each piece of promotion activity information.

[0071] Among them, the attribution activity information can be promotion activity information that has a key role in promoting user conversion behavior, which is screened through priority. For example, the attribution activity information can be the promotion activity information with the highest priority among all promotion activity information, or it can be the promotion activity information that is ranked in the top several in terms of priority from high to low among all promotion activity information. Exemplarily, since "Limited-time special offer for gifts" is a conversion-type promotion activity, the corresponding promotion activity information has the highest priority. Therefore, the promotion activity information corresponding to the "Limited-time special offer for gifts" promotion activity can be used as the attribution activity information, and the target behavior event attributed to the attribution activity information is "staying in the live broadcast room for more than 1 hour."

[0072] Since different promotions have different impacts on user behavior when users trigger multiple promotions, promotions with higher priorities often have a more direct and critical role in driving the final conversion of users. Therefore, promotion effect reports can be generated based on the promotion information corresponding to the promotions with higher priorities, i.e., attribution information, and the target behavior events to which the attribution information belongs, to ensure that the promotion effect reports include promotions that play a core driving role. Moreover, in a multi-channel, multi-touch environment, users may trigger multiple promotions. If the activities with higher priorities are not screened, data analysis will become cumbersome and difficult to interpret. This can simplify the subsequent attribution analysis process, quickly locate effective promotions, and improve the readability of promotion effect reports.

[0073] The technical solution of this embodiment ensures the identification of promotional activities that have a core driving effect on user behavior by prioritizing the information of multiple promotional activities, avoiding attribution ambiguity or incorrect attribution, and making the effect evaluation more accurate; moreover, by screening out the attribution activity information, the report content is more focused on effective promotional activities, so that subsequent operation personnel can quickly understand and interpret the data, thereby improving the attribution efficiency.

[0074] In another embodiment, a promotion activity effect report is generated based on the attribution activity information and the target behavior events attributed to the attribution activity information, including: generating key attribution activity data based on the attribution activity information and the target behavior events attributed to the attribution activity information; generating activity exposure data based on other promotion activity information that does not belong to the attribution activity information in each promotion activity information, and the target behavior events attributed to other promotion activity information; generating a promotion activity effect report based on the key attribution activity data and the activity exposure data.

[0075] Among them, the key attribution activity data is the data that integrates the attribution activity information and the target behavior event to which the attribution activity information belongs. For example, the key attribution activity data is as follows:

[0076] Target user account: User001;

[0077] Target behavior event: Watching live broadcast for more than 1 hour;

[0078] Trigger time: 9:00 am on December 10, 2024;

[0079] Promotion Information: The name of the promotion is Limited Time Gift Offer.

[0080] Among them, activity exposure data is the data of the target behavior events that integrate other promotional activity information and other promotional activity information. Activity exposure data can also record the number of times a promotional activity is exposed, which is the number of times a user sees or comes into contact with the promotional activity during the promotional activity, reflecting the reach and coverage of the promotional activity. For example, activity exposure data is as follows:

[0081] Target user account: User002;

[0082] Target behavior event: click on the ad page;

[0083] Trigger time: 11:00 am on December 10, 2024;

[0084] Promotion information: The name of the promotion is to get points for browsing the page;

[0085] Number of exposures: 2.

[0086] The technical solution of this embodiment generates a promotion activity effect report based on key attribution activity data and activity exposure data. Since the key attribution activity data shows which activities have truly promoted user conversions, and the activity exposure data shows the user's interaction in other promotion activities and provides the exposure of other promotion activities, the conversion effect and the exposure effect are recorded separately to help subsequent operation personnel understand the actual contribution and exposure of the promotion activities more clearly; by analyzing the key attribution activity data, efficient activities are identified to improve the accuracy of resource investment. At the same time, the activity exposure data is used to understand the user's exposure to other activities, providing a basis for improving activity reach and interaction; and detailed report data is provided to support subsequent efficient and accurate attribution analysis.

[0087] In another embodiment, determining a target user account based on user description data includes: determining that the user account to which the user description data belongs belongs to the target user account when the user behavior represented by the user description data conforms to the preset entity behavior; and determining that the user account to which the user description data belongs belongs to the target user account when the user attributes represented by the user description data conform to the preset entity attributes.

[0088] The user description data may include behavior data such as clicking on the activity interface, registering, logging in, purchasing, etc., and may also include attribute data such as user age, gender, device type, region, etc. User behavior and user attributes can be determined based on the user description data.

[0089] Among them, the preset entity behavior may include predefined user behaviors, such as not logging in for more than 15 days, registering within the past 3 days, etc., which can be used to distinguish newly registered user accounts from user accounts that have not logged in for a long time.

[0090] Among them, the preset entity attributes may include predefined user attributes, such as using a specific brand of mobile phone, being between 18 and 25 years old, and being located in a first-tier city.

[0091] The technical solution of this embodiment ensures that the screened target user accounts accurately meet the needs of the promotion activities through dual matching of user behavior and attributes; supports flexible setting of behavior conditions and attribute conditions according to different promotion goals to meet diverse business needs; automatically matches user description data with preset conditions to improve screening efficiency and reduce manual intervention.

[0092] In another embodiment, obtaining user description data collected during the promotion activity includes: obtaining the activity validity period of the promotion activity; and obtaining the user description data collected during the promotion activity when the current time is within the activity validity period.

[0093] Among them, the validity period of the promotion activity is the time period between the start time and end time set for the promotion activity, for example, the validity period of the activity is from 00:00 on June 1, 2024 to 23:59 on June 7, 2024.

[0094] In a specific implementation, the terminal can obtain the current timestamp of the system to determine the current time, and judge whether the current time is within the validity period of the promotion activity. If the current time is within the validity period of the activity, the user description data collected during the promotion activity is obtained.

[0095] Since multiple promotional activities may exist at the same time, but their validity periods are different. Optionally, the terminal can store the validity period of each promotional activity, and dynamically detect the current time and the validity period of all promotional activities each time the user description data needs to be collected, and filter out the currently valid promotional activities from all promotional activities. When multiple promotional activities are valid at the same time, the user description data related to the user and these activities needs to be collected in parallel.

[0096] The technical solution of this embodiment only collects user data within the validity period of the promotion activity, ensures that the data is relevant to the current promotion activity, and improves the timeliness and relevance of attribution data collection; by limiting the time window, data noise unrelated to the promotion activity is eliminated, providing accurate data support for subsequent effect analysis and attribution analysis.

[0097] In another embodiment, before obtaining the user description data collected during the promotion activity, it also includes obtaining creation information of the promotion activity; the creation information includes the activity validity period, priority, preset triggering event and activity population of the promotion activity; and the promotion activity is created based on the creation information.

[0098] Optionally, Java code can be dynamically compiled and executed at runtime through a lightweight Java compiler, which can be used in scenarios of dynamic script execution and custom rules. Therefore, scripts can be written through a lightweight Java compiler to configure the creation information of promotion activities without modifying the core code or redeploying the system. It flexibly supports complex activity creation logic, and non-professional technicians can also quickly define creation information through simple scripts or configuration interfaces, reducing the threshold for use.

[0099] Among them, the activity validity period can be used to set the time range of the activity to ensure that data collection is carried out within the validity period of the activity; the priority is used to distinguish the importance and attribution order of the promotion activities; the preset trigger event is used to clarify the specific behavior that users need to perform to trigger the promotion activities; the activity population is the population restricted by the promotion activities, ensuring that the promotion activities only reach eligible users.

[0100] Then, the above creation information is used to automatically generate promotion activities, configure the activity validity period, priority, preset trigger events and activity population, and provide a unified promotion activity management configuration tool to help companies quickly add and modify specific behavior attribution plans, so that companies can flexibly adjust promotion configurations according to actual needs, and optimize promotion plans by customizing attribution rules, weight distribution and other parameters according to actual business scenarios. In this way, the promotion channel layout can be optimized through a highly configurable management method to improve the flexibility and scalability of the system.

[0101] The technical solution of this embodiment automatically generates promotional activities based on creation information, reduces manual intervention, and improves work efficiency; ensures that promotional activities are accurately pushed to eligible users based on the activity population definition in the creation information, thereby improving the effectiveness of the activity; dynamically collects user description data related to the activity during the validity period of the promotional activity to ensure the real-time and effectiveness of the data; supports priority attribution to provide support for subsequent attribution analysis, and ensures that user behavior can be attributed to the most important promotional activities through set priority rules, thereby ensuring that the setting and execution of promotional activities are more automated and precise, while improving the timeliness of data collection and the accuracy of promotion effect evaluation.

[0102] In another embodiment, Figure 3 As shown, a behavioral attribution method is provided, which can be applied to Figure 1 The terminal 102 in the example is used as an example to illustrate, and the following steps are included:

[0103] S302, obtaining creation information of a promotion activity.

[0104] The creation information includes the campaign validity period, priority, preset trigger events and campaign target groups.

[0105] S304, creating a promotion activity according to the creation information.

[0106] S306, obtaining the validity period of the promotion activity.

[0107] S308, when the current time is within the validity period of the activity, obtaining user description data collected during the promotion activity.

[0108] S310, determining a target user account according to the user description data.

[0109] The target user accounts are user accounts that meet the activity population of the promotion activity.

[0110] In one of the embodiments, determining a target user account based on user description data includes: determining that a user account to which the user description data belongs belongs to the target user account when the user behavior represented by the user description data conforms to a preset entity behavior; and determining that a user account to which the user description data belongs belongs to the target user account when the user attributes represented by the user description data conform to preset entity attributes.

[0111] S312: When detecting that the target user account triggers a target behavior event, determine promotion activity information of the target behavior event.

[0112] The target behavior event is a behavior event that meets the preset trigger event. The promotion activity information is the description information of the promotion activity triggered by the target behavior event.

[0113] S314, recording at least one target behavior event triggered by the target user account within a preset statistical time period and promotion activity information of each target behavior event.

[0114] S316, determining attribution activity information from each piece of promotion activity information according to the priority of each piece of promotion activity information.

[0115] S318, generating a promotion activity effect report based on the attribution activity information and the target behavior event to which the attribution activity information is attributed.

[0116] In one of the embodiments, a promotion activity effect report is generated based on attribution activity information and target behavior events attributed to the attribution activity information, including: generating key attribution activity data based on the attribution activity information and target behavior events attributed to the attribution activity information; generating activity exposure data based on other promotion activity information that does not belong to the attribution activity information in each promotion activity information, and target behavior events attributed to other promotion activity information; generating a promotion activity effect report based on the key attribution activity data and activity exposure data.

[0117] It should be noted that the specific limitations of the above steps can be found in the specific limitations of a behavior attribution method above.

[0118] It should be understood that, although the various steps in the flowcharts involved in the above-mentioned embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above-mentioned embodiments can include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0119] Based on the same inventive concept, the embodiment of the present application also provides a behavior attribution device for implementing the behavior attribution method involved above. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above method, so the specific limitations in one or more behavior attribution device embodiments provided below can refer to the limitations on the behavior attribution method above, and will not be repeated here.

[0120] In an exemplary embodiment, Figure 4 As shown, a behavior attribution device is provided, including:

[0121] The acquisition module 410 is used to acquire user description data collected during the promotion activity;

[0122] An account determination module 420 is used to determine a target user account according to the user description data; the target user account is a user account that meets the activity group of the promotion activity;

[0123] The activity determination module 430 is used to determine the promotion activity information of the target behavior event when detecting that the target user account triggers the target behavior event; the target behavior event is a behavior event that meets the preset trigger event; the promotion activity information is the description information of the promotion activity triggered by the target behavior event;

[0124] The generation module 440 is used to generate a promotion activity effect report according to the target behavior event and the promotion activity information.

[0125] In one of the embodiments, the generation module 440 is specifically used to record at least one of the target behavior events triggered by the target user account within a preset statistical time period and the promotion activity information of each of the target behavior events; determine the attribution activity information from each of the promotion activity information according to the priority of each of the promotion activity information; and generate the promotion activity effect report according to the attribution activity information and the target behavior event to which the attribution activity information is attributed.

[0126] In one embodiment, the generation module 440 is specifically used to generate key attribution activity data based on the attribution activity information and the target behavior events to which the attribution activity information is attributed; generate activity exposure data based on other promotional activity information that does not belong to the attribution activity information in each of the promotional activity information, and the target behavior events to which the other promotional activity information is attributed; and generate the promotional activity effect report based on the key attribution activity data and the activity exposure data.

[0127] In one of the embodiments, the account determination module 420 is specifically used to determine that the user account to which the user description data belongs belongs to the target user account when the user behavior represented by the user description data conforms to the preset entity behavior; and to determine that the user account to which the user description data belongs belongs to the target user account when the user attributes represented by the user description data conform to the preset entity attributes.

[0128] In one embodiment, the acquisition module 410 is specifically used to acquire the validity period of the promotion activity; when the current time is within the validity period of the activity, acquire the user description data collected during the promotion activity.

[0129] In one of the embodiments, the behavior attribution device also includes a creation module; the creation module is specifically used to obtain creation information of the promotion activity; the creation information includes the activity validity period, priority, preset trigger event and activity population of the promotion activity; and the promotion activity is created based on the creation information.

[0130] Each module in the above-mentioned behavior attribution device can be implemented in whole or in part by software, hardware, or a combination thereof. Each of the above-mentioned modules can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in a computer device in the form of software, so that the processor can call and execute the operations corresponding to each of the above modules.

[0131] In an exemplary embodiment, a computer device is provided. The computer device may be a terminal, and its internal structure diagram may be as shown in FIG. Figure 5As shown. The computer device includes a processor, a memory, an input / output interface, a communication interface, a display unit and an input device. The processor, the memory and the input / output interface are connected through a system bus, and the communication interface, the display unit and the input device are connected to the system bus through the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be implemented through WIFI, a mobile cellular network, near field communication (NFC) or other technologies. When the computer program is executed by the processor, a behavior attribution method is implemented. The display unit of the computer device is used to form a visually visible picture, which can be a display screen, a projection device or a virtual reality imaging device. The display screen can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covering the display screen, or a button, trackball or touchpad set on the computer device shell, or an external keyboard, touchpad or mouse.

[0132] Those skilled in the art will understand that Figure 5 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0133] In an exemplary embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the steps in the above-mentioned method embodiments when executing the computer program.

[0134] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps in the above-mentioned method embodiments are implemented.

[0135] In one embodiment, a computer program product is provided, including a computer program, which implements the steps in the above method embodiments when executed by a processor.

[0136] 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 regulations.

[0137] A person of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment method can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, an artificial intelligence (AI) processor, etc., but are not limited to this.

[0138] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0139] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A behavior attribution method, characterized in that: The method comprises: Obtain user profile data collected during the promotion; Determine a target user account according to the user description data; the target user account is a user account that meets the activity group of the promotion activity; In the case of detecting that the target user account triggers a target behavior event, determining promotion activity information of the target behavior event; the target behavior event is a behavior event that meets a preset trigger event; the promotion activity information is description information of the promotion activity triggered by the target behavior event; Generate a promotion activity effect report based on the target behavior event and the promotion activity information.

2. The method according to claim 1, characterized in that Generating a promotion activity effect report according to the target behavior event and the promotion activity information includes: Record at least one of the target behavior events triggered by the target user account within a preset statistical time period and promotion activity information of each of the target behavior events; Determining attribution activity information from each piece of promotion activity information according to a priority of each piece of promotion activity information; The promotion activity effect report is generated according to the attribution activity information and the target behavior event to which the attribution activity information is attributed.

3. The method according to claim 2, characterized in that The generating of the promotion activity effect report according to the attribution activity information and the target behavior event to which the attribution activity information is attributed includes: Generate key attribution activity data according to the attribution activity information and the target behavior event to which the attribution activity information is attributed; Generate activity exposure data according to other promotion activity information that does not belong to the attribution activity information in each of the promotion activity information, and the target behavior event to which the other promotion activity information belongs; Generate the promotion activity effect report based on the key attribution activity data and the activity exposure data.

4. The method according to claim 1, characterized in that: The step of determining a target user account according to the user description data includes: In a case where the user behavior represented by the user description data conforms to the preset entity behavior, determining that the user account to which the user description data belongs belongs to the target user account; In a case where the user attributes represented by the user description data conform to the preset entity attributes, it is determined that the user account to which the user description data belongs belongs to the target user account.

5. The method according to claim 1, characterized in that The obtaining of user description data collected during the promotion activity includes: Get the validity period of the promotion activity; When the current time is within the validity period of the activity, user description data collected during the promotion activity is obtained.

6. The method according to claim 1, characterized in that Before obtaining the user description data collected during the promotion activity, the method further includes: Acquire creation information of the promotion activity; the creation information includes the activity validity period, priority, preset triggering event and activity population of the promotion activity; The promotion activity is created according to the creation information.

7. A behavior attribution device, characterized in that: The device comprises: An acquisition module, used to acquire user description data collected during the promotion activity; An account determination module is used to determine a target user account according to the user description data; the target user account is a user account that meets the activity group of the promotion activity; An activity determination module, for determining promotion activity information of a target behavior event when detecting that the target user account triggers a target behavior event; the target behavior event is a behavior event that meets a preset trigger event; the promotion activity information is description information of the promotion activity triggered by the target behavior event; A generation module is used to generate a promotion activity effect report based on the target behavior event and the promotion activity information.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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