Operation method based on big data, storage medium and equipment

Abstract

The invention provides an operation method, system and device based on big data and a storage medium, and the method comprises the steps: obtaining key data of an activity scene, and the key data comprises the feedback data of a user and the attribute data of the activity scene; displaying the key data to obtain a selection result, which is determined by an operator according to the key data, of whether to continue to operate the activity scene; and when the selection result is that the activity scene continues to be operated, determining a target user, and formulating an operation strategy for operating the activity scene for the target user. According to the invention, the operation personnel can comprehensively know the content of the activity scene according to the displayed key data, the operation personnel can objectively analyze the requirements of the activity scene and formulate the operation strategy according to the target user after determining to continuously operate the activity scene, so that the problem of poor operation effect achieved by the operation strategy in the prior art is solved, and the user experience is improved. And the operation effect of the operation activity scene is improved.

Description

Technical Field

[0001] The present invention relates to the field of big data processing technology, and in particular to an operation method, system, device and storage medium based on big data. Background Art

[0002] Enterprises usually operate multiple different types of activity scenarios on their products. The demand for operational strategies formulated for activity scenarios mostly comes from the needs of the operation department. Since the factors considered in operational mining are mainly targeted at one aspect, for example, only considering the user's activity, ignoring holidays, operation objects, etc., it is not objective enough, resulting in poor operational effects achieved by the operational strategies formulated for operating activity scenarios. Summary of the invention

[0003] In view of the above problems, the present invention is proposed to provide an operation method, storage medium and device based on big data that overcome the above problems or at least partially solve the above problems, and can solve the problem of poor operation effect achieved by the operation strategy.

[0004] Specifically, the present invention provides an operation method based on big data, comprising:

[0005] Acquire key data of the activity scene, wherein the key data includes user feedback data and attribute data of the activity scene;

[0006] The key data is displayed to obtain a selection result of whether to continue operating the activity scenario determined by the operator according to the key data;

[0007] When the selection result is to continue to operate the activity scenario, a target user is determined, and an operation strategy for operating the activity scenario is formulated for the target user.

[0008] Optionally, the obtaining of key data of the activity scene includes:

[0009] Acquire initial scene data of the activity scene stored in the cloud;

[0010] The initial scene data is cleaned to obtain the key data.

[0011] Optionally, presenting the key data on a scene platform includes:

[0012] Obtaining query information input by the operator;

[0013] Based on a preset language interaction model, the key data corresponding to the query information is displayed.

[0014] Optionally, the determining of the target user includes:

[0015] Get the preset user tag;

[0016] The target user is selected from all users according to preset user tags, where the preset user tags include all active users, new users, lost users, silent users or seed users.

[0017] Optionally, the obtaining of a preset user tag includes:

[0018] Obtaining a user tag selected by the operator;

[0019] The user tag selected by the operator is used as the preset user tag.

[0020] Optionally, the formulating an operation strategy for operating the activity scene for the target user includes: formulating an initial operation strategy for the activity scene using a preset activity strategy;

[0021] Determine whether the initial operation strategy is reasonable according to preset evaluation rules;

[0022] If the initial operation strategy is reasonable, the initial operation strategy is used as the operation strategy.

[0023] Optionally, presenting the key data on a scene platform includes:

[0024] Monitor the activity data in the feedback data, and display corresponding warning information when the activity data is less than the corresponding preset threshold.

[0025] Optionally, after formulating an operation strategy for operating the activity scenario according to the target users, the operation method further includes:

[0026] Operating the activity scenario according to the operation strategy to obtain an operation result of the activity scenario;

[0027] The operation results are reviewed to obtain review data.

[0028] According to another aspect of the present invention, the present invention further provides a machine-readable storage medium having a machine executable program stored thereon, wherein the machine executable program, when executed by a processor, implements the operating method according to any one of the above items.

[0029] According to another aspect of the present invention, the present invention also provides a computer device, which includes a memory, a processor, and a machine executable program stored in the memory and running on the processor, and the processor implements any of the above-mentioned operating methods when executing the machine executable program.

[0030] In the operation method based on big data of the present invention, the operation personnel determine whether to continue to operate the activity scene according to the displayed key data, and when continuing to operate the activity scene, determine the target user, and formulate the operation strategy for the target user for the operation of the activity scene. Compared with the method of formulating operation strategy in the prior art, the present invention enables the operation personnel to fully understand the content of the activity scene according to the displayed key data, enables the operation personnel to objectively analyze the needs of the activity scene, and formulates the operation strategy for the operation of the activity scene according to the target user after determining to continue to operate the activity scene, solves the problem of poor operation effect achieved by the operation strategy in the prior art, and improves the operation effect of the operation activity scene.

[0031] Based on the following detailed description of specific embodiments of the present invention in conjunction with the accompanying drawings, those skilled in the art will become more aware of the above and other objects, advantages and features of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Hereinafter, some specific embodiments of the present invention will be described in detail in an exemplary and non-limiting manner with reference to the accompanying drawings. The same reference numerals in the accompanying drawings indicate the same or similar components or parts. It should be understood by those skilled in the art that these drawings are not necessarily drawn to scale. In the accompanying drawings:

[0033] Figure 1 is a schematic flow chart of an operation method based on big data according to an embodiment of the present invention;

[0034] Figure 2 is a schematic flow chart of obtaining key data in an operation method according to an embodiment of the present invention;

[0035] Figure 3 is a schematic flow chart of querying key data through a language interaction model according to an embodiment of the present invention;

[0036] Figure 4 is a schematic flow chart of determining a target user according to an embodiment of the present invention;

[0037] Figure 5 is a schematic diagram of target user grouping according to an embodiment of the present invention;

[0038] Figure 6 is a schematic flow chart of determining whether an initial operation strategy is reasonable according to an embodiment of the present invention;

[0039] Figure 7 is a schematic diagram of a review dashboard page according to an embodiment of the present invention;

[0040] Figure 8 is a schematic diagram of a scene platform page according to an embodiment of the present invention;

[0041] Fig. 9 is a schematic diagram of an operation dashboard page according to an embodiment of the present invention;

[0042] Fig.10 is a schematic structural diagram of a machine-readable storage medium according to an embodiment of the present invention;

[0043] Fig.11 is a schematic structural diagram of a computer device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0044] Refer to the following Figures 1 to 11 To describe the operation method, storage medium and device based on big data of the embodiment of the present invention. In the description of this embodiment, it should be understood that the terms "first" and "second" are used for descriptive purposes only, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features, that is, include one or more of the features. In the description of the present invention, the meaning of "multiple" is at least two, such as two, three, etc., unless otherwise clearly and specifically defined. When a feature "includes or contains" one or some of the features it covers, unless otherwise specifically described, this indicates that other features are not excluded and other features may be further included.

[0045] In the description of the present embodiment, the description with reference to the terms "one embodiment", "some embodiments", "illustrative embodiments", "examples", "specific examples", or "some examples" means that the specific features, structures, materials, or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0046] More and more IoT companies pay attention to developing whole-house smart solutions that fit users, and have developed a variety of activity scenarios based on weather, space, region, crowd and other dimensions, with the aim of improving the life experience of IoT appliance users and creating a smart model for whole-house intelligence. After the activity scenario is developed and launched, in order to let users understand the experience as soon as possible, the operation team needs to promote it. At present, the more common methods of operation promotion include SMS push, application activity promotion, message push, etc. The key to the implementation of these strategies is to determine the operation promotion needs, determine the target users, and determine the operation strategy; however, the current operation promotion methods generally have the following problems: ① Because the user data and scenario data of most companies are stored in different databases on different servers, data operations need to obtain data from various databases, which has low work efficiency, poor data quality, and a lot of invalid data. ② Which activity scenario to promote this month, and why the operation strategy for promoting this activity scenario is not accurate. ③ The effect of operation promotion adopts the method of manual data acquisition and review, which has low work efficiency, high labor costs, and untimely feedback, which is not conducive to the iterative optimization of operation strategies. ④ The data visibility dimension is single. ⑤ The operation strategy is to carry out operation promotion for all users, causing disturbance to non-target users. ⑥ The target user's circle classification relies on many platforms, the manual operation cycle is long, and the target user's circle classification rules are not unified. ⑦ Manual monitoring of scene activity indicators is inefficient, resulting in delays in the issuance of operation strategies.

[0047] In response to the above problems, the present invention proposes an operation method based on big data. The operation method of the present invention relies on the enterprise to have relatively complete big data storage, governance, and visualization analysis capabilities; rich activity scene development capabilities; stable user center management system; digital platform construction capabilities; and natural language interaction and machine learning development capabilities.

[0048] Figure 1 is a schematic flow chart of an operation method based on big data according to an embodiment of the present invention, such as Figure 1 As shown, an embodiment of the present invention provides an operation method based on big data, comprising the following steps:

[0049] Step S100: Acquire key data of the activity scene, wherein the key data includes user feedback data and attribute data of the activity scene.

[0050] Step S101: Display the key data on the scenario platform to obtain the selection result of whether to continue operating the activity scenario determined by the operator based on the key data; when the selection result is to continue operating the activity scenario, execute step S102.

[0051] Step S102: Determine the target user, and formulate an operation strategy for the target user for the operation activity scenario.

[0052] In this embodiment, the user's feedback data includes user personal information data, daily activity data of users in activity scenarios, monthly activity data of users, execution success rate of activity scenarios, opening conversion rate of activity scenarios, weekly retention rate of activity scenarios, active user data, new user data, seed user data, silent user data, lost user data, 24-hour activity trend, activity goal completion rate, activity user activity trend, activity conversion funnel, etc.

[0053] The attribute data of the activity scene includes the scene name, scene ID, product type, current date, launch date, number of days online, serial number, active region, user tag, rule grouping, activity name and activity period, etc.

[0054] In step S101, before the operator makes a selection, the operator will enter the operation dashboard in the scenario platform to learn the detailed information of the activity scenario. For example, how many seed users and lost users the activity scenario has; in which regions the activity scenario is active; in what time period do users often use the activity scenario within 24 hours; what is the retention rate of the activity scenario, etc. The operator can judge the user stickiness by understanding the above information in detail and decide whether it is necessary to operate the above activity scenario.

[0055] Through the setting method of this embodiment, the present invention enables the operating personnel to fully understand the content of the activity scene based on the displayed key data, enables the operating personnel to objectively analyze the needs of the activity scene, and after determining to continue operating the activity scene, formulate an operating strategy for operating the activity scene according to the target users, thereby solving the problem of poor operating effects achieved by the operating strategies in the prior art and improving the operating effects of the operating activity scene.

[0056] In some embodiments of the present invention, Figure 2 As shown, obtaining key data of the activity scene in step S100 includes the following steps:

[0057] Step S200: Acquire initial scene data of the activity scene stored in the cloud.

[0058] Step S201: Clean the initial scene data to obtain key data.

[0059] In this embodiment, the data fed back by the user using the mobile terminal is uniformly stored in the cloud database, and the ways of using the data fed back by the mobile terminal include but are not limited to voice, application, mini-program, smart screen, etc. Since the initial scene data stored in the cloud is redundant and numerous, this embodiment cleans and analyzes the initial scene data to obtain key data. For example, the repeated initial scene data is cleaned to obtain the corresponding separate key data; or the obviously abnormal data in the initial scene data is deleted.

[0060] Through the configuration of this embodiment, the initial scene data uniformly stored in the cloud is cleaned, processed and analyzed to obtain key data. Compared with the prior art of pulling data from different databases in different servers, the present invention can improve the efficiency of obtaining key data, avoid interference from invalid data, save time for operators to obtain key data, and thus improve work efficiency.

[0061] In some embodiments of the present invention, Figure 3 As shown, step S101 of displaying key data on the scene platform includes the following steps:

[0062] Step S300: obtaining query information input by an operator;

[0063] Step S301: Based on a preset language interaction model, key data corresponding to the query information is displayed on the scenario platform.

[0064] In this embodiment, the language interaction model is GPT (Generative Pre-Trained Transformer); the query information is the information that the operator interacts with the scenario platform. When the operator needs to know the key data of other dimensions, the other dimensions include time dimension, space dimension, etc.; for example, the average daily activity of users in a month. The operator can interact with the scenario platform through dialogue, and the key data that the operator wants to know will be displayed on the scenario platform.

[0065] Through the setting method of this embodiment, the present invention enables operators to interact with the scene platform to obtain key data that operators want to view in the key data, which is efficient and flexible, so that operators can fully and detailedly understand the key data of the activity scene.

[0066] In some embodiments of the present invention, Figure 4 As shown, determining the target user in step S102 includes the following steps:

[0067] Step S400: Obtain a preset user tag.

[0068] Step S401: Select a target user from all users according to preset user tags, where the preset user tags include all active users, new users, lost users, silent users or seed users.

[0069] In this embodiment, the present invention formulates user tags according to preset classification rules, and the preset classification rules are rules determined according to the user's activity, the user's registration time, the user's silent time, the user's level, etc. Figure 5 As shown, the preset user label is Figure 5 One of the user tags in the activity scene. When formulating the operation strategy of the activity scene, the operation staff will determine the target users from the new users, all active users, lost users, silent users and seed users on the target user segmentation page to formulate the operation strategy for the activity scene in a targeted manner. At the same time, select the active region and the rule segmentation information.

[0070] Through the configuration of this embodiment, the present invention can formulate an operation strategy for an activity scene in a targeted manner according to determined target users, so as to avoid disturbing irrelevant users when promoting the activity scene, thereby improving the user experience.

[0071] In some embodiments of the present invention, step S400 includes: obtaining a user tag selected by an operator; and using the user tag selected by the operator as a preset user tag.

[0072] In this embodiment, after the operator determines the user tag corresponding to the target user, the user tag selected by the operator is obtained; the user tag selected by the operator is used as the preset user tag. When the preset user tag is not a preset specific user tag, the scenario platform will connect to the preset activity strategy configuration platform to formulate an initial operation strategy.

[0073] When the preset user tag is a preset specific user tag, the scenario platform will automatically obtain the preset operation strategy corresponding to the specific user tag. For example, if the specific tag user is a new user, the preset operation strategy is that the scenario platform will use a fixed automatic promotion mechanism to promote the activity scenario. As long as the conditions of the new user are met, such as the user registration time is within seven days, the message and activities corresponding to the activity scenario will be pushed regularly.

[0074] Through the configuration of this embodiment, the present invention can select a corresponding preset operation strategy for a preset specific user tag to reduce the number of times the operation strategy is repeatedly formulated, thereby improving the operation efficiency of the activity scene.

[0075] In some embodiments of the present invention, Figure 6 As shown, formulating an operation strategy for the operation activity scenario for the target user in step S102 includes the following steps:

[0076] Step S500: adopting a preset activity strategy to formulate an initial operation strategy for the above activity scenario.

[0077] Step S501: determine whether the initial operation strategy is reasonable according to preset evaluation rules; if the initial operation strategy is reasonable, execute step S502.

[0078] Step S502: taking the initial operation strategy as the above operation strategy.

[0079] In this embodiment, the preset activity strategy is a preset activity strategy configuration platform; after determining the target user, the scenario platform will connect to the preset activity strategy configuration platform to formulate an initial operation strategy, and then judge whether the initial operation strategy is reasonable according to the preset evaluation rules, for example, whether the number of SMS pushes and message reminders to the user exceeds the corresponding preset number, whether the position of the activity scenario promotion window is reasonable, etc. When a reasonable initial activity strategy is obtained, the initial activity strategy is used as the above activity strategy, and the above activity strategy is launched on the set launch date to operate the activity scenario.

[0080] When the preset activity strategy configuration platform cannot generate the operation strategy that the operator wants, the operator will build an activity strategy configuration platform to formulate a suitable operation strategy.

[0081] Through the configuration of this embodiment, the present invention can semi-automatically formulate an initial operation strategy that fits the target user, and determine whether the initial operation strategy is reasonable, thereby reducing disturbance to the user and improving the operation efficiency of the activity scene.

[0082] In some embodiments of the present invention, in step S101: displaying key data on the scenario platform includes: monitoring activity data in the feedback data, and displaying corresponding warning information on the scenario platform when the activity data is less than a corresponding preset threshold.

[0083] In this embodiment, during the operation of the activity scene, the monitoring program set in the scene platform will monitor the user's activity data in the feedback data. When the user's activity data is less than the corresponding preset threshold, the monitoring program will display the corresponding warning information at the preset position of the scene platform so that the operator can receive the warning information in time.

[0084] Through the setting method of this embodiment, the present invention can monitor the changes in the user's activity data through the monitoring program in the scene platform, so that when the user's activity data is less than a preset threshold, the operation personnel are notified, avoiding manual monitoring of the changes in the user's activity data, thereby reducing labor costs and improving monitoring efficiency.

[0085] In some embodiments of the present invention, after step S102, the operation method further includes: operating the activity scenario according to the operation strategy to obtain the operation result of the activity scenario, and reviewing the operation result to obtain review data.

[0086] In this embodiment, after operating the above-mentioned activity scenario according to the above-mentioned operation strategy, the scenario platform will generate the operation results of the above-mentioned activity scenario into the replay data on the replay dashboard page, such as Figure 7 As shown in the figure, the review data includes the activity goal completion rate, activity user activity trend, scenario user activity trend and activity conversion funnel. Then optimize the above operation strategy based on the review data.

[0087] Through the configuration of this embodiment, the operator can understand the operation results of the activity scene through the review data, and then optimize the operation strategy according to the review data. The operator can optimize the current operation strategy according to the current review data and create richer activity scenes, thereby maintaining or improving the user's activity and improving the user experience.

[0088] In some embodiments of the present invention, when the key data is displayed on the scene platform, such as Figure 8 As shown, the key data displayed on the scenario platform includes the serial number, the scenario name of the activity scenario, the scenario ID, the daily activity data, the product type, the date, the download button, the operation dashboard button, and the interactive robot. The operator can download the detailed data of the activity scenario through the download button; through the operation dashboard button, the operator can enter the operation dashboard page to understand the operation dashboard data; and the operator can communicate with the interactive robot to understand the key data that the operator wants to see.

[0089] In some embodiments of the present invention, Fig. 9 As shown in the figure, based on the monthly and daily activity data of users in the key data, the user portrait, user retention, and active trends in the operation dashboard page are generated so that the operation staff can intuitively understand the key data of the activity scene. The dashboard includes the following capabilities: ① Layer the user data and build preset user tags. The preset user tags include active users, new users, seed users, silent users, and lost users in the user portrait. ② The key data of the activity scene is counted according to the preset calculation rules within 24 hours, including the user retention data and the data used in the activity scenes in various regions.

[0090] In some embodiments of the present invention, the present invention gathers the operational data of millions of activity scenes through the cloud, and conducts in-depth study on the development of activity scenes, the operational process of activity scenes, etc. through data mining and deep learning technology training. A scenario platform for the entire process of activity scenes is built, and the key data displayed on the scenario platform informs the operators which activity scenes should be promoted and which activity scenes are suitable for which users, thereby achieving one-stop precise operation. The scenario platform for the entire process of activity scenes built by the present invention provides a strict standardized management system, improves the accuracy of data operations, improves data operation efficiency, and reduces the waste of human resources.

[0091] In some embodiments of the present invention, the current demand for activity promotion mostly comes from the demand manually mined by the operation department and the demand of the business department. There is often a problem that the demand is not objective enough and the operation resources are wasted. Whether the activity scene of the present invention continues to operate depends on the operation personnel to make an accurate judgment after understanding the key data displayed on the scene platform, and the operation goal is clear. In addition, the present invention automates the work in the early stage of formulating the operation strategy, and emphasizes the innovation ability and solution design ability of the operation personnel in the later stage.

[0092] This embodiment also provides a machine-readable storage medium and a computer device. Fig.10 is a schematic diagram of a machine-readable storage medium 40 according to an embodiment of the present invention, Fig.11 is a schematic diagram of a computer device 50 according to one embodiment of the present invention.

[0093] The machine-readable storage medium 40 stores a machine executable program 41 thereon, and when the machine executable program 41 is executed by a processor, the operating method of any of the above-mentioned embodiments is implemented.

[0094] The computer device 50 may include a memory 520, a processor 510, and a machine executable program 41 stored in the memory 520 and running on the processor 510, and the processor 510 implements the operation method of any of the above embodiments when executing the machine executable program 41.

[0095] It should be noted that the logic and / or steps represented in the flowchart or described in other ways herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be specifically implemented in any machine-readable storage medium for use by an instruction execution method, apparatus or device (such as a computer-based method, a processor-including method or other method that can fetch instructions from an instruction execution method, apparatus or device and execute instructions), or used in combination with these instruction execution methods, apparatuses or devices.

[0096] For the description of this embodiment, the machine-readable storage medium 40 can be any device that can contain, store, communicate, propagate or transmit a program for use in an instruction execution method, device or apparatus or in conjunction with these instruction execution methods, devices or apparatuses. More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection portion (electronic device) having one or more wirings, a portable computer disk box (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and editable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium 40 can even be paper or other suitable media on which the program can be printed, because the program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting or processing in other suitable ways as necessary, and then stored in a computer memory.

[0097] It should be understood that each part of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution method.

[0098] The computer device 50 may be, for example, a server, a desktop computer, a notebook computer, a tablet computer, or a smart phone. In some examples, the computer device 50 may be a cloud computing node. The computer device 50 may be described in the general context of computer method executable instructions (such as program modules) executed by a computer method. Typically, a program module may include routines, programs, target programs, components, logic, data structures, etc. that perform specific tasks or implement specific abstract data types. The computer device 50 may be implemented in a distributed cloud computing environment where remote processing devices linked through a communication network perform tasks. In a distributed cloud computing environment, program modules may be located on a local or remote computing method storage medium including a storage device.

[0099] The computer device 50 may include a processor 510 adapted to execute stored instructions, and a memory 520 providing temporary storage space for the operation of the instructions during operation. The processor 510 may be a single-core processor, a multi-core processor, a computing cluster, or any number of other configurations. The memory 520 may include random access memory (RAM), read-only memory, flash memory, or any other suitable storage method.

[0100] The processor 510 may be connected to an I / O interface (input / output interface) suitable for connecting the computer device 50 to one or more I / O devices (input / output devices) by means of a method interconnection (e.g., PCI, PCI-Express, etc.). The I / O devices may include, for example, a keyboard and a pointing device, wherein the pointing device may include a touch pad or a touch screen, etc. The I / O devices may be built-in components of the computer device 50, or may be devices externally connected to the computing device.

[0101] Processor 510 can also be linked to a display interface suitable for connecting computer device 50 to a display device through a method interconnection. Display device can include a display screen as a built-in component of computer device 50. Display device can also include a computer monitor, a television or a projector, etc., which are externally connected to computer device 50. In addition, a network interface controller (network interface controller, NIC) can be suitable for connecting computer device 50 to a network through a method interconnection. In some embodiments, NIC can use any suitable interface or protocol (such as Internet small computer method interface, etc.) to transmit data. The network can be a cellular network, a radio network, a wide area network (WAN)), a local area network (LAN) or the Internet, etc. A remote device can be connected to a computing device through a network.

[0102] The flowchart provided in this embodiment is not intended to indicate that the operations of the method will be performed in any particular order, or that all operations of the method are included in all every case. Within the scope of the technical ideas provided by the method of this embodiment, additional changes can be made to the above method.

[0103] At this point, those skilled in the art should recognize that, although multiple exemplary embodiments of the present invention have been shown and described in detail herein, many other variations or modifications that conform to the principles of the present invention can still be directly determined or derived based on the content disclosed in the present invention without departing from the spirit and scope of the present invention. Therefore, the scope of the present invention should be understood and recognized as covering all these other variations or modifications.

Claims

1. An operation method based on big data, characterized in that: include: Acquiring key data of the activity scene, wherein the key data includes user feedback data and attribute data of the activity scene; The key data is displayed to obtain a selection result of whether to continue operating the activity scenario determined by the operator based on the key data; When the selection result is to continue operating the activity scenario, target users are determined, and an operation strategy for operating the activity scenario is formulated for the target users.

2. The operation method according to claim 1, characterized in that: The key data of the activity scene is obtained, including: Obtaining initial scene data of the activity scene stored in the cloud; The initial scene data is cleaned to obtain the key data.

3. The operation method according to claim 1, characterized in that: The presenting of the key data on the scene platform includes: Obtaining query information input by the operator; Based on a preset language interaction model, the key data corresponding to the query information is displayed.

4. The operating method according to claim 1, characterized in that: The determining of target users includes: Get the preset user tag; The target user is selected from all users according to preset user tags, where the preset user tags include all active users, new users, lost users, silent users or seed users.

5. The operating method according to claim 4, characterized in that: The step of obtaining the preset user tag includes: Obtaining a user tag selected by the operator; The user tag selected by the operator is used as the preset user tag.

6. The operating method according to claim 1, characterized in that: The step of formulating an operation strategy for operating the activity scenario for the target user includes: Formulate an initial operational strategy for the activity scenario using a preset activity strategy; Determine whether the initial operating strategy is reasonable based on preset evaluation rules; If the initial operation strategy is reasonable, the initial operation strategy is used as the operation strategy.

7. The operating method according to claim 1, characterized in that: The presenting of the key data on the scene platform includes: Monitor activity data in the feedback data, and display corresponding warning information when the activity data is less than a corresponding preset threshold.

8. The operating method according to claim 1, characterized in that: After formulating an operation strategy for operating the activity scenario according to the target users, the method further includes: Operating the activity scenario according to the operation strategy to obtain an operation result of the activity scenario; The operation results are reviewed to obtain review data.

9. A machine-readable storage medium having a machine-executable program stored thereon, wherein the machine-executable program, when executed by a processor, implements the operating method according to any one of claims 1 to 8.

10. A computer device comprising a memory, a processor, and a machine executable program stored in the memory and running on the processor, wherein the processor implements the operating method according to any one of claims 1 to 8 when executing the machine executable program.

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