Advertisement tracing method, device and equipment, and storage medium

Abstract

The embodiment of the invention provides an advertisement tracing method and device, equipment and a storage medium. The method comprises the following steps: acquiring corresponding first environment information when at least one first device accesses an advertisement collected by at least one out-of-end platform, and corresponding second environment information when at least one second device triggers an advertisement conversion behavior collected by an in-end device within a preset duration; the corresponding environment information is used for indicating the identification information of the corresponding equipment; and aiming at each piece of second environment information, taking the out-of-end platform corresponding to the first environment information consistent with the second environment information as a source platform of the corresponding conversion behavior, so that the scheme realizes convenient and low-cost advertisement traceability.

Description

Technical Field

[0001] This application relates to the field of data processing technology, and in particular to an advertising tracing method, apparatus, device, and storage medium. Background Technology

[0002] With the continuous development of network technology, many companies use different channels and platforms to promote advertising. Advertisers need to clearly understand the conversion effect of advertising on different platforms. By analyzing the device environment information of users from seeing the advertisement to completing the conversion behavior, they can accurately locate the source of advertising conversion and provide key data support for optimizing the subsequent advertising strategy.

[0003] Traditional solutions track which channel a user downloaded the application from by generating a unique installation package for each channel and embedding a different channel identifier (ChannelID) in each package.

[0004] However, with the increase in the number of channels, the existing solution requires maintaining more channel packages, which increases the workload of development and management. Summary of the Invention

[0005] This application provides an advertising source tracing method, apparatus, device, and storage medium to achieve advertising source tracing conveniently, quickly, and at low cost.

[0006] In a first aspect, embodiments of this application provide an advertising source tracing method, applied to an in-device device, the method comprising:

[0007] The system acquires first environmental information corresponding to at least one first device accessing an advertisement collected by at least one external platform, and second environmental information corresponding to at least one second device triggering the conversion behavior of the advertisement within a preset time period collected by the internal device. The corresponding environmental information is used to indicate the identification information of the corresponding device.

[0008] For each second environment information, the external platform corresponding to the first environment information that is consistent with the second environment information is taken as the source platform for the corresponding conversion behavior.

[0009] In one possible implementation, the step of using the external platform corresponding to the first environmental information that is consistent with the second environmental information as the source platform for the corresponding conversion behavior includes:

[0010] At least one first candidate environmental information that is consistent with the second environmental information is determined from the at least one first environmental information;

[0011] The second candidate environmental information closest to the current time is determined from the collection time corresponding to the at least one first candidate environmental information;

[0012] The external platform corresponding to the second candidate environment information is used as the source platform for the corresponding conversion behavior.

[0013] In one possible implementation, the identification information of the corresponding device includes at least one of the following: the IP address of the corresponding device and the user agent information of the corresponding device, the anonymous device identifier OAID of the corresponding device, and the advertising identifier IDFA of the corresponding device.

[0014] In one possible implementation, the identification information of the corresponding device includes: the OAID or IDFA of the corresponding device;

[0015] Accordingly, acquiring the second environmental information corresponding to at least one second device triggering the conversion behavior of the advertisement within a preset time period, including:

[0016] In response to the user authorization to obtain OAID or IDFA triggered by the at least one second device, second environmental information corresponding to the conversion behavior of the advertisement triggered by the at least one second device is collected.

[0017] In one possible implementation, the method further includes:

[0018] For each second device, based on the second environment information corresponding to the second device, obtain the operational behavior after the second device triggers the conversion behavior of the advertisement;

[0019] The operation behavior is updated to the user's historical operation data corresponding to the local unique identifier of the second device;

[0020] Based on the user's historical operation data, a delivery strategy for delivering the advertisement is determined.

[0021] In one possible implementation, determining the delivery strategy for delivering the advertisement based on the user's historical operation data includes:

[0022] Based on the user's historical operation data, a user profile is generated;

[0023] Based on the user profile, an advertising delivery strategy is generated.

[0024] Secondly, embodiments of this application provide an advertising traceability device, applied to an in-device device, the device comprising:

[0025] The acquisition module is used to acquire first environment information corresponding to at least one first device accessing the advertisement collected by at least one external platform, and second environment information corresponding to at least one second device triggering the conversion behavior of the advertisement collected by the internal device within a preset time period. The corresponding environment information is used to indicate the IP address of the corresponding device and the user agent information of the corresponding device.

[0026] The determination module is used to determine, for each second environment information, the external platform corresponding to the first environment information that is consistent with the second environment information as the source platform for the corresponding conversion behavior.

[0027] In one possible implementation, the determining module is specifically used for:

[0028] At least one first candidate environmental information that is consistent with the second environmental information is determined from the at least one first environmental information;

[0029] The second candidate environmental information closest to the current time is determined from the collection time corresponding to the at least one first candidate environmental information;

[0030] The external platform corresponding to the second candidate environment information is used as the source platform for the corresponding conversion behavior.

[0031] In one possible implementation, the determining module is further configured to:

[0032] Based on the identifier of the source platform of the conversion behavior corresponding to the at least one second device and the historical delivery data of the at least one external platform for the advertisement, delivery information of the at least one external platform for the advertisement in the future time period is generated.

[0033] In one possible implementation, the identification information of the corresponding device includes at least one of the following: the IP address of the corresponding device and the user agent information of the corresponding device, the anonymous device identifier OAID of the corresponding device, and the advertising identifier IDFA of the corresponding device.

[0034] In one possible implementation, the identification information of the corresponding device includes: the OAID or IDFA of the corresponding device;

[0035] Correspondingly, the acquisition module acquires second environmental information corresponding to at least one second device triggering the conversion behavior of the advertisement within a preset time period, specifically used for:

[0036] In response to the user authorization to obtain OAID or IDFA triggered by the at least one second device, second environmental information corresponding to the conversion behavior of the advertisement triggered by the at least one second device is collected.

[0037] In one possible implementation, the determining module is further configured to:

[0038] For each second device, based on the second environment information corresponding to the second device, obtain the operational behavior after the second device triggers the conversion behavior of the advertisement;

[0039] The operation behavior is updated to the user's historical operation data corresponding to the local unique identifier of the second device;

[0040] Based on the user's historical operation data, a delivery strategy for delivering the advertisement is determined.

[0041] In one possible implementation, the determining module determines a delivery strategy to be applied to the delivery of the advertisement based on the user's historical operation data, specifically for:

[0042] Based on the user's historical operation data, a user profile is generated;

[0043] Based on the user profile, an advertising delivery strategy is generated.

[0044] Thirdly, embodiments of this application provide an electronic device, including: a memory and a processor;

[0045] The memory stores computer-executed instructions;

[0046] The processor executes computer execution instructions stored in the memory, causing the processor to perform the first aspect and / or various possible implementations of the first aspect as described above.

[0047] Fourthly, embodiments of this application provide a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the first aspect and / or various possible implementations of the first aspect.

[0048] Fifthly, embodiments of this application provide a computer program product, including a computer program that, when executed by a processor, implements the first aspect and / or various possible implementations of the first aspect.

[0049] The advertising tracing method, apparatus, device, and storage medium provided in this application embodiment acquire first environmental information corresponding to at least one first device accessing an advertisement collected by at least one external platform, and second environmental information corresponding to at least one second device triggering an advertising conversion behavior collected by an internal device within a preset time period. The corresponding environmental information is used to indicate the identification information of the corresponding device. For each second environmental information, the external platform corresponding to the first environmental information that is consistent with the second environmental information is taken as the source platform of the corresponding conversion behavior. This solution constructs a complete advertising placement and conversion information chain by collecting first-environment information (accessing ads on external platforms) and second-environment information (triggered ad conversion behavior on internal devices). Based on this, a consistency comparison between the second-environment information and the first-environment information allows for accurate matching of ad display and conversion behavior. External platforms corresponding to first-environment information consistent with the second-environment information are identified as the source platform for the conversion behavior. This approach effectively avoids misjudgments of conversion sources due to information fragmentation, significantly improving the accuracy of ad conversion source tracking. It helps advertisers clearly understand the advertising performance on various external platforms, providing reliable data support for optimizing placement strategies and rationally allocating advertising budgets, thereby improving the overall efficiency and profitability of advertising placement. Attached Figure Description

[0050] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0051] Figure 1 A flowchart illustrating the advertising source tracing method provided in this application embodiment. Figure 1 ;

[0052] Figure 2 A flowchart illustrating the advertising source tracing method provided in this application embodiment. Figure 2 ;

[0053] Figure 3 A flowchart illustrating the advertising source tracing method provided in this application embodiment. Figure 3 ;

[0054] Figure 4 A flowchart illustrating the advertising source tracing method provided in this application embodiment. Figure 4 ;

[0055] Figure 5 This is a first implementation example diagram of the advertising tracing method provided in the embodiments of this application;

[0056] Figure 6 A second implementation example diagram of the advertising tracing method provided in this application embodiment;

[0057] Figure 7 A third implementation example diagram of the advertising tracing method provided in this application embodiment;

[0058] Figure 8 This is a schematic diagram of the advertising traceability device provided in the embodiments of this application;

[0059] Figure 9 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application.

[0060] The accompanying drawings illustrate specific embodiments of this application, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concept of this application to those skilled in the art through reference to particular embodiments. Detailed Implementation

[0061] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0062] First, let me explain the terms used in this application:

[0063] 1. Channel ID: A unique identifier used to identify the source or channel of an advertisement. It helps advertisers and advertising platforms track ad performance and understand which channel users encountered the ad from and which generated a conversion.

[0064] Specifically, the channel ID is a channel identifier written into the Android installation package. It is usually found in the channel field of the manifest.xml file of the Android application package (APK) installation package. It accompanies the entire usage life of the installation package and is used to distinguish the user groups and advertising effects of different channels.

[0065] 2. Unified Threat Management (UTM) parameters: Used for traffic tracking of web links, while channel IDs are more used for mobile application ad tracking and user behavior analysis; suitable for traffic statistics of web ads and landing pages, while channel IDs are suitable for mobile application installation packages and ad delivery; used for macro-level traffic analysis, while channel IDs provide more granular user behavior data.

[0066] 3. Internet Protocol (IP): This is the network layer protocol in the TCP / IP architecture. It is the core of the entire Transmission Control Protocol (TCP) / IP protocol suite and the foundation of the Internet. IP resides at the network layer of the TCP / IP model (equivalent to the network layer of the Open Systems Interconnection Model (OSI)). It can provide information on various protocols to the transport layer, such as TCP and User Datagram Protocol (UDP). Downstream, IP packets can be placed at the data link layer and transmitted through various technologies such as Ethernet and Token Ring networks.

[0067] 4. Internet Protocol version 4 (IPv4): This is the fourth revision of the Internet Protocol and the first version to be widely deployed. IPv4 is the core of the Internet and the most widely used version of the Internet Protocol.

[0068] 5. Internet Protocol version 6 (IPv6): This is the next-generation IP protocol designed to replace IPv4. It is said to have enough addresses to assign an address to every grain of sand in the world.

[0069] 6. User Agent (UA) is part of the HTTP protocol and is a component of the header field. It is used to identify the client type, operating system, browser, and other information that initiated the request to the server.

[0070] Specifically, its functions are as follows:

[0071] Content adaptation: Websites can determine the user's device and browser based on the User Agent string, thereby providing optimized content and functions and improving user experience;

[0072] Browser compatibility: The server can perform adaptation and compatibility processing for specific browsers based on User Agent information to ensure that web pages are displayed correctly on different browsers;

[0073] Data statistics and analysis: By analyzing User Agent data, websites can understand the distribution of user devices, the popularity of operating systems, and the market share of browsers, thereby making corresponding optimization decisions;

[0074] Security and risk control: The server can identify potential malicious behavior, crawler or bot access by checking the User Agent string and take appropriate security measures;

[0075] 7. Open Anonymous Device Identifier (OAID): Provides a unified device identification scheme to replace traditional device identifiers such as IMEI while protecting user privacy;

[0076] It has the following characteristics:

[0077] Anonymity: OAID is an anonymous device identifier that does not directly expose the user's real identity information;

[0078] User control: Users can reset their OAID or opt out of ad tracking, thereby controlling its usage;

[0079] Privacy protection: OAID's design philosophy emphasizes privacy protection and is suitable for scenarios such as ad tracking, user analysis, and marketing effectiveness evaluation.

[0080] 8. Identifier for Advertising (IDFA): A device identifier primarily used for advertising tracking and marketing analytics; it allows advertisers to track ad performance on user devices, helping them understand the effectiveness of their campaigns, conduct user behavior analysis, and evaluate marketing results; for example, when a user sees an ad in an app, IDFA can help advertisers identify the user and display relevant ads in other apps.

[0081] Specifically, it has the following characteristics:

[0082] User control: Users can reset IDFA or opt out of ad tracking, thus controlling its usage.

[0083] Privacy protection: Applications are required to obtain user permission before using IDFA;

[0084] Next, the technical background involved in this application will be explained:

[0085] With the continuous development of network technology, many companies use different channels and platforms to promote advertising. Advertisers need to clearly understand the conversion effect of advertising on different platforms. By analyzing the device environment information of users from seeing the advertisement to completing the conversion behavior, they can accurately locate the source of advertising conversion and provide key data support for optimizing the subsequent advertising strategy.

[0086] Traditional solutions track which channel a user downloaded the application from by generating a unique installation package for each channel and embedding different channel identifiers in each package.

[0087] The specific implementation is as follows:

[0088] 1. Generate Channel Packages: Developers generate a unique channel installation package for each channel. Each package contains a different channel identifier, meaning that different app stores will have a corresponding channel package.

[0089] 2. User downloading the application: When a user downloads an application through a specific channel, the installation package will be marked with the identifier of that channel. For example, an application downloaded by a user through channel A will be marked as channel "A".

[0090] 3. Data Collection and Analysis: Operations personnel can use these channel identifiers to analyze the effectiveness of each channel. When a user installs and launches the application, the application collects device information and matches it with data on the server to determine which channel the user downloaded the application from.

[0091] However, existing solutions have the following technical problems:

[0092] 1. High maintenance costs: As the number of channels increases, more channel packages need to be maintained, increasing the workload of development and management;

[0093] 2. Limited applicability: This method is not applicable to some non-app store promotion channels, such as social media and email.

[0094] Based on the aforementioned technical problems, the inventor's technical concept is as follows: The essence of ad conversion is the correlation of device environment information: when a user encounters an ad through an external platform (such as social media, websites, or applications), the device will leave information including IP address and user agent information, IDFA, or OAID; when the user completes the conversion within a preset time period through an internal device (such as within an app), the device will record IP address and user agent information, IDFA, or OAID; if the two sets of data are consistent, it indicates that the same device first encountered the ad externally and then completed the conversion internally. Without relying on the installation package bound to the channel number, the conversion source platform can be directly located through environmental information matching.

[0095] The technical solution of this application and how the technical solution of this application solves the above-mentioned technical problems are described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments. The embodiments of this application will now be described with reference to the accompanying drawings.

[0096] Figure 1A flowchart illustrating the advertising source tracing method provided in this application embodiment. Figure 1 ,like Figure 1 As shown, applied to an in-device device (platform), the method includes:

[0097] Step 11: Obtain first environment information corresponding to at least one first device accessing the advertisement collected by at least one external platform, and second environment information corresponding to at least one second device triggering the conversion behavior of the advertisement within a preset time period collected by the internal device;

[0098] The corresponding environmental information is used to indicate the identification information of the corresponding device;

[0099] In this step, when the first device accesses an advertisement, it can be an advertisement link or logo carried in the interface of an application provided by an external platform, such as a webpage or video software. When the user browses or clicks through the interface on the first device, the external platform can collect the identification information corresponding to the first device. The internal device can periodically obtain multiple first environment information collected by at least one external platform.

[0100] Furthermore, since the advertisement is delivered from within the device to applications provided by different external platforms, when the advertisement triggers a conversion, it indicates a direct correlation with the business or operational goals of the device.

[0101] For example, clicking a link, downloading an installation package, etc.

[0102] Optionally, the identification information of the corresponding device includes at least one of the following: the IP address of the corresponding device, the user agent information of the corresponding device, the OAID of the corresponding device, and the IDFA of the corresponding device.

[0103] The user agent information may include information such as device type, operating system, and browser version.

[0104] Optionally, to increase the accuracy of the source platform's judgment, an effective time window (i.e., a preset duration, such as 24 hours) from ad display to conversion behavior is used to filter invalid associations (i.e., the following credential stuffing).

[0105] It should be understood that the above information acquisition can be achieved based on data tracking technology.

[0106] Step 12: For each second environment information, the external platform corresponding to the first environment information that is consistent with the second environment information is taken as the source platform for the corresponding conversion behavior.

[0107] In this step, taking the IP address and user agent information of the corresponding device as an example, the second environment information (i.e., IP+User-Agent) corresponding to each conversion behavior is compared with the first environment information of all previously recorded ad accesses. When the IP address and user agent information in the two environment information are completely consistent, it is considered to be the same device, that is, the credential stuffing is considered successful, and the external platform corresponding to the first environment information is taken as the source platform that achieved the successful conversion behavior.

[0108] For example: If a user sees an advertisement on software A (an external platform) (recording the first environmental information), and completes a purchase on software B (an internal device) 2 hours later (recording the second environmental information), and the environmental information of the two matches, then software A is considered to be the source platform of the order.

[0109] Furthermore, it can also perform the following: based on the identifier of the source platform of the conversion behavior corresponding to at least one second device and the historical delivery data of the advertisement on at least one external platform, generate the delivery information of the advertisement on at least one external platform in the future time period.

[0110] In this implementation, if the external platform corresponding to each conversion behavior is obtained in the aforementioned implementation, it means that the external platform is more in line with expectations for the internal device. At this time, relevant data of past advertising on each external platform are collected. Combined with the historical advertising data and the source platform of the conversion behavior corresponding to at least one second device, the conversion path and time period of users on different platforms are analyzed. In this way, at least one external platform is ranked or rated for revenue, and advertising information for at least one external platform in the future is generated.

[0111] For example, historical campaign data could include: impressions: the number of times an ad is displayed on the platform; clicks: the number of times a user clicks on an ad; conversion rate: the percentage of users who convert after clicking on an ad; cost data: the cost per impression or click; and user profile: the characteristics of target users (age, region, interest tags, etc.) obtained through the platform.

[0112] In this implementation, the budget for advertising can be increased for high-rated external platforms, and the budget for advertising can be reduced for low-rated external platforms.

[0113] The advertising source tracing method provided in this application obtains first environment information corresponding to at least one first device accessing an advertisement collected by at least one external platform, and second environment information corresponding to at least one second device triggering an advertising conversion behavior collected by an internal device within a preset time period. The corresponding environment information is used to indicate the identification information of the corresponding device. For each second environment information, the external platform corresponding to the first environment information that is consistent with the second environment information is taken as the source platform of the corresponding conversion behavior. This solution constructs a complete advertising placement and conversion information chain by collecting the first environment information of the first device accessing the advertisement on the external platform and the second environment information of the second device triggering the advertising conversion behavior on the internal device. On this basis, the consistency comparison between the second environment information and the first environment information can accurately match the advertising display and conversion behavior, and identify the external platform corresponding to the first environment information that is consistent with the second environment information as the source platform of the conversion behavior. This method effectively avoids misjudgment of conversion source caused by information fragmentation, greatly improves the accuracy of advertising conversion source tracking, helps advertisers clearly understand the advertising placement effect of each external platform, and provides reliable data support for optimizing placement strategies and rationally allocating advertising budgets, thereby improving the overall efficiency and revenue of advertising placement.

[0114] Based on the above embodiments, Figure 2 A flowchart illustrating the advertising source tracing method provided in this application embodiment. Figure 2 ,like Figure 2 As shown, step 12 may include:

[0115] Step 21: Determine at least one first candidate environmental information that is consistent with the second environmental information from at least one first environmental information;

[0116] In this step, since there may be multiple different first devices accessing the same advertisement within a preset time period, and these devices may exist in the same network environment, have the same user agent information, or have the same device accessing the advertisement on different external platforms, but they are not necessarily the devices corresponding to the conversion behavior, this step first filters these devices to obtain at least one first candidate environment information that is consistent with the second environment information.

[0117] For example, each piece of second environment information is matched with all first environment information at the field level. Taking IP address and user agent information as an example, it is compared whether the IP address and user agent information of the two are completely consistent. Only when the IP address and user agent information are completely consistent are they considered to belong to the behavior of the same device, and the corresponding first environment information is marked as the first candidate environment information.

[0118] Step 22: Determine the second candidate environmental information that is closest to the current time from the collection time corresponding to at least one first candidate environmental information;

[0119] In this step, after identifying at least one first candidate environmental information, the collection time corresponding to each first candidate environmental information is compared to determine the first candidate environmental information that is closest to the current time, which is then used as the second candidate environmental information.

[0120] That is, the first environmental information that is closest to the current time is considered to be the environmental information in which the actual transformation behavior has occurred.

[0121] Step 23: Use the external platform corresponding to the second candidate environment information as the source platform for the corresponding conversion behavior.

[0122] In this step, after the first two steps of screening, the external platform associated with the only second candidate environmental information will be directly identified as the source platform of the conversion behavior.

[0123] For example, if the second candidate environment information comes from the advertising access records of the "APP 1" platform, then "APP 1" is determined to be the source platform for this conversion.

[0124] Furthermore, different business tags, behavioral tags, strong and weak intents can be formulated based on conversion behavior to enable in-app integration in different scenarios.

[0125] Specific strategy tag implementations could be:

[0126] 1) Whether the credential stuffing attack was successful: 0 - No hit, 1 - Hit; 2) Business line: C2B, B2C, etc.; 3) Intent strength: 0 - Weak intent, 1 - Strong intent; 4) Intent strength factor: Multiple values ​​are separated by commas: 0 - Weak intent, 1 - Click behavior within 24 hours, 2 - Started within 30 minutes after the last behavior, 3 - Browsing frequency greater than 1 time within 24 hours; 5) Whether there was activity in the previous 7 days: 0 - No activity, 1 - Activity; 6) Restoration strength: 0 - Weak restoration, 1 - Strong restoration; 7) Acceptance method AB value; 8) Acceptance method: Multiple values ​​are separated by commas: 0 - No restoration, 1 - Direct restoration, 2 - Pop-up window, 3 - Bottom floating layer, 4 - Fixed entry point; 9) Whether it is a newly launched user: 0 - Not a newly launched user, 1 - Newly launched user.

[0127] Furthermore, regarding the implementation of strategy tags: taking the B2C scenario as an example, it can display customized landing pages, lists of products such as interest categories and models, entry points to activity pages, or pop-ups; and taking the C2B scenario as an example, it can display recycling guidance entry points + bonus coupons, etc.

[0128] The advertising source tracing method provided in this application identifies at least one first candidate environment information that matches the second environment information from at least one first environment information. It then identifies the second candidate environment information closest to the current time from the collection time corresponding to the at least one first candidate environment information. The external platform corresponding to the second candidate environment information is then used as the source platform for the corresponding conversion behavior. This solution accurately locates the advertising conversion source through two screening processes: first, it narrows down the scope by locking down the first candidate environment information that matches the second environment information from numerous first environment information sources; then, it filters out the second candidate environment information closest to the current time based on the collection time. Considering the immediacy of user behavior, the possibility of conversion after recent ad exposure is higher. This effectively avoids misjudgment of the source due to duplicate environment information, reduces the influence of interfering information, and makes the judgment of advertising conversion source more closely aligned with the actual user behavior path. This improves the accuracy and timeliness of advertising performance analysis, helping advertisers more efficiently evaluate the value of various external platforms and optimize their placement strategies.

[0129] Based on the above embodiments, Figure 3 A flowchart illustrating the advertising source tracing method provided in this application embodiment. Figure 3 ,like Figure 3 As shown, the method may include:

[0130] Step 31: In response to the user authorization for obtaining OAID or IDFA triggered by at least one second device, collect the second environment information corresponding to the conversion behavior of the advertisement triggered by at least one second device;

[0131] In this step, if the second device is an Android system, the second environment information is OAID; if the second device is an iOS system, the second environment information is IDFA.

[0132] In this implementation, when collecting the OAID or IDFA of the second device, for example in the implementation of mounting advertisements on an external platform, when a user opens the external platform through the second device, the external platform will pop up a prompt asking whether to allow the acquisition of the OAID or IDFA of the second device. When the user clicks "agree", the user authorization for acquiring the OAID or IDFA triggered by the second device is approved.

[0133] Subsequently, when a user triggers a conversion behavior related to an advertisement, the OAID or IDFA of the second device can be obtained.

[0134] It should be understood that step 31 may be an implementation where the identification information of the corresponding device includes: the OAID or IDFA of the corresponding device; the following steps may be for any implementation where the identification information is an IP address and user agent information, OAID, and IDFA.

[0135] Step 32: For each second device, based on the second environment information corresponding to the second device, obtain the operation behavior after the second device triggers the conversion behavior of the advertisement;

[0136] The operational behavior can be a subsequent behavior after the transformation, for example:

[0137] Taking the e-commerce industry as an example, these could include actions such as placing an order, adding items to the shopping cart, and claiming coupons; taking internet products as an example, these could include subscription services, paid top-ups, and app downloads and installations; taking content platforms as an example, these could include actions such as liking, commenting, and sharing.

[0138] Step 33: Update the operation behavior to the user's historical operation data corresponding to the unique identifier (e.g., Token) on the second device;

[0139] In this solution, when the second environment information of the second device is obtained for the first time, a local Token corresponding to the second environment information can be created to store the operation behavior in a database, thereby storing the corresponding operation behavior for subsequent analysis.

[0140] In this step, the operational behavior of the second device obtained this time will be updated into the user's historical operation data.

[0141] Step 34: Determine the ad delivery strategy based on the user's historical operation data.

[0142] In this step, an advertising delivery strategy for the second device is determined based on the updated user history operation data.

[0143] In this implementation, the user's historical operation data performed by the second device after conversion is analyzed, user interest or demand characteristics are extracted, and tags are generated based on the operation behavior to determine the appropriate advertising strategy.

[0144] The advertising tracing method provided in this application collects second environment information corresponding to the conversion behavior of at least one second device triggering an advertisement, in response to user authorization for obtaining OAID or IDFA triggered by at least one second device. For each second device, based on the second environment information corresponding to the second device, the method obtains the operation behavior after the conversion behavior of the advertisement triggered by the second device, updates the operation behavior to the user's historical operation data corresponding to the unique identifier of the second device, and determines the advertising strategy to be applied based on the user's historical operation data. This solution can more accurately build user profiles and identify high-value conversion nodes and behavior patterns by integrating and analyzing historical operation data (such as behavioral preferences, conversion paths, activity levels, etc.), thereby dynamically optimizing advertising strategies (such as targeted audiences, delivery time periods, content formats, etc.), improving the matching degree between advertisements and user needs, and ultimately achieving a comprehensive improvement in advertising conversion rate, user engagement, and ROI, while ensuring the legality of data use based on compliant authorization.

[0145] Based on the above embodiments, Figure 4 A flowchart illustrating the advertising source tracing method provided in this application embodiment. Figure 4 ,like Figure 4 As shown, step 34 may include the following implementation:

[0146] Step 41: Generate a user profile based on the user's historical operation data;

[0147] In this step, the user's historical operation data can be from before the current time and is used to analyze the user's behavior in relation to the advertisement on the second device.

[0148] For example: E-commerce scenarios: browsing product categories, adding to cart, favorites, reviews, and sharing links; Content scenarios: video viewing time, like / comment on content types, and following specific bloggers; Tool scenarios: setting preferences (such as selecting "dark mode") and using specific functions (such as "public transport routes" in map apps).

[0149] User profiles can be generated based on browsing / search content (e.g., "Men's clothing → Shirts → Casual style").

[0150] Step 42: Generate an advertising delivery strategy based on the user profile.

[0151] In this step, the advertising delivery strategy for users corresponding to the second device is selected based on the user profile tags, such as:

[0152] 1) Customize creative content based on user interests and preferences (e.g., images of casual shirts paired with jeans); 2) Select external platforms where users are active; 3) Increase exposure during peak user hours (e.g., 6:00 PM - 10:00 PM after work).

[0153] The advertising source tracing method provided in this application generates user profiles based on users' historical operation data, and then generates advertising delivery strategies based on these user profiles. This technical solution generates user profiles from historical user operation data, transforming fragmented user behaviors (such as clicks, browsing, and purchases) into a visualized and structured tag system, clearly showcasing users' interests, consumption habits, and active time periods. Based on accurate user profiles, the generated advertising delivery strategies achieve a high degree of matching between advertising content, delivery time, delivery channels, and target user needs, effectively reducing invalid exposure, increasing ad click-through rates and conversion rates, while simultaneously lowering delivery costs and improving advertisers' return on investment. This provides users with an advertising experience that better meets their needs, achieving a win-win situation of accurate advertising delivery and satisfied user experience.

[0154] Figure 5 The first implementation example diagram of the advertising tracing method provided in the embodiments of this application is shown below. Figure 5 As shown, this example includes:

[0155] Processing of basic data from external platforms: publishing videos (user A places an order in software B), video binding (binding data orders, software B, and video identifiers), metadata processing (associating video tagging data with software B orders every hour), real-time data tagging (taging each piece of real-time data based on video identifiers and software B order association, and some logical processing of external user playback and other behavioral data).

[0156] In-platform (in-device) logic processing: user triggers credential stuffing (i.e., determining the source platform) conditions (starting the APP or triggering a certain type of interface, i.e., conversion behavior), initiates credential stuffing request (initiates credential stuffing action), receives and processes credential stuffing (receives big data status request and completes user tag logic processing), receives data (the platform receives data and completes distribution logic judgment), and differentiates acceptance (the business accepts data differentiatedly according to business rules and user tags).

[0157] Figure 6 A second implementation example diagram of the advertising tracing method provided in the embodiments of this application is shown below. Figure 6 As shown, this example includes:

[0158] External data transmission > Business tagging > Internal data transmission > Real-time database attack > Real-time tagging > Differentiated service delivery.

[0159] (Offline) External platform transmits click and impression data (i.e., the first environment information corresponding to at least one first device accessing the advertisement); data center receives and forwards data; server-side data tracking; big data side analyzes data, performs credential stuffing to match users; attribution and statistical analysis of ROI metrics;

[0160] In addition, (in real time) click and impression data can be transmitted back; the data center receives and forwards the data; the project is tagged in real time in Kafka; big data is tagged and cleaned and sent to downstream Kafka; the platform side performs a credential stuffing attack based on the start event; and the credential stuffing result is given to the B2C / outbound business side for processing.

[0161] Figure 7 A third implementation example diagram of the advertising tracing method provided in the embodiments of this application is shown below. Figure 7 As shown, this example includes:

[0162] Taking Software 1 as an example, the data is returned; the IPv4+UA in the full click / exposure IPV4+UA+24h window is matched with the IPv4+UA in the full client tracking, and the IPv6+UA in the full click / exposure IPV6+UA+24h window is matched with the IPv6+UA in the full client tracking; then the two sets of data are merged and the first token that is successfully matched in the 24h window for each click and exposure is retrieved; the ROI is attributed and calculated, and the business line and other tags are obtained through the maintenance table;

[0163] Taking Software 2 as an example, the data is returned; the IPv4+UA+24h window of the full click / exposure is matched with the IPv4+UA in the full client tracking, the IPv6+UA+24h window of the full click / exposure is matched with the IPv6+UA in the full client tracking, the OAID+24h window of the full click / exposure on Android is matched with the OAID in the full client tracking, and the IDFA+24h window of the full click / exposure on iOS is matched with the IDFA in the full client tracking; then the four sets of data are merged and the first token that is successfully matched by OAID / IDFA in each click and exposure within the 24h window is retrieved. If no match is found, the first token that is successfully matched by IP+UA is retrieved. The ROI is attributed and calculated, and the business line and other tags are obtained through the maintenance table.

[0164] In the above implementation, Flink is used for real-time data cleaning; Kafka, as a distributed message queue, can efficiently receive and store real-time data streams from various data sources, providing stable data input for Flink; Redis is used to store user viewing behavior, business tags, user basic data, etc. before and after the credential stuffing attack; and Java is used to build the credential stuffing attack service and interact with the platform.

[0165] The technical solutions and effects in the above examples are implemented in a similar manner to the above embodiments, and will not be repeated here.

[0166] Figure 8 This is a schematic diagram of the advertising traceability device provided in the embodiments of this application, as shown below. Figure 8 As shown, this device, applied to an intra-terminal device, includes:

[0167] The acquisition module 81 is used to acquire the first environment information corresponding to the access of at least one first device to the advertisement collected by at least one external platform, and the second environment information corresponding to the conversion behavior of at least one second device triggered by the advertisement collected by the internal device within a preset time period. The corresponding environment information is used to indicate the IP address of the corresponding device and the user agent information of the corresponding device.

[0168] The determination module 82 is used to determine, for each second environment information, the external platform corresponding to the first environment information that is consistent with the second environment information as the source platform for the corresponding conversion behavior.

[0169] In one possible implementation, the determining module 82 is specifically used for:

[0170] At least one first candidate environmental information that is consistent with the second environmental information is determined from at least one first environmental information;

[0171] Determine the second candidate environmental information that is closest to the current time from the collection time corresponding to at least one first candidate environmental information;

[0172] The external platform corresponding to the second candidate environment information is used as the source platform for the corresponding conversion behavior.

[0173] In one possible implementation, the determining module 82 is further configured to:

[0174] Based on the identifier of the source platform of the conversion behavior corresponding to at least one second device and the historical delivery data of the advertisement on at least one external platform, generate the delivery information of the advertisement on at least one external platform in the future time period.

[0175] In one possible implementation, the identification information of the corresponding device includes at least one of the following: the IP address of the corresponding device and the user agent information of the corresponding device, the anonymous device identifier OAID of the corresponding device, and the advertising identifier IDFA of the corresponding device.

[0176] In one possible implementation, the identification information of the corresponding device includes: the OAID or IDFA of the corresponding device;

[0177] Correspondingly, the acquisition module 81 acquires the second environment information corresponding to the conversion behavior of at least one second device triggering the advertisement, collected by the device within the terminal within a preset time period, specifically used for:

[0178] In response to user authorization for obtaining OAID or IDFA triggered by at least one second device, second environment information corresponding to the conversion behavior of the advertisement triggered by at least one second device is collected.

[0179] In one possible implementation, the determining module 82 is further configured to:

[0180] For each second device, based on the second environment information corresponding to the second device, obtain the operational behavior after the second device triggers the conversion behavior of the advertisement;

[0181] Update the operation behavior to the user's historical operation data corresponding to the local unique identifier of the second device;

[0182] Based on users' historical operation data, determine the ad delivery strategy to be applied.

[0183] In one possible implementation, the determining module 82 determines the ad delivery strategy to be applied based on the user's historical operation data, specifically for:

[0184] Generate user profiles based on users' historical operation data;

[0185] Based on user profiles, generate ad delivery strategies.

[0186] The advertising traceability device provided in this embodiment can execute the method provided in the above method embodiment. Its implementation principle and technical effect are similar, and will not be described in detail here.

[0187] Figure 9 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Figure 9 As shown, the electronic device provided in this embodiment can be the aforementioned in-terminal device, including:

[0188] The device includes at least one processor 901 and a memory 902. Optionally, the device also includes a communication component 903. The processor 901, memory 902, and communication component 903 are connected via a bus 904.

[0189] In a specific implementation, at least one processor 901 executes computer execution instructions stored in memory 902, causing at least one processor 901 to perform the above-described method.

[0190] The specific implementation process of processor 901 can be found in the above method embodiments, and its implementation principle and technical effect are similar. It will not be repeated here.

[0191] In the above embodiments, it should be understood that the processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), etc. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in this invention can be directly implemented by a hardware processor, or implemented by a combination of hardware and software modules within the processor.

[0192] The memory may include random access memory (RAM) and may also include non-volatile memory (NVM), such as at least one disk storage device.

[0193] The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc. For ease of illustration, the buses shown in the accompanying drawings are not limited to a single bus or a single type of bus.

[0194] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the above-described method.

[0195] This application also provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the above-described method.

[0196] The aforementioned readable storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. The readable storage medium can be any available medium accessible to a general-purpose or special-purpose computer.

[0197] An exemplary readable storage medium is coupled to a processor, enabling the processor to read information from and write information to the readable storage medium. Of course, the readable storage medium can also be a component of the processor. The processor and the readable storage medium can reside in an Application Specific Integrated Circuit (ASIC). Alternatively, the processor and the readable storage medium can exist as discrete components in the device.

[0198] The division of units is merely a logical functional division; in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be indirect coupling or communication connection through some interfaces, devices, or units, and may be electrical, mechanical, or other forms.

[0199] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0200] In addition, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0201] If a function is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0202] Those skilled in the art will understand that all or part of the steps of the above-described method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When executed, the program performs the steps of the above-described method embodiments; and the aforementioned storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disks, or optical disks.

[0203] Finally, it should be noted that other embodiments of the invention will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This invention is intended to cover any variations, uses, or adaptations of the invention that follow the general principles of the invention and include common knowledge or customary techniques in the art not disclosed herein, and is not limited to the precise structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of the invention is limited only by the appended claims.

Claims

1. A method for tracing the source of advertising, characterized in that, Applied to an in-device device, the method includes: The system acquires first environmental information corresponding to at least one first device accessing an advertisement collected by at least one external platform, and second environmental information corresponding to at least one second device triggering the conversion behavior of the advertisement within a preset time period collected by the internal device. The corresponding environmental information is used to indicate the identification information of the corresponding device. For each second environment information, the external platform corresponding to the first environment information that is consistent with the second environment information is taken as the source platform for the corresponding conversion behavior.

2. The method according to claim 1, characterized in that, The step of using the external platform corresponding to the first environmental information that is consistent with the second environmental information as the source platform for the corresponding conversion behavior includes: At least one first candidate environmental information that is consistent with the second environmental information is determined from the at least one first environmental information; The second candidate environmental information closest to the current time is determined from the collection time corresponding to the at least one first candidate environmental information; The external platform corresponding to the second candidate environment information is used as the source platform for the corresponding conversion behavior.

3. The method according to claim 1 or 2, characterized in that, The method further includes: Based on the identifier of the source platform of the conversion behavior corresponding to the at least one second device and the historical delivery data of the at least one external platform for the advertisement, delivery information of the at least one external platform for the advertisement in the future time period is generated.

4. The method according to claim 1 or 2, characterized in that, The identification information of the corresponding device includes at least one of the following: the IP address of the corresponding device, the user agent information of the corresponding device, the anonymous device identifier OAID of the corresponding device, and the advertising identifier IDFA of the corresponding device.

5. The method according to claim 4, characterized in that, The identification information of the corresponding device includes: the OAID or IDFA of the corresponding device; Accordingly, acquiring the second environmental information corresponding to at least one second device triggering the conversion behavior of the advertisement within a preset time period, including: In response to the user authorization to obtain OAID or IDFA triggered by the at least one second device, second environmental information corresponding to the conversion behavior of the advertisement triggered by the at least one second device is collected.

6. The method according to claim 1 or 2, characterized in that, The method further includes: For each second device, based on the second environment information corresponding to the second device, obtain the operational behavior after the second device triggers the conversion behavior of the advertisement; The operation behavior is updated to the user's historical operation data corresponding to the local unique identifier of the second device; Based on the user's historical operation data, a delivery strategy for delivering the advertisement is determined.

7. The method according to claim 6, characterized in that, The step of determining the delivery strategy to be applied to the advertisement based on the user's historical operation data includes: Based on the user's historical operation data, a user profile is generated; Based on the user profile, an advertising delivery strategy is generated.

8. An advertising traceability device, characterized in that, Applied to an in-terminal device, the device includes: The acquisition module is used to acquire first environment information corresponding to at least one first device accessing the advertisement collected by at least one external platform, and second environment information corresponding to at least one second device triggering the conversion behavior of the advertisement collected by the internal device within a preset time period. The corresponding environment information is used to indicate the identification information of the corresponding device. The determination module is used to determine, for each second environment information, the external platform corresponding to the first environment information that is consistent with the second environment information as the source platform for the corresponding conversion behavior.

9. An electronic device, characterized in that, include: Memory, processor; The memory stores computer-executed instructions; The processor executes computer execution instructions stored in the memory, causing the processor to perform the method as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the method as described in any one of claims 1-7.

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