Method and apparatus for promoting objects

Abstract

The present application provides a method and device for processing promotion objects, relating to the field of Internet technology. The method includes: obtaining business attribute information of a target business; determining multiple promotion objects corresponding to the target business from a promotion object library; obtaining historical feedback data, historical delivery data, and reference attribute information of a first reference business corresponding to the multiple promotion objects; wherein the first reference business is a business that has delivered at least one promotion object among the multiple promotion objects; based on the business attribute information, historical feedback data, historical delivery data, and reference attribute information, determining the delivery value of the multiple promotion objects; and sorting the multiple promotion objects according to the delivery value to obtain an object sorting result. Based on this solution, the recommendation matching and accuracy of the promotion objects can be improved, thereby optimizing the promotion effect.

Description

Technical Field

[0001] This application relates to the field of Internet technology, and in particular to a method and apparatus for processing promotional objects. Background Technology

[0002] With the popularization and development of the internet, online advertising has become an important way to promote information, advertise business products, and attract new customers. Existing technologies typically allocate and expose advertising to overall traffic or associated targets to improve business conversion rates. While this may have some macroscopic effect, these methods lack business targeting and target selection measures, resulting in poor promotional effects. Furthermore, they cannot effectively trace and pinpoint the impact of various factors on the promotional results.

[0003] Therefore, there is a need to provide an improved solution for handling promotional targets in order to solve the problems existing in the prior art and optimize the promotion effect. Summary of the Invention

[0004] This application provides a method and apparatus for processing promotional objects, specifically including the following:

[0005] On the one hand, this application provides a method for processing promotional targets, the method comprising:

[0006] Obtain the business attribute information of the target business;

[0007] Identify multiple promotional targets corresponding to the target business from the promotional target library;

[0008] Obtain historical feedback data, historical delivery data, and reference attribute information of the first reference business corresponding to the plurality of promotional objects; wherein, the first reference business is a business that has been delivered to at least one of the plurality of promotional objects;

[0009] Based on the business attribute information, the historical feedback data, the historical delivery data, and the reference attribute information, the delivery value of the multiple promotion targets is determined;

[0010] The multiple promotional targets are sorted according to the placement value to obtain the object ranking result.

[0011] On the other hand, a processing device for promotional targets is provided, the device comprising:

[0012] First information acquisition module: used to acquire business attribute information of the target business;

[0013] Promotion Target Determination Module: Used to determine multiple promotion targets corresponding to the target business from the promotion target library;

[0014] The second information acquisition module is used to acquire historical feedback data, historical delivery data, and reference attribute information of the first reference service corresponding to the plurality of promotional objects; wherein, the first reference service is a service that has been delivered to at least one of the plurality of promotional objects;

[0015] The value determination module is used to determine the value of the multiple promotion targets based on the business attribute information, the historical feedback data, the historical delivery data, and the reference attribute information.

[0016] Object sorting module: used to sort the multiple promotional objects according to the placement value, and obtain the object sorting result.

[0017] On the other hand, a processing device for promotional objects is provided, the device including a processor and a memory, the memory storing at least one instruction or at least one program segment, the at least one instruction or the at least one program segment being loaded and executed by the processor to implement the processing method for promotional objects as described above.

[0018] On the other hand, a computer-readable storage medium is provided, wherein at least one instruction or at least one program is stored therein, the at least one instruction or the at least one program being loaded and executed by a processor to implement the processing method of the generalized object as described above.

[0019] On the other hand, a server is provided, the server including a processor and a memory, the device including a processor and a memory, the memory storing at least one instruction or at least one program, the at least one instruction or the at least one program being loaded and executed by the processor to implement the processing method of the generalized object as described above.

[0020] On the other hand, a computer program product or computer program is provided, which includes computer instructions that, when executed by a processor, implement the processing method of the generalized object as described above.

[0021] The processing method, apparatus, equipment, storage medium, server, and computer program product for the target object provided in this application have the following technical effects:

[0022] This application obtains business attribute information of the target business; identifies multiple promotional targets corresponding to the target business from the promotional target database; obtains historical feedback data, historical delivery data, and reference attribute information of a first reference business for the multiple promotional targets; wherein the first reference business is a business that has been promoted to at least one of the multiple promotional targets; determines the delivery value of the multiple promotional targets based on the business attribute information, historical feedback data, historical delivery data, and reference attribute information; and sorts the multiple promotional targets according to their delivery value to obtain a ranking result. Based on this scheme, the delivery value of each promotional target for the target business can be determined by comprehensively considering multi-dimensional information, and the obtained ranking result is strongly correlated with the attributes, feedback expectations, and historical delivery status of the target business. This facilitates relevant personnel in determining target promotional targets based on the result, improving the matching and accuracy of promotional target recommendations, and thus optimizing the promotion effect. Attached Figure Description

[0023] To more clearly illustrate the technical solutions and advantages in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0024] Figure 1 This is a schematic diagram of an application environment provided in an embodiment of this application;

[0025] Figure 2 This is a structural block diagram of a social operation management platform provided in an embodiment of this application;

[0026] Figure 3 This is a data flow diagram of a social operation management platform provided in an embodiment of this application;

[0027] Figure 4 This is a flowchart illustrating a method for processing a promotional object provided in an embodiment of this application;

[0028] Figure 5-11 This is a schematic diagram of the platform interface corresponding to the social operation management platform displayed on the terminal according to one embodiment of this application;

[0029] Figure 12 This is a flowchart illustrating a method for processing promotional objects provided in an embodiment of this application;

[0030] Figure 13 This is a flowchart illustrating a method for processing promotional objects provided in an embodiment of this application;

[0031] Figure 14This is a schematic diagram of the operation flow of an information display interface for a social management client provided in an embodiment of this application;

[0032] Figure 15 This is a flowchart illustrating a method for processing promotional objects provided in an embodiment of this application;

[0033] Figure 16 This is a schematic diagram of the structure of a processing device for a target application provided in an embodiment of this application;

[0034] Figure 17 This is a schematic diagram of the structure of a processing device for a target application provided in an embodiment of this application;

[0035] Figure 18 This is a hardware structure block diagram of a server for a method of processing promotional objects provided in an embodiment of this application. Detailed Implementation

[0036] The embodiments of this application can be applied to various scenarios such as cloud technology, artificial intelligence, intelligent transportation, and assisted driving. The technical solutions of the embodiments of this application can utilize cloud computing and cloud storage technologies to provide resource data services such as business data and object data for the processing of promotional objects.

[0037] Cloud computing refers to the delivery and usage model of IT infrastructure, meaning obtaining necessary resources through a network in an on-demand and easily scalable manner. In a broader sense, cloud computing also refers to the delivery and usage model of services, meaning obtaining necessary services through a network in an on-demand and easily scalable manner. These services can be IT and software related, internet-related, or other services. Cloud computing is a product of the development and integration of traditional computer and network technologies such as grid computing, distributed computing, parallel computing, utility computing, network storage technologies, virtualization, and load balancing. Cloud storage is a new concept that extends and develops from cloud computing. A distributed cloud storage system (hereinafter referred to as a storage system) refers to a storage system that uses cluster applications, grid technology, and distributed storage file systems to aggregate a large number of various types of storage devices (storage devices are also called storage nodes) in a network to work collaboratively, providing data storage and business access functions.

[0038] Currently, the storage method of storage systems is as follows: Logical volumes are created. During the creation of a logical volume, physical storage space is allocated to each logical volume. This physical storage space may consist of a single storage device or the disks of several storage devices. Clients store data on a logical volume, which means storing the data on the file system. The file system divides the data into many parts, each part being an object. Each object contains not only the data but also additional information such as a data identifier (ID, ID entity). The file system writes each object to the physical storage space of that logical volume and records the storage location information of each object. Therefore, when a client requests access to data, the file system can allow the client to access the data based on the storage location information of each object.

[0039] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this application.

[0040] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or server that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or devices.

[0041] See also Figure 1 , Figure 1 This is a schematic diagram of an application environment provided in an embodiment of this application, such as... Figure 1 As shown, the application environment may include at least server 01 and terminal 02. In practical applications, server 01 and terminal 02 can be directly or indirectly connected via wired or wireless communication to enable interaction between terminal 02 and server 01. This application does not impose any restrictions on this.

[0042] In this embodiment, server 01 can be an independent physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDN (Content Delivery Network), and big data and artificial intelligence platforms. Specifically, the server can include physical devices, such as network communication units, processors, and memory, and software running on the physical devices, such as applications. In this embodiment, server 01 can be used to obtain business attribute information of the target business, determine multiple promotional objects corresponding to the target business from the promotional object library; obtain historical feedback data, historical delivery data, and reference attribute information of the first reference business corresponding to the multiple promotional objects; determine the delivery value of the multiple promotional objects based on the business attribute information, historical feedback data, historical delivery data, and reference attribute information; sort the multiple promotional objects according to the delivery value to obtain the object sorting result; generate and send a list of promotional objects corresponding to the multiple promotional objects to the terminal based on the object sorting result, so that the terminal can display the list of promotional objects. Specifically, server 01 can also provide services such as generating business performance reports and identifying target audiences for promotion.

[0043] In this embodiment, terminal 02 may include physical devices such as smartphones, desktop computers, tablets, laptops, digital assistants, augmented reality (AR) / virtual reality (VR) devices, smart TVs, smart speakers, smart wearable devices, and in-vehicle terminal devices, and may also include software running on the physical device, such as applications.

[0044] In this embodiment, terminal 02 can provide an information display interface and generate corresponding operation instructions in response to interactive information submitted by the account for the information display interface. The operation instructions are then sent to server 01, enabling server 01 to perform corresponding information processing based on the information carried by the operation instructions. Specifically, the interactive information may include login information, business selection information, and information on viewing promotional targets. Furthermore, terminal 02 can also display the list of promotional targets and business performance reports sent by server 01 on the corresponding display interface.

[0045] In addition, it should be noted that, Figure 1 The example shown is merely an application environment for a method of processing promotional objects. This application environment may include more or fewer nodes, and this application does not impose any restrictions here.

[0046] In this embodiment, the server can run a social operations management platform, and the processing method for the promotion targets of this application is implemented based on the social operations management platform. The social operations management platform is an online social management platform serving business project teams. Taking a game project team as an example, the social operations management platform can provide recommendation services such as preferred gameplay activities and gift packs corresponding to the game's characteristics, and can achieve social traffic distribution for the game through algorithms and system empowerment. Correspondingly, the terminal can run a social operations client that matches the social operations management platform.

[0047] In some embodiments, please refer to Figure 2 , Figure 2 This diagram illustrates the structure of a social media operations management platform. The platform comprises the following subsystems: a promotion target database, a project business database, a feedback database, a scheduling management system, data statistics, a promotion target / feedbacker tag update system, and a recommendation algorithm subsystem. The promotion target database stores promotion target data; the project business database stores business attribute information for each project; the feedback database stores data on feedbackers associated with the social media operations management platform; the scheduling management subsystem manages and schedules the launch of recommended promotion targets; the data statistics subsystem performs statistical processing on feedback data and business deployment data; the promotion target / feedbacker tag update subsystem stores and updates tag information for promotion targets and associated feedbackers; and the recommendation algorithm subsystem stores preset value algorithms and preset target recommendation models to determine the deployment value of promotion targets and to identify the target promotion targets for the current business. Specifically, taking a game project group as the business project group and an activity gameplay as the promotion target, the promotion target database stores activity gameplay data, and the project business database stores business data such as game attribute information for each game project. In some cases, feedbackers are users within the social media operations management platform.

[0048] For details, please refer to Figure 3 The platform can periodically generate and update the campaign value of each campaign in the campaign target library based on the recommendation algorithm subsystem, using data from the feedbacker library, the campaign target / feedbacker tag update subsystem, the project business library, and the data statistics subsystem. For example, it can update the campaign value at 0:00 every day. After the campaign target goes live, it collects the corresponding feedback data and synchronizes it to the data statistics subsystem. The statistically generated data is then written into the project business library, which in turn provides data support for the campaign target / feedbacker tag update subsystem to generate updated feedbacker tags and write the updated feedbacker tag data into the feedbacker library.

[0049] The following describes a method for processing promotional targets based on the above application environment and / or social operation management platform, applied to the server side. Figure 4This is a flowchart illustrating a method for processing a target object according to an embodiment of this application. This specification provides method operation steps as shown in the embodiments or flowcharts, but based on conventional or non-inventive labor, more or fewer operation steps may be included. The order of steps listed in the embodiments is merely one possible execution order among many, and does not represent the only execution order. In actual system or server product execution, the method can be executed sequentially according to the embodiments or drawings, or in parallel (e.g., in a parallel processor or multi-threaded processing environment). Specifically, as shown... Figure 4 As shown, the method may include:

[0050] S201: Obtain the business attribute information of the target business.

[0051] In this embodiment, the target service can be a service determined based on interactive information sent by the terminal. The target service provides services to a target object, which may include a feedback provider associated with the social operation management platform or a registered account of a feedback provider, or a potential feedback provider outside the social operation management platform. The social operation management platform may have multiple target accounts, each with corresponding management permissions, capable of viewing and configuring associated project information. Each associated project includes at least one service. The aforementioned interactive information may be information submitted by the target account to the social management client on the terminal. For example, the interactive information may be account login information submitted by the target account on the terminal. After receiving the account login information, the server provides services under the management permissions of the target account based on the account login information, thereby determining it as the target service. In some cases, one target account corresponds to multiple services, and the interactive information may also include service-specific operation information submitted by the target account on the terminal. The server determines the corresponding specified service as the target service based on this service-specific operation information. Specifically, the target service may include, but is not limited to, game services, instant messaging services, and multimedia services. Specifically, the service attribute information represents the multi-dimensional attributes of the service, and may include, but is not limited to, service category information, lifecycle information, and service target information. Among them, business category information represents the business category, which can be a category identifier. The business category can be set based on actual needs. For example, the game category can include action, adventure, simulation, role-playing, and casual games, etc.; lifecycle information represents the current life stage of the target business in its lifecycle. For example, the lifecycle can be the cycle of a user targeting the target business, from new registration to activity and then to churn, including the corresponding life stages, such as the new user stage, active stage, dormant stage, and churn stage, etc.; business objective information represents the currently configured business objectives of the target business, such as business objectives; for example, business objectives can be attracting new users, attracting returning users, increasing activity, or attracting paying users, etc. S203: Determine multiple promotional objects corresponding to the target business from the promotional object library.

[0052] In this embodiment, the promotion object library stores promotion objects configured in the social management and operation platform. These promotion objects are stored in association with projects and / or businesses. Multiple promotion objects corresponding to a target business can be promotion objects associated with the target business itself, or promotion objects associated with the project to which the target business belongs. Specifically, promotion objects can be, but are not limited to, advertising campaigns, new user acquisition campaigns, promotional activities, or game activity gameplay. Taking a game as an example, the promotion objects can be game activity gameplay. Specifically, game activity gameplay based on social promotion refers to activities aimed at spreading game applications on social platforms to achieve business goals such as new user acquisition, user retention, user activity, and revenue generation. The gameplay format is not fixed (it may include lotteries, referral programs, card collection, trial play, short videos, etc.), and the gameplay carrier is not fixed (it can include H5, mini-programs, audio, or video, etc.).

[0053] S205: Obtain historical feedback data, historical delivery data, and reference attribute information of the first reference business corresponding to multiple promotion targets.

[0054] Specifically, it obtains historical feedback data, historical delivery data, and reference attribute information of the first reference business that delivered the promotion to each of the multiple promotion targets.

[0055] In this embodiment, the first reference business is a business that has been promoted to at least one of the multiple promotional targets corresponding to the target business. Specifically, the feedback data is data obtained based on the interaction behavior of the target target towards the promotional target. Specifically, the feedback data may include, but is not limited to, information such as the reach conversion rate determined based on the interaction behavior data of the feedback provider towards the promotional target, and information such as the social fission reward value determined based on the fission data of the feedback provider towards the promotional target. The reach conversion rate is the percentage of the target feedback providers (those who received promotional exposure information from the promotional target) who can be converted into effective target feedback providers; effective target feedback providers can be defined according to actual needs. For example, if the business goal is to attract new users, then the reach conversion rate is the percentage of the target feedback providers who can be converted into registered target feedback providers. Social viral marketing promotes, disseminates, or sells business products through interpersonal social interactions. The social viral marketing reward value represents the promotional effect achieved by the promoted product during the social viral marketing process. For example, interaction behavior data can represent users' clicks, trial behaviors, or payment behaviors related to the promoted product; viral marketing data can represent users' sharing behaviors related to the promoted product, such as sharing the promoted product with other users to invite them to register, help, or share. Correspondingly, historical feedback data includes feedback data obtained after each round of promotion for the promoted product. Specifically, business placement data may include, but is not limited to, category placement data and market placement data. Category placement data refers to the placement data of businesses in the same category as the target business on the same promotional target. This may include the number of times a second reference business belonging to the same business category as the target business has placed placements on the same promotional target, as well as the total number of times the second reference business has placed placements on various promotional targets. Market placement data includes the object data of reference promotional targets placed on the social operation management platform that meet the preset activity conditions. Specifically, this may include the object content data of reference promotional targets placed on various social platforms in the social operation management platform within the most recent preset time period that meet the preset activity conditions. Taking the promotional target as a game activity gameplay as an example, the object content data represents the content of the gameplay, such as lottery gameplay content, help gameplay content, or trial gameplay. Among them, meeting the preset activity conditions means that the activity level of the feedback users of the promotional target is greater than or equal to the activity threshold. Correspondingly, historical placement data includes the business placement data obtained after each placement of the promotional target. Specifically, the reference attribute information of the first reference business is similar to the aforementioned business attribute information and will not be repeated here.

[0056] S207: Determine the advertising value of multiple target audiences based on business attribute information, historical feedback data, historical campaign data, and reference attribute information.

[0057] In this embodiment of the application, the value of the campaign represents the degree of compatibility between the target and the target business. It can be understood that for the target business, the higher the degree of compatibility, the better the expected campaign effect after the campaign is launched. The campaign effect may include, but is not limited to, the effect of reaching new users / returning users, the dissemination effect (such as the number of page views / the number of page view feedback users), the effect of reaching conversion and the effect of sharing.

[0058] In some embodiments, the target audience's advertising value is determined based on a preset value algorithm. Accordingly, preset S207 includes the following steps.

[0059] S301: Match business attribute information and reference attribute information to obtain attribute matching values ​​corresponding to multiple promotion objects.

[0060] In practical applications, business attribute information includes multi-dimensional attribute information of the business, and reference attribute information includes information corresponding to the various dimensions of the business attribute information of the first reference business. Specifically, the reference attribute information of the first reference business corresponding to each promotion object is matched with the business attribute information to obtain the attribute matching value of each promotion object. The first reference business corresponding to each promotion object is the business that has been promoted to that promotion object; when multiple first reference businesses have been promoted to the same promotion object, the sub-attribute matching value between the reference attribute information and the business attribute information of each first reference business is determined, and then the weighted average of each sub-attribute matching value is calculated to obtain the attribute matching value corresponding to the promotion object; the weights involved in the weighted average can be set according to actual needs, and this application does not impose any restrictions.

[0061] In a specific embodiment, the business attribute information includes the business objective information and lifecycle information of the target business. S301 may include the following steps.

[0062] S3011: Match the business target information with the reference target information in the reference attribute information to obtain the first matching value corresponding to each of the multiple promotion objects.

[0063] Specifically, business objective information represents the currently configured business objectives of the target business. For example, business objectives may include, but are not limited to, at least one of the following: attracting new users, attracting returning users, increasing user activity, and driving revenue. Reference attribute information may include reference objective information and reference lifecycle information of the first reference business, as well as reference category information, etc. Reference objective information represents the business objective configured when the first reference business targets one of multiple promotional targets. For instance, if the business objective of the first reference business targeting one of multiple promotional targets is attracting returning users and driving revenue, then its business objective information represents the information related to attracting returning users and driving revenue.

[0064] Specifically, for each promotional object, the matching degree is calculated for the reference target information and business target information of the first reference business, resulting in a first matching value for each promotional object. If multiple first reference businesses have promoted the same object, the matching degree is calculated for the reference target information and business attribute information of each first reference business separately. Then, the weighted average of the obtained sub-matching degrees is taken to obtain the first matching value for that promotional object. It can be understood that a higher first matching value indicates a higher degree of matching between the promotional object and the currently configured business target of the target business.

[0065] S3012: Match the lifecycle information with the reference lifecycle information in the reference attribute information to obtain the second matching value corresponding to each of the multiple promotion objects.

[0066] Specifically, lifecycle information represents the current life stage of a target business within its lifecycle. For example, the lifecycle can be the effective operational cycle of a business, such as the cycle of a user's journey towards the target business, from initial registration to activity and then to churn, including corresponding life stages such as the initial registration stage, active stage, dormant stage, and churn stage. The lifecycle information can be used to represent the life stage of one of multiple promotional targets for a first reference business.

[0067] Specifically, for each promotional target, the matching degree is calculated between the reference lifecycle information of the first reference business and the lifecycle information of the target business to obtain a second matching value for each promotional target. If multiple first reference businesses have promoted the same target, the matching degree is calculated separately for the reference lifecycle information of each first reference business and the lifecycle information of the target business. Then, the weighted average of the obtained sub-matching degrees is taken to obtain the second matching value for that promotional target. Understandably, a higher second matching value indicates a higher degree of matching between the promotional target and the current lifecycle stage of the target business.

[0068] S3013: Perform a weighted summation of the corresponding first and second matching values ​​to obtain the attribute matching values ​​corresponding to each of the multiple promotion objects.

[0069] Specifically, corresponding to the first and second matching values ​​of the same promotional object, a weighted summation is performed on the first and second matching values ​​of each of the multiple promotional objects to obtain their respective attribute matching values. The weight information involved in the weighted summation process in step S3013 can be preset by the platform or submitted by the target account through the weight setting interface displayed on the terminal.

[0070] Calculating attribute matching values ​​can improve the relevance between the value of ad placement and business attributes, that is, improve the fit between the final target audience and the target business, thereby optimizing the ad placement effect.

[0071] S303: Perform multi-dimensional statistical processing on historical feedback data to obtain multi-dimensional feedback values ​​corresponding to multiple promotional targets.

[0072] In practical applications, historical feedback data includes multi-dimensional data such as the historical reach conversion rate and social sharing reward value for each promotional target. Specifically, it includes the historical reach conversion rate and social sharing reward value generated after each promotional campaign for each target. The social sharing reward value represents the promotional effect achieved by the promotional target during a single social sharing campaign. This social sharing reward value can be set and calculated based on the actual needs of business promotion. For example, the social sharing reward value can include: the cumulative value of links shared by the active feedbacker to the passive feedbacker in each past campaign, or the cumulative value of passive feedbackers clicking the link and then clicking a preset sharing control (such as the "help" button).

[0073] Specifically, the historical feedback data corresponding to each promotional target is statistically processed to obtain the feedback values ​​for each promotional target in various dimensions. In a specific embodiment, the historical feedback data includes data on two dimensions: the historical reach conversion rate and the social fission reward value corresponding to each of the multiple promotional targets. S303 may include the following steps.

[0074] S3031: Perform a weighted average of the historical reach conversion rates generated from each of the various campaigns for each of the multiple promotional targets to obtain the average reach conversion rate for each of the multiple promotional targets.

[0075] Specifically, a weighted average is calculated for the historical reach conversion rates generated from each campaign for each advertised target, resulting in the average reach conversion rate for each target. In some cases, the weights involved in this weighted averaging process can be related to the reference attributes of the primary reference business for each campaign for that advertised target. For example, the closer the business category, the higher the weight; the closer the lifecycle of the primary reference business at the time of the campaign, the higher the weight; or it can be related to the campaign time, such as the shorter the interval between the campaign time and the current time, the higher the weight; or it can be set according to actual needs. Understandably, a higher average reach conversion rate indicates better reach conversion performance for that advertised target.

[0076] S3032: Accumulate the social fission reward values ​​obtained by each of the multiple promotional targets in each of their previous campaigns to obtain the total fission reward value for each of the multiple promotional targets.

[0077] Specifically, the cumulative social sharing reward value obtained by each advertiser across all campaigns is obtained, and the total social sharing reward value for that advertiser is determined based on this cumulative value. As can be understood, the total social sharing reward value represents the overall promotional effect achieved by the advertiser during the social sharing process, signifying its contribution to promoting interaction among respondents and business promotion. The higher the total social sharing reward value, the better the effect of promoting interaction among respondents and business promotion for that advertiser.

[0078] S3033: The corresponding average reach conversion rate and total viral reward value are weighted and summed to obtain the feedback value for each of the multiple promotion targets.

[0079] Specifically, corresponding to the average reach conversion rate and total viral reward value of the same promotional target, a weighted summation is performed on the average reach conversion rate and total viral reward value of each of the multiple promotional targets to obtain the attribute matching value corresponding to each of the multiple promotional targets. Similar to S3013, the weight information involved in the weighted summation process in step S3033 can be preset by the platform or submitted by the target account through the weight setting interface displayed on the terminal.

[0080] Calculating feedback values ​​can improve the correlation between the value of the campaign and the behavior of the person providing feedback, thereby optimizing the effectiveness of the campaign.

[0081] S305: Calculate the delivery rate and the similarity of the target audience in the same period based on the historical delivery data to obtain the historical delivery rate and delivery similarity value for multiple target audiences.

[0082] In practical applications, historical campaign data includes category-specific campaign data and market-specific campaign data for the target product. Category-specific campaign data includes the number of times a second reference business in the same category as the target business campaigns for the same target product. The historical campaign rate is determined by obtaining the reference number of campaigns for each target product campaigned by the second reference business and the total number of campaigns for all target products campaigned by all second reference businesses within the social operations management platform. The ratio of the reference number of campaigns to the total number of campaigns is used to determine the historical campaign rate. In some cases, the historical campaign rate is the ratio of the reference number of campaigns to the total number of campaigns; in other cases, it is the product of this ratio and a preset campaign weight, which can be set based on actual needs. Understandably, a higher historical campaign rate indicates a higher acceptance rate for the target product within the same category of business.

[0083] In practical applications, marketing data includes content data of reference promotional targets that meet preset activity levels and have been placed on various social media platforms within the social operations management platform over the most recent preset period. For example, the preset period can be 30 days or 60 days, etc. This system monitors the targeting and performance data of reference promotional targets across various social media platforms within the social operations management platform. Performance data represents the effectiveness of the promotional targets, including but not limited to data on new user acquisition / return traffic, dissemination effectiveness (e.g., page views / number of users providing feedback, number of users participating in feedback, number of users checking in), conversion rates, and sharing effectiveness (e.g., number of clicks and successful shares). Based on the performance data, the activity level of reference promotional targets can be determined, identifying those that meet preset activity levels within a predetermined timeframe. Reference content data for each identified reference promotional target is then obtained. For example, if the promotional target is a game activity, the reference content data represents the content of the reference activity, such as a lottery, a referral bonus, or a trial game. The similarity data of each promotional target corresponding to the target business is compared with the reference content data to obtain the object similarity between each promotional target and each reference promotional target. The similarity value for each promotional target is then determined based on the object similarity. Specifically, the similarity value can be a weighted average of the object similarities. Understandably, a higher similarity score indicates a higher level of market and user acceptance and familiarity with the target audience.

[0084] Calculating historical delivery rates and delivery similarity values ​​can improve the relevance of delivery value to the target business category and market acceptance, thereby enhancing the effectiveness of targeted delivery.

[0085] S307: Determine the advertising value of multiple target audiences based on attribute matching values, feedback values, historical delivery rates, and delivery similarity values.

[0086] In practical applications, the advertising value of each target audience can be determined by summing or averaging its attribute matching value, feedback value, historical delivery rate, and ad similarity value. Alternatively, the weighted sum or weighted average of these factors can be used as the advertising value of the target audience.

[0087] Understandably, attribute matching values, feedback values, historical delivery rates, and delivery similarity values ​​can be mapped to their respective scores, with the score range being, for example, 0-100 points. Then, the scores can be summed, averaged, weighted summed, or weighted averaged to obtain the delivery value.

[0088] Based on the implementation methods of steps S301 to S307 above, in a specific embodiment, the specific implementation method for determining the placement value of multiple promotional objects based on business attribute information, historical feedback data, historical placement data, and reference attribute information can be as follows: The first matching value, second matching value, average reach conversion rate, total viral reward value, historical placement rate, and placement similarity value of each promotional object are weighted and summed based on preset weight information to obtain the placement value of each promotional object. The corresponding calculation formula is: Placement Value = Average Reach Conversion Rate * Weight A + Historical Placement Rate * Weight B + Placement Similarity * Weight C + Second Matching Value * Weight D + First Matching Value * Weight E + Total Viral Reward Value * Weight F.

[0089] Weights A, B...F are primarily used to adjust the degree of influence of each parameter on the value of ad placement. They can address market demands at different times and fine-tune the sorting logic of the target audience. For example, to strengthen the guidance of "historical placement rate," the weight value corresponding to the historical placement rate will be increased, while the weight values ​​of other items will remain unchanged or be decreased.

[0090] In one example, taking the aforementioned game as an example, the first matching value, the second matching value, the average reach conversion rate, the total viral reward value, the historical delivery rate, and the delivery similarity value are mapped to the corresponding scores (0-100). Then, the gameplay delivery value = historical conversion rate score * weight A + category usage rate score * weight B + market usage popularity score * weight C + lifecycle matching score * weight D + business goal matching score * weight E + feedback social interaction score * weight F.

[0091] The historical conversion rate score corresponds to the average reach conversion rate mentioned above. It is a score mapping value that is the weighted average of the reach conversion rates of each past launch of this gameplay. A higher score indicates a higher conversion rate. The category usage rate score corresponds to the historical deployment rate. It is a score mapping value that is the percentage of times each game project in the current game category has used this gameplay in the total number of times games in that category have used all types of gameplay. A higher score indicates a higher acceptance of this gameplay within the game category. The market usage popularity score corresponds to the deployment similarity score. It is a score of the similarity between popular activities on various social media platforms monitored within the recent preset time and this gameplay. A higher score indicates a higher market acceptance and familiarity with this gameplay. The lifecycle matching score corresponds to the second matching value. It is a matching score between the target game's current lifecycle stage and the lifecycle stages of various games that have historically used this gameplay. A higher score indicates a higher degree of matching between this gameplay and the target game's current lifecycle stage. The Business Goal Matching Score corresponds to the First Match Value, which is the matching score between the business goals selected for the target game and the business goals selected for each game that has historically used this gameplay. A higher score indicates a higher degree of match between the gameplay and the project's current selected business goals. The Feedback Provider Social Interaction Score corresponds to the Total Viral Reward Value, which is the cumulative score of the number of times the active feedback provider shared a link with the passive feedback provider during each previous launch of this gameplay, and the number of times the passive feedback provider clicked the "Help" button after opening it. It is used to evaluate whether this gameplay can promote sharing and interaction among feedback providers; a higher score indicates that the gameplay is more effective in promoting feedback provider interaction.

[0092] In one example, please refer to Figure 11 , Figure 11 The weight information setting window is displayed. The numerical range of weights A, B...F is 1.0 to 2.0. The target account can submit the weight information set based on this window.

[0093] In other embodiments, the delivery value of each promotion target can be determined based on a preset object recommendation model. Accordingly, S207 may include the following steps.

[0094] S401: Perform feature mapping processing on the business attribute information, as well as the historical feedback data, historical delivery data, and reference attribute information corresponding to each promotion object, to generate the corresponding business feature information and the object feature information of each promotion object.

[0095] Specifically, feature mapping is performed on each object data or information included in the historical feedback data, historical delivery data, and reference attribute information of each promotion target, such as reference business objectives and market delivery data, to obtain the object characteristics of each object data or information. Based on all the object characteristics of each promotion target, its object characteristic information is generated. For each business data or business information of the target business, such as the aforementioned business objectives, business categories, and business lifecycle, feature mapping is performed to obtain the object characteristics of each business data or information. Based on all the business characteristics of each promotion target, its business characteristic information is generated.

[0096] Specifically, the object recommendation model may include a feature mapping layer and a feature encoder. Step S401 can be executed based on the feature mapping layer of the object recommendation model. In one embodiment, the feature mapping layer performs feature mapping processing on the words to be identified based on one-hot encoding. Each business data, business information, object data, or object information is mapped to a binary feature using one-hot encoding. One-hot encoding is a single-bit encoding, which uses an N-bit state register to encode N states. Each state has its own independent register bit, and at any given time, only one bit is valid. For each feature, if it has L possible values, then after one-hot encoding, it becomes L binary features. Furthermore, these features are mutually exclusive, with only one activated at a time.

[0097] S403: Perform feature encoding processing on the business feature information and the object feature information respectively to obtain the corresponding business feature vector and object feature vector.

[0098] Specifically, each business feature in the business feature information is feature-encoded to achieve its vectorization, resulting in a business feature sub-vector. A business feature vector is then generated based on these sub-vectors, and the business feature vector can be a sequence of these sub-vectors. Similarly, each object feature in the object feature information is feature-encoded to achieve its vectorization, resulting in a object feature sub-vector. An object feature vector is then generated based on these sub-vectors, and the object feature vector can be a sequence of these sub-vectors.

[0099] Specifically, the feature encoder may include an input layer, a feature cross layer, and a fully connected layer, and step S403 may be performed based on the input layer of the feature encoder.

[0100] S405: Perform feature cross processing on the business feature vector and the object feature vector to obtain the first feature vector and the second feature vector corresponding to each promotion object.

[0101] Specifically, the first feature vector is used to represent the overall features of the corresponding promotional object, and the second feature vector is used to represent the pairwise correlations between the features of the business feature information and the features of the object feature information of the corresponding promotional object. Step S405 can be executed based on the feature cross-layer of the feature encoder.

[0102] In one embodiment, the feature cross-processing layer performs cross-operations on the business feature vector and object feature vector corresponding to each input promotion object, mining the correlations between business feature sub-vectors, object feature sub-vectors, and business feature sub-vectors and object feature sub-vectors. Then, the second feature vectors obtained from the cross-operations are concatenated to obtain the first feature vector for each promotion object. Correspondingly, the second feature vector is the cross-feature vector obtained from the cross-operations, and the first feature vector is the overall feature vector obtained by concatenating the cross-feature vectors. Specifically, feature cross-processing is performed on each business feature sub-vector and each object feature sub-vector to generate cross-feature values; based on the cross-feature values, the second feature vector is generated. The cross-feature values ​​characterize the pairwise correlations between each business feature sub-vector and each object feature sub-vector.

[0103] S407: Determine the placement value of each promotion target based on the first feature vector and the second feature vector.

[0104] Specifically, deep feature extraction can be performed on the first and second feature vectors to determine the advertising value of each target audience.

[0105] Specifically, step S407 can be executed based on the fully connected layer of the feature encoder to extract features from the first feature vector and the second feature vector. The value can be the classification probability output by the model, or a score value generated based on the mapping of the classification probability.

[0106] Optionally, the feature encoder can be built based on PNN.

[0107] S209: Sort multiple promotional targets according to their value to obtain the target ranking results.

[0108] Based on the above scheme, this application can comprehensively determine the advertising value of each target business by integrating multi-dimensional information. The ranking results are strongly correlated with the attributes of the target business, feedback expectations of the feedbackers, and historical advertising performance. This makes it easier for relevant personnel to determine the target advertising targets based on the results, improve the matching and accuracy of the advertising targets, and thus optimize the advertising effect.

[0109] Based on some or all of the above implementation methods, in this embodiment of the application, the method further includes S211: generating and sending a list of promotion objects corresponding to multiple promotion objects to the terminal based on the object sorting result, so that the terminal can display the list of promotion objects.

[0110] In this embodiment, multiple promotional targets corresponding to the target business are sorted according to their value, and a list of promotional targets is generated. In response to a target account's operation to view promotional targets for the target business, the terminal can display this list of promotional targets on the corresponding interface.

[0111] Taking the business as a game and the target audience as the activity format as an example, please refer to... Figure 5 and 6 , Figure 5 and 6 The diagrams illustrate the workbench window and gameplay window of a social operations management platform provided in one embodiment. After the target account logs in, the platform can identify the target account's projects and the related businesses. Upon receiving the business selection information submitted by the target account to the platform interface of the social operations management platform, the corresponding business window is displayed, such as... Figure 5 The workbench window displays information about currently launched or previously launched activities and gameplay for the target game, including launch time, new user entry points, returning user entry points, feedback data statistics, behavior distribution, and funnel data. When a target account selects a gameplay option in the social operations management interface, the terminal responds by displaying a list of corresponding activities and gameplay in the gameplay window of the management interface. For example... Figure 6 As shown, the gameplay window displays a selection of gameplay options from the activity gameplay list based on object sorting results. Optionally, based on object sorting results, promotional objects with higher targeting value can be marked as preferred promotional objects, for example... Figure 6 Gameplay methods 1-3 are the preferred methods.

[0112] S213: Receive object filtering information submitted for the list of promotion objects.

[0113] In practical applications, target accounts can filter the list of promotional targets displayed on the terminal, and the terminal sends the corresponding target filtering information to the server. In some embodiments, the interface or window displaying the list of promotional targets may have filtering options, and target accounts can select these options to perform filtering operations and submit the corresponding target filtering information.

[0114] Specifically, object filtering information may include, but is not limited to, at least one of the following: business target filtering information, business category filtering information, and lifecycle filtering information. For an example, please refer to... Figure 6 The game's business objective filtering options can include "attracting new users", "attracting returning users", "attracting active users", and "attracting paying users".

[0115] S215: Identify candidate promotion targets that match the target selection information from multiple promotion targets.

[0116] In practical applications, each promoted object is tagged with its own information. This tag information can include, but is not limited to, at least one of business objective tags, lifecycle tags, and business category tags, representing its respective business objective, lifecycle, or business category. Based on the tag information of each promoted object, the promoted objects that match the current object filtering information can be identified from among multiple promoted objects, thus obtaining candidate promoted objects. Taking a game activity as an example, the business category tags for the gameplay can include "new user acquisition," "returning user," "active user acquisition," and "paying user acquisition." After receiving a filtering operation targeting the "new user acquisition" option for the business objective, promoted objects with the tag information "new user acquisition" can be filtered out from among multiple promoted objects to serve as candidate promoted objects.

[0117] S217: Update the list of promotion targets based on the candidate promotion targets.

[0118] In practical applications, ad targets that do not match the target selection information are removed from the ad target list, resulting in an ad target list containing only the candidate ad targets, thus updating the ad target list. Please refer to [link / reference]. Figure 7 After receiving the target account's "attract new users" operation for this gameplay window, the target filtering information is determined, and a target promotion list matching "attract new users" is determined. Unmatched gameplays 1, 2, 5, and 6 are removed from the original target promotion list.

[0119] Furthermore, each service also has a corresponding service information window; please refer to [the relevant documentation]. Figure 8 In response to the target account's trigger action regarding gameplay information, the terminal displays a corresponding gameplay information window, which can show past performance data, scheduling information, and historical campaign data for that gameplay. Past performance data includes campaign performance data for the target audience within a preset time period, and may include, but is not limited to, data representing new user / return visit effectiveness, dissemination effectiveness (such as page views / number of users providing feedback, number of users participating in feedback, number of users checking in), conversion effectiveness, and target audience sharing effectiveness (such as number of clicks to share and number of successful shares). Figure 7 Conversion rate is data that characterizes the effectiveness of reaching conversions.

[0120] Based on some or all of the above embodiments, please refer to the embodiments of this application. Figure 12 The methods also include:

[0121] S219: Based on the value of the campaign or the object determination information submitted for the list of promotional objects, determine the target promotional objects that match the target business from the list of promotional objects.

[0122] In some embodiments, the highest-value or the top preset number of promotional objects in the promotional object list can be used as target promotional objects. In other embodiments, the terminal can receive an object determination operation submitted by the target account for the promotional object list and send the corresponding object determination information to the server. The server identifies the promotional object corresponding to the object determination information in the promotional object list, thereby obtaining the target promotional object. This target promotional object is the promotional object to be launched for the target business.

[0123] S221: Obtain the first advertising period information of the target audience currently being advertised by the second reference service, and the second advertising period information of the target audience currently being advertised.

[0124] In practical applications, the second reference business is a business belonging to the same business category as the target business. The first ad placement time information includes the ad placement time periods for each reference promotion target that has been configured and is currently online or about to be launched by each second reference business within the social operation platform; the second ad placement time information includes the ad placement time periods configured by other businesses within the social operation platform for the target promotion target.

[0125] S223: Based on the information of the first and second delivery periods, perform staggered delivery scheduling analysis to obtain recommended delivery periods for the target audience.

[0126] In practical applications, based on a staggered scheduling mechanism, a staggered scheduling analysis is performed on the first and second campaign periods to obtain recommended campaign periods. This recommended campaign period information includes scheduling conflict alerts and recommended campaign periods. Preferably, the recommended campaign periods are those that avoid the corresponding campaign periods in the first and second campaign periods. This achieves staggered launches with similar business promotions and the same target audience, reducing internal resource conflicts and waste, minimizing user poaching within the same product category, avoiding negative impacts on user engagement, and ensuring the promotional effect remains unaffected through time-based and group-based priority promotion strategies, thereby guaranteeing campaign effectiveness and conversion rates.

[0127] Please refer to Figure 9 Taking the aforementioned game as an example, the system generates and displays the gameplay schedule of the second reference business that has been launched and is about to be launched within the next 90 days (or other durations) in one stop, and displays the calendar. After receiving the schedule period selected by the target account for the calendar, it determines whether there is a schedule conflict based on the first and second placement time information. If so, it generates schedule conflict information and recommended placement time and sends it to the terminal for display.

[0128] Based on some or all of the above embodiments, the method in this application embodiment further includes:

[0129] S225: Obtain feedback data within the first preset time period after the target audience is reached.

[0130] In practical applications, target feedbackers provide feedback data after the target promotion object goes live. Target feedbackers are the ones who receive promotion exposure information after the target promotion object goes live.

[0131] S227: Obtain feedback information from the target feedback provider who provided the feedback data.

[0132] In practical applications, feedback information can include basic profile information of the target feedback user and business profile information specific to the target service. When the feedback user is a user, the basic profile information may include, but is not limited to, the feedback user's account age, internet device identifier, network identifier, and network device address. The business profile information may include, but is not limited to, the feedback user's registered age for that service, total online time, daily online time, and service usage information. Taking a game as an example, service usage information may include, but is not limited to, the selected game character, game scene, game account level, equipment level, and equipment consumption history. The method of obtaining this feedback information can be the same as existing technologies and is not limited here.

[0133] S229: Generate feedback tags for target feedbackers based on feedback data and feedbacker information. Feedbacker tags are used to characterize the matching degree between feedbackers and target audiences.

[0134] In practical applications, based on each target feedbacker's existing profile and their feedback data regarding the promoted object (such as interaction behavior data), a feedbacker engagement value is generated. Based on this engagement value, the feedbacker's tag is generated and updated. Participating target feedbackers will also be tagged to further record their future behavior within a preset timeframe, such as making payments or further encouraging other feedbackers to use the target service or promoted object. The feedbacker engagement value represents the depth of the feedbacker's participation in the promoted object's activities within the target service or on social media platforms. Different levels of engagement result in different engagement values ​​(e.g., different engagement values ​​for simply browsing versus participating in activities, and different engagement values ​​for participating in activities versus sharing). The feedbacker engagement value is used to identify the feedbacker's level of engagement with the promoted object.

[0135] In practical applications, feedback recipient tags can be generated based on a feedback recipient identification model. This model can be an existing identification model or something similar to the aforementioned object recommendation model.

[0136] Based on some or all of the above embodiments, the method in this application embodiment further includes:

[0137] S231: Periodically perform statistical processing on the feedback data after the target audience is targeted for promotion to obtain multi-dimensional promotion statistics.

[0138] S233: Generate a report on the delivery performance of the target audience based on multi-dimensional promotion statistics.

[0139] In practical applications, multi-dimensional promotional statistics can include, but are not limited to, new visitor / return visit information, dissemination information (such as page views / number of page viewers providing feedback), conversion information, and referral information (such as sharing information). For an example, please refer to... Figure 10 The social operations management platform's interface includes a report window that displays reports on the performance of each launched campaign and related time limits.

[0140] In practical applications, data from the target audience is recorded and updated in real time after going live on the platform. Upon going offline, a corresponding campaign performance report is immediately generated within the platform for easy review. These performance reports, along with the behavioral data of those providing feedback, facilitate further evaluation of the target audience's ability to drive revenue growth and the quality of feedback. Figure 10 The example report includes user acquisition and return data for gameplay activities, click hotspot data, and redirect funnel data.

[0141] The following describes a method for processing promotional targets based on the above application environment and / or social operation management platform, which is applied to the terminal. Figure 13 This is a flowchart illustrating a method for processing a target object according to an embodiment of this application. This specification provides method operation steps as shown in the embodiments or flowcharts, but based on conventional or non-inventive labor, more or fewer operation steps may be included. The order of steps listed in the embodiments is merely one possible execution order among many, and does not represent the only execution order. In actual system or server product execution, the method can be executed sequentially according to the embodiments or drawings, or in parallel (e.g., in a parallel processor or multi-threaded processing environment). Specifically, as shown... Figure 13 As shown, the method may include the following steps.

[0142] S501: In response to a target business request, determine multiple promotional objects corresponding to the target business from the promotional object library.

[0143] In this embodiment of the application, the terminal can be used to provide an information display interface and generate corresponding operation instructions or requests in response to the interactive information submitted by the account for the information display interface. The target business request can be a request submitted by the target account for the information display interface to obtain the display information of the promotion object corresponding to the target business.

[0144] Specifically, the social operations management platform can have multiple target accounts, each with corresponding management permissions, capable of viewing and configuring associated project information. Each associated project includes at least one business. The aforementioned target business request can be a request generated based on the interaction information submitted by the target account to the social management client on the terminal. For example, the interaction information may include the account login information and business-specific operation information submitted by the target account on the terminal. After receiving the account login information, the terminal displays the businesses under the target account's management permissions based on the account login information and identifies the business corresponding to the business-specific operation information as the target business; then, it obtains and displays multiple promotional targets corresponding to the target business. Specifically, the method for obtaining multiple promotional targets is similar to the aforementioned step S203, and will not be repeated here.

[0145] S503: Obtain the campaign value of multiple target audiences. The campaign value is determined based on the business attribute information of the target business, as well as the historical feedback data, historical campaign data, and reference attribute information of the first reference business for each target audience. The first reference business is the business that has campaigned with at least one of the multiple target audiences.

[0146] In this embodiment of the application, the target value of the promotion object can be determined based on the aforementioned steps S201, S205 and S207, which will not be repeated here.

[0147] S505: Sort multiple promotional targets according to their value to obtain the target ranking results.

[0148] In this embodiment, S505 is similar to S209 described above, and will not be repeated here.

[0149] In some embodiments, the method further includes the following steps.

[0150] S507: Displays a list of promotional objects corresponding to multiple promotional objects generated based on the object sorting results.

[0151] In practical applications, the terminal's information display interface includes a promotional object display interface, which can display multiple promotional objects associated with the target business based on object sorting results, and can display promotional objects in descending order of their advertising value. In one embodiment, the promotional object display interface is as follows: Figure 6 and Figure 7 As shown.

[0152] S509: Receive object filtering requests submitted for the list of promotional objects.

[0153] S511: Parse the object filtering request to obtain the corresponding object filtering information.

[0154] S513: Identify candidate promotion targets that match the target selection information from multiple promotion targets.

[0155] S515: Update the list of promotion targets based on the candidate promotion targets.

[0156] In practical applications, target accounts can perform filtering operations on the promotional target display interface displayed on the terminal by triggering a filter control. This submits a corresponding target filtering request, which is then parsed to obtain the target filtering information. In one embodiment, please refer to... Figure 6 The filtering controls can be "Attract New Users," "Attract Returning Users," "Attract Active Users," and "Attract Paying Users." When a target account triggers the "Attract New Users" control, it submits an "Attract New Users" filtering request. Based on the corresponding "Attract New Users" filtering information, the terminal determines the available gameplay options and then obtains and displays an updated list of gameplay options, such as... Figure 7 As shown.

[0157] In some embodiments, the method further includes the following steps.

[0158] S517: Based on the value of the campaign or in response to an object determination request submitted for the list of promotional objects, determine the target promotional objects that match the target business from the list of promotional objects.

[0159] S519: Obtain the first advertising period information for the target audience currently being advertised by the second reference business, and the second advertising period information for the target audience currently being advertised by the second reference business. The second reference business is a business belonging to the same business category as the target business.

[0160] S521: Based on the information of the first and second delivery periods, perform staggered delivery scheduling analysis to obtain recommended delivery periods for the target audience.

[0161] In practical applications, steps S517-S521 are similar to those described above in steps S219-S223, and will not be repeated here.

[0162] In some embodiments, after S519, the method further includes the following steps.

[0163] S523: In response to an object scheduling request for the target audience, display information for the first and second delivery periods.

[0164] S525: Receive the desired delivery time period information.

[0165] S527: If there is an overlap between the delivery time period corresponding to the expected delivery time period information and the delivery time period corresponding to at least one of the first delivery time period information and the second delivery time period information, a scheduling conflict prompt message is generated.

[0166] In practical applications, the scheduling display interface can show information on the first and second delivery time slots within a certain duration; it can also receive delivery time slot selection operations submitted by the target account using the date control on the scheduling display interface to obtain the desired delivery time slot information corresponding to the selection operation. In the case of overlapping time slots, a scheduling conflict warning message is generated and displayed to alert the target account that the desired delivery time slot conflicts with the current delivery time slot. Furthermore, S521 can be executed to generate and display recommended delivery time slot information. In one embodiment, the scheduling display interface is as follows: Figure 9 As shown. In some embodiments, the method further includes the following steps.

[0167] S529: Periodically perform statistical processing on the feedback data after the target audience is targeted for promotion to obtain multi-dimensional promotion statistics.

[0168] S531: Generate a report on the delivery performance of the target audience based on multi-dimensional promotion statistics.

[0169] S533: In response to a report query request, display the campaign performance report.

[0170] In practical applications, steps S529-S531 are similar to those described in steps S231-S233, and will not be repeated here. The target account can submit a report query request to the information display interface to display the corresponding campaign performance report on the performance report interface. In one embodiment, the performance report interface is as follows: Figure 10 As shown.

[0171] In one embodiment, please refer to Figure 14 The operation process for the target account's information display interface on the social management client can be as follows: the target account logs into the project group, selects the target business on the information display interface, then selects the target promotion object for the target business, then selects the target promotion object's campaign schedule, so that the target promotion object is launched and put online within the corresponding time period, and then views the associated data after the target promotion object goes online, and, if a campaign performance report for the target promotion object has been generated, views the campaign performance report.

[0172] Further, please refer to Figure 15 Taking the business as a game and the promotion target as the gameplay of the game, this paper introduces the method of handling the promotion target based on the information display interface of the social management client.

[0173] S1 starts the system.

[0174] S2 determines whether the target account is already logged in. If yes, proceed to S3; otherwise, proceed to S4.

[0175] S3 identifies the game project group to which the target account belongs.

[0176] S4 displays the login control on the account login screen of the information display interface.

[0177] S5 identifies the target game.

[0178] If the target account corresponds to only one game, that game is identified as the target game. If the target account corresponds to multiple games, the target game is identified from among the multiple games.

[0179] After identifying the target game, the display content for the information display interface, the workbench interface, the gameplay interface, and the report interface can be generated. The corresponding interface is displayed in response to the target account's triggering or selection actions on these three interfaces. Accordingly, the method also includes the following steps.

[0180] S6 responds to workbench selection operations by displaying the workbench interface.

[0181] For example, the workbench interface can be as follows: Figure 5 The interface shown.

[0182] S7 determines whether the target game currently has online gameplay activities; if yes, proceed to S8; otherwise, proceed to S9.

[0183] S8 displays data on currently online gameplay activities on the workbench interface.

[0184] Data for currently online gameplay activities can include estimated online duration information, statistical data, daily PV / UV, daily new and returning users, cumulative conversion rate, behavior distribution, funnel data, and gift consumption progress, etc. Please refer to... Figure 5 , Figure 5 The workbench interface displays data for an online gameplay activity.

[0185] S9 displays guidance information to navigate to the gameplay interface.

[0186] The S10 responds to gameplay selection actions by displaying the gameplay interface.

[0187] For example, the gameplay interface can be as follows: Figure 6 The interface shown.

[0188] S11 displays a list of gameplay options generated from the available gameplay activities of the target game on the gameplay interface.

[0189] S12 responds to the target account's submission of a gameplay selection action on the gameplay interface and displays the gameplay details interface to show the associated data of the gameplay.

[0190] The associated data for a gameplay feature can include a main interface demo, historical daily average overall campaign performance data, historical conversion rate data, and currently scheduled campaign times for that feature. For example, the gameplay details interface could look like this: Figure 8 The interface shown.

[0191] S13 responds to the scheduling request submitted by the target account for the gameplay details interface and displays the scheduling display interface.

[0192] The scheduling display interface can show the release time slots for other games featuring the current gameplay mode, as well as the release time slots for other gameplay modes recently scheduled by other games in the same category. For example, the scheduling display interface can be as follows: Figure 9 The interface shown.

[0193] S14 If a target account submits a time slot selection operation, determine whether the desired time slot corresponding to the time slot selection operation is occupied; if yes, proceed to S15; otherwise, proceed to S16.

[0194] S15 displays a scheduling conflict warning message.

[0195] S16 scheduling has been successfully confirmed.

[0196] S17 responds to the report selection operation by displaying the report interface.

[0197] For example, the reporting interface can be as follows: Figure 10 The interface shown is used to display the performance report after the gameplay is launched.

[0198] This application embodiment also provides a processing device 600 for promotional objects, such as... Figure 16 As shown, Figure 16 This illustration shows a schematic diagram of a processing device for a target object provided in an embodiment of this application. The device may include:

[0199] First information acquisition module 610: Used to acquire business attribute information of the target business.

[0200] Module 620 for determining target customers: This module is used to determine multiple target customers corresponding to the target business from the target customer database.

[0201] The second information acquisition module 630 is used to acquire historical feedback data, historical delivery data, and reference attribute information of the first reference business for multiple promotional targets. The first reference business is a business that has been deployed to at least one of the multiple promotional targets.

[0202] The 640 module for determining the value of a campaign is used to determine the value of a campaign for multiple targets based on business attribute information, historical feedback data, historical campaign data, and reference attribute information.

[0203] Object sorting module 650: Used to sort multiple promotional objects according to their placement value and obtain the object sorting results.

[0204] In some embodiments, the apparatus further includes:

[0205] List generation module: Used to generate and send a list of promotional objects corresponding to multiple promotional objects to the terminal based on the object sorting results, so that the terminal can display the list of promotional objects.

[0206] Filtering information receiving module: Used to receive object filtering information submitted for the list of promotion objects.

[0207] Candidate Promotion Target Determination Module: Used to identify candidate promotion targets that match the target filtering information from multiple promotion targets.

[0208] List Update Module: Used to update the list of promotion targets based on the candidates for promotion.

[0209] In some embodiments, the apparatus further includes:

[0210] Target audience identification module: Based on the value of the campaign or the object identification information submitted for the target audience list, it identifies the target audience that matches the target business from the target audience list.

[0211] The campaign time slot information acquisition module is used to acquire the first campaign time slot information for the target audience currently being targeted by the second reference business, as well as the second campaign time slot information for the target audience. The second reference business is a business belonging to the same business category as the target business.

[0212] The ad placement time recommendation module is used to perform ad placement staggered scheduling analysis based on the first ad placement time information and the second ad placement time information to obtain ad placement time recommendation information corresponding to the target audience.

[0213] In some embodiments, the apparatus further includes:

[0214] Feedback data acquisition module: Used to acquire feedback data within the first preset time period after the target audience is targeted for promotion.

[0215] Profile information acquisition module: Used to acquire feedback information of the target feedback provider who provides feedback data.

[0216] Feedback Provider Tag Generation Module: This module generates feedback provider tags for target feedback providers based on feedback data and feedback provider information. Feedback provider tags are used to characterize the matching degree between the feedback provider and the target audience.

[0217] In some embodiments, the apparatus further includes:

[0218] The statistical processing module is used to periodically process the feedback data after the target audience is targeted for promotion, and obtain multi-dimensional promotion statistics.

[0219] The campaign performance report generation module is used to generate campaign performance reports for the target audience based on multi-dimensional promotion statistics.

[0220] In some embodiments, the delivery value determination module 640 includes:

[0221] The attribute matching value calculation submodule is used to match business attribute information and reference attribute information to obtain attribute matching values ​​for multiple promotion objects.

[0222] Feedback value calculation submodule: Used to perform multi-dimensional statistical processing on historical feedback data to obtain multi-dimensional feedback values ​​for multiple promotional targets.

[0223] Similarity Calculation Submodule: Used to calculate the delivery rate and the similarity of objects in the same period based on historical delivery data, to obtain the historical delivery rate and delivery similarity value for multiple promotion objects.

[0224] The campaign value calculation submodule is used to determine the campaign value of multiple promotional targets based on attribute matching values, feedback values, historical campaign rates, and campaign similarity values.

[0225] In some embodiments, the business attribute information includes business target information and lifecycle information of the target business. The attribute matching value calculation submodule includes:

[0226] The first matching value calculation unit is used to match the business target information with the reference target information in the reference attribute information to obtain the first matching value corresponding to each of the multiple promotion objects. The reference target information represents the business target configured when the first reference business targets one of the multiple promotion objects.

[0227] The second matching value calculation unit is used to match the lifecycle information with the reference lifecycle information in the reference attribute information to obtain the second matching value corresponding to each of the multiple promotional objects. The reference lifecycle information represents the lifecycle stage of one of the multiple promotional objects deployed by the first reference business.

[0228] Attribute matching value calculation unit: used to perform weighted summation of the corresponding first matching value and second matching value to obtain the attribute matching value corresponding to each of the multiple promotion objects.

[0229] In some embodiments, historical feedback data includes the historical reach conversion rate and social sharing reward value for each of the multiple promotional targets. The feedback value calculation submodule includes:

[0230] Average reach conversion rate calculation unit: used to perform weighted average processing on the historical reach conversion rates generated by each of the previous campaigns for multiple promotional objects, to obtain the average reach conversion rate for each of the multiple promotional objects.

[0231] Total Fission Reward Value Calculation Unit: This unit is used to accumulate the social fission reward values ​​obtained by each of the multiple promotional targets in their previous campaigns, and to obtain the total fission reward value for each of the multiple promotional targets.

[0232] Feedback value calculation unit: Used to perform weighted summation of the corresponding average reach conversion rate and total viral reward value to obtain the feedback value corresponding to each of the multiple promotion targets.

[0233] In other embodiments, the delivery value determination module 640 includes:

[0234] Feature mapping processing submodule: It is used to perform feature mapping processing on business attribute information, as well as historical feedback data, historical delivery data and reference attribute information corresponding to each promotion object, to generate corresponding business feature information and object feature information of each promotion object.

[0235] Feature encoding processing submodule: Used to perform feature encoding processing on business feature information and object feature information respectively, to obtain the corresponding business feature vector and object feature vector.

[0236] Feature Cross Processing Submodule: Used to perform feature cross processing on business feature vectors and object feature vectors to obtain the first feature vector and second feature vector corresponding to each promotion object.

[0237] The Value Determination Submodule is used to determine the value of each target audience based on the first and second feature vectors.

[0238] The above-described apparatus and method embodiments are based on the same implementation methods.

[0239] This application embodiment also provides a processing device 700 for promotional objects, such as... Figure 17 As shown, Figure 17 The diagram shows a schematic of a processing device for promotional objects provided in an embodiment of this application. The device may include a promotional object determination module 710: used to determine multiple promotional objects corresponding to the target business from the promotional object library in response to a target business request.

[0240] The value acquisition module 720 is used to acquire the value of the multiple promotional targets. The value is determined based on the business attribute information of the target business, as well as the historical feedback data, historical delivery data, and reference attribute information of the first reference business corresponding to the multiple promotional targets. The first reference business is a business that has been promoted to at least one of the multiple promotional targets.

[0241] Object sorting module 730: used to sort the multiple promotion objects according to the placement value, and obtain the object sorting result.

[0242] In some embodiments, the apparatus further includes the following modules.

[0243] List Display Module: Used to display a list of promotional objects corresponding to multiple promotional objects generated based on the object sorting results.

[0244] Filtering Request Receiving Module: Used to receive object filtering requests submitted for the list of promotional objects.

[0245] Filtering Request Parsing Module: Used to parse object filtering requests and obtain the corresponding object filtering information.

[0246] The target audience matching module is used to identify candidate targets that match the target audience filtering information from multiple target audiences.

[0247] List Update Module: Used to update the list of promotion targets based on the candidates for promotion.

[0248] In some embodiments, the apparatus further includes the following modules.

[0249] Target Promotion Object Determination Module: Based on the value of the campaign or in response to a request to determine the target promotion object from the list of promotion objects, it determines the target promotion object that matches the target business.

[0250] The campaign time slot information acquisition module is used to acquire the first campaign time slot information for the target audience currently being targeted by the second reference business, as well as the second campaign time slot information for the target audience. The second reference business is a business belonging to the same business category as the target business.

[0251] Off-peak scheduling analysis module: Used to perform off-peak scheduling analysis based on the first and second campaign time information to obtain the recommended campaign time information for the target audience.

[0252] In some embodiments, the apparatus further includes the following modules.

[0253] The delivery time period information display module is used to display the first and second delivery time period information in response to the object scheduling request for the target promotion object after obtaining the first delivery time period information of the current promotion object of the second reference business and the second delivery time period information of the current target promotion object.

[0254] Desired delivery time period receiving module: Used to receive desired delivery time period information.

[0255] Schedule conflict alert module: Used to generate schedule conflict alert information when there is an overlap between the scheduled period corresponding to the expected delivery time period information and at least one of the delivery time periods corresponding to the first delivery time period information and the second delivery time period information.

[0256] In some embodiments, the apparatus further includes the following modules.

[0257] Feedback data statistics module: Used to periodically process the feedback data after the target audience is targeted for promotion, and obtain multi-dimensional promotion statistics information.

[0258] The campaign performance report generation module is used to generate campaign performance reports for the target audience based on multi-dimensional promotion statistics.

[0259] The campaign performance report display module is used to display campaign performance reports in response to report query requests.

[0260] The above-described apparatus and method embodiments are based on the same implementation methods.

[0261] This application provides a processing device for a promotional object, which includes a processor and a memory. The memory stores at least one instruction or at least one program segment. The at least one instruction or at least one program segment is loaded and executed by the processor to implement the processing method for the promotional object as provided in the above method embodiments.

[0262] Memory is used to store software programs and modules. The processor executes these stored software programs and modules to perform various functional applications and data processing. Memory can primarily consist of a program storage area and a data storage area. The program storage area stores the operating system, application programs required for functionality, etc.; the data storage area stores data created based on device usage, etc. Furthermore, memory can include high-speed random access memory (RAM) and non-volatile memory, such as at least one disk storage device, flash memory device, or other volatile solid-state storage device. Accordingly, memory can also include a memory controller to provide the processor with access to the memory.

[0263] The methods and embodiments provided in this application can be executed on mobile terminals, computer terminals, servers, or similar computing devices. Taking running on a server as an example, Figure 18 This is a hardware structure block diagram of a server for a method of processing promotional objects provided in an embodiment of this application. For example... Figure 18 As shown, the server 800 can vary significantly due to different configurations or performance. It may include one or more Central Processing Units (CPUs) 810 (CPUs 810 may include, but are not limited to, microprocessors (MCUs) or programmable logic devices (FPGAs), a memory 830 for storing data, and one or more storage media 820 (e.g., one or more mass storage devices) for storing application programs 823 or data 822. The memory 830 and storage media 820 may be temporary or persistent storage. The program stored in the storage media 820 may include one or more modules, each module including a series of instruction operations on the server. Furthermore, the CPU 810 may be configured to communicate with the storage media 820 and execute a series of instruction operations stored in the storage media 820 on the server 800. The server 800 may also include one or more power supplies 860, one or more wired or wireless network interfaces 850, one or more input / output interfaces 840, and / or one or more operating systems 821, such as Windows Server. TM Mac OS X TM Unix TM Linux™, FreeBSD™, etc.

[0264] The input / output interface 840 can be used to receive or send data via a network. Specific examples of the network described above may include a wireless network provided by the communication provider of server 800. In one example, the input / output interface 840 includes a network interface controller (NIC), which can connect to other network devices via a base station to communicate with the Internet. In another example, the input / output interface 840 may be a radio frequency (RF) module for wireless communication with the Internet.

[0265] Those skilled in the art will understand that Figure 18 The structure shown is for illustrative purposes only and does not limit the structure of the aforementioned electronic device. For example, server 800 may also include... Figure 18 The more or fewer components shown, or having the same Figure 18 The different configurations shown.

[0266] Embodiments of this application also provide a computer-readable storage medium, which can be disposed in a server to store at least one instruction or at least one program related to implementing a method for processing a promotional object in the method embodiment. The at least one instruction or the at least one program is loaded and executed by the processor to implement the method for processing a promotional object provided in the above method embodiment.

[0267] Optionally, in this embodiment, the storage medium may be located at at least one of the multiple network servers in a computer network. Optionally, in this embodiment, the storage medium may include, but is not limited to, various media capable of storing program code, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.

[0268] According to one aspect of this application, a computer program product or computer program is provided, comprising computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the methods provided in the various alternative implementations described above.

[0269] As can be seen from the embodiments of the processing method, apparatus, equipment, server, or storage medium for promotional objects provided in this application, this application obtains business attribute information of the target business; determines multiple promotional objects corresponding to the target business from the promotional object library; obtains historical feedback data, historical delivery data, and reference attribute information of a first reference business corresponding to the multiple promotional objects; wherein, the first reference business is a business that has been delivered to at least one of the multiple promotional objects; determines the delivery value of the multiple promotional objects based on the business attribute information, historical feedback data, historical delivery data, and reference attribute information; and sorts the multiple promotional objects according to the delivery value to obtain the object ranking result. Based on this scheme, the delivery value of each promotional object of the target business can be determined by comprehensively considering multi-dimensional information, and the obtained ranking result is strongly correlated with the attributes of the target business, the feedback expectations of the feedbackers, and the historical delivery situation, which facilitates relevant personnel to determine the target promotional objects based on the result, improves the recommendation matching and accuracy of the promotional objects, and thus optimizes the promotion effect.

[0270] It should be noted that the order of the embodiments described above is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. Furthermore, the above description focuses on specific embodiments of this application. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps described in the claims can be performed in a different order than that shown in the embodiments and still achieve the desired results. Additionally, the processes depicted in the drawings do not necessarily require a specific or sequential order to achieve the desired results. In some implementations, multitasking and parallel processing are also possible or may be advantageous.

[0271] The various embodiments in this application are described in a progressive manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, the device, equipment, and storage medium embodiments are basically similar to the method embodiments, so the descriptions are relatively simple; relevant parts can be referred to the descriptions of the method embodiments.

[0272] Those skilled in the art will understand that all or part of the steps of the above embodiments can be implemented by hardware, or by a program instructing the relevant hardware to implement them. The program can be stored in a computer-readable storage medium, such as a read-only memory, a disk, or an optical disk.

[0273] The above are merely preferred embodiments of this application and are not intended to limit this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. A method for processing promotional targets, characterized in that, The method includes: Obtain the business attribute information of the target business; Identify multiple promotional targets corresponding to the target business from the promotional target library; Obtain historical feedback data, historical delivery data, and reference attribute information of the first reference business corresponding to the plurality of promotional objects; wherein, the first reference business is a business that has been delivered to at least one of the plurality of promotional objects; Based on the business attribute information, the historical feedback data, the historical delivery data, and the reference attribute information, the delivery value of the multiple promotion targets is determined; the business attribute information includes the business objective information and lifecycle information of the target business; The multiple promotional targets are sorted according to the placement value to obtain the object ranking result; The determination of the targeting value of the multiple promotional targets based on the business attribute information, the historical feedback data, the historical delivery data, and the reference attribute information includes: The business attribute information and the reference attribute information are matched to obtain the attribute matching values ​​corresponding to the multiple promotion objects; The historical feedback data is subjected to multi-dimensional statistical processing to obtain multi-dimensional feedback values ​​corresponding to the multiple promotion targets; The historical delivery data is used to calculate the delivery rate and the similarity of the target objects in the same period to obtain the historical delivery rate and delivery similarity value corresponding to the multiple promotion objects. The historical delivery rate is determined based on the ratio of the reference delivery count to the total number of target object deliveries. The reference delivery count is the number of times the corresponding promotion object is delivered by the second reference business. The total number of target object deliveries is the total number of deliveries made by all second reference businesses to various promotion objects within the social operation management platform. The delivery similarity value is obtained by comparing the object content data of each promotion object corresponding to the target business with the similarity data of each reference content data. The reference content data is the object content data of the reference promotion objects that meet the preset activity conditions and are delivered in the social operation management platform within the most recent preset time period. The advertising value of the multiple promotional targets is determined based on the attribute matching value, the feedback value, the historical delivery rate, and the delivery similarity value.

2. The method according to claim 1, characterized in that, The method further includes: Based on the object sorting result, a list of promotion objects corresponding to the multiple promotion objects is generated and sent to the terminal so that the terminal can display the list of promotion objects. Receive object filtering information submitted for the list of promotion targets; From the plurality of promotional targets, select candidate promotional targets that match the target screening information; Update the list of promotion targets based on the candidate promotion targets.

3. The method according to claim 1 or 2, characterized in that, The method further includes: Based on the placement value or the object determination information submitted for the list of promotion objects, determine the target promotion objects that match the target business from the list of promotion objects; Obtain the first advertising period information of the target audience currently being advertised by the second reference service, and the second advertising period information of the target audience currently being advertised by the second reference service; the second reference service is a service of the same business category as the target service. Based on the first and second delivery time period information, a staggered delivery schedule analysis is performed to obtain the delivery time period recommendation information corresponding to the target promotion object.

4. The method according to claim 3, characterized in that, The method further includes: Obtain feedback data within a first preset time period after the target promotion is launched; Obtain feedback information of the target feedback provider who provided the feedback data; The feedback data and the feedbacker information are used to generate a feedbacker tag for the target feedbacker; the feedbacker tag is used to characterize the matching degree between the feedbacker and the target promotion object.

5. The method according to claim 3, characterized in that, The method further includes: The feedback data after the target promotion is launched is periodically statistically processed to obtain multi-dimensional promotion statistics. A campaign performance report for the target audience is generated based on the multi-dimensional promotional statistics.

6. The method according to claim 1, characterized in that, The business attribute information includes the business objective information and lifecycle information of the target business; the step of matching the business attribute information and the reference attribute information to obtain the attribute matching values ​​corresponding to the multiple promotion objects includes: The business objective information is matched with the reference objective information in the reference attribute information to obtain the first matching value corresponding to each of the plurality of promotion objects; the reference objective information represents the business objective configured when the first reference business delivers one of the plurality of promotion objects; The lifecycle information is matched with the reference lifecycle information in the reference attribute information to obtain the second matching value corresponding to each of the plurality of promotion objects; the reference lifecycle information represents the life stage at which the first reference service places one of the plurality of promotion objects. The corresponding first matching value and second matching value are weighted and summed to obtain the attribute matching value corresponding to each of the multiple promotion objects.

7. The method according to claim 1, characterized in that, The historical feedback data includes the historical reach conversion rate and social sharing reward value for each of the multiple promotional targets; the social sharing reward value represents the promotional effect achieved by the promotional target in a single social sharing campaign; the multi-dimensional statistical processing of the historical feedback data to obtain the multi-dimensional feedback values ​​for the multiple promotional targets includes: The historical reach conversion rates generated by each of the various promotional targets in each campaign are weighted and averaged to obtain the average reach conversion rate of each of the various promotional targets. The social fission reward values ​​obtained by each of the multiple promotional targets in each of their previous campaigns are accumulated to obtain the total fission reward value for each of the multiple promotional targets. The corresponding average reach conversion rate and total viral reward value are weighted and summed to obtain the feedback value for each of the multiple promotional targets.

8. A method for processing promotional targets, characterized in that, The method includes: In response to a target business request, determine multiple promotional objects corresponding to the target business from the promotional object library; The placement value of the plurality of promotional objects is obtained; the placement value is determined based on the business attribute information of the target business, as well as the historical feedback data, historical placement data, and reference attribute information of the first reference business corresponding to the plurality of promotional objects; the first reference business is a business that has placed orders with at least one of the plurality of promotional objects; the placement value is determined using the promotional object processing method of any one of claims 1-7; The multiple promotional targets are sorted according to the placement value to obtain the object ranking result.

9. The method according to claim 8, characterized in that, The method further includes: Display a list of promotional objects corresponding to the multiple promotional objects generated based on the object sorting results; Receive object filtering requests submitted for the list of promotional objects; Parse the object filtering request to obtain the corresponding object filtering information; From the plurality of promotional targets, select candidate promotional targets that match the target screening information; Update the list of promotion targets based on the candidate promotion targets.

10. The method according to claim 8, characterized in that, The method further includes: Based on the placement value or in response to an object determination request submitted for the list of promotion objects, determine the target promotion object that matches the target business from the list of promotion objects; Obtain the first advertising period information of the target audience currently being advertised by the second reference service, and the second advertising period information of the target audience currently being advertised by the second reference service; the second reference service is a service of the same business category as the target service. Based on the first and second delivery time period information, a staggered delivery schedule analysis is performed to obtain the delivery time period recommendation information corresponding to the target promotion object.

11. The method according to claim 10, characterized in that, After obtaining the first campaign period information of the currently targeted promotional object of the second reference service, and the second campaign period information of the currently targeted promotional object, the method further includes: In response to an object scheduling request for the target promotion object, the first delivery time period information and the second delivery time period information are displayed; Receive desired delivery time period information; If there is an overlap between the delivery time period corresponding to the expected delivery time period information and the delivery time period corresponding to at least one of the first delivery time period information and the second delivery time period information, a scheduling conflict prompt information is generated.

12. A processing device for promotional targets, characterized in that, The device includes: First information acquisition module: used to acquire business attribute information of the target business; Promotion Target Determination Module: Used to determine multiple promotion targets corresponding to the target business from the promotion target library; The second information acquisition module is used to acquire historical feedback data, historical delivery data, and reference attribute information of the first reference service corresponding to the plurality of promotional objects; wherein, the first reference service is a service that has been delivered to at least one of the plurality of promotional objects; The value determination module is used to determine the value of the multiple promotion targets based on the business attribute information, the historical feedback data, the historical delivery data, and the reference attribute information; the business attribute information includes the business objective information and lifecycle information of the target business; The object sorting module is used to sort the multiple promotional objects according to the placement value, and obtain the object sorting result; the placement value determination module includes: Attribute matching value calculation submodule: used to match the business attribute information and the reference attribute information to obtain the attribute matching values ​​corresponding to the multiple promotion objects; Feedback value calculation submodule: Performs multi-dimensional statistical processing on the historical feedback data to obtain multi-dimensional feedback values ​​corresponding to the multiple promotion targets; The similarity calculation submodule is used to calculate the delivery rate and the similarity of objects in the same period based on the historical delivery data, so as to obtain the historical delivery rate and delivery similarity value corresponding to the multiple promotion objects. The historical delivery rate is determined based on the ratio of the number of reference delivery times to the total number of object delivery times. The number of reference delivery times is the number of times the corresponding promotion object is delivered by the second reference business. The total number of object delivery times is the total number of times all the second reference businesses in the social operation management platform have delivered to various promotion objects. The delivery similarity value is obtained by comparing the object content data of each promotion object corresponding to the target business with the similarity data of each reference content data. The reference content data is the object content data of the reference promotion objects that meet the preset activity conditions and have been delivered in the social operation management platform within the most recent preset time period. The value calculation submodule is used to determine the value of the multiple promotional targets based on the attribute matching value, the feedback value, the historical delivery rate, and the delivery similarity value.

13. A processing device for promotional targets, characterized in that, The device includes: Promotion Target Determination Module: In response to a target business request, this module determines multiple promotion targets corresponding to the target business from the promotion target library. The value acquisition module is used to acquire the value of the multiple promotional objects; the value of the promotional object is determined based on the business attribute information of the target business, as well as the historical feedback data, historical delivery data and reference attribute information of the first reference business corresponding to the multiple promotional objects; the first reference business is a business that has been promoted to at least one of the multiple promotional objects; the value of the promotional object is determined by the processing method of the promotional objects according to any one of claims 1-7. Object sorting module: used to sort the multiple promotional objects according to the placement value, and obtain the object sorting result.

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