Data processing method and related device

Abstract

The invention discloses a data processing method and a related device, and relates to the field of digital advertisement, and the method comprises the steps: obtaining the identification information of a traffic user; determining the income generated by the traffic user and the acquisition cost of the traffic user based on the monitoring identifier clicked by the user; based on the income generated by the traffic user and the acquisition cost of the traffic user, determining the return on investment of the traffic user; and when the return on investment of the traffic user is greater than the target return on investment, returning the identification information of the traffic user to the target platform, so that the target platform searches for a target user whose user value is matched with the traffic user corresponding to the identification of the traffic user, and sends the target user to the target platform according to the target object information indicated by the information identification. And displaying the target object to the target user. According to the invention, screening of user traffic can be realized, and the probability of loss of users attracted in a buying stage at the present stage is reduced.

Description

Technical Field

[0001] The present application relates to the field of digital advertising technology, and in particular to a data processing method and related devices. Background Art

[0002] Ad traffic and ad monetization have become core components of digital marketing and the mobile app ecosystem. Ad traffic refers to the process of delivering advertising content to users via the internet, apps, and other channels to achieve marketing goals such as brand exposure and user acquisition. Ad monetization refers to the process of converting traffic (user visits or activity) into actual revenue by displaying advertising content to users. Ad traffic platforms and ad monetization platforms are separate platforms, and users diverted from ad platforms to monetization platforms may experience churn due to inconsistent user experiences. Summary of the Invention

[0003] In view of the above problems, this application provides a data processing method and related devices that can filter user traffic and reduce the probability of users attracted during the acquisition phase being lost during the monetization phase. The specific solution is as follows:

[0004] The first aspect of the present application provides a data processing method, comprising:

[0005] Obtain identification information of a traffic user; wherein the traffic user is a user who clicks a target object displayed on a target platform, and the identification information includes an identifier of the traffic user, an information identifier of the target object, and a user click monitoring identifier generated after clicking the target object;

[0006] Determining the revenue generated by the traffic user and the acquisition cost of the traffic user based on the user click monitoring identifier;

[0007] Determining a return on investment for the traffic user based on the revenue generated by the traffic user and the acquisition cost of the traffic user;

[0008] When the return on investment of the traffic user is greater than the target return on investment, the identification information of the traffic user is transmitted back to the target platform, so that the target platform searches for a target user whose user value matches the traffic user corresponding to the identification of the traffic user, and displays the target object to the target user according to the target object information indicated by the information identification.

[0009] In a possible implementation, determining the revenue generated by the traffic user and the acquisition cost of the traffic user based on the user click monitoring identifier includes:

[0010] Determining, based on the user click monitoring identifier, the type of a target application entered by clicking the target object;

[0011] If the target application is of the first type, summing the bid prices for each ad exposure of a traffic user after the traffic user enters the target application to obtain the revenue generated by the traffic user, and using the ratio of the traffic purchase cost corresponding to the information identifier of the target object to the number of daily active users as the acquisition cost of the traffic user;

[0012] If the type of the target application is the second type, the bidding prices of each advertisement exposure after multiple traffic users enter the target application are summed to obtain the revenue generated by the traffic user, and the conversion bid is used as the acquisition cost of the traffic user.

[0013] In a possible implementation, the method further includes:

[0014] Obtaining the number of postbacks corresponding to the information identifier of the target object and the number of clicks on the target object;

[0015] Determine the ratio of the number of postbacks to the number of clicks to obtain a target conversion rate;

[0016] When the target conversion rate is greater than the conversion rate upper limit, increasing the target return on investment;

[0017] When the target conversion rate is less than the conversion rate lower limit, the target return on investment is reduced.

[0018] In a possible implementation, the method further includes:

[0019] If at least one of conditions 1 to 3 is met, the identification information of the traffic user is transmitted back to the target platform:

[0020] Condition 1: The number of times the traffic user clicks on the target advertisement is greater than a first preset number; the target advertisement is an advertisement displayed by a target application, and the target application is an application entered by clicking the target object;

[0021] Condition 2: The number of times the advertisement is displayed to the traffic user is greater than a second preset number;

[0022] Condition three: the number of times the traffic user invokes the target application is greater than a third preset number.

[0023] In a possible implementation, after determining the revenue generated by the traffic user and the acquisition cost of the traffic user, the method further includes:

[0024] Determine the user acquisition cost and user lifetime value of the target platform based on the revenue generated by the traffic users and the acquisition cost of the traffic users;

[0025] Determine the return on investment of the target platform based on the user acquisition cost and user lifetime value of the target platform;

[0026] When the return on investment of the target platform exceeds a preset range, determining a target parameter that affects the return on investment of the target platform;

[0027] The target parameters are adjusted so that the return on investment of the target platform is within the preset range.

[0028] In a possible implementation, adjusting the target parameter so that the return on investment of the target platform is within the preset range includes:

[0029] With the goal of maximizing the return on investment of the target platform, and with the budget value not exceeding the budget ceiling of the target platform and the cost of a single action not exceeding the cost ceiling, the buying volume parameters and / or monetization parameters are adjusted to ensure that the return on investment of the target platform is within the preset range.

[0030] A second aspect of the present application provides a data processing system, comprising:

[0031] An acquisition module is configured to acquire identification information of a traffic user; wherein the traffic user is a user who clicks a target object displayed on a target platform, and the identification information includes an identification of the traffic user, an information identification of the target object, and a user click monitoring identification generated after clicking the target object;

[0032] A first calculation module is configured to determine the revenue generated by the traffic user and the acquisition cost of the traffic user based on the user click monitoring identifier;

[0033] a second calculation module, configured to determine a return on investment of the traffic user based on the revenue generated by the traffic user and the acquisition cost of the traffic user;

[0034] A feedback module is used to transmit the identification information of the traffic user back to the target platform when the return on investment of the traffic user is greater than the target return on investment, so that the target platform can search for a target user whose user value matches the traffic user corresponding to the identification of the traffic user, and display the target object to the target user according to the target object information indicated by the information identifier.

[0035] A third aspect of the present application provides a computer program product, comprising computer-readable instructions. When the computer-readable instructions are executed on an electronic device, the electronic device implements the data processing method of the first aspect or any implementation of the first aspect.

[0036] A fourth aspect of the present application provides an electronic device, comprising at least one processor and a memory connected to the processor, wherein:

[0037] The memory is used to store computer programs;

[0038] The processor is used to execute the computer program so that the electronic device can implement the data processing method of the first aspect or any implementation manner of the first aspect.

[0039] In a fifth aspect, the present application provides a computer storage medium, which carries one or more computer programs. When the one or more computer programs are executed by an electronic device, the electronic device can implement the data processing method of the first aspect or any implementation method of the first aspect.

[0040] By means of the above technical solution, the data processing method and related devices provided by the present application obtain the identification information of the traffic user and calculate the return on investment based on the traffic user. If the return on investment of the traffic user is high, the identification information of the traffic user is transmitted back to the target platform, so that the target platform can attract target users whose user value matches the user value of the traffic user by displaying target objects with the same target object information, thereby realizing the screening of user traffic and reducing the probability of loss of the attracted users during the monetization stage. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] The above and other features, advantages, and aspects of the various embodiments of the present disclosure will become more apparent with reference to the following detailed description in conjunction with the accompanying drawings. Throughout the drawings, the same or similar reference numerals represent the same or similar elements. It should be understood that the drawings are schematic and that the originals and elements are not necessarily drawn to scale.

[0042] Figure 1 A flow chart of a data processing method provided in this application;

[0043] Figure 2 A structural diagram of a data processing system provided for this application;

[0044] Figure 3 This is a schematic diagram of the structure of an electronic device provided in this application. DETAILED DESCRIPTION

[0045] The following describes the embodiments of the present application in conjunction with the accompanying drawings. The terms used in the implementation methods of the present application are only used to explain the specific embodiments of the present application and are not intended to limit the present application.

[0046] The embodiments of the present application are described below in conjunction with the accompanying drawings. Those skilled in the art will appreciate that, with the development of technology and the emergence of new scenarios, the technical solutions provided in the embodiments of the present application are also applicable to similar technical problems.

[0047] The terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequential order. It should be understood that the terms used in this way can be interchangeable under appropriate circumstances, and this is merely a way of distinguishing the objects of the same attributes when describing them in the embodiments of the present application. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, so that the process, method, system, product or equipment comprising a series of units need not be limited to those units, but may include other units that are not clearly listed or inherent to these processes, methods, products or equipment.

[0048] Reference Figure 1 , Figure 1 A data processing method according to an embodiment of the present invention is shown in FIG. Figure 1 As shown, a data processing method provided in an embodiment of the present application can be applied to an advertising monetization platform. The method can include steps 101 to 104, and these steps are described in detail below.

[0049] Step 101: Obtain identification information of the traffic user; wherein, the traffic user is a user who clicks on the target object displayed on the target platform, and the identification information includes the traffic user's identification, the information identification of the target object, and the user click monitoring identification generated after clicking the target object.

[0050] The traffic users are users directed from the target platform, which can be an advertising platform or a traffic platform. The advertising monetization platform pays the target platform and displays the target object that the advertising monetization platform needs to display on the target platform. The target object can be an advertising link, an application link, etc.

[0051] The identification information of the traffic user includes the identifier of the traffic user. The identifier of the traffic user may be an identifier that uniquely represents the traffic user, and may be a user identifier or a device identifier. When the identifier of the traffic user is an identifier of the device used by the traffic user, the identifier of the traffic user may be an OAID (Open Anonymous Device Identifier).

[0052] The identification information of the traffic user also includes the information identification of the target object. Since the target object may contain advertising materials such as pictures and videos, the information of the target object may include information of the advertising materials, such as picture information or video information, etc. The information of the target object may also include the target object's purchase plan, etc.

[0053] The identification information of the traffic user also includes a user click monitoring identifier, which is used to track the user's click behavior, such as the source, channel, and advertising identifier.

[0054] Step 102: Based on the user click monitoring identifier, determine the revenue generated by the traffic user and the acquisition cost of the traffic user.

[0055] Since the user click monitoring identifier can track the advertising identifier, source, and channel, the revenue generated by the traffic user and the acquisition cost of the traffic user can be determined through the advertising identifier and the advertising source and channel.

[0056] In one possible implementation, determining the revenue generated by a traffic user and the acquisition cost of the traffic user based on the user click monitoring identifier includes:

[0057] Determine the type of target application entered by clicking the target object based on the user click monitoring identifier;

[0058] If the target application is of the first type, the revenue generated by the traffic user is calculated by summing the bid prices for each ad exposure after the traffic user enters the target application. The acquisition cost of the traffic user is calculated as the ratio of the purchase cost corresponding to the target object's information identifier to the number of daily active users.

[0059] If the target application is of the second type, the bidding prices of each ad exposure after multiple traffic users enter the target application are summed to obtain the revenue generated by the traffic users, and the conversion bid is used as the acquisition cost of the traffic users.

[0060] Because different target applications can generate different monetization values, some applications have higher monetization values, enabling a positive return on investment (ROI) for a single user. Therefore, an advertising ROI (Return on Investment) feedback strategy can be adopted. On the other hand, some applications have lower monetization values, making it difficult to achieve a positive ROI for a single user. Therefore, a multi-user ROI feedback strategy can be adopted.

[0061] The monetization value of the first type of applications is higher than that of the second type of applications. For the first type of applications, the return on investment brought by a single traffic user entering the application can be calculated. For the second type of applications, such as quick applications, the return on investment brought by multiple users entering the application can be calculated.

[0062] The return on investment is the ratio of revenue to cost. Therefore, before calculating the return on investment, you can determine the revenue generated by traffic users and the cost of acquiring traffic users.

[0063] If the target application is type 1, the revenue generated by the traffic user is calculated by summing the bid prices for each ad exposure after the traffic user enters the target application. The traffic user enters the target application through the target platform, where an ad is displayed within the target application. This ad can be exposed once or multiple times, and each exposure is associated with a bid price. The revenue generated by the traffic user is calculated by summing these bid prices. This bid price represents the price paid by advertisers for conversions (e.g., ad views, clicks, and orders) when their ads appear within the target application.

[0064] If the target application is of the first type, the consumption is calculated at the OAID granularity, using the average cost at the target object's information identifier granularity. In practical applications, the purchase cost corresponding to the target object's information identifier and the DAU (Daily Active Users) corresponding to the target object's information identifier can be determined. The ratio of the purchase cost corresponding to the target object's information identifier to the number of daily active users is used as the acquisition cost of the traffic user.

[0065] If the target application is of the second type, calculate the ad impression price for each OAID corresponding to the target object's information identifier on that day. Sum the bid prices for each ad impression after multiple traffic users access the target application to calculate the revenue generated by the traffic user. The conversion bid is used as the acquisition cost of the traffic user. This conversion bid is the target price set for the user to complete the conversion behavior.

[0066] Step 103: Determine the return on investment of the traffic user based on the revenue generated by the traffic user and the acquisition cost of the traffic user.

[0067] Calculate the ratio of the revenue generated by traffic users to the acquisition cost of traffic users to obtain the return on investment of traffic users.

[0068] If the target application is of the first type, the ROI for that traffic user is the ratio of the advertising revenue from that traffic flow to the cost per DAU. The advertising revenue for that traffic flow is the sum of the bid prices for each ad exposure after a traffic user enters the target application. The cost per DAU is the ratio of the traffic purchase cost corresponding to the target application's information identifier to the number of daily active users.

[0069] If the target application is of the second type, the ROI of the traffic user is the ratio of the total revenue generated by multiple users to the conversion bid. The total revenue generated by multiple users is the sum of the bid prices for each ad exposure after the traffic users enter the target application.

[0070] Step 104: When the traffic user's return on investment is greater than the target return on investment, the traffic user's identification information is transmitted back to the target platform, so that the target platform searches for a target user whose user value matches the traffic user corresponding to the traffic user's identification, and displays the target object to the target user according to the target object information indicated by the information identifier.

[0071] To improve advertising efficiency and effectiveness, a return can be made when the ROI of traffic users exceeds the target ROI. This target ROI can be 1 or greater, such as 1.1 or 1.2, and can be set according to actual needs.

[0072] For type 1 target applications, a callback can be triggered when a traffic user's return on investment (ROI) exceeds 1 (i.e., the ratio of advertising revenue from this traffic investment to the cost per daily active user (DAU) is greater than 1). The data returned in this case contains the traffic user's identification information. In actual applications, the ROI can be written to a Kafka stream, and data can be updated at a preset interval, such as every minute. This Kafka stream field can include the traffic user's identification information and the ROI. The ROI can also be queried from the Kafka stream using the traffic user's identification information.

[0073] For the second type of target application, a callback can be triggered when the ratio of the sum of the bid prices for each ad exposure of multiple traffic users after they access the target application to the conversion bid exceeds the target return on investment. The data returned in this case can be the identification information of one of the multiple traffic users, and this traffic user can be the user with the highest bid price for the first ad exposure of the day.

[0074] The above feedback methods can mitigate the phenomenon of ignoring the unit price of ad impressions, which can lead to an increase in CVR (Conversion Rate) but a decrease in ROI. By monitoring CVR and ROI in real time and dynamically adjusting feedback methods, you can ensure a stable ROI.

[0075] After transmitting the identification information of the traffic user back to the target platform, the target platform can search for a target user whose user value matches the traffic user corresponding to the identification of the traffic user, and display the target object to the target user according to the target object information indicated by the information identifier.

[0076] To enable the target platform to provide more suitable users to the monetization platform and optimize advertising effectiveness, the identification information of the traffic user can be transmitted back to the target platform. The target platform can then use this identification information to find matching users, specifically by user value. This user value can be the entire lifecycle value, which includes the user's advertising value, paid value, and retention value. Advertising value is the monetization revenue generated by users through ad exposure / clicks, paid value is the net revenue generated by users' direct consumption, and retention value is the indirect value generated by users' continued activity.

[0077] This user value can be derived based on the constructed user value model. The user value model construction process involves obtaining the identifiers corresponding to each traffic user on the target platform, acquiring user behavior data (such as registration, payment, and active users) from the ad monetization platform, and all ad request, fill, impression, click, and revenue data received from the ad monetization platform. This data also carries the identifiers corresponding to each traffic user. The full-link data chain, including traffic acquisition, ad clicks, app launches, behavior (such as registration, payment, and active users), and monetization, is mapped to the identifiers identifying the traffic user. This mapping allows data from the same traffic acquisition source to be associated with the corresponding monetization data. This allows for the effective integration and sharing of traffic acquisition data (such as traffic consumption, impressions, clicks, installs, key behavior conversions, and costs) from the target platform and monetization data (such as ad revenue, impressions, and clicks) from the monetization platform. The acquired traffic user data is cleaned to remove abnormal data. The contribution of each channel, ad group, and creative to user activation, ad monetization, and user payment is analyzed. Key indicators may include but are not limited to user ROI, user acquisition cost, key behavior cost, eCPM (effective Cost Per Mille), etc., calculate and predict the user's advertising value, payment value, retention value and other life cycle values, and build a user value model.

[0078] After finding the target user whose user value matches the traffic user corresponding to the identifier of the traffic user, the target object can be displayed to the target user according to the target object information indicated by the information identifier. The target object information indicated by the information identifier may include but is not limited to a creative combination of advertising materials, an advertising plan, a volume purchase plan, etc. The creative combination of advertising materials is a combination of pictures and videos, and the advertising plan includes exposure, clicks, conversion rate, etc. The volume purchase plan includes plans to acquire high-value users. Displaying the target object to the target user according to the above target object information realizes the screening of user traffic. The user traffic is the number of users who visit a platform, website, application or service within a certain period of time. It reflects the user's attention, activity and frequency of use of the product or service, and is an important indicator for measuring business scale, user stickiness and market influence. Adjust the goals of the advertising delivery strategy according to the monetization data to make the user's performance in the volume purchase stage and the monetization stage consistent, and reduce the probability of users attracted in the volume purchase stage being lost in the monetization stage.

[0079] In a possible implementation, the data processing method further includes:

[0080] Obtain the number of postbacks corresponding to the information identifier of the target object and the number of clicks on the target object;

[0081] Determine the ratio of postbacks to clicks to get the target conversion rate;

[0082] When the target conversion rate is greater than the upper conversion rate limit, increase the target return on investment;

[0083] When the target conversion rate is lower than the conversion rate lower limit, reduce the target return on investment.

[0084] Click monitoring can be used to calculate the number of clicks on the target object, and the target conversion rate can be updated at intervals, such as once per minute. If the target conversion rate is greater than the upper conversion rate limit, the number of postbacks may be high. In this case, you can reduce postbacks and increase the target ROI by, for example, 0.05 or another value. If the target conversion rate is less than the lower conversion rate limit, the number of postbacks may be low. In this case, you can increase postbacks and decrease the target ROI by, for example, 0.05 or another value.

[0085] Optionally, the target conversion rate may be adjusted based on the ROI. Specifically, when the ROI is greater than the upper limit of the ROI, the target return on investment may be increased, and when the ROI is less than the lower limit of the ROI, the target return on investment may be decreased.

[0086] In a possible implementation, the data processing method further includes:

[0087] If at least one of conditions 1 to 3 is met, the traffic user's identification information is transmitted back to the target platform:

[0088] Condition 1: The number of times the traffic user clicks on the target advertisement is greater than a first preset number; the target advertisement is an advertisement displayed by the target application, and the target application is the application entered by clicking the target object;

[0089] Condition 2: The number of times the advertisement is displayed to traffic users is greater than a second preset number;

[0090] Condition three: The number of times the traffic user invokes the target application is greater than a third preset number.

[0091] In the early stages of an advertising monetization platform, it may be difficult to achieve a positive ROI. At this time, you can acquire more traffic to increase user clicks, ad exposures, and app activations.

[0092] For ad click callback, the callback may be triggered when the number of times a traffic user clicks on a target ad is greater than a first preset number.

[0093] For advertisement exposure feedback, the feedback may be triggered when the number of times the advertisement is displayed to traffic users is greater than a second preset number.

[0094] For application call-back, the call-back may be triggered when the number of times the traffic user calls up the target application program is greater than a third preset number.

[0095] In a possible implementation, after determining the revenue generated by the traffic user and the acquisition cost of the traffic user in step 102, the method further includes:

[0096] Determine the user acquisition cost and user lifetime value of the target platform based on the revenue generated by traffic users and the acquisition cost of traffic users;

[0097] Determine the target platform's ROI based on its user acquisition cost and user lifetime value.

[0098] In the case where the return on investment of the target platform exceeds a preset range, determining target parameters that affect the return on investment of the target platform;

[0099] Target parameters are adjusted so that the return on investment of the target platform is within the preset range.

[0100] Traffic users are also users of the target platform. If there are multiple target platforms, the user value model can be used to calculate the user acquisition cost and user lifetime value for each target platform based on the revenue generated by each traffic user and the acquisition cost of the traffic user. Then, the ratio of user lifetime value to the user acquisition cost of the target platform can be used to determine the return on investment of the target platform.

[0101] After calculating the return on investment of the target platform, if the return on investment is high, higher than the upper limit of the preset range, the possible reason is that the user lifetime value is high and / or the user acquisition cost of the target platform is low. In this case, the user lifetime value can be reduced and / or the user acquisition cost of the target platform can be increased; if the return on investment is low, lower than the lower limit of the preset range, the possible reason is that the user lifetime value is low and / or the user acquisition cost of the target platform is high. In this case, the user lifetime value can be increased and / or the user acquisition cost of the target platform can be reduced.

[0102] Adjustments to user acquisition costs and user lifetime value can be achieved by adjusting target parameters, including volume and monetization parameters. Volume parameters can include ad bids and creative combinations, while monetization parameters can include ad price per unit (e.g., eCPM), ad display frequency, and format, including rewarded video and interstitial ads. These target parameters are adjusted to ensure the target platform's return on investment falls within a preset range.

[0103] In one possible implementation, target parameters are adjusted so that the return on investment of the target platform is within a preset range, including:

[0104] With the goal of maximizing the target platform's ROI, and subject to the budget not exceeding the target platform's budget cap and the cost per action (CPA) not exceeding the cost cap, adjust the volume buying parameters and / or monetization parameters to ensure the target platform's ROI is within the preset range.

[0105] Target parameters related to user acquisition costs include traffic parameters, such as ad bids and ad creative combinations. Higher bids increase user acquisition costs, and vice versa. When adjusting bids for traffic parameters, you can use a user value model to identify users with different lifetime values (ULVs). The higher the ULV, the higher the ad bid. The effectiveness of ad creative combinations (such as click-through rate and conversion rate) can be measured through A / B testing. Choosing ad creative combinations with high click-through rates or conversion rates will increase user acquisition costs.

[0106] Target parameters related to user lifetime value include monetization parameters such as ad unit price (e.g., eCPM), ad display frequency, and format. Ad unit price refers to the price paid by advertisers for ads played on the ad monetization platform. Increasing ad unit price can increase user ad value, thereby improving user lifetime value. Higher ad display frequency increases ad value, further increasing user lifetime value. Different ad display formats correspond to different ad unit prices, thus adjusting user lifetime value.

[0107] To balance user experience and revenue, you can dynamically adjust ad display frequency based on user behavior data (such as registration, payment, and active users) to avoid user churn caused by excessive display. Ad display formats can be dynamically adjusted based on performance evaluation. To maximize revenue, you can prioritize high eCPM ad formats. You can also make user targeting adjustments, such as displaying ads with different content based on user age or location.

[0108] By adjusting both acquisition and monetization parameters with the goal of maximizing the return on investment (ROI) on the target platform, we can address the problem of existing ad platform algorithms typically optimizing only single metrics (such as click-through rate or impressions) while ignoring the balance between user lifetime value (LTV) and ROI. This allows for full optimization of the entire process, from user acquisition to monetization. For example, advertisers can adjust their advertising strategies in real time based on monetization data and optimize monetization strategies based on user sources.

[0109] The above describes a data processing method provided in an embodiment of the present application. The following describes a system for executing the above data processing method.

[0110] See also Figure 2 , Figure 2 This is a structural diagram of a data processing system provided in an embodiment of the present application. Figure 2 As shown, the data processing system includes:

[0111] Acquisition module 201 is used to obtain the identification information of the traffic user; wherein, the traffic user is the user who clicks the target object displayed on the target platform, and the identification information includes the traffic user's identification, the information identification of the target object, and the user click monitoring identification generated after clicking the target object.

[0112] The first calculation module 202 is used to determine the revenue generated by the traffic user and the acquisition cost of the traffic user based on the user click monitoring identifier.

[0113] The second calculation module 203 is configured to determine a return on investment of the traffic user based on the revenue generated by the traffic user and the acquisition cost of the traffic user.

[0114] The feedback module 204 is used to transmit the identification information of the traffic user back to the target platform when the return on investment of the traffic user is greater than the target return on investment, so that the target platform can find a target user whose user value matches the traffic user corresponding to the identification of the traffic user, and display the target object to the target user according to the target object information indicated by the information identifier.

[0115] In a possible implementation, the first calculation module 202 is specifically configured to:

[0116] Determine the type of target application entered by clicking the target object based on the user click monitoring identifier;

[0117] If the target application is of the first type, the revenue generated by the traffic user is calculated by summing the bid prices for each ad exposure after the traffic user enters the target application. The acquisition cost of the traffic user is calculated as the ratio of the purchase cost corresponding to the target object's information identifier to the number of daily active users.

[0118] If the target application is of the second type, the bidding prices of each ad exposure after multiple traffic users enter the target application are summed to obtain the revenue generated by the traffic users, and the conversion bid is used as the acquisition cost of the traffic users.

[0119] In one possible implementation, the data processing system provided by the present application further includes:

[0120] The target return on investment adjustment module is used to obtain the number of callbacks corresponding to the information identifier of the target object and the number of clicks on the target object; determine the ratio of the number of callbacks to the number of clicks to obtain the target conversion rate; when the target conversion rate is greater than the upper limit of the conversion rate, increase the target return on investment; when the target conversion rate is less than the lower limit of the conversion rate, reduce the target return on investment.

[0121] In a possible implementation, the return module 204 is further configured to:

[0122] If at least one of conditions 1 to 3 is met, the traffic user's identification information is transmitted back to the target platform:

[0123] Condition 1: The number of times the traffic user clicks on the target advertisement is greater than a first preset number; the target advertisement is an advertisement displayed by the target application, and the target application is the application entered by clicking the target object;

[0124] Condition 2: The number of times the advertisement is displayed to traffic users is greater than a second preset number;

[0125] Condition three: The number of times the traffic user invokes the target application is greater than a third preset number.

[0126] In one possible implementation, the data processing system provided by the present application further includes:

[0127] The parameter adjustment module is used to determine the user acquisition cost and user lifetime value of the target platform based on the revenue generated by traffic users and the acquisition cost of traffic users after determining the revenue generated by traffic users and the acquisition cost of traffic users; determine the return on investment of the target platform based on the user acquisition cost and user lifetime value of the target platform; when the return on investment of the target platform exceeds a preset range, determine the target parameters that affect the return on investment of the target platform; and adjust the target parameters so that the return on investment of the target platform is within the preset range.

[0128] In a possible implementation, the parameter adjustment module is further configured to:

[0129] With the goal of maximizing the return on investment of the target platform, and with the budget value not exceeding the budget ceiling of the target platform and the cost of a single action not exceeding the cost ceiling, adjust the buying parameters and / or monetization parameters to ensure that the return on investment of the target platform is within the preset range.

[0130] An electronic device is also provided in an embodiment of the present application. Figure 3 , which shows a schematic diagram of the structure of an electronic device suitable for implementing the embodiments of the present application. The electronic device in the embodiments of the present application may include, but is not limited to, fixed terminals such as mobile phones, laptops, PDAs (personal digital assistants), PADs (tablet computers), desktop computers, etc. Figure 3 The electronic device shown is merely an example and should not limit the functions and scope of use of the embodiments of the present application.

[0131] like Figure 3 As shown, the electronic device may include a processing device (e.g., a central processing unit, a graphics processing unit, etc.) 301, which can perform various appropriate actions and processes based on programs stored in a read-only memory (ROM) 302 or programs loaded from a storage device 308 into a random access memory (RAM) 303. When the electronic device is powered on, the RAM 303 also stores various programs and data required for the operation of the electronic device. The processing device 301, ROM 302, and RAM 303 are interconnected via a bus 304. An input / output (I / O) interface 305 is also connected to the bus 304.

[0132] Typically, the following devices may be connected to the I / O interface 305: an input device 306 including, for example, a touch screen, a touchpad, a keyboard, a mouse, a camera, a microphone, an accelerometer, a gyroscope, etc.; an output device 307 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; a storage device 308 including, for example, a memory card, a hard disk, etc.; and a communication device 309. The communication device 309 may allow the electronic device to communicate with other devices wirelessly or by wire to exchange data. Figure 3 The electronic device is shown with various devices, but it should be understood that it is not required to implement or possess all of the devices shown. More or fewer devices may be implemented or possessed instead.

[0133] The electronic device can implement the above-mentioned data processing method.

[0134] An embodiment of the present application also provides a computer program product including computer-readable instructions. When the computer-readable instructions are executed on an electronic device, the electronic device implements any data processing method provided in the embodiment of the present application.

[0135] A computer-readable storage medium is also provided in an embodiment of the present application. The storage medium carries one or more computer programs. When the one or more computer programs are executed by an electronic device, the electronic device can implement any data processing method provided in the embodiment of the present application.

[0136] It should also be noted that the device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separate, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed across multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the present embodiment. In addition, in the drawings of the device embodiments provided in this application, the connection relationship between the modules indicates that there is a communication connection between them, which can be specifically implemented as one or more communication buses or signal lines.

[0137] Through the description of the above embodiments, those skilled in the art can clearly understand that the present application can be implemented by means of software plus necessary general hardware, and of course can also be implemented by special hardware including application-specific integrated circuits, special CPUs, special memories, special components, etc. In general, all functions performed by computer programs can be easily implemented with corresponding hardware, and the specific hardware structures used to implement the same function can also be diverse, such as analog circuits, digital circuits or special circuits, etc. However, for the present application, software program implementation is a better implementation method in most cases. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art can be embodied in the form of a software product, which is stored in a readable storage medium, such as a computer's floppy disk, USB flash drive, mobile hard disk, ROM, RAM, magnetic disk or optical disk, etc., and includes a number of instructions to enable a computer device (which can be a personal computer, training equipment, or network equipment, etc.) to execute the methods described in each embodiment of the present application.

[0138] In the above embodiments, all or part of the embodiments may be implemented by software, hardware, firmware, or any combination thereof. When implemented by software, all or part of the embodiments may be implemented in the form of a computer program product.

[0139] The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from a website, a computer, a training device or a data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) mode to another website, a computer, a training device or a data center. The computer-readable storage medium can be any available medium that a computer can store or a data storage device such as a training device, a data center, etc. that includes one or more available media integrations. The available medium can be a magnetic medium, (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a solid-state drive (SSD)).

Claims

1. A data processing method, characterized in that: include: Obtain identification information of a traffic user; wherein the traffic user is a user who clicks a target object displayed on a target platform, and the identification information includes an identifier of the traffic user, an information identifier of the target object, and a user click monitoring identifier generated after clicking the target object; Determining the revenue generated by the traffic user and the acquisition cost of the traffic user based on the user click monitoring identifier; Determining a return on investment for the traffic user based on the revenue generated by the traffic user and the acquisition cost of the traffic user; When the return on investment of the traffic user is greater than the target return on investment, the identification information of the traffic user is transmitted back to the target platform, so that the target platform searches for a target user whose user value matches the traffic user corresponding to the identification of the traffic user, and displays the target object to the target user according to the target object information indicated by the information identification.

2. The data processing method according to claim 1, wherein: The determining, based on the user click monitoring identifier, the revenue generated by the traffic user and the acquisition cost of the traffic user, includes: Determining, based on the user click monitoring identifier, the type of a target application entered by clicking the target object; If the target application is of the first type, summing the bid prices for each ad exposure of a traffic user after the traffic user enters the target application to obtain the revenue generated by the traffic user, and using the ratio of the traffic purchase cost corresponding to the information identifier of the target object to the number of daily active users as the acquisition cost of the traffic user; If the type of the target application is the second type, the bidding prices of each advertisement exposure after multiple traffic users enter the target application are summed to obtain the revenue generated by the traffic user, and the conversion bid is used as the acquisition cost of the traffic user.

3. The data processing method according to claim 1, wherein: Also includes: Obtaining the number of postbacks corresponding to the information identifier of the target object and the number of clicks on the target object; Determine the ratio of the number of postbacks to the number of clicks to obtain a target conversion rate; When the target conversion rate is greater than the conversion rate upper limit, increasing the target return on investment; When the target conversion rate is less than the conversion rate lower limit, the target return on investment is reduced.

4. The data processing method according to claim 1, wherein: Also includes: If at least one of conditions 1 to 3 is met, the identification information of the traffic user is transmitted back to the target platform: Condition 1: The number of times the traffic user clicks on the target advertisement is greater than a first preset number; The target advertisement is an advertisement displayed by a target application, and the target application is an application entered by clicking the target object; Condition 2: The number of times the advertisement is displayed to the traffic user is greater than a second preset number; Condition three: the number of times the traffic user invokes the target application is greater than a third preset number.

5. The data processing method according to any one of claims 1 to 4, characterized in that: After determining the revenue generated by the traffic user and the acquisition cost of the traffic user, the method further includes: Determine the user acquisition cost and user lifetime value of the target platform based on the revenue generated by the traffic users and the acquisition cost of the traffic users; Determine the return on investment of the target platform based on the user acquisition cost and user lifetime value of the target platform; When the return on investment of the target platform exceeds a preset range, determining a target parameter that affects the return on investment of the target platform; The target parameters are adjusted so that the return on investment of the target platform is within the preset range.

6. The data processing method according to claim 5, characterized in that: The adjusting the target parameters so that the return on investment of the target platform is within the preset range includes: With the goal of maximizing the return on investment of the target platform, and with the budget value not exceeding the budget ceiling of the target platform and the cost of a single action not exceeding the cost ceiling, the buying volume parameters and / or monetization parameters are adjusted to ensure that the return on investment of the target platform is within the preset range.

7. A data processing system, characterized in that: include: An acquisition module is configured to acquire identification information of a traffic user; wherein the traffic user is a user who clicks a target object displayed on a target platform, and the identification information includes an identification of the traffic user, an information identification of the target object, and a user click monitoring identification generated after clicking the target object; A first calculation module is configured to determine the revenue generated by the traffic user and the acquisition cost of the traffic user based on the user click monitoring identifier; a second calculation module, configured to determine a return on investment of the traffic user based on the revenue generated by the traffic user and the acquisition cost of the traffic user; A feedback module is used to transmit the identification information of the traffic user back to the target platform when the return on investment of the traffic user is greater than the target return on investment, so that the target platform can search for a target user whose user value matches the traffic user corresponding to the identification of the traffic user, and display the target object to the target user according to the target object information indicated by the information identifier.

8. A computer program product, characterized in that The method comprises computer-readable instructions, which, when executed on an electronic device, enable the electronic device to implement the data processing method according to any one of claims 1 to 6.

9. An electronic device, characterized in that: comprising at least one processor and a memory connected to the processor, wherein: The memory is used to store computer programs; The processor is configured to execute the computer program so that the electronic device can implement the data processing method according to any one of claims 1 to 6.

10. A computer storage medium, characterized in that The storage medium carries one or more computer programs, and when the one or more computer programs are executed by an electronic device, the electronic device can implement the data processing method according to any one of claims 1 to 6.

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