Marketing activity generation method and device, computer readable storage medium, computer program product and terminal equipment

Abstract

The invention provides a marketing activity generation method and device, a computer readable storage medium, a computer program product and terminal equipment, and the method comprises the steps: obtaining user demand information, wherein the user demand information is used for at least indicating a target activity type; determining a target activity template matched with the target activity type in the historical activity data, wherein the target activity template comprises a plurality of process nodes; analyzing first activity data consistent with the target activity type in the historical activity data, and generating target contents of a plurality of process nodes in combination with an analysis result and user demand information; and filling the target contents of the plurality of process nodes into the plurality of process nodes to generate a target marketing activity. The invention provides a scheme capable of improving the marketing activity generation efficiency.

Description

Technical Field

[0001] This application relates to the field of computer technology, and in particular, to a method and device for generating marketing activities, a computer-readable storage medium, a computer program product, and a terminal device. Background Art

[0002] Marketing activity configuration refers to the process of designing and setting specific marketing activity processes, content, channels, and execution plans according to an enterprise's marketing goals and strategies. It is a key link in the success of marketing activities, ensuring that the activities can accurately reach the target customers and achieve the expected results. Specifically, it can include the following steps: (1) clarifying the activity goals; (2) defining the target audience; (3) selecting marketing channels; (4) designing the activity content; (5) setting the activity process; (6) configuring automation tools; (7) testing and optimization; (8) execution and monitoring. Among them, when configuring automation tools in (6), activities can be configured through marketing automation tools (such as a Customer Relationship Management (CRM) system): setting trigger conditions and workflows, automatically sending emails, text messages, or push notifications, and tracking customer behavior and activity effects.

[0003] However, the current marketing activity configuration process is cumbersome and inefficient. When configuring marketing activities, users usually need to manually select and input a large amount of information, and existing systems lack automated recommendation and optimization mechanisms. This makes users spend a lot of time determining configuration details and is prone to missing some key steps or making configuration errors. Summary of the Invention

[0004] This application provides a solution that can improve the efficiency of generating marketing activities.

[0005] To achieve the above object, this application provides the following technical solutions:

[0006] In a first aspect, a method for generating a marketing activity is provided. The method is applied to a terminal device, or a chip in the terminal device, or a chip module. The method for generating a marketing activity includes: obtaining user requirement information, where the user requirement information is used to at least indicate a target activity type; determining a target activity template that matches the target activity type in historical activity data, where the target activity template includes a plurality of process nodes; analyzing first activity data that is consistent with the target activity type in the historical activity data, and generating target content for the plurality of process nodes by combining the analysis result with the user requirement information; and filling the target content of the plurality of process nodes into the plurality of process nodes to generate a target marketing activity.

[0007] Optionally, the analysis of the first activity data in the historical activity data that is consistent with the target activity type includes: analyzing the first activity data to determine historical evaluation indicators for each historical content of each process node; determining historical content with a historical evaluation indicator value higher than a first threshold as candidate historical content; and determining the target content of each process node based at least on the candidate historical content of each process node.

[0008] Optionally, the determining the target content of each process node based at least on the candidate historical content of each process node includes: in response to the number of the candidate historical content of at least one process node being multiple, determining the historical configuration preference of the user in the historical activity data for the at least one process node; and determining the candidate historical content that matches the historical configuration preference of the at least one process node as the target content of the at least one process node.

[0009] Optionally, the determining the target content of each process node based at least on the candidate historical content of each process node includes: in response to the number of the candidate historical content of at least one process node being multiple, determining the business rules of the at least one process node; and determining the candidate historical content that satisfies the business rules of the at least one process node as the target content of the at least one process node.

[0010] Optionally, the analysis of the first activity data in the historical activity data that is consistent with the target activity type includes: mining historical configuration combinations for at least two process nodes in the first activity data as the historical content of the at least two process nodes, where the support degree of the historical configuration combination is greater than a first threshold; calculating the evaluation indicator value of a historical marketing activity including the historical configuration combination; and determining the target content of the at least two process nodes based on the historical configuration combinations in the historical marketing activities with an evaluation indicator value higher than a preset threshold.

[0011] Optionally, the determining a target activity template that matches the target activity type in the historical activity data includes: clustering the historical activity data according to target configuration characteristics to obtain multiple historical activity clusters; determining a target activity cluster that matches the target activity type in the historical activity clusters; selecting a target activity with a first evaluation indicator greater than a second threshold in the target activity cluster, and generating the target activity template based on the target activity, where the first evaluation indicator is used to measure the execution result of the target activity.

[0012] Optionally, the marketing activity generation method further includes: in response to receiving the user's configuration behavior data, adjusting the content of one or more process nodes according to the configuration behavior data to determine the adjusted content of the one or more process nodes; analyzing the first historical evaluation index value of the adjusted content of each process node in the one or more process nodes and the second evaluation index value of each historical content of each process node according to the historical activity data; selecting the target historical content in each historical content of each process node whose second evaluation index value is higher than the first historical evaluation index value, and pushing the target historical content as an optimization suggestion to the user.

[0013] Optionally, the user demand information includes the screening conditions of the target user, and the multiple process nodes include a target user node; filling the target content of the multiple process nodes into the multiple process nodes includes: filling the screening conditions of the target user into the target user node.

[0014] In a second aspect, the present application also discloses a marketing activity generation device, where the marketing activity generation device includes: an acquisition module, configured to acquire user demand information, and the user demand information is used to at least indicate a target activity type; a target activity template determination module, configured to determine a target activity template matching the target activity type in the historical activity data, and the target activity template includes multiple process nodes; an analysis module, configured to analyze the first activity data consistent with the target activity type in the historical activity data, and generate the target content of the multiple process nodes by combining the analysis result with the user demand information; a marketing activity generation module, configured to fill the target content of the multiple process nodes into the multiple process nodes to generate a target marketing activity.

[0015] In a third aspect, a computer-readable storage medium is provided, on which a computer program is stored, and the computer program is run by a processor to execute a method provided in the first aspect.

[0016] In a fourth aspect, a marketing activity generation device is provided, including a storage module and a processor, where a computer program that can run on the processor is stored on the storage module, and the processor runs the computer program to execute a method provided in the first aspect.

[0017] In a fifth aspect, a computer program product is provided, on which a computer program is stored, and the computer program is run by a processor to execute a method provided in the first aspect.

[0018] In a sixth aspect, an embodiment of the present application further provides a chip, on which a computer program is stored, and when the computer program is executed by the chip, the steps of the above method are implemented.

[0019] In a seventh aspect, an embodiment of the present application further provides a system-on-chip, which is applied to a terminal. The system-on-chip includes at least one processor and an interface circuit. The interface circuit and the at least one processor are interconnected by a line. The at least one processor is configured to execute instructions to perform a method according to the first aspect.

[0020] Compared with the prior art, the technical solution of the present application has the following beneficial effects:

[0021] Through in-depth mining of historical activity data, the technical solution of the present application determines a target activity template that matches the target activity type, and the target content of multiple process nodes in the target activity template, and automatically generates a target marketing activity. On the one hand, it can ensure the comprehensiveness and accuracy of the generation of the marketing activity, avoiding missing key nodes or configuration errors; on the other hand, it simplifies the user's operation process, eliminating the need for the user to manually select, input a large amount of information, and determine configuration details, improving the generation efficiency of the marketing activity and reducing the operation complexity. In addition, the historical activity data also includes the execution effect of the historical marketing activity, which can provide a reference for generating the marketing activity and further optimize the marketing activity.

[0022] Furthermore, the technical solution of the present application can also determine the target historical content with a higher evaluation index value according to the adjustment content of the user for one or more process nodes, combined with the first historical evaluation index value of the adjustment content and the second evaluation index value of each historical content of each process node, and recommend it to the user to achieve the optimization of one or more process nodes and further improve the execution effect of the marketing process. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 is a flowchart of a method for generating a marketing activity provided by an embodiment of the present application;

[0024] Figure 2 is a flowchart of another method for generating a marketing activity provided by an embodiment of the present application;

[0025] Figure 3 is a flowchart of yet another method for generating a marketing activity provided by an embodiment of the present application;

[0026] Figure 4 is a schematic diagram of a marketing activity provided by an embodiment of the present application;

[0027] Figure 5 is a schematic structural diagram of another marketing activity generation device provided by an embodiment of the present application;

[0028] Figure 6 is a schematic hardware structure diagram of a marketing activity generation device provided by an embodiment of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0029] As described in the background art, the current configuration process of marketing activities is cumbersome and inefficient. When configuring marketing activities, users usually need to manually select and input a large amount of information, and the existing system lacks an automated recommendation and optimization mechanism. This makes it take users a lot of time to determine the configuration details, and it is easy to miss some key steps or make configuration errors.

[0030] Through in-depth mining of historical activity data, the technical solution of this application determines a target activity template that matches the target activity type, as well as the target content of multiple process nodes in the target activity template, and automatically generates a target marketing activity. On the one hand, it can ensure the comprehensiveness and accuracy of the generation of marketing activities, avoiding missing key nodes or configuration errors; on the other hand, it simplifies the user's operation process, eliminating the need for the user to manually select, input a large amount of information, and determine configuration details, improving the generation efficiency of marketing activities and reducing operation complexity. In addition, the historical activity data also includes the execution effects of historical marketing activities, which can provide a reference for generating marketing activities and further optimize marketing activities.

[0031] In the embodiments of this application, the so-called process node represents a phased goal or action in a marketing activity, usually corresponding to a specific task or decision point, and multiple process nodes can be combined to form a complete marketing process.

[0032] Exemplarily, the process nodes of a live e-commerce activity include: product selection → script planning → preheating publicity → live execution → data review → after-sales follow-up.

[0033] In the embodiments of this application, the so-called historical activity data refers to the relevant data of completed marketing activities, and specifically may include at least one of the following dimensions of data: activity configuration data, user behavior data, execution result data, external environment data.

[0034] Among them, the activity configuration data may include basic activity information, budget allocation methods, themes and content, template information, and screening conditions (rules or parameters for targeting users in marketing activities). Specifically, the basic activity information may include an identifier (such as a number), name, type (such as promotional activities, new user acquisition, user recall, new product promotion, member exclusive, holiday marketing (such as National Day, Spring Festival), etc.), creation time, and person in charge. The budget allocation methods may include advertising costs, coupon costs, etc. The theme and content include activity copywriting (such as titles (time-limited purchases, exclusive premieres), body text), and visual materials (such as Banner images, video links). The template information includes template identifiers (such as email templates, SMS templates). The screening conditions may specifically include: user attributes (such as age, gender, region, occupation, purchase frequency, average order value, time of last consumption, etc.), behavior trigger conditions (such as adding items to the cart but not making a payment, browsing a specific product page more than three times, not logging in within the past 30 days, etc.), and grouping rules (such as custom labels: "user group 1", "user group 2", etc., machine learning grouping: dividing user groups through clustering algorithms, etc.).

[0035] Among them, user behavior data includes participation behavior and conversion path data. Specifically, the participation behavior includes the number of visits to the activity page, click-through rate, dwell time, bounce rate, number of coupon redemptions, usage rate, and redemption time. The conversion path data includes: the overall conversion rate from activity exposure → click → purchase; the response differences of users on different channels (such as email, app push, SMS).

[0036] Among them, the execution result data represents the actual effect data of historical marketing activities. The execution result data includes evaluation metrics, exception records, and user feedback. The evaluation metrics are used to evaluate the effectiveness of marketing activities or the effectiveness of node content. The exception records specifically include: configuration errors (such as rule conflicts, budget overruns), technical failures (such as push failures, page loading timeouts); the user feedback specifically includes: direct feedback and indirect feedback. The direct feedback includes questionnaire scores, complaints or suggestions in customer service work orders; the indirect feedback may include sentiment analysis of social media comments (such as the proportion of negative keywords).

[0037] Among them, the external environment data includes time factors and market competition data. The time factors may specifically include the activity period (such as holidays, weekdays), push time periods (such as 9 am, late at night). The market competition data includes the types of concurrent competitor activities, the intensity of concurrent competitor promotions (obtained through web scraping or third-party data platforms, for example).

[0038] The configuration behavior data referred to in the embodiments of this application refers to the operation steps and decisions executed by users during the configuration process of marketing activities. Specifically, it may include at least one of the following categories of data: activity basic settings, target user screening conditions, content design and channel selection, rule verification and advanced settings.

[0039] Among them, the activity basic settings may specifically include the activity type, such as promotions (e.g., full reduction, discount), acquiring new users (e.g., new user packages), recall (e.g., activating dormant users); the activity time plan, which is used to set the start and end times of the marketing activity and the push time window (e.g., the email sending period); the budget allocation, which is used to define the total budget and breakdown costs (e.g., advertising costs, coupon amounts, channel investment ratios).

[0040] Among them, the screening conditions are the rules or parameters used to locate target users in marketing activities.

[0041] Among them, the content design and channel selection include copywriting design, such as titles, body texts, call-to-action (CTA) copywriting; personalized content, such as dynamically inserting "Dear {user name}" according to the user name; visual material configuration, such as Banner graphics, videos, landing page design.

[0042] Among them, the rule verification and advanced settings may specifically include discount rules, such as discount strength, full reduction gradients, coupon validity periods; stacking restrictions, such as "cannot be used simultaneously with other offers"; risk control may specifically include: budget warning: setting a budget consumption threshold (e.g., triggering a reminder when reaching 80%); frequency control: restricting the number of user participations (e.g., each person is limited to receiving 1 coupon).

[0043] The evaluation indicators referred to in the embodiments of this application may be recall rate, redemption rate, conversion rate, return on investment (ROI), gross merchandise volume (GMV), click-through rate (CTR), number of new users, repurchase rate, increase in average order value, etc.

[0044] Exemplarily, for the process node "push channel", its indicators may be recall rate and conversion rate.

[0045] Exemplarily, for the process nodes "offer type" and "offer rules", their indicators may be redemption rate.

[0046] Exemplarily, for a marketing activity, its evaluation indicator may be ROI.

[0047] The configuration features referred to in the embodiments of the present application represent features used to measure marketing activities, which may specifically be activity types, budgets, user coverage rates, preferential intensities, effects of historical similar activities, and the foregoing evaluation indicators.

[0048] Exemplarily, when predicting the activity success rate (i.e., binary classification: success / failure), the configuration features used include activity types, budgets, and user coverage rates.

[0049] Exemplarily, when predicting indicators such as ROI and conversion rates, the configuration features used include preferential intensities and effects of historical similar activities.

[0050] The configuration combinations referred to in the embodiments of the present application, which may also be referred to as frequent itemsets, refer to combinations of parameters that occur in a dataset with a frequency reaching or exceeding a preset threshold.

[0051] The user data involved in the technical solution of the present application is all obtained with user authorization. For example, the purpose, scope, and permissions of the data are explicitly informed to the user through an interactive interface, and after the user actively checks the consent or completes an electronic signature, valid authorization is obtained.

[0052] To make the above objects, features, and advantages of the present application more obvious and understandable, the following specifically describes the embodiments of the present application with reference to the accompanying drawings.

[0053] The embodiments of the present application provide a method for generating a marketing activity. Refer to Figure 1 , and the following will be described in detail through specific steps.

[0054] It can be understood that in specific implementations, the method for generating a marketing activity may be implemented in the form of a software program that runs in a processor integrated inside a chip or a chip module. This method may also be implemented in a manner combining software and hardware, and the present application does not make any restrictions.

[0055] In step 101, user demand information is obtained, and the user demand information is used to at least indicate the target activity type.

[0056] In specific implementations, the user may input the user demand information in the interactive interface to indicate the information of the marketing activity to be created. The user demand information includes at least the type of the marketing activity, that is, the target activity type. For example, the user demand information includes: the target activity type is member recall.

[0057] In a specific embodiment, the user demand information may include the target activity type and the screening conditions for the target users. The screening conditions for the target users are used to determine the target users in the marketing activity.

[0058] For example, the user needs to configure a target activity type as a "member recall" activity, with the goal of awakening member users who have not consumed in the past six months. At this time, the target activity type is member recall, and the screening condition is member users who have not consumed in the past six months.

[0059] Furthermore, there may be partial overlap or complete consistency between the user demand information and the types of configuration behavior data and historical activity data of the user in the marketing activity configuration. According to different actual application scenarios, the user demand information may include any other appropriate information that can be implemented, such as budget, budget allocation method, theme and content, etc., and this application does not limit this.

[0060] In step 102, determine a target activity template that matches the target activity type in the historical activity data. The target activity template includes multiple process nodes.

[0061] In this embodiment, the historical activity data can be the relevant data of the completed marketing activities collected in advance and stored in the database in advance. Specifically, the database can include a historical success case library and a historical failure case library. The historical success case library includes the data of historical marketing activities with a relatively high conversion rate (for example, the conversion rate is greater than a certain threshold), such as activity themes, screening conditions, channels, etc. The historical failure case library is used to record the data of historical marketing activities with a relatively low ROI (for example, lower than a preset threshold) or a relatively large number of user complaints (for example, higher than a preset threshold).

[0062] In specific implementation, since the historical activity data includes the data of historical marketing activities of multiple activity types, in order to ensure the accuracy of the target marketing, it is first necessary to determine a target activity template that matches the target activity type. Specifically, at least one historical marketing activity that matches the target activity type can be determined first, and then the target activity template can be selected from the historical activity data corresponding to the at least one historical marketing activity. Specifically, the activity template used by the historical marketing activity can be selected in combination with the evaluation indicators (such as ROI) of the at least one historical marketing activity as the target activity template.

[0063] In a non-limiting embodiment, by analyzing the historical activity data in the historical success case library, select the target activity template used by the historical marketing activity with relatively high evaluation indicators (such as ROI) to ensure the performance of each node of the marketing activity. Please refer to Figure 2 , Figure 2 which shows a way to determine the target activity template.

[0064] In step 201, cluster the historical activity data according to the target configuration characteristics to obtain multiple historical activity clusters.

[0065] In this embodiment, the target configuration features used for clustering historical activity data are related to the target activity type. In other words, the target configuration features are the features used to measure marketing activities of the target activity type.

[0066] Taking the target activity type of member recall as an example, the target configuration feature can be the recall rate. Since the historical activity data includes evaluation indicators of historical marketing activities, such as the recall rate, the historical activity data can be clustered according to the recall rate to obtain multiple historical activity clusters with different recall rates.

[0067] In step 202, a target activity cluster that matches the target activity type is determined in the historical activity clusters.

[0068] Since the marketing activities in the historical activity clusters may have various activity types, to ensure the match of the target, screening can be performed in the historical activity clusters based on the target activity type to determine the target activity cluster that matches the target activity type.

[0069] In step 203, target activities with a first evaluation indicator greater than a second threshold are selected from the target activity cluster, and a target activity template is generated based on the target activities. The first evaluation indicator is used to measure the execution result of the target activities.

[0070] In this embodiment, target activities with better execution results are selected through the first evaluation indicator, and the activity template used by the target activities can be used as the target activity template. For example, when the target activity type is member recall, the first evaluation indicator can be ROI.

[0071] In an alternative embodiment, it is also possible to cluster the first activity data in the historical activity data that is consistent with the target activity type according to the target configuration features. In other words, the first activity data in the historical activity data is clustered according to the recall rate to obtain multiple historical activity clusters with different recall rates. In this case, step 202 does not need to be executed, and target activities with a first evaluation indicator greater than a second threshold are directly selected from the multiple historical activity clusters, and a target activity template is generated based on the target activities.

[0072] In a specific embodiment, the target activity template includes multiple process nodes. Taking the target activity type of member recall as an example, the target activity template includes the following process nodes:

[0073] Target user node, preferential rule node, push channel node, push time node, budget allocation node.

[0074] Continue to refer to Figure 1, in step 103, analyze the first activity data in the historical activity data that is consistent with the target activity type, and generate the target content of multiple process nodes by combining the analysis results with the user requirement information.

[0075] In step 104, fill the target content of multiple process nodes into the multiple process nodes to generate a target marketing activity.

[0076] In this embodiment, by deeply mining the historical activity data, determine the target content of multiple process nodes in the target activity template, and automatically generate a target marketing activity.

[0077] Taking the target activity type of member recall as an example, the target marketing activity includes:

[0078] Target user node: members who have not consumed in the past 6 months;

[0079] Discount rule node: a 20-yuan coupon without threshold (valid for 7 days);

[0080] Push channel node: SMS push and application push;

[0081] Push time node: 10:00 am;

[0082] Budget allocation node: the budget ratio for SMS push is 30%, the budget ratio for APP push is 70%, and the total budget is 5000 yuan.

[0083] It should be noted that the sequence numbers of the steps in this embodiment do not represent the limitation on the execution order of each step.

[0084] In a non-limiting embodiment, in order to ensure the effect of the target content of the process node, the target content of the process node can be selected in combination with the historical evaluation index. Specifically, reference can be made to Figure 3 , Figure 3 which shows a schematic diagram for determining the target content of the process node.

[0085] In step 301, analyze the first activity data to determine the historical evaluation index for each historical content of each process node.

[0086] In specific implementation, the evaluation indexes adopted by different process nodes can be different.

[0087] Exemplarily, for the process node "push channel", its index can be the recall rate.

[0088] Exemplarily, for the process nodes "discount type" and "discount rule", its index can be the redemption rate.

[0089] In specific implementation, the historical evaluation indicators of different historical contents of the same process node may be different. For example, the recall rate of the process node "push channel" is "SMS push + application push" is 65%, and the recall rate of the process node "push channel" is "SMS push" is 40%. The recall rate of dual-channel coverage of "SMS push + application push" is 25% higher than that of a single channel.

[0090] For example, the redemption rate of the process node discount type "no threshold coupon" is 70%, and the redemption rate of the process node discount type "full-discount coupon" is 40%. The redemption rate of "no threshold coupon" is 30% higher than that of "full-discount coupon".

[0091] In a specific embodiment of step 301, historical configuration combinations for at least two process nodes in the first activity data are mined as historical contents of the at least two process nodes, and the support of the historical configuration combination is greater than a first threshold; and an evaluation index value of the historical marketing activity including the historical configuration combination is calculated. Here, the at least two process nodes are process nodes in the target activity template.

[0092] Specifically, the historical configuration combination includes a combination of historical contents of at least two process nodes. For example, for the process node discount rule node, push channel node, and target user node, the historical configuration combination can be: "full-discount activity + email push + target user is a dormant user".

[0093] Specifically, the support of the historical configuration combination represents the frequency of the historical configuration appearing in the first activity data, and the calculation formula is: Support(X)=the number of marketing activities containing the historical configuration combination / the total number of marketing activities.

[0094] Furthermore, the target content of at least two process nodes is determined based on the historical configuration combination in the historical marketing activities whose evaluation index value is higher than the preset threshold. In the case where the historical content of at least two process nodes of the historical marketing activities is the historical configuration combination, the evaluation index value of the marketing activity is calculated. For example, the historical content of the historical marketing activity 1 for the three process nodes is "full reduction activity + email push + target users are dormant users" and the conversion rate is 80%, while the average conversion rate of all historical marketing activities is 40%, which means that the historical content of at least two process nodes of the marketing activity 1 is the historical configuration combination with a higher conversion rate. Therefore, it can be determined that the historical content of the three process nodes in the marketing activity 1, "full reduction activity + email push + target users are dormant users", is the target content of the three process nodes.

[0095] Continue to refer to Figure 3 In step 302, historical contents whose historical evaluation index values ​​are higher than a first threshold are determined as candidate historical contents.

[0096] In this embodiment, historical content with relatively high historical evaluation indicators can be selected as candidate historical content. The target content of a process node is selected from the candidate historical content of the process node.

[0097] In step 303, the target content of each process node is determined at least based on the candidate historical content of the process node.

[0098] In a specific embodiment, historical content with the highest historical evaluation indicator can be selected from the candidate historical content of the process node as the target content of the process node.

[0099] In another specific embodiment, the target content of the process node can also be selected from the candidate historical content of the process node in combination with other factors. The other factors can be the user's historical configuration preferences or the business rules of the process node.

[0100] In a specific embodiment of step 303, the target content of the process node can be selected from the candidate historical content of the process node in combination with the user's historical configuration preferences.

[0101] In specific implementation, in response to the number of candidate historical contents of at least one process node being multiple, the historical configuration preferences of the user for at least one process node in the historical activity data are determined. The candidate historical content that matches the historical configuration preferences of at least one process node is determined as the target content of at least one process node.

[0102] Specifically, first, the first activity data of the user in the historical activity data is determined, and then the historical configuration preferences of the user for at least one process node can be determined according to the frequency of the historical content of the user for at least one process node in the first activity data.

[0103] For example, for the process node push channel, if the user's historical configuration preference is application push, then in the case where the historical content with relatively high recall rate includes SMS push and application push, application push can be selected as the target content of the process node push channel.

[0104] This embodiment determines the target content of the process node in combination with the user's historical configuration preferences, which can meet the personalized needs of the user.

[0105] In another specific embodiment of step 303, the target content of the process node can be selected from the candidate historical content of the process node in combination with the business rules of the process node.

[0106] In specific implementation, in response to the number of candidate historical contents of at least one process node being multiple, the business rules of at least one process node are determined. The candidate historical content that meets the business rules of at least one process node is determined as the target content of at least one process node.

[0107] This embodiment determines the target content of the process node in combination with the business rules of the process node, which can meet personalized business requirements.

[0108] Specifically, different business rules can be set for different process nodes. For example, for the preferential rule node, the business rule includes that "the new user activity needs to include the first order discount". Specifically, the candidate historical content of the process node can be matched with the business rules of the process node. When the business rules of the process node are met, the candidate historical content can be determined as the target content of the process node.

[0109] In a non - restrictive embodiment, after generating the preliminary target marketing activity, the user can modify one or more process nodes in the preliminary target marketing activity. This embodiment can automatically analyze and optimize the adjustment content of the user for one or more process nodes in combination with historical activity data, further ensuring the effect of the marketing activity.

[0110] In specific implementation, in response to receiving the user's configuration behavior data, adjust the content of one or more process nodes according to the configuration behavior data to determine the adjustment content of one or more process nodes; analyze the first historical evaluation index value of the adjustment content of each process node in one or more process nodes, and the second evaluation index value of each historical content of each process node according to historical activity data.

[0111] For example, for the push channel node, the user wants to add phone push. Then this application can calculate in combination with historical activity data that based on SMS push and application push, the recall rate of superimposing phone push is 70% (i.e., the first historical evaluation index value), while based on SMS push and application push, the recall rate of superimposing email push is 80% (i.e., the second evaluation index value).

[0112] Furthermore, select the target historical content in each historical content of each process node whose second evaluation index value is higher than the first historical evaluation index value, and push the target historical content as an optimization suggestion to the user.

[0113] For example, the recall rate of superimposing email push is 10% higher than that of superimposing phone push based on SMS push and application push. Therefore, for the push channel node, it can be recommended to the user to superimpose email push (i.e., the target historical content is email push).

[0114] For another example, for the preferential rule node, the user wants to adjust the amount of the threshold-free coupon to 25 yuan. The redemption rate of the threshold-free coupon with an amount of 25 yuan is calculated to be 40% by combining the target historical content, and the redemption rate of the threshold-free coupon with an amount of 30 yuan is 55%. The redemption rate of the threshold-free coupon with an amount of 30 yuan is 15% higher than that of the threshold-free coupon with an amount of 25 yuan. Therefore, for the preferential rule node, it is recommended that the user set the amount of the threshold-free coupon to 30 yuan (that is, the target historical content is the threshold-free coupon amount of 30 yuan).

[0115] For specific reference, please refer to Figure 4 , Figure 4 Figure 4 shows a specific marketing activity. The marketing activity includes a start node, a query and screening node, an application node, a SMS node, a coupon node, and an end node. Among them, the query and screening node accurately locates target users from a large amount of user or behavior data through data query and conditional screening. Taking the target activity type of member recall as an example, the query and screening node screens out member users who have not consumed in the past six months as target users.

[0116] The application node is used to issue coupons to target users through the application; the SMS node is used to issue coupons to target users through SMS.

[0117] The coupon node is a key link specifically designed for planning, issuing, redeeming, and tracking the effects of coupons.

[0118] It should be noted that each node in the marketing activity can be adaptively set according to the actual application scenario, and this application does not limit this.

[0119] In a specific application scenario, the product form of the embodiment of this application can be an intelligent assistant system integrated into the existing marketing CRM system. Among them, the marketing CRM system is a tool that combines CRM and marketing automation, aiming to help enterprises better manage customer data, optimize marketing processes, and improve customer satisfaction.

[0120] The intelligent assistant system has no invasiveness to the marketing CRM system, does not need to serve specific modules separately, and can realize the automatic generation and optimization of influence activities based on the user's input information, improving the generation efficiency of marketing activities.

[0121] In specific implementation, the user inputs user requirement information by interacting with the intelligent assistant system. The intelligent assistant system can execute the steps in the foregoing embodiments, such as steps 101 to 104, to generate a target marketing activity.

[0122] For reference, please refer to Figure 5 , Figure 5A marketing activity generation device 50 is shown. The marketing activity generation device 50 may include:

[0123] An acquisition module 501, configured to acquire user requirement information, where the user requirement information is used to at least indicate a target activity type;

[0124] A target activity template determination module 502, configured to determine a target activity template that matches the target activity type from historical activity data, where the target activity template includes multiple process nodes;

[0125] An analysis module 503, configured to analyze first activity data in the historical activity data that is consistent with the target activity type, and generate target content for multiple process nodes by combining the analysis result with the user requirement information;

[0126] A marketing activity generation module 504, configured to fill the target content of multiple process nodes into the multiple process nodes to generate a target marketing activity.

[0127] Further, the analysis module 503 may include: a first analysis unit, configured to analyze the first activity data to determine historical evaluation indicators for each historical content of each process node; a candidate historical content determination unit, configured to determine historical content with a historical evaluation indicator value higher than a first threshold as candidate historical content; a first target content determination unit, configured to determine the target content of each process node at least according to the candidate historical content of each process node.

[0128] Further, the analysis module 503 may include: a second analysis unit, configured to mine historical configuration combinations for at least two process nodes in the first activity data as historical content for the at least two process nodes, where the support degree of the historical configuration combination is greater than a first threshold; a calculation unit, configured to calculate an evaluation indicator value of a historical marketing activity including the historical configuration combination; a second target content determination unit, configured to determine the target content of at least two process nodes according to the historical configuration combination in the historical marketing activity with an evaluation indicator value higher than a preset threshold.

[0129] Further, the target activity template determination module 502 may include: a clustering unit, configured to cluster the historical activity data according to target configuration features to obtain multiple historical activity clusters; a matching unit, configured to determine a target activity cluster that matches the target activity type from the historical activity clusters; a target activity template generation unit, configured to select a target activity with a first evaluation indicator greater than a second threshold from the target activity clusters, and generate a target activity template based on the target activity, where the first evaluation indicator is used to measure the execution result of the target activity.

[0130] Further, the marketing activity generation device 50 may include: an adjustment content determination module, configured to, in response to receiving user configuration behavior data, adjust the content of one or more process nodes according to the configuration behavior data to determine the adjusted content of the one or more process nodes;

[0131] An evaluation module, configured to analyze the first historical evaluation index value of the adjusted content of each process node among the one or more process nodes, and the second evaluation index value of each historical content of each process node according to historical activity data;

[0132] A recommendation module, configured to select the target historical content in each historical content of each process node whose second evaluation index value is higher than the first historical evaluation index value, and push the target historical content as an optimization recommendation to the user.

[0133] In a specific implementation, the above-mentioned marketing activity generation device 50 may correspond to a chip with a marketing activity generation function in a terminal device, such as a System-On-a-Chip (SOC), a baseband chip, etc.; or correspond to a chip module including a chip with a marketing activity generation function in a terminal device; or correspond to a chip module with a data processing function chip, or correspond to a terminal device.

[0134] Other related descriptions of the marketing activity generation device 50 may refer to the relevant descriptions in the foregoing embodiments, and will not be elaborated here.

[0135] Regarding each device and product described in the above embodiments, each module / unit included therein can be a software module / unit, a hardware module / unit, or can be partially a software module / unit and partially a hardware module / unit. For example, for each device and product applied to or integrated into a chip, each module / unit included therein can be implemented in the form of hardware such as circuits. Alternatively, at least some of the modules / units can be implemented in the form of software programs that run on the processor integrated inside the chip, and the remaining (if any) part of the modules / units can be implemented in the form of hardware such as circuits. For each device and product applied to or integrated into a chip module, each module / unit included therein can be implemented in the form of hardware such as circuits. Different modules / units can be located in the same component (such as a chip, a circuit module, etc.) or different components of the chip module. Alternatively, at least some of the modules / units can be implemented in the form of software programs that run on the processor integrated inside the chip module, and the remaining (if any) part of the modules / units can be implemented in the form of hardware such as circuits. For each device and product applied to or integrated into a terminal device, each module / unit included therein can be implemented in the form of hardware such as circuits. Different modules / units can be located in the same component (such as a chip, a circuit module, etc.) or different components inside the terminal device. Alternatively, at least some of the modules / units can be implemented in the form of software programs that run on the processor integrated inside the terminal device, and the remaining (if any) part of the modules / units can be implemented in the form of hardware such as circuits.

[0136] An embodiment of the present application also discloses a storage medium, which is a computer-readable storage medium, on which a computer program is stored. When the computer program runs, it can execute the steps of the method shown in the foregoing embodiments. The storage medium can include a read-only memory module (ROM), a random access memory module (RAM), a magnetic disk, an optical disk, etc. The storage medium can also include a non-volatile storage module or a non-transitory storage module, etc.

[0137] Please refer to Figure 6 , an embodiment of the present application also provides a schematic hardware structure diagram of a marketing activity generation device. The device includes a processor 601, a storage module 602, and a transceiver 603.

[0138] The processor 601 may be a general-purpose central processing unit (CPU), a microprocessor, an application-specific integrated circuit (ASIC), or one or more integrated circuits for controlling the execution of the program of the solution of the present application. The processor 601 may also include multiple CPUs, and the processor 601 may be a single-CPU processor or a multi-CPU processor. The processor here may refer to one or more devices, circuits, or processing cores for processing data (such as computer program instructions).

[0139] The storage module 602 may be a ROM or other type of static storage device that can store static information and instructions, a RAM, or other type of dynamic storage device that can store information and instructions. It may also be an electrically erasable programmable read-only memory (EEPROM), a compact disc read-only memory (CD-ROM), or other optical disc storage, optical disc storage (including compact discs, laser discs, optical discs, digital versatile discs, Blu-ray discs, etc.), a magnetic disk storage medium, or any other medium that can be used to carry or store the desired program code in the form of instructions or data structures and can be accessed by a computer. The embodiments of the present application do not impose any restrictions on this. The storage module 602 may exist independently (in this case, the storage module 602 may be located outside the device or inside the device), or may be integrated with the processor 601. Among them, the storage module 602 may contain computer program code. The processor 601 is used to execute the computer program code stored in the storage module 602, so as to implement the method provided by the embodiments of the present application.

[0140] The processor 601, the storage module 602, and the transceiver 603 are connected through a bus. The transceiver 603 is used to communicate with other devices or communication networks. Optionally, the transceiver 603 may include a transmitter and a receiver. The device in the transceiver 603 for implementing the receiving function may be regarded as a receiver, and the receiver is used to execute the receiving steps in the embodiments of the present application. The device in the transceiver 603 for implementing the sending function may be regarded as a transmitter, and the transmitter is used to execute the sending steps in the embodiments of the present application.

[0141] When Figure 6When the structural schematic diagram shown is used to illustrate the structure of the terminal device involved in the above embodiments, the processor 601 is used to control and manage the actions of the terminal device. For example, the processor 601 is used to support the terminal device in performing the actions executed by the terminal device in other processes described in the embodiments of the present application. The storage module 602 is used to store the program code and data of the terminal device.

[0142] In the embodiments of the present application, "a plurality of" means two or more.

[0143] In the embodiments of the present application, the descriptions such as first and second are only for schematic and differentiating the described objects, without an order, nor do they represent a special limitation on the number of devices in the embodiments of the present application, and cannot constitute any limitation to the embodiments of the present application.

[0144] In the embodiments of the present application, "connection" means various connection methods such as direct connection or indirect connection to achieve communication between devices, and the present application embodiments do not make any limitations thereto.

[0145] The above embodiments can be implemented in whole or in part by software, hardware, firmware, or any other combination. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the processes or functions described in the embodiments of the present application are generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center in a wired or wireless manner.

[0146] It should be understood that in various embodiments of the present application, the magnitudes of the sequence numbers of the above processes do not mean the sequence of execution, and the execution sequence of each process should be determined according to its function and internal logic, and should not constitute any limitation to the implementation process of the embodiments of the present application.

[0147] In several embodiments provided by this application, it should be understood that the disclosed methods, apparatuses, and systems can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for example, the division of the units is only a logical function division, and there can be other division methods in actual implementation; for example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed couplings or direct couplings or communication connections to each other can be through some interfaces, and the indirect couplings or communication connections of the apparatuses or units can be in electrical, mechanical, or other forms.

[0148] The units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they can be located in one place, or can be distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0149] In addition, in each embodiment of this application, the functional units can be integrated in a processing unit, or each unit can be physically included separately, or two or more units can be integrated in one unit. The above-mentioned integrated units can be implemented in the form of hardware, or in the form of hardware plus software functional units.

[0150] The above-mentioned integrated units implemented in the form of software functional units can be stored in a computer-readable storage medium. The above-mentioned software functional units stored in a storage medium include several instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to execute some steps of the methods described in each embodiment of this application.

[0151] Although this application is disclosed as above, this application is not limited thereto. Any person skilled in the art can make various changes and modifications without departing from the spirit and scope of this application. Therefore, the protection scope of this application should be subject to the scope defined by the claims.

Claims

1. A marketing activity generation method, characterized in that Including: Obtain user requirement information, where the user requirement information is used to at least indicate a target activity type; Determine a target activity template that matches the target activity type in historical activity data, where the target activity template includes multiple process nodes; Analyze first activity data in the historical activity data that is consistent with the target activity type, and generate target content for the multiple process nodes by combining the analysis results with the user requirement information; Fill the target content of the multiple process nodes into the multiple process nodes to generate a target marketing activity.

2. The marketing activity generation method according to claim 1, wherein The analyzing the first activity data in the historical activity data that is consistent with the target activity type includes: Analyze the first activity data to determine historical evaluation indicators for each historical content of each process node; Determine that the historical content with a historical evaluation indicator value higher than a first threshold is candidate historical content; Determine the target content of each process node at least based on the candidate historical content of each process node.

3. The marketing campaign generation method according to claim 2, characterized in that, The determining the target content of each process node at least based on the candidate historical content of each process node includes: In response to the number of the candidate historical content of at least one process node being multiple, determine the historical configuration preference of the user in the historical activity data for the at least one process node; Determine that the candidate historical content that matches the historical configuration preference of the at least one process node is the target content of the at least one process node.

4. The marketing activity generation method according to claim 2, wherein The determining the target content of each process node at least based on the candidate historical content of each process node includes: In response to the number of the candidate historical content of at least one process node being multiple, determine the business rules of the at least one process node; Determine that the candidate historical content that satisfies the business rules of the at least one process node is the target content of the at least one process node.

5. The marketing activity generation method according to claim 1, characterized in that The analyzing the first activity data in the historical activity data that is consistent with the target activity type includes: Mine historical configuration combinations for at least two process nodes in the first activity data as the historical content of the at least two process nodes, where the support degree of the historical configuration combination is greater than a first threshold; Calculate the evaluation indicator value of a historical marketing activity including the historical configuration combination; Determine the target content of the at least two process nodes based on the historical configuration combinations in the historical marketing activities with evaluation indicator values higher than a preset threshold.

6. The marketing campaign generation method according to claim 1, wherein The determining a target activity template that matches the target activity type in historical activity data includes: Cluster the historical activity data according to target configuration characteristics to obtain multiple historical activity clusters; Determine a target activity cluster that matches the target activity type in the historical activity clusters; Select a target activity in the target activity cluster with a first evaluation indicator greater than a second threshold, and generate the target activity template based on the target activity, where the first evaluation indicator is used to measure the execution result of the target activity.

7. The marketing activity generation method according to claim 1, characterized in that Also including: In response to receiving user configuration behavior data, adjust the content of one or more process nodes according to the configuration behavior data to determine the adjusted content of the one or more process nodes; Analyze the first historical evaluation index value of the adjustment content of each process node among the one or more process nodes according to the historical activity data, and the second evaluation index value of each historical content of each process node; Select the target historical content with the second evaluation index value higher than the first historical evaluation index value among the various historical contents of each process node, and push the target historical content as an optimization suggestion to the user.

8. The marketing activity generation method according to claim 1, characterized in that The user requirement information includes the screening conditions of the target user, and the multiple process nodes include the target user node; filling the target content of the multiple process nodes into the multiple process nodes includes: Fill the screening conditions of the target user into the target user node.

9. A marketing activity generation device, characterized in that Includes: An acquisition module for acquiring user requirement information, where the user requirement information is used to at least indicate a target activity type; A target activity template determination module for determining a target activity template matching the target activity type in the historical activity data, where the target activity template includes multiple process nodes; An analysis module for analyzing the first activity data consistent with the target activity type in the historical activity data, and generating the target content of the multiple process nodes in combination with the analysis result and the user requirement information; A marketing activity generation module for filling the target content of the multiple process nodes into the multiple process nodes to generate a target marketing activity.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is run by a computer, it executes the steps of the marketing activity generation method according to any one of claims 1 to 8.

11. A computer program product, comprising a computer program / instructions, characterized in that, When the computer program / instructions are executed by a computer, the steps of the method according to claims 1 to 8 are implemented.

12. A terminal device, comprising a storage module and a processor, wherein a computer program that can run on the processor is stored on the storage module, and is characterized in that When the processor runs the computer program, it executes the steps of the marketing activity generation method according to any one of claims 1 to 8.

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