Operation management method, device and computer storage medium

Abstract

The embodiments of the present application provide an operation management method, device and computer storage medium. The method includes: obtaining at least one merchant operation parameter corresponding to the merchant; determining an associated parameter for analyzing and processing the at least one merchant operation parameter; determining at least one target negative indicator corresponding to the merchant based on the associated parameter and at least one merchant operation parameter; and performing operation management on the merchant based on the target negative indicator. The technical solution provided by the present application determines the target negative indicator by associating the parameter and at least one merchant operation parameter, can quickly and accurately determine the indicator that has a negative impact on the merchant's operation, can accurately identify the problems existing in the merchant's operation, and then perform operation management on the merchant based on the target negative indicator, thereby not only improving the efficiency of the merchant's operation management, but also being able to manage the core operation problems existing in the merchant in a targeted manner, thereby reducing the cost of the merchant's operation management.

Description

Technical Field

[0001] The present application relates to the field of data processing technology, and in particular to an operation management method, device, and computer storage medium. Background Art

[0002] With the rapid development of e-commerce platforms, the number of merchants on the e-commerce platforms is increasing. For merchants on the e-commerce platforms, the business conditions of the merchants have an important impact on their retention. Therefore, improving the merchant performance has a significant effect on the growth of the number of merchants on the e-commerce platforms.

[0003] For e-commerce platforms, all operational data of all merchants are accumulated on the platforms. However, due to the complexity of data types and application scenarios and the multitude of functions, if merchants want to improve their operational results, they need to conduct detailed analysis and processing of platform data based on experience. In this way, merchants need to recruit experienced operators and third-party agents to operate stores and analyze data, which greatly increases operating costs. Summary of the Invention

[0004] The embodiments of the present application provide an operation management method, device, and computer storage medium, which can reduce the operation and management costs of a store.

[0005] In a first aspect, an embodiment of the present application provides an operation management method, including:

[0006] Obtain at least one merchant operation parameter corresponding to the merchant;

[0007] Determining associated parameters for analyzing and processing the at least one merchant operation parameter;

[0008] Determining at least one target negative indicator corresponding to the merchant based on the association parameter and the at least one merchant operation parameter, wherein the target negative indicator can have a negative impact on the merchant operation;

[0009] The merchant is operated and managed based on the target negative indicator.

[0010] In a second aspect, an embodiment of the present application provides an operation management device, including:

[0011] An acquisition module, configured to acquire at least one merchant operation parameter corresponding to the merchant;

[0012] A first determining module, configured to determine associated parameters for analyzing and processing the at least one merchant operation parameter;

[0013] a second determining module, configured to determine at least one target negative indicator corresponding to the merchant based on the association parameter and the at least one merchant operation parameter, wherein the target negative indicator can have a negative impact on the merchant operation;

[0014] A management module is used to perform operational management on the merchant based on the target negative indicator.

[0015] In a third aspect, an embodiment of the present application provides an electronic device comprising: a memory and a processor; wherein the memory is used to store one or more computer instructions, wherein the one or more computer instructions, when executed by the processor, implement the operation management method shown in the first aspect above.

[0016] In a fourth aspect, an embodiment of the present invention provides a computer storage medium for storing a computer program, wherein the computer program enables a computer to implement the operation management method shown in the first aspect when executed.

[0017] In a fifth aspect, an embodiment of the present invention provides a computer program product, comprising: a computer program, which, when executed by a processor of an electronic device, enables the processor to execute the steps in the operation management method shown in the first aspect above.

[0018] The technical solution provided by the embodiment of the present application obtains at least one merchant operation parameter corresponding to the merchant, determines the associated parameter for analyzing and processing the at least one merchant operation parameter, and determines at least one target negative indicator corresponding to the merchant based on the associated parameter and the at least one merchant operation parameter, and then performs operation management on the merchant based on the target negative indicator. In the above scheme, since the target negative indicator is determined based on the associated parameter and at least one merchant operation parameter, it is only necessary to obtain the associated parameter and at least one merchant operation parameter to quickly and accurately determine the indicator that has a negative impact on the merchant's operation. Therefore, it is no longer necessary for professional and experienced personnel to analyze and process the merchant's operation data, and the target negative indicator can also be quickly and accurately determined, further improving the practicality of the technical solution. Moreover, after obtaining the target negative indicator, the merchant can also be operated and managed based on the target negative indicator, effectively achieving targeted management of the merchant's existing operational problems, which can not only improve the efficiency of merchant operation management, but also reduce merchant operation management costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, a brief introduction will be given below to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0020] Figure 1 This is a schematic diagram of an application scenario of an operation management method according to an exemplary embodiment of the present application;

[0021] Figure 2 A flowchart of an operation management method according to an exemplary embodiment of the present application is provided;

[0022] Figure 3 This is a schematic diagram of an application scenario of an operation management method according to an exemplary embodiment of the present application;

[0023] Figure 4 This is a schematic diagram of an application scenario of an operation management method according to an exemplary embodiment of the present application;

[0024] Figure 5 A schematic diagram of a process for determining associated parameters for analyzing and processing at least one merchant operation parameter provided in an embodiment of the present application;

[0025] Figure 6 A flowchart of another operation management method according to an exemplary embodiment of the present application is provided;

[0026] Figure 7 A schematic diagram of a process for stratifying all merchants in the same industry to obtain at least two merchant layers provided in an embodiment of the present application;

[0027] Figure 8 A flowchart for determining at least one target negative indicator corresponding to a merchant is provided for an embodiment of the present application;

[0028] Figure 9 A flowchart of another operation management method provided in an embodiment of the present application;

[0029] Figure 10 A schematic diagram of the training process of a merchant prediction renewal probability model is provided for an embodiment of the present application;

[0030] Figure 11 A schematic diagram of a process for determining association parameters based on layer indicator parameters of an associated merchant layer is provided for an embodiment of the present application;

[0031] Figure 12 A flowchart of a method for determining a merchant's corresponding operational problems and adjustment solutions based on a merchant problem diagnosis model is provided for an embodiment of the present application;

[0032] Figure 13 A hierarchical causal relationship diagram of merchant operation parameters is provided for the embodiment of this application;

[0033] Figure 14 A schematic diagram of the structure of an operation management device provided in an embodiment of the present application;

[0034] Figure 15 for Figure 14 A structural diagram of the electronic equipment corresponding to the operation management device shown. DETAILED DESCRIPTION

[0035] To make the purpose, technical solutions, and advantages of the embodiments of this application more clear, the technical solutions in the embodiments of this application will be clearly and completely described below in conjunction with the drawings in the embodiments of this application. Obviously, the described embodiments are part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0036] The terms used in the examples of this application are for the purpose of describing specific embodiments only and are not intended to limit this application. The singular forms "a," "an," and "the" used in the examples of this application and the appended claims are also intended to include plural forms, unless the context clearly indicates otherwise. "A plurality of" generally includes at least two, but does not exclude the inclusion of at least one.

[0037] It should be understood that the term "and / or" as used herein is merely a description of the relationship between associated objects, indicating that three possible relationships exist. For example, "A and / or B" can represent: A exists alone, A and B exist simultaneously, or B exists alone. Furthermore, the character " / " in this document generally indicates that the associated objects are in an "or" relationship.

[0038] As used herein, the words "if" and "if" may be interpreted as "at the time of" or "when" or "in response to determining" or "in response to detecting," depending on the context. Similarly, the phrases "if it is determined" or "if (stated condition or event) is detected" may be interpreted as "when it is determined" or "in response to the determination" or "when detecting (stated condition or event)" or "in response to detecting (stated condition or event)," depending on the context.

[0039] It should also be noted that the terms "include," "comprises," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a product or system comprising a series of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such product or system. In the absence of further limitations, an element defined by the phrase "comprises a..." does not exclude the presence of other identical elements in the product or system comprising the element.

[0040] In addition, the step sequence in the following method embodiments is only an example and not a strict limitation.

[0041] Definition of terms:

[0042] Merchant Lifetime Value (LTV): used to identify the value that a merchant will create for the platform.

[0043] Renewal and termination: Renewal means that the paying merchant renews the contract upon expiration, and termination means that the paying merchant does not renew the contract upon expiration.

[0044] LightGBM: An open source machine learning tool based on gradient boosting decision trees.

[0045] shap value: SHapley Additive exPlanations, an open source algorithm for explaining the contribution of each indicator to the results in the algorithm model.

[0046] Customer relationship: the emotional connection between product and service providers and their customers.

[0047] To facilitate those skilled in the art to understand the technical solutions provided in the embodiments of the present application, the following is a brief description of the relevant technologies:

[0048] With the rapid development of e-commerce platforms, the number of merchants on the e-commerce platforms is increasing, and many business operations problems will also arise. For merchants on the e-commerce platforms, the business conditions of the merchants have an important impact on their retention. Therefore, improving the business performance of merchants has a significant effect on the growth of the number of merchants on the e-commerce platforms.

[0049] For e-commerce platforms, all operational data of all merchants are accumulated on the platforms. However, due to the complexity of data types and application scenarios and the multitude of functions, when merchants encounter problems with their operating results and want to improve their operating results, they need to conduct detailed analysis and processing of platform data based on experience. In this way, merchants need to recruit experienced operators and third-party agents to operate stores and analyze data, which greatly increases operating costs.

[0050] In order to solve the above technical problems, the prior art provides a method for digitally diagnosing merchant problems, the specific implementation process of which may include: obtaining all merchant operation data corresponding to the merchant, determining the rules for analyzing and processing the operation data of each merchant, and analyzing and processing each operation data based on the rules corresponding to each operation data to identify the operation problems corresponding to each operation data.

[0051] However, the above processing process requires analysis and processing of all merchant operation data based on the rules corresponding to each operation data, that is, one type of merchant operation data corresponds to one analysis and processing rule, and each type of merchant operation data requires an analysis and processing operation. This not only increases the amount of data processing, but also increases the steps of data processing, making the data processing process more complicated, which is not conducive to improving the efficiency of data processing; at the same time, due to the lack of core indicators, a large number of operational problems will also be generated, resulting in merchants having no optimization focus, making the actual investment very high, and increasing the operating costs of merchants.

[0052] In order to solve the above technical problems, this embodiment provides an operation management method, device and computer storage medium, wherein the execution subject of the method can be an operation management device, which is communicatively connected to the request end / client, and the operation management device is ... Figure 1 As shown:

[0053] The client / requester can be any computing device with a certain data transmission capability. In specific implementations, the client / requester can be a mobile phone, a personal computer (PC), a tablet computer, a setting application, etc. In addition, the basic structure of the client may include: at least one processor. The number of processors depends on the configuration and type of the client. The client may also include memory, which can be volatile, such as RAM, or non-volatile, such as read-only memory (ROM), flash memory, etc., or it may include both types. The memory typically stores an operating system (OS), one or more application programs, and may also store program data, etc. In addition to the processing unit and memory, the client also includes some basic configurations, such as a network card chip, an I / O bus, a display component, and some peripheral devices. Optionally, some peripheral devices may include, for example, a keyboard, a mouse, an input pen, a printer, etc. Other peripheral devices are well known in the art and are not described in detail here.

[0054] An operations management device refers to equipment that can provide operations management services within a network virtual environment, typically a device that utilizes the network for information planning and operations management operations. Physically, an operations management device can be any device capable of providing computing services, responding to operations management service requests, and performing operations management services based on those requests. Examples include cluster servers, conventional servers, cloud servers, cloud hosts, and virtual centers. The components of an operations management device primarily include a processor, hard drive, memory, and system bus, similar to a general-purpose computer architecture.

[0055] In the above embodiment, the client / requester can establish a network connection with the operation and management device, and the network connection can be a wireless or wired network connection. If the client / requester is connected to the operation and management device for communication, the network standard of the mobile network can be any one of 2G (GSM), 2.5G (GPRS), 3G (WCDMA, TD-SCDMA, CDMA2000, UTMS), 4G (LTE), 4G+ (LTE+), WiMax, 5G, 6G, etc.

[0056] In an embodiment of the present application, the client / requesting end can obtain an operation management request corresponding to a merchant, and the operation management request can include the identity identifier of the merchant to be managed. Specifically, this embodiment does not limit the specific implementation method for the requesting end to obtain the operation management request corresponding to the merchant. In some instances, the requesting end is configured with an interactive interface, and the execution operation input by the user in the interactive interface is obtained. Based on the execution operation, the operation management request corresponding to the merchant can be obtained. In other instances, the operation management request corresponding to the merchant can be stored in a third device, and the third device is in communication with the requesting end, and the operation management request corresponding to the merchant is actively or passively obtained through the third device. After obtaining the operation management request, the operation management request can be sent to the operation management device, so that the operation management device can perform operation management operations on the merchant based on the operation management request.

[0057] The operation management device is used to obtain the operation management request sent by the requesting end, and then obtain at least one merchant operation parameter corresponding to the merchant based on the operation management request. Specifically, at least one merchant operation parameter corresponding to the merchant can be obtained based on the identity identifier of the merchant to be managed included in the operation management request, wherein the merchant operation parameter may include at least one of the following: the merchant's product parameters, traffic parameters, inquiry parameters, transaction parameters, promotion parameters, etc.

[0058] It should be noted that the operation management device can not only passively perform corresponding operation management operations based on operation management requests, but also actively perform operation management operations, for example: actively obtaining at least one merchant operation parameter corresponding to the merchant at regular intervals according to a preset detection cycle, or actively obtaining at least one merchant operation parameter corresponding to the merchant in real time.

[0059] After obtaining at least one merchant operation parameter, the associated parameters for analyzing and processing the at least one merchant operation parameter can be determined; and based on the associated parameters and the at least one merchant operation parameter, at least one target negative indicator corresponding to the merchant can be determined. After obtaining the target negative indicator, the merchant can be operated and managed based on the target negative indicator.

[0060] The technical solution provided in this embodiment obtains at least one merchant operation parameter corresponding to the merchant, determines the associated parameters for analyzing and processing the at least one merchant operation parameter, and then determines at least one target negative indicator corresponding to the merchant based on the associated parameters and at least one merchant operation parameter. Finally, the merchant is operated and managed according to the target negative indicator, effectively realizing the ability to automatically analyze and process the core operation indicator data corresponding to the merchant. This not only makes the data processing process simpler and accurately identifies problems in the merchant operation, but also can manage the merchant operation based on the target negative indicator, that is, it realizes targeted management of the merchant's operational problems, thereby effectively improving operational efficiency, while helping to reduce the cost of merchant operation management, further improving the practicality of the method, and facilitating market promotion and application.

[0061] Some embodiments of the present invention are described in detail below with reference to the accompanying drawings. The following embodiments and features thereof may be combined with one another unless they conflict with each other. Furthermore, the sequence of steps in the following method embodiments is provided for illustrative purposes only and is not intended to be a strict limitation.

[0062] Figure 2 This is a flow chart of an operation management method according to an exemplary embodiment of the present application; Figure 2 As shown, this embodiment provides an operation management method, the execution subject of the method may be an operation management device. It is understandable that the operation management device may be implemented as software or a combination of software and hardware. Specifically, the operation management method may include:

[0063] Step S201: Acquire at least one merchant operation parameter corresponding to the merchant.

[0064] Step S202: Determine associated parameters for analyzing and processing at least one merchant operation parameter.

[0065] Step S203: Based on the association parameter and at least one merchant operation parameter, determine at least one target negative indicator corresponding to the merchant, where the target negative indicator can have a negative impact on the merchant operation.

[0066] Step S204: Performing operations management on the merchant based on the target negative indicator.

[0067] The following is a detailed description of each of the above steps:

[0068] Step S201: Acquire at least one merchant operation parameter corresponding to the merchant.

[0069] Among them, merchant operation parameters refer to parameters that can reflect the merchant's operating status, which can specifically include at least one of the following: merchant product parameters (e.g., product pricing, product sales volume, product storage capacity), traffic parameters, inquiry parameters, transaction parameters (e.g., product transaction unit price, number of transactions, total product transaction price, etc.), promotion parameters, etc. Of course, merchant operation parameters are not limited to the parameter types described above. Those skilled in the art can also select merchant operation parameters of other parameter types based on specific application requirements and design requirements, which will not be elaborated here.

[0070] In addition, since there are many types of merchant operation parameters that can affect the operation effect of goods, and different merchant operation parameters can have different degrees of influence on merchant operations, in order to highlight that different merchant operation parameters can have different degrees of influence on merchant operations, at least one merchant operation parameter corresponding to the merchant can be configured to include: core indicator operation parameters and general indicator operation parameters; wherein, core indicator operation parameters refer to operation parameters that play a decisive role in the merchant's operating status, which can directly affect the merchant's operating status; and general indicator operation parameters refer to operation parameters that play an auxiliary role in the merchant's operating status. In specific implementation, in order to reduce the amount of data processing, at least one merchant operation parameter corresponding to the merchant can also only include core indicator operation parameters, which is not specifically limited in the embodiments of the present invention.

[0071] It should be noted that the core indicator operating parameters and the common indicator operating parameters can be pre-configured parameters. For example, the pre-configured core indicator operating parameters may include: average order value, business opportunity conversion rate, number of exposures, click-through rate, and other parameters. The pre-configured common indicator operating parameters may include the proportion of video products among exposed products, the proportion of misplaced categories, the proportion of high-quality products among exposed products, etc. Alternatively, the core indicator operating parameters and the common indicator voice parameters can be determined based on the degree of parameter influence. In this case, after obtaining at least one merchant operating parameter, the degree of influence that each merchant operating parameter can have on the merchant's operating results can be determined. The degree of influence can be obtained through analysis and processing using a preset algorithm or a preset machine learning model. When the degree of influence is greater than or equal to a preset threshold, the merchant operating parameter can be determined as a core indicator operating parameter; when the degree of influence is less than the preset threshold, the merchant operating parameter can be determined as a common indicator operating parameter, thereby effectively achieving the determination operation of the core indicator operating parameters and the common indicator operating parameters.

[0072] In addition, this embodiment does not limit the specific implementation method for obtaining at least one merchant operation parameter corresponding to the merchant. Those skilled in the art can set it according to specific application requirements. For example, the merchant operation parameters corresponding to the merchant can be pre-configured and stored in a preset area. The operation management device can obtain at least one merchant operation parameter corresponding to the merchant by accessing the preset area. Alternatively, the merchant operation parameter can be generated based on the user's execution operation. In this case, the operation management device can be configured with an interactive interface. Further, obtaining at least one merchant operation parameter corresponding to the merchant may include: displaying an interactive interface for implementing human-computer interaction operations, obtaining the execution operation entered by the user in the interactive interface, and obtaining at least one merchant operation parameter corresponding to the merchant based on the execution operation.

[0073] Of course, those skilled in the art may also adopt other methods to obtain at least one merchant operation parameter corresponding to the merchant, as long as the accuracy and reliability of obtaining the at least one merchant operation parameter can be guaranteed, which will not be elaborated here.

[0074] In specific applications, in addition to the merchant operation parameters that can directly affect the merchant's operation results or reflect the merchant's operation results, there are other parameters that can affect or reflect the merchant's operation results, such as: the industry in which the merchant is located, etc. Therefore, in order to improve the quality and efficiency of the operation management of the merchant, in the process of operation management of the merchant, in addition to obtaining at least one merchant operation parameter corresponding to the merchant, the merchant's basic information and the merchant's corresponding industry data can also be obtained based on the application scenario or design requirements. The merchant's basic information may include at least one of the following: the merchant's scale information, the merchant's industry, and the merchant's corresponding industry data may include at least one of the following: the total number of merchants in the industry, the average transaction volume of merchants in the industry, the transaction price of products traded among merchants in the industry, etc. By obtaining the merchant's basic information and the merchant's corresponding industry data, combined with at least one merchant operation parameter corresponding to the merchant, it is possible to more effectively analyze and process the merchant's operation status, so as to obtain a more targeted operation management strategy to solve the merchant's corresponding operation problems.

[0075] Step S202: Determine associated parameters for analyzing and processing at least one merchant operation parameter.

[0076] The correlation parameters may be pre-configured parameters used to analyze and process merchant operational parameters, which, to a certain extent, can reflect the operational results or operational indicators that the merchant expects or should achieve. The correlation parameters may be determined based on the experience of professionals or data from the merchant's industry. For example, the average or median value of the merchant's industry may be used to determine the correlation parameters.

[0077] In other instances, the association parameter may refer to a layer indicator parameter of an associated merchant layer corresponding to a merchant. In this case, the association parameter may specifically be a statistical result of the indicator parameters of at least some merchants in the associated merchant layer. For example, the association parameter may specifically include at least one of the following: the median, mean, standard deviation, etc., of the merchant's operating parameters at the associated merchant layer. Different types of merchant operating parameters may correspond to different association parameters.

[0078] After obtaining at least one merchant operating parameter corresponding to a merchant, in order to understand the merchant's operating performance, associated parameters for analyzing and processing the at least one merchant operating parameter can be further determined. Specifically, layer indicator parameters corresponding to the associated merchant layer can be obtained, and then the layer indicator parameters can be directly determined as associated parameters for analyzing and processing the at least one merchant operating parameter.

[0079] Step S203: Based on the association parameter and at least one merchant operation parameter, determine at least one target negative indicator corresponding to the merchant, where the target negative indicator can have a negative impact on the merchant operation.

[0080] For merchants, there are often various indicator parameters that can affect the merchant's operating results. The above indicator parameters can be divided into positive indicator parameters and negative indicator parameters according to the degree of influence on the merchant's operating results. Among them, positive indicator parameters can have a positive impact on merchant operations, such as: increasing the merchant's traffic, increasing the merchant's transaction volume, etc.; while negative indicator parameters can have a negative impact on merchant operations, such as: reducing the merchant's inquiry volume and the merchant's transaction volume, etc.

[0081] When operating and managing a merchant, in order to ensure and improve the merchant's operational effectiveness, since positive indicator parameters can have a positive impact on merchant operations, while negative indicator parameters can have a negative impact on merchant operations, adjustments to the relevant operations of the positive indicator parameters can be ignored, and only adjustments to the merchant operations can be made to the negative indicator parameters. Specifically, after obtaining at least one merchant operation parameter and associated parameters, the associated parameters and the at least one merchant operation parameter can be analyzed and processed to determine at least one target negative indicator corresponding to the merchant. The target negative indicator refers to an indicator parameter that can have a negative impact on the merchant's operations.

[0082] In addition, this embodiment does not limit the implementation method of determining at least one target negative indicator corresponding to a merchant based on the associated parameters and at least one merchant operation parameter. Those skilled in the art can make settings according to specific application scenarios or application requirements. For example: a machine learning model for processing the associated parameters and at least one merchant operation parameter is pre-configured. After obtaining the associated parameters and at least one merchant operation parameter, the associated parameters and at least one merchant operation parameter can be input into the machine learning model, and then at least one target negative indicator output by the machine learning model can be obtained.

[0083] Step S204: Performing operations management on the merchant based on the target negative indicator.

[0084] Since target negative indicators can have a negative impact on merchant operations, after determining at least one target negative indicator corresponding to a merchant, the merchant's operations can be managed using this target negative indicator. For example, if the target negative indicator is the number of visitors to the merchant, the merchant's exposure can be increased to increase the number of visitors; if the target negative indicator is the corresponding click-through rate of the merchant, the proportion of high-quality products in the exposed products can be increased, while the proportion of misplaced categories can be reduced, etc. This allows for more targeted adjustments to the merchant's operating conditions to achieve the goal of improving the merchant's operating results. This not only improves operational management efficiency, but also reduces merchant operational management costs.

[0085] The operation management method provided in the embodiment of the present application obtains at least one merchant operation parameter corresponding to the merchant, determines the associated parameter for analyzing and processing the at least one merchant operation parameter, and determines at least one target negative indicator corresponding to the merchant based on the associated parameter and the at least one merchant operation parameter, and then performs operation management on the merchant based on the target negative indicator. In the above scheme, since the target negative indicator is determined based on the associated parameter and at least one merchant operation parameter, it is only necessary to obtain the associated parameter and at least one merchant operation parameter to quickly and accurately determine the indicator that has a negative impact on the merchant's operation. Therefore, it is no longer necessary for professional and experienced personnel to analyze and process the merchant's operation data, and the target negative indicator can also be quickly and accurately determined, further improving the practicality of the technical solution. Moreover, after obtaining the target negative indicator, the merchant can also be operated and managed based on the target negative indicator, effectively achieving targeted management of the merchant's existing operational problems, which can not only improve the efficiency of the merchant's operation management, but also reduce the merchant's operation management costs.

[0086] It should be noted that the above operation management method is not only applicable to e-commerce application scenarios, but also to many application scenarios, such as video playback, article publishing, etc. Figure 3 and attached Figure 4 An exemplary description is given.

[0087] Application Example 1, refer to the attached Figure 3 As shown, this embodiment provides an operation management method that can improve the operating effect of a video playback website. Specifically, the execution subject of the operation management method is an operation management device, which can be communicatively connected to a video playback device to promptly identify problems existing in the video playback website (corresponding to a target negative indicator) and perform operation management of the video playback website based on the identified problems. Specifically, the method includes:

[0088] Step 1: Obtain at least one operation parameter corresponding to the video playback website.

[0089] In specific applications, at least one operating parameter corresponding to the video playback website may include at least one of the following parameters: advertising volume, advertising duration, video layout, number of videos, promotion volume, etc. It can be understood that there are many parameters that can affect the operating effect of the video playback website. In order to improve the quality and efficiency of data processing, several operating parameters that have a major impact on the operating effect of the video playback website can be obtained based on experience, and then the operating status of the video playback website can be analyzed through the above-mentioned operating parameters.

[0090] Step 2: Determine associated parameters for analyzing at least one operation parameter.

[0091] After obtaining at least one operating parameter, it is necessary to process the at least one operating parameter. In order to accurately identify whether there is a problem with at least one operating parameter corresponding to the video playback website, it is necessary to determine the associated parameters used to analyze and process the at least one operating parameter. The associated parameters here can be the median, mean, and standard deviation corresponding to the operating effect expected to be achieved by the video playback website.

[0092] Step 3: Based on the correlation parameter and at least one operation parameter, determine at least one target negative indicator corresponding to the video playback website, where the target negative indicator can have a negative impact on the operation of the video playback website.

[0093] Step 4: Operate and manage the video playback website based on the target negative indicators.

[0094] After determining the target negative indicators that have a negative impact on the operation of the video playback website, the operational parameters of the video playback website with problems can be determined, so that the operational problems corresponding to the video playback website can be identified, and then the video playback website can be operated and managed based on the operational problems, effectively achieving the ability to make targeted adjustments or management of the operational problems existing in the video playback website, which can not only improve the operational management efficiency, but also reduce the operational management costs of the video playback website.

[0095] The operation management method provided by this application embodiment analyzes and processes at least one operation parameter corresponding to the video playback website to determine the target negative indicator that affects the operation effect of the video playback website, and then manages the video playback website based on the target negative indicator to accurately improve the operation effect of the video playback website. At the same time, it can also improve the operation management efficiency and reduce the operation management costs of merchants.

[0096] Application Example 2, refer to the attached Figure 4As shown, this embodiment provides an operation management method that can improve the operating effect of a novel reading website. Specifically, the execution subject of the operation management method is an operation management device, which can communicate with the novel reading device to promptly identify problems existing in the novel reading website (corresponding to the target negative indicator) and perform operation management of the novel reading website based on the identified problems. Specifically, the method includes:

[0097] Step 1: Obtain at least one operation parameter corresponding to the novel reading website.

[0098] In specific applications, at least one operating parameter corresponding to the novel reading website may include at least one of the following parameters: advertising volume, advertising duration, page layout, number of novels, promotion volume, etc. It can be understood that there are many parameters that can affect the operating effect of the novel reading website. In order to improve the quality and efficiency of data processing, several operating parameters that have a major impact on the operating effect of the novel reading website can be obtained based on experience, and then the operating status of the novel reading website can be analyzed through the above-mentioned operating parameters.

[0099] Step 2: Determine associated parameters for analyzing at least one operation parameter.

[0100] After obtaining at least one operating parameter, it is necessary to process the at least one operating parameter. In order to accurately identify whether there is a problem with at least one operating parameter corresponding to the novel reading website, it is necessary to determine the associated parameters used to analyze and process the at least one operating parameter. The associated parameters here can be the median, mean, and standard deviation corresponding to the operating effect expected to be achieved by the novel reading website.

[0101] Step 3: Based on the correlation parameter and at least one operation parameter, determine at least one target negative indicator corresponding to the novel reading website, where the target negative indicator can have a negative impact on the operation of the novel reading website.

[0102] Step 4: Operate and manage the novel reading website based on the target negative indicators.

[0103] After determining the target negative indicators that have a negative impact on the operation of the novel reading website, the operational parameters of the novel reading website with problems can be determined, so that the corresponding operational problems of the novel reading website can be identified, and then the operation and management of the novel reading website can be carried out based on the operational problems, effectively achieving the targeted adjustment or management of the operational problems of the novel reading website, which can not only improve the operational management efficiency, but also reduce the operational management costs of the novel reading website.

[0104] The operation management method provided by this application embodiment analyzes and processes at least one operation parameter corresponding to the novel reading website to determine the target negative indicator that affects the operation effect of the novel reading website, and then manages the novel reading website based on the target negative indicator to accurately improve the operation effect of the novel reading website. At the same time, it can also improve the operation management efficiency and reduce the operation management costs of merchants.

[0105] Figure 5 A flow chart of determining associated parameters for analyzing and processing at least one merchant operation parameter provided in an embodiment of the present application; based on the above embodiment, refer to the attached Figure 5 As shown, this embodiment provides an implementation method for determining associated parameters based on the associated merchant layer and the layer indicator parameters corresponding to the associated merchant layer. Specifically, in this embodiment, determining the associated parameters for analyzing and processing at least one merchant operation parameter may include:

[0106] Step S501: Acquire the associated merchant layer corresponding to the merchant.

[0107] After obtaining at least one merchant operating parameter corresponding to a merchant, in order to further analyze the merchant operating parameters, it is necessary to obtain the associated merchant layer corresponding to the merchant. A merchant layer refers to a hierarchical structure obtained by layering all merchants in the same industry. Different merchant layers may correspond to different operating effects, may include different merchants, and may include the same or different numbers of merchants in different merchant layers.

[0108] The associated merchant layer may refer to a merchant layer that has an associated relationship with a merchant. In some instances, it may be an upper merchant layer or a current merchant layer. The operating effect of the upper merchant layer may be higher than that of the current merchant layer.

[0109] Specifically, when the associated merchant layer is an upper merchant layer, obtaining the associated merchant layer corresponding to the merchant in this embodiment may include: obtaining the upper merchant layer corresponding to the merchant, the lifetime value of the merchants in the upper merchant layer being greater than the lifetime value of the merchant, and determining the upper merchant layer as the associated merchant layer. Because the lifetime value of the merchants in the upper merchant layer is greater than the lifetime value of the merchant, determining the upper merchant layer as the associated merchant layer can improve the merchant's operating performance standards.

[0110] For example, all merchants in the industry to which the merchant belongs are stratified into three layers in total. The merchant layer corresponding to this merchant is the second layer, and the merchant life cycle value in the first layer of merchant layers is greater than the merchant life cycle value. Then the merchant layer corresponding to the first layer can be used as the associated merchant layer corresponding to the merchant.

[0111] It should be noted that if the upper merchant layer corresponding to the merchant cannot be obtained, the merchant's current merchant layer can be directly determined as the associated merchant layer. In other words, the merchant's current merchant layer is already the highest layer, and the current merchant layer is directly determined as the associated merchant layer corresponding to the merchant. For example, merchants in the merchant's industry are stratified into two layers, and the lifetime value of merchants in the first merchant layer is greater than the lifetime value of merchants in the second layer. When the merchant is in the first merchant layer, the first merchant layer is directly determined as the associated merchant layer corresponding to the merchant.

[0112] In another optional embodiment, the associated merchant layer may be the current merchant layer. In this case, obtaining the associated merchant layer corresponding to the merchant may include obtaining the current merchant layer corresponding to the merchant and determining the current merchant layer as the associated merchant layer. When obtaining the associated merchant layer corresponding to the merchant, the current merchant layer in which the merchant is located may also be directly used as the associated merchant layer. In this case, the layer indicator parameters corresponding to the associated merchant layer can at least maintain the merchant's operating performance.

[0113] Step S502: Determine the layer indicator parameters corresponding to the associated merchant layer.

[0114] After obtaining the associated merchant layer corresponding to the merchant, the merchant operation parameters of at least some of the merchants in the associated merchant layer can be analyzed and processed to determine the layer indicator parameters corresponding to the associated merchant layer. In some instances, the indicator statistics corresponding to all merchants in the associated merchant layer can be counted, and the indicator statistics can be determined as the layer indicator parameters. In this case, the layer indicator parameters correspond to all merchants in the associated merchant layer. In other instances, the top N merchants in the associated merchant layer (i.e., merchants with relatively good operation results) can be determined based on the operation results of each merchant, and the layer indicator parameters can be determined based on the merchant operation parameters of the top N merchants. In this case, the layer indicator parameters correspond to some merchants in the associated merchant layer.

[0115] In an optional embodiment, determining the layer indicator parameter corresponding to the associated merchant layer may include:

[0116] Step S5021: Determine the median, average, and standard deviation of the indicators corresponding to all merchants in the associated merchant layer.

[0117] Step S5022: Determine the index median, index mean, and index standard deviation as layer index parameters.

[0118] After determining the associated merchant layer, determine the indicator median, indicator average and indicator standard deviation corresponding to at least some of the merchants in the associated merchant layer, and determine the indicator median, indicator average and indicator standard deviation as the layer indicator parameters. The layer indicator parameters can identify the average operating level or average operating effect of at least some of the merchants in the associated merchant layer to a certain extent.

[0119] Step S503: Determine the layer indicator parameters as associated parameters, and the associated parameters are used to maintain or improve the merchant's operating results.

[0120] After determining the layer indicator parameters corresponding to the associated merchant layer, the layer indicator parameters are determined as the associated parameters. Since the associated parameters are determined based on the layer indicator parameters, the associated parameters may include the median, mean, and standard deviation corresponding to at least some merchants in the associated merchant layer.

[0121] When the associated merchant layer is the upper merchant layer, since the operating effect of the upper merchant layer is higher than the merchant's operating effect, the merchant's operating effect can be improved by determining the layer indicator parameters corresponding to the upper merchant layer as the associated parameters and managing the merchant's operating effect based on the associated parameters. When the associated merchant layer is the front merchant layer, since the operating effect of the current merchant layer is basically the same as the merchant's operating effect, the merchant's operating effect can be maintained by determining the layer indicator parameters corresponding to the current merchant layer as the associated parameters and managing the merchant's operating effect based on the associated parameters.

[0122] In this embodiment, the associated parameters for analyzing and processing at least one merchant operation parameter corresponding to the merchant are determined based on the layer indicator parameters corresponding to the associated merchant layer, which not only improves the accuracy and reliability of the determination of the associated parameters, but also further improves the accuracy of analyzing and processing at least one merchant operation parameter corresponding to the merchant.

[0123] Figure 6 This is a flow chart of another operation management method of an exemplary embodiment of the present application; based on any of the above embodiments, continue to refer to the attached Figure 6 As shown, since the associated merchant layer is obtained by analyzing and processing the layer structure after the merchant is layered, in order to ensure that the associated merchant layer is obtained accurately, before obtaining the associated merchant layer corresponding to the merchant, this embodiment further provides an implementation scheme for layering each merchant. Specifically, the method may further include:

[0124] Step S601: Acquire the operating data of other merchants in the same industry as the merchant.

[0125] Step S602: All merchants in the same industry are layered based on other merchant operation data and merchant operation parameters to obtain at least two merchant layers, where different merchant layers include merchants with different values.

[0126] In the field of e-commerce technology, there are tens of thousands of merchants on the e-commerce platform, and the industries to which each merchant belongs may be the same or different. In order to facilitate the management of several merchants on the e-commerce platform, the merchants included in the e-commerce platform can be layered according to their industries and operating results.

[0127] When it is necessary to perform operation and management operations on a certain merchant, in order to ensure the quality and efficiency of the operation and management operations, all merchants in the industry in which the merchant is located can be layered first, that is, merchants in the same industry and at the same operation level need to be divided into a layer structure. At this time, in order to ensure the quality and effect of the layering, in addition to obtaining at least one merchant operation parameter corresponding to the merchant, it is also necessary to obtain the operation data of other merchants in the same industry as the merchant. Among them, the merchant operation data is related to Figure 1 At least one merchant operation parameter in the illustrated embodiment is similar and will not be described in detail here.

[0128] In addition, the specific implementation method of obtaining the operating data of other merchants belonging to the same industry as the merchant can be: the merchant operating data can be stored in a preset area of ​​the e-commerce platform, and the operation management device can obtain the operating data of other merchants belonging to the same industry as the merchant by accessing the preset area. After obtaining the operating data of other merchants belonging to the same industry as the merchant, the operating data of other merchants and the merchant operating data can be analyzed and processed to stratify all merchants in the same industry. In some instances, all merchants in the same industry are stratified based on the operating data of other merchants and the merchant operating parameters. Obtaining at least two merchant layers may include: determining the corresponding value information of all merchants in the same industry based on the operating data of other merchants and the merchant operating parameters. The value information can be obtained by analyzing and processing the merchant operating data / merchant operating parameters through preset rules or machine learning models; and then sorting in reverse order based on the corresponding value information of all merchants to obtain at least two merchant layers, wherein different merchant layers include merchants with different values, and all merchants in the same merchant layer have the same or similar values.

[0129] In an embodiment of the present invention, at least two merchant layers are obtained by obtaining the operational data of other merchants in the same industry as the merchant, and stratifying all merchants in the same industry based on the operational data of other merchants and the merchant operational parameters. Then, based on the merchant stratification results, an associated merchant layer corresponding to the merchant is obtained, the layer indicator parameters corresponding to the associated merchant layer are determined, and the layer indicator parameters are determined as associated parameters. Then, based on the associated parameters and at least one merchant operational parameter, at least one target negative indicator corresponding to the merchant is determined. The target negative indicator determined in this way is more accurate and reliable. Since the target negative indicator can have a negative impact on the merchant's operations, the corresponding operational problems of the merchant can be more accurately diagnosed based on the target negative indicator. Finally, by conducting operational management of the merchant based on the target negative indicator, the merchant's operational problems can be managed in a targeted manner, so that the merchant's operational results can be more effectively improved, thereby improving the merchant's operational management efficiency. There is no need to blindly invest a large amount of cost to manage the merchant's operations, thereby reducing the operational management costs of the merchant's store.

[0130] Figure 7 The embodiment of the present application provides a flow chart for stratifying all merchants in the same industry to obtain at least two merchant layers; based on the above embodiment, refer to the attached Figure 7 As shown, this embodiment provides an implementation method for stratifying all merchants in the same industry based on other merchant operation data and merchant operation parameters to obtain at least two merchant layers. Specifically, in this embodiment, stratifying all merchants in the same industry based on other merchant operation data and the merchant operation parameters to obtain at least two merchant layers may include:

[0131] Step S701: Determine the corresponding generation cycle value of each merchant based on other merchant operation data and merchant operation parameters. The life cycle value is used to identify the value created by the merchant for the platform.

[0132] Step S702: All merchants are layered based on their respective lifetime values ​​to obtain at least two merchant layers.

[0133] In the process of operational management of merchants, since the layer indicator parameters of the associated merchant layer serve as the standard for diagnosing merchant operational problems, how to stratify merchants will directly affect the diagnostic results of merchant operational problems. For e-commerce platforms, since the value created by merchants for the platform directly determines the development of the e-commerce platform, all merchants in the same industry can be stratified based on the value they create for the platform. Specifically, the corresponding generation cycle value of each merchant is determined based on the operational data and merchant operating parameters of other merchants. The life cycle value is used to identify the value created by the merchant for the platform. All merchants are stratified based on their corresponding life cycle values ​​to obtain at least two merchant layers.

[0134] In addition, for merchants, the value they create for the platform determines the development of the e-commerce platform, and merchant retention directly affects whether merchants can create value for the platform. Therefore, the merchant's life cycle value is related to the merchant's renewal probability. The merchant's life cycle can be further determined based on the merchant's renewal probability. Specifically, the corresponding life cycle value of each merchant is determined based on other merchant operation data and merchant operation parameters, which may include:

[0135] Step S7011: Determine the renewal probability corresponding to each merchant based on the operating data of other merchants and the merchant operating parameters.

[0136] Among them, the renewal probability refers to the probability that the merchant renews with the platform to which it belongs after the expiration, and the renewal probability is directly related to the merchant data. For example: if a merchant has higher operating indicators such as sales volume, visitor volume, exposure volume, etc. on the platform to which it belongs, then the renewal probability between the merchant and the platform to which it belongs can be higher; if a merchant has lower operating indicators such as sales volume, visitor volume, exposure volume, etc. on the platform to which it belongs, then the renewal probability between the merchant and the platform to which it belongs can be lower. Therefore, the operating data of all merchants (including other merchant operating data and the merchant operating parameters) can be analyzed and processed to determine the corresponding renewal probability of each merchant. In addition, this embodiment does not limit the specific implementation method for determining the corresponding renewal probability of each merchant. Those skilled in the art can set it according to specific application requirements. For example, one feasible method is to determine the corresponding renewal probability of each merchant through a preset machine learning model. Specifically, determining the corresponding renewal probability of each merchant based on other merchant operating data and the merchant operating parameters can include:

[0137] The first machine learning model is used to analyze and process the operating data of other merchants and the merchant operating parameters to obtain renewal probabilities corresponding to each merchant. The first machine learning model is trained to determine the renewal probabilities corresponding to each merchant. The merchant's historical data can be used as training samples for the first machine learning model, and the first machine learning model is trained using an open source machine learning tool based on a gradient boosting decision tree.

[0138] After determining the renewal probability for each merchant, the lifetime value (LV) for all merchants can be determined based on the renewal probabilities for all merchants. The LV is positively correlated with the renewal probability, i.e., the greater the renewal probability, the higher the LV, and the lower the renewal probability, the lower the LV. In some instances, the lifetime value for all merchants can be directly determined as the renewal probability for all merchants.

[0139] In an optional embodiment, since there are tens of thousands of merchants on the e-commerce platform, when each merchant signs a contract with the e-commerce platform, in order to meet the different scenario needs of different merchants, the e-commerce platform can provide different membership services for different merchants. The above-mentioned membership services can correspond to different merchant permissions and capabilities. For example: senior members correspond to high-level promotion and publicity services, and ordinary members correspond to ordinary-level promotion and publicity services.

[0140] When merchants sign up for different membership services, they need to pay a certain membership fee. It is understandable that the higher the membership service level, the higher the membership fee paid, and the higher the merchant value corresponding to the merchant; the lower the membership service level, the lower the membership fee paid, and the lower the merchant value corresponding to the merchant. Therefore, the lifetime value of a merchant can be reflected not only by the merchant's renewal probability, but also by the membership fee required by the merchant on the platform. At this time, based on the renewal probability corresponding to all merchants, determining the lifetime value corresponding to all merchants can include: obtaining the membership fee required by all merchants when they are on the platform, and determining the product of the membership fee corresponding to all merchants and the renewal probability as the lifetime value corresponding to all merchants.

[0141] Specifically, suppose merchant A belongs to the same industry as merchants B and C. The membership fee required for merchant A on the platform is x1, and the renewal probability of merchant A is y1. Therefore, the corresponding lifetime value of merchant A is x1*y1. Suppose the membership fee required for merchant B on the platform is x2, and the renewal probability of merchant B is y2. Then, the corresponding lifetime value of merchant B is x2*y2. Suppose the membership fee required for merchant C on the platform is x3, and the renewal probability of merchant C is y3. Then, the corresponding lifetime value of merchant B is x3*y3. Using this method, the corresponding lifetime value of all merchants in the industry to which merchant A belongs can be calculated.

[0142] After determining the generation cycle value corresponding to each merchant, all merchants can be stratified based on their respective life cycle values ​​to obtain at least two merchant layers. Specifically, all merchants are sorted in reverse order based on their life cycle values ​​to obtain sorting information, and all merchants are stratified based on the sorting information to obtain at least two merchant layers. For example: merchants are sorted in reverse order according to their life cycle values, and all merchants belonging to the same industry are divided into two layers. Specifically, all merchants in the sorting queue whose life cycle values ​​are greater than T can be determined as the first layer of merchants, and all remaining merchants in the sorting queue can be determined as the second layer of merchants. Alternatively, merchants can be sorted in reverse order according to their life cycle values, and all merchants belonging to the same industry can be divided into three, four or more layers, and so on.

[0143] In another optional embodiment, in addition to analyzing and processing all merchants based on the lifetime value, all merchants can also be analyzed and processed in combination with the renewal probability corresponding to all merchants. At this time, all merchants are stratified based on the merchant ranking information to obtain at least two merchant layers, which can include: obtaining the renewal probability corresponding to all merchants, and stratifying all merchants based on the renewal probability corresponding to all merchants and the ranking information of all merchants to obtain at least two merchant layers.

[0144] Specifically, after obtaining the renewal probabilities corresponding to all merchants, all merchants can be grouped according to the renewal probabilities, and all merchants with renewal probabilities greater than or equal to a preset threshold (which can be 0.5, 0.6 or 0.8, etc.) can be divided into a first set, and all merchants with renewal probabilities less than the preset threshold can be divided into a second set. At this time, two merchant sets can be obtained. For the above-mentioned first set, all merchants in the first set can be sorted according to the merchant's life cycle value to achieve stratification of all merchants in the first set and obtain at least two merchant layers. For the above-mentioned second set, the second set can be directly determined as another merchant layer located under the at least two merchant layers, thereby effectively achieving stratification of all merchants.

[0145] For example, when the preset threshold is 0.5, all merchants with a renewal probability greater than or equal to 0.5 can be divided into a first set, and all merchants with a renewal probability less than 0.5 can be divided into a second set. Then, for all merchants in the first set, they can be sorted according to the merchant's life cycle value. For example, the merchants can be sorted according to their life cycle value, and the merchants ranked in the top 20% can be divided into a first merchant layer, the merchants ranked in the top 20%-50% can be divided into a second merchant layer, the merchants ranked below 50% can be divided into a third merchant layer, and all merchants included in the second set can be determined as a fourth merchant layer. The life cycle value of merchants in the above-mentioned first merchant layer, second merchant layer, third merchant layer and fourth merchant layer gradually decreases.

[0146] In this embodiment, the generation cycle value corresponding to each merchant is determined through other merchant operation data and merchant operation parameters, and then all merchants are stratified based on their respective life cycle values ​​to obtain at least two merchant layers, thereby effectively realizing the merchant stratification operation. This not only ensures the accuracy and reliability of obtaining the merchant layer, but also improves the accuracy and reliability of determining the associated merchant layer, thereby effectively improving the stability and reliability of the use of this method.

[0147] Continue to refer to the attached Figure 8In this embodiment, a flowchart of determining at least one target negative indicator corresponding to a merchant is provided; based on the above embodiment, refer to the attached Figure 8 As shown, this embodiment provides a method for implementing a target negative indicator that has a key or core impact on merchant operations. In this case, the number of target negative indicators obtained is relatively small. Specifically, in this embodiment, based on the association parameter and at least one merchant operation parameter, determining at least one target negative indicator corresponding to the merchant may include:

[0148] Step S801: Determine at least one negative operating parameter included in at least one merchant operating parameter.

[0149] Among them, negative operating parameters refer to operating parameters that have a negative impact on merchant operations. There may be one or more negative operating parameters in the merchant operating parameters. In some instances, negative operating parameters can be determined by the positive or negative degree of impact on merchant operations. Since the degree of impact on merchant operations is related to the contribution of each merchant operating parameter, the negative operating parameters included in at least one merchant operating parameter can be determined based on the contribution of each merchant operating parameter. Specifically, determining at least one negative operating parameter included in at least one merchant operating parameter may include:

[0150] Step S8011: Obtain the contribution degree corresponding to at least one merchant operation parameter, wherein the contribution degree is used to identify the degree of influence of the merchant operation parameter on the merchant operation.

[0151] Step S8012: When the contribution is less than zero, the merchant operation parameter corresponding to the contribution is determined as a negative operation parameter.

[0152] Specifically, to identify negative operating parameters included in merchant operating parameters, after obtaining at least one merchant operating parameter, the contribution of each merchant operating parameter can be obtained. In some instances, the contribution of each merchant operating parameter can be calculated using the SHAP algorithm, where the contribution is used to identify the degree of impact of the merchant operating parameter on the merchant's operations. Alternatively, the contribution of each merchant operating parameter can be calculated using the XGBoost algorithm.

[0153] After obtaining the contribution degree corresponding to at least one merchant operation parameter, the contribution degree can be analyzed and compared with zero. When the contribution degree is less than zero, the merchant operation parameter corresponding to the contribution degree is determined to be a negative operation parameter, thereby accurately determining the negative operation parameter that has a negative impact on the merchant operation. When the contribution degree is greater than zero, the merchant operation parameter corresponding to the contribution degree can be determined to be a positive operation parameter that can have a positive impact on the merchant operation.

[0154] Step S802: Based on the association parameter and at least one negative operation parameter, determine at least one target negative indicator corresponding to the merchant.

[0155] After obtaining at least one negative operating parameter corresponding to the merchant, since the number of negative operating parameters may be relatively large, in order to be able to determine the core indicators of the merchant's operation in a targeted manner, the negative operating parameters can be further screened to determine the target negative indicator (i.e., the core indicator). Specifically, at least one target negative indicator corresponding to the merchant can be determined based on the associated parameters and at least one negative operating parameter. In some instances, a machine learning model for determining the target negative indicator is pre-trained. After obtaining the associated parameters and at least one negative operating parameter, the associated parameters and at least one negative operating parameter can be input into the machine learning model, so that at least one target negative indicator output by the machine learning model can be obtained, thereby effectively achieving the determination of the target negative indicator among many negative operating parameters. The determined target negative indicator is the core operating parameter that has a major negative impact on the merchant's operation.

[0156] In another optional embodiment, based on the association parameter and the at least one negative operating parameter, determining at least one target negative indicator corresponding to the merchant may include:

[0157] Step S8021: Determine at least one indicator offset based on the associated parameter and at least one negative operating parameter.

[0158] Step S8022: Based on at least one indicator offset, determine at least one target negative indicator corresponding to the merchant.

[0159] Among them, since the associated parameters are used to identify the target values ​​of the operating effects that merchants need to achieve, after obtaining the associated parameters and at least one negative operating parameter, the associated parameters and at least one negative operating parameter can be analyzed and processed to obtain at least one indicator offset, which is used to measure the degree to which the negative operating parameter deviates from the associated parameter.

[0160] Specifically, when the associated parameters include the associated indicator mean and the associated indicator standard deviation, determining at least one indicator offset based on the associated parameters and at least one negative operating parameter may include: obtaining the difference between each negative operating parameter and the associated indicator mean, and then determining the indicator offset based on the ratio between the difference and the associated indicator standard deviation.

[0161] For example, the negative operating parameter is x, the mean of the associated indicator is u, and the standard deviation of the associated indicator is δ. The difference between the negative operating parameter and the mean of the associated indicator is obtained, that is, the difference is xu. Then, the ratio (xu) / δ between the difference and the standard deviation of the associated indicator is determined. After obtaining the above ratio, the indicator offset can be determined based on the above ratio. For example, this ratio can be directly determined as the indicator offset, that is, the indicator offset is (xu) / δ; or, the sum of the ratio and the preset parameter can be determined as the indicator offset, or the product value between the ratio and the preset parameter can be determined as the indicator offset, thereby effectively ensuring the flexibility and reliability of determining the indicator offset.

[0162] Since the indicator offset can reflect the degree of deviation between the negative operating parameter and the corresponding associated parameter (target value), for example, the larger the indicator offset, the greater the degree of deviation between the negative operating parameter and the associated parameter, that is, the negative operating parameter has a higher degree of impact on the merchant's operation; the smaller the indicator offset, the smaller the degree of deviation between the negative operating parameter and the associated parameter, that is, the negative operating parameter has a lower degree of impact on the merchant's operation. Therefore, after determining the indicator offset, at least one target negative indicator corresponding to the merchant is determined based on at least one indicator offset. Specifically, based on at least one indicator offset, determining at least one target negative indicator corresponding to the merchant may include: determining the minimum indicator offset among at least one indicator offset, and determining at least one negative operating parameter corresponding to the minimum indicator offset as at least one target negative indicator corresponding to the merchant.

[0163] In actual applications, when a merchant's business conditions are poor, there will be a large number of negative operating parameters. If the merchant's operations are managed based on each negative operating parameter, the operating problems corresponding to each negative operating parameter can be obtained first. Since there are many identified operating problems, when managing the merchant's operations based on the identified operating problems, it is easy to blindly optimize the merchant's existing operating problems, resulting in a situation where there is no optimization focus. This will not only reduce the merchant's operational management efficiency, but also increase the merchant's operating costs. Therefore, in this embodiment, by analyzing and processing the negative operating parameters, a target negative indicator with the largest degree of deviation from the associated parameters is obtained. In other words, the target negative indicator is the merchant's operating parameter that has the greatest negative impact on the merchant's operations. This greatly reduces the number of operational problems that affect the merchant's operations, thereby helping to improve the quality and efficiency of the merchant's operations.

[0164] In this embodiment, by determining at least one negative operating parameter included in at least one merchant operating parameter, at least one target negative indicator corresponding to the merchant is determined based on the associated parameters and the at least one negative operating parameter. In this way, the merchant operating parameter that has the greatest negative impact on the merchant operation can be determined, and then the core problems existing in the merchant operation process can be accurately identified based on the target negative indicator. This not only simplifies the identification and analysis process of merchant operation problems, but also improves the practicality of the technical solution.

[0165] Figure 9 This is a flow chart of another operation management method provided in the embodiment of the present application; based on the above embodiment, refer to the attached Figure 9 As shown, after determining the target negative indicator, in order to improve the practicality of the method, the merchant can be operated and managed based on the target negative indicator, which may include:

[0166] Step S901: Acquire at least one hierarchical causal indicator corresponding to the target negative indicator.

[0167] After determining the target negative indicator, since there are multiple other parameters that affect the target negative indicator, for example, when the target negative indicator is the number of buyers placing orders, based on experience, it can be determined that other parameters that affect the number of buyers placing orders may include the number of opportunity buyers and the transaction conversion rate. The number of opportunity buyers is related to the opportunity conversion rate and the number of visitors. Therefore, it can be determined that other parameters that affect the target negative indicator may include: the number of opportunity buyers, the transaction conversion rate, the opportunity conversion rate, the number of visitors, etc.

[0168] In order to accurately perform operational management operations based on the target negative indicator, after obtaining the target negative indicator, at least one hierarchical causal indicator corresponding to the target negative indicator can be obtained. This embodiment does not limit the specific implementation method for obtaining at least one hierarchical causal indicator corresponding to the target negative indicator. For example, at least one hierarchical causal indicator corresponding to the target negative indicator can be stored in a preset area, and the operational management device can obtain at least one hierarchical causal indicator corresponding to the target negative indicator by accessing the preset area. Alternatively, the hierarchical causal relationship corresponding to the target negative indicator can be sorted out based on experience, and at least one hierarchical causal indicator corresponding to the target negative indicator can be determined based on the hierarchical causal relationship. Alternatively, algorithmic modeling can be used to obtain the hierarchical causal relationship corresponding to the target negative indicator, and then at least one hierarchical causal indicator corresponding to the target negative indicator can be determined based on the hierarchical causal relationship.

[0169] Of course, those skilled in the art may also adopt other methods to obtain at least one level of causal indicator corresponding to the target negative indicator, as long as the accuracy and reliability of obtaining at least one level of causal indicator corresponding to the target negative indicator can be guaranteed. No further details will be given here.

[0170] Step S902: Determine target operating parameters corresponding to the merchant.

[0171] After obtaining at least one hierarchical causal indicator corresponding to the target negative indicator, the target operating parameters corresponding to the merchant can be determined. The target operating parameters can serve as the target values ​​that the merchant operating parameters need to be adjusted to achieve. In some instances, the target operating parameters can include the median indicator number corresponding to the upper merchant layer or the mean indicator number corresponding to the upper merchant layer.

[0172] Specifically, when the target operating parameters can include the median index number corresponding to the upper merchant layer or the mean index number corresponding to the upper merchant layer, the implementation method for determining the target operating parameters corresponding to the merchant can be: obtain the upper merchant layer corresponding to the merchant, and determine the median index number or the mean index number corresponding to the upper merchant layer as the target operating parameters corresponding to the merchant.

[0173] Step S903: Determine the operation management parameters corresponding to the merchant based on the target operation parameters and at least one hierarchical causal indicator.

[0174] After determining the target operating parameters corresponding to the merchant, the target operating parameters and at least one hierarchical causal indicator can be analyzed and processed to determine the operating management parameters corresponding to the merchant, which correspond to at least a portion of the at least one hierarchical causal indicator.

[0175] In an optional embodiment, determining the operation management parameters corresponding to the merchant based on the target operation parameters and at least one hierarchical causal indicator may include:

[0176] Step S9031: Determine the degree of influence of each level of causal indicators on the target negative indicator.

[0177] Because a target negative indicator may be associated with multiple hierarchical causal indicators, and different hierarchical causal indicators have different degrees of influence on the target negative indicator, directly adjusting and managing the merchant's operations based on each hierarchical causal indicator after obtaining at least one hierarchical causal indicator will not only increase the workload of operations management, but may also fail to significantly improve the merchant's operating results.

[0178] After obtaining at least one level of causal indicators, the degree of influence of each level of causal indicators on the target negative indicator can be determined first. In some instances, determining the degree of influence of each level of causal indicators on the target negative indicator can include: determining the degree of influence of each level of causal indicators on the target negative indicator based on the associated parameters. Specifically, the degree of influence can be determined by determining the indicator offset of each level of causal indicators relative to the associated parameters. The larger the indicator offset, the greater the degree of influence, and the smaller the indicator offset, the smaller the degree of influence.

[0179] Step S9032: Determine at least one key causal indicator based on the degree of influence in at least one hierarchical causal indicator.

[0180] After determining the degree of influence of each hierarchical causal indicator on the target negative indicator, at least one key causal indicator can be determined based on the degree of influence. In some examples, determining at least one key causal indicator based on the degree of influence can include: first determining the current indicator layer to which each hierarchical causal indicator belongs; when the current indicator layer has an associated cause indicator layer, obtaining a first degree of influence of the hierarchical causal indicator in the current indicator layer and a second degree of influence of the hierarchical causal indicator in the cause indicator layer, wherein the cause indicator layer includes other hierarchical causal indicators that influence the hierarchical causal indicator in the current indicator layer; and then determining at least one key causal indicator based on the first degree of influence and the second degree of influence.

[0181] In practical applications, empirically based causal relationships are layered across merchant operational parameters to identify indicator layers corresponding to each merchant operational parameter. When a key causal indicator is identified within at least one hierarchical causal indicator, the current indicator layer to which each hierarchical causal indicator belongs can be first obtained. If the current indicator layer has an associated causal indicator layer, not only the first impact degree of the hierarchical causal indicator in the current indicator layer but also the second impact degree of the hierarchical causal indicator in the causal indicator layer should be obtained. The first and second impact degrees are then compared to determine at least one key causal indicator.

[0182] Specifically, determining at least one key causal indicator based on the first and second degrees of influence may include: when the first degree of influence is greater than the second degree of influence, directly determining the hierarchical causal indicator in the current indicator layer as the at least one key causal indicator; and when the first degree of influence is less than the second degree of influence, using the cause indicator layer as the new current indicator layer and determining at least one key causal indicator based on the new current indicator layer. In other words, determining the key causal indicator that has the greatest impact on the target negative indicator from the hierarchical causal indicators.

[0183] Step S9033: Based on at least one key causal indicator and the target operation parameter, determine the operation management parameters corresponding to the merchant.

[0184] Since at least one key causal indicator is one or more indicators that have the greatest impact on the target negative indicator, the indicator currently most impacting the merchant's operations can be determined based on the at least one key causal indicator. Then, based on the at least one key causal indicator and the target operating parameters, corresponding operational management parameters for the merchant are determined. These operational management parameters may include specific parameters for improving the merchant's operational performance and the corresponding adjustment ranges for the parameters.

[0185] In another optional embodiment, determining the operational management parameters corresponding to the merchant based on the target operational parameter and at least one hierarchical causal indicator may include: determining the degree of influence of the hierarchical causal indicator on the target negative indicator, ranking the hierarchical causal indicators based on the degree of influence of the hierarchical causal indicator on the target negative indicator, obtaining indicator ranking information, and then determining the operational management parameters corresponding to the merchant based on the ranking information and the target operational parameter. Since the target negative indicator is equivalent to an indicator of a problem existing in the merchant, ranking the hierarchical causal indicators based on the degree of influence on the target negative indicator is equivalent to ranking the merchant's problems according to the hierarchical causal relationship, identifying the core problem, and then determining the operational management parameters corresponding to the merchant based on the core problem and the target operational parameter.

[0186] Step S904: Perform operation management on the merchant based on the operation management parameters.

[0187] Since the operation management parameters are determined based on the target operation parameters and at least one level of causal indicators, operation management of merchants based on the operation management parameters can not only accurately identify the operation problems that require merchants to adjust, but also accurately adjust the merchant operation problems to achieve the purpose of improving the merchant's operation results.

[0188] In this embodiment, by obtaining at least one hierarchical causal indicator corresponding to the target negative indicator, the target operating parameters corresponding to the merchant are determined, and then based on the target operating parameters and at least one hierarchical causal indicator, the operating management parameters corresponding to the merchant are determined, and the merchant is operated and managed based on the operating management parameters. The operational problems of the merchant can be managed in a targeted manner, which can not only improve the merchant's operating management efficiency, but also reduce the merchant's operating management costs.

[0189] In specific applications, this application embodiment provides an operation management method, which can realize timely and flexible operation management of merchants based on the merchant's operational problems. Specifically, the operation management method includes the following steps:

[0190] Step 1: Obtain the historical operating data of each merchant and other merchants in the same industry, as well as the historical renewal probability corresponding to each merchant.

[0191] Among them, the merchant's historical operating data may include the merchant's basic information, the merchant's product data, traffic data, inquiry data, transaction data, promotion data and industry data, etc.

[0192] Step 2: Based on the historical operating data and historical renewal probabilities of the merchant and other merchants in the same industry, the merchant prediction renewal probability model is trained to obtain the merchant prediction renewal probability model.

[0193] Among them, the merchant renewal probability prediction model is used to determine the merchant's corresponding renewal probability. The merchant renewal probability prediction model can be trained by the lightweight gradient boosting machine model LightGBM, so that the model can determine the merchant's renewal probability based on the merchant's operating data. The specific training process can be referred to in the attached Figure 10 shown.

[0194] After obtaining the merchant predicted renewal probability model, the merchant predicted renewal probability model can be used to manage merchant operations.

[0195] Step 3: When there is a merchant to be managed, the current merchant data can be downloaded through the e-commerce platform to obtain at least one merchant operation parameter corresponding to the merchant.

[0196] Step 4: Use the SHAP algorithm to calculate the contribution of at least one merchant operation parameter. The contribution is used to identify the degree of influence of the merchant operation parameter on the merchant operation.

[0197] Step 5: Using the merchant renewal probability prediction model, process the obtained at least one merchant operation parameter corresponding to the merchant to obtain the renewal probability corresponding to the merchant.

[0198] Step 6: Calculate the lifetime value of the merchant based on the merchant's corresponding renewal probability and the merchant's membership fee.

[0199] Step 7: Obtain the operating data of other merchants in the same industry as the merchant and the corresponding life cycle value of other merchants.

[0200] Step 8: Based on lifetime value, stratify all merchants in the same industry to obtain at least two merchant strata.

[0201] In specific applications, a recommended merchant stratification method may include: arranging all merchants in the same industry in reverse order according to the size of their life cycle value, and stratifying merchants in the same industry according to the renewal probability of 0.5 or above and ranking in the top 20%, the renewal probability of 0.5 or above and ranking in the top 50%, and ranking below 50% and with a predicted renewal rate of 0.5 or above and a renewal probability of 0.5 or above.

[0202] Step 9: Based on the stratification results, the layer indicator parameters of all merchant operation parameters at different merchant layers are counted. The layer indicator parameters include: layer indicator standard deviation, layer indicator median, and layer indicator average.

[0203] Step 10: Obtain the upper merchant layer corresponding to the merchant, and associate each merchant operation parameter of the merchant with the layer indicator parameters of the upper merchant layer.

[0204] The specific merchant stratification process and the specific implementation process of associating the merchant operation parameters of each merchant with the layer indicator parameters of the upper merchant layer can be referred to in the attached Figure 11 .

[0205] Step 11: Input the merchant's stratification results, at least one merchant operating parameter, the corresponding contribution of at least one merchant operating parameter, and the layer indicator parameters associated with the previous layer into the problem diagnosis model to obtain the merchant's corresponding operating problems and adjustment plans.

[0206] Among them, refer to the attached Figure 12-13 Based on the diagnostic model, determining the corresponding operational issues and adjustments for merchants may include:

[0207] Step S111: Determine the causal hierarchical relationship between merchant operation parameters based on experience or algorithmic modeling.

[0208] In an optional embodiment, a hierarchical causal relationship of merchant operating parameters can be derived based on experience. For example, the first layer includes the following indicators: the merchant's gross merchandise volume (GMV), customer relationships, and merchant activity affect the merchant's corresponding life cycle value. Since the number of ordering buyers, payment conversion, and average order value can affect the merchant's GMV, the number of ordering buyers, payment conversion, and average order value can be determined as the second layer; similarly, since the number of opportunity buyers and transaction conversion rate can affect the number of ordering buyers, the number of opportunity buyers and transaction conversion rate can be determined as the third layer; since the number of merchant visitors and opportunity conversion rate can affect the number of opportunity buyers, the number of merchant visitors and opportunity conversion rate can be determined as the fourth layer; since the merchant search exposure and click-through rate can affect the number of visitors, the merchant search exposure and click-through rate can be determined as the fifth layer.

[0209] Step S112: After determining the causal hierarchical relationship between the business operation parameters, determine at least one negative operation parameter based on the contribution degree corresponding to each of the at least one business operation parameters.

[0210] Among them, the merchant operation parameters whose corresponding contribution is less than zero are determined as negative operation parameters, and the merchant operation parameters whose corresponding contribution is greater than zero are determined as positive operation parameters.

[0211] Step S113: Calculate the indicator offset based on at least one negative operating parameter and the layer indicator parameter.

[0212] Specifically, the layer indicator parameters are the indicator parameters corresponding to the upper merchant layer corresponding to the merchant, which may include the layer indicator standard deviation δ and the layer indicator average u. After obtaining at least one negative operating parameter x, the indicator offset zscore = (xu) / δ can be obtained based on the following formula, where the smaller the offset, the farther the indicator offsets the distribution of the upper merchant layer.

[0213] Step S114: sorting at least one negative operation parameter based on the indicator offset corresponding to each negative operation parameter to obtain indicator sorting information.

[0214] By sorting the negative operating parameters according to the size of zscore, we can get the priority of the problem indicators, thereby determining the priority of the operating problems corresponding to each negative operating parameter, and thus identifying the core problem.

[0215] Step S115: Determine whether the current merchant layer where the merchant is located has an associated cause indicator layer. If no associated cause indicator layer exists, determine the key causal indicators corresponding to the merchant based on the indicator sorting information; if an associated cause indicator layer exists, obtain the first influence degree of the hierarchical causal indicators in the current indicator layer and the second influence degree of the hierarchical causal indicators in the cause indicator layer, and determine at least one key causal indicator based on the first influence degree and the second influence degree.

[0216] The cause indicator layer includes other hierarchical causal indicators that influence the hierarchical causal indicators in the current indicator layer. When the first degree of influence is greater than the second degree of influence, the hierarchical causal indicators in the current indicator layer are determined as at least one key causal indicator. When the first degree of influence is less than the second degree of influence, the cause indicator layer is used as the new current indicator layer, and at least one key causal indicator is determined based on the new current indicator layer.

[0217] For example, after obtaining the key causal indicator KPI, the corresponding impact degree of the key core indicator KPI can be obtained, and the negative level causal indicator A with the largest "cost" can be found in the next level of the key causal indicator KPI. If the negative level causal indicator A in the next level has a greater impact degree than the current key core indicator KPI, then the search can continue downward to the negative level causal indicator B with the largest "cost" in the next level of the negative level causal indicator A. If the impact degree of the negative level causal indicator B is less than the impact degree of the negative level causal indicator A, then the negative level causal indicator B can be determined as the largest negative indicator, that is, the negative level causal indicator B can be determined as at least one key causal indicator.

[0218] Step S116: Determine the operation management parameters corresponding to the merchant based on at least one key causal indicator and the median of the layer indicator.

[0219] Step S117: Perform operation management on the merchant based on the operation management parameters.

[0220] Finally, merchant operations management is performed based on the operation management parameters. Merchant operation management may include adjusting the merchant operation status. For example, the adjustments may include: adjusting product keywords, product images, customizing marketing plans, optimizing through train bids, etc.

[0221] The technical solution provided in this embodiment predicts core indicators and diagnoses merchant operations in a hierarchical manner, and combines machine learning models (predicting LTV) and prior knowledge (hierarchical KPI relationships) to accurately determine operational problems that are directly related to merchants. Operational recommendation parameters can then be generated based on the operational problems, and the merchant can be managed based on the operational recommendation parameters, thereby quickly and specifically improving the merchant's operational results, further improving the practicality of the method, and facilitating market promotion and application.

[0222] Figure 14 This is a flow chart of an operation management device provided in an embodiment of the present application; Figure 14 As shown, this embodiment provides an operation management device for executing the above Figure 1 The operation management method shown, specifically, the operation management device may include:

[0223] The acquisition module 11 is configured to acquire at least one merchant operation parameter corresponding to a merchant.

[0224] The first determining module 12 is configured to determine associated parameters for analyzing and processing at least one merchant operation parameter.

[0225] The second determination module 13 is configured to determine at least one target negative indicator corresponding to the merchant based on the associated parameter and at least one merchant operation parameter, where the target negative indicator can have a negative impact on the merchant operation.

[0226] The management module 14 is used to perform operation management on merchants based on target negative indicators.

[0227] In some embodiments, when determining the associated parameters for analyzing and processing at least one merchant operation parameter, the first determination module 12 is used to: obtain the associated merchant layer corresponding to the merchant; determine the layer indicator parameters corresponding to the associated merchant layer; determine the layer indicator parameters as associated parameters, and the associated parameters are used to maintain or improve the merchant's operating results.

[0228] In some instances, when the first determination module 12 obtains an associated merchant layer corresponding to a merchant, the first determination module 12 is used to: obtain an upper merchant layer corresponding to the merchant, the life cycle value of the merchants in the upper merchant layer being greater than the life cycle value of the merchant; and determine the upper merchant layer as an associated merchant layer.

[0229] In some examples, when the first determining module 12 obtains the associated merchant layer corresponding to the merchant, the first determining module 12 is configured to: obtain the current merchant layer corresponding to the merchant; and determine the current merchant layer as the associated merchant layer.

[0230] In some instances, when determining the layer indicator parameters corresponding to the associated merchant layer, the first determination module 12 is used to: determine the indicator median, indicator average, and indicator standard deviation corresponding to all merchants in the associated merchant layer; and determine the indicator median, indicator average, and indicator standard deviation as the layer indicator parameters.

[0231] In some instances, before obtaining the associated merchant layer corresponding to the merchant, the device also includes a stratification module, which is used to: obtain the operating data of other merchants belonging to the same industry as the merchant; stratify all merchants in the same industry based on the operating data of other merchants and the merchant operating parameters to obtain at least two merchant layers, and different merchant layers include merchants with different values.

[0232] In some instances, when all merchants in the same industry are stratified based on other merchant operating data and merchant operating parameters to obtain at least two merchant layers, the stratification module is used to: determine the corresponding generation cycle value of each merchant based on other merchant operating data and merchant operating parameters, and the life cycle value is used to identify the value created by the merchant for the platform; stratify all merchants based on the corresponding life cycle value of all merchants to obtain at least two merchant layers.

[0233] In some instances, when determining the generation cycle value corresponding to each merchant based on other merchant operating data and merchant operating parameters, the stratification module is used to: determine the renewal probability corresponding to each merchant based on other merchant operating data and the merchant operating parameters; and determine the life cycle value corresponding to all merchants based on the renewal probability corresponding to all merchants.

[0234] In some instances, when determining the life cycle value corresponding to all merchants based on the renewal probability corresponding to all merchants, the layering module is used to: obtain the membership fees required for all merchants on the platform; and determine the product of the membership fees corresponding to all merchants and the renewal probability as the life cycle value corresponding to all merchants.

[0235] In some instances, when all merchants are stratified based on their respective life cycle values ​​to obtain at least two merchant layers, the stratification module is used to: sort all merchants in reverse order based on their life cycle values ​​to obtain sorting information; and stratify all merchants based on the sorting information to obtain at least two merchant layers.

[0236] In some instances, when all merchants are stratified based on ranking information to obtain at least two merchant layers, the stratification module is used to: obtain the renewal probability corresponding to all merchants; and stratify all merchants based on the renewal probability and ranking information to obtain at least two merchant layers.

[0237] In some instances, when determining at least one target negative indicator corresponding to a merchant based on associated parameters and at least one merchant operating parameter, the second determination module 13 is used to: determine at least one negative operating parameter included in at least one merchant operating parameter; and determine at least one target negative indicator corresponding to the merchant based on the associated parameters and at least one negative operating parameter.

[0238] In some instances, when determining at least one negative operating parameter included in at least one merchant operating parameter, the second determination module 13 is used to: obtain the contribution degree corresponding to each of the at least one merchant operating parameters, where the contribution degree is used to identify the degree of impact of the merchant operating parameter on the merchant operation; when the contribution degree is less than zero, the merchant operating parameter corresponding to the contribution degree is determined as a negative operating parameter.

[0239] In some instances, when determining at least one target negative indicator corresponding to a merchant based on associated parameters and at least one negative operating parameter, the second determination module 13 is used to: determine at least one indicator offset based on the associated parameters and at least one negative operating parameter; and determine at least one target negative indicator corresponding to the merchant based on at least one indicator offset.

[0240] In some instances, when the associated parameters include: an associated indicator mean and an associated indicator standard deviation, and at least one indicator offset is determined based on the associated parameters and at least one negative operating parameter, the second determination module 13 is used to: obtain the difference between each negative operating parameter and the associated indicator mean; and determine the indicator offset based on the ratio between the difference and the associated indicator standard deviation.

[0241] In some instances, when determining at least one target negative indicator corresponding to a merchant based on at least one indicator offset, the second determination module 13 is used to: determine the minimum indicator offset among the at least one indicator offset; and determine at least one negative operating parameter corresponding to the minimum indicator offset as the at least one target negative indicator corresponding to the merchant.

[0242] In some instances, when performing operational management on a merchant based on a target negative indicator, the management module 14 is used to: obtain at least one hierarchical causal indicator corresponding to the target negative indicator; determine target operational parameters corresponding to the merchant; determine operational management parameters corresponding to the merchant based on the target operational parameters and at least one hierarchical causal indicator; and perform operational management on the merchant based on the operational management parameters.

[0243] In some instances, when determining the target operating parameters corresponding to a merchant, the management module 14 is used to: obtain the upper merchant layer corresponding to the merchant; and determine the median index number or mean index number corresponding to the upper merchant layer as the target operating parameters corresponding to the merchant.

[0244] In some instances, when determining the operation management parameters corresponding to the merchant based on the target operation parameters and at least one hierarchical causal indicator, the management module 14 is used to: determine the degree of influence of each hierarchical causal indicator on the target negative indicator; determine at least one key causal indicator based on the degree of influence in at least one hierarchical causal indicator; and determine the operation management parameters corresponding to the merchant based on at least one key causal indicator and the target operation parameters.

[0245] In some examples, when determining the degree of influence of the hierarchical causal indicator on the target negative indicator, the management module 14 is configured to determine the degree of influence of the hierarchical causal indicator on the target negative indicator based on the association parameter and the standard causal parameter.

[0246] In some instances, when determining at least one key causal indicator based on the degree of influence, the management module 14 is used to: determine the current indicator layer to which each hierarchical causal indicator belongs; when there is an associated cause indicator layer in the current indicator layer, obtain the first degree of influence of the hierarchical causal indicators in the current indicator layer and the second degree of influence of the hierarchical causal indicators in the cause indicator layer, wherein the cause indicator layer includes other hierarchical causal indicators that have an impact on the hierarchical causal indicators in the current indicator layer; based on the first degree of influence and the second degree of influence, determine at least one key causal indicator.

[0247] In some instances, when determining at least one key causal indicator based on a first degree of influence and a second degree of influence, the management module 14 is used to: when the first degree of influence is greater than the second degree of influence, determine the hierarchical causal indicator in the current indicator layer as at least one key causal indicator; when the first degree of influence is less than the second degree of influence, use the cause indicator layer as the new current indicator layer, and determine at least one key causal indicator based on the new current indicator layer.

[0248] Figure 14 The operation management device shown can execute Figures 1-13 For the method of the embodiment shown in FIG. 1 , reference may be made to the description of the part not described in detail in the embodiment. Figures 1-13 The implementation process and technical effects of this technical solution can be found in Figures 1-13 The description in the illustrated embodiment will not be repeated here.

[0249] In one possible design, Figure 14 The structure of the operation management device shown can be implemented as an electronic device, which can be a cluster server, a conventional server, a cloud server, a cloud host, a virtual center, etc. Figure 15 As shown, the electronic device may include: a first processor 21 and a first memory 22. The first memory 22 is used to store the corresponding electronic device to perform the above Figures 1-13 The program of the operation management method provided in the illustrated embodiment, the first processor 21 is configured to execute the program stored in the first memory 22 .

[0250] The program includes one or more computer instructions, wherein when the one or more computer instructions are executed by the first processor 21, the following steps can be implemented: obtaining at least one merchant operation parameter corresponding to the merchant; determining an associated parameter for analyzing and processing the at least one merchant operation parameter; based on the associated parameter and at least one merchant operation parameter, determining at least one target negative indicator corresponding to the merchant, the target negative indicator can have a negative impact on the merchant operation; and performing operation management on the merchant based on the target negative indicator.

[0251] Furthermore, the first processor 21 is also used to execute the aforementioned Figures 1-13 All or part of the steps in the illustrated embodiments.

[0252] The structure of the electronic device may further include a first communication interface 23 for the electronic device to communicate with other devices or a communication network.

[0253] In addition, an embodiment of the present invention provides a computer storage medium for storing computer software instructions used by electronic devices, which includes instructions for executing the above Figures 1-13 The procedures involved in the operation management method in the illustrated method embodiment.

[0254] In addition, an embodiment of the present invention provides a computer program product, comprising: a computer program, when the computer program is executed by a processor of an electronic device, causing the processor to execute Figures 1-13 The operations management method in the illustrated method embodiment.

[0255] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units. That is, they may be located in one place or distributed across multiple network units. Some or all of the modules may be selected based on actual needs to achieve the objectives of the present embodiment. Persons of ordinary skill in the art will be able to understand and implement the present invention without inventive effort.

[0256] Through the description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by adding a necessary general hardware platform, and of course can also be implemented by combining hardware and software. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a computer product. This application can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0257] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable device to produce a machine, so that the instructions executed by the processor of the computer or other programmable device generate instructions for implementing the steps in the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0258] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0259] These computer program instructions can also be loaded onto a computer or other programmable device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0260] In a typical configuration, a computing device includes one or more processors (CPUs), input / output interfaces, network interfaces, and memory.

[0261] Memory may include non-permanent storage in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. Memory is an example of a computer-readable medium.

[0262] Computer-readable media includes permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. The information can be computer-readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer-readable media does not include transitory computer-readable media (transitory media), such as modulated data signals and carrier waves.

[0263] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some or all of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the scope of the technical solutions of the embodiments of the present application.

Claims

1. An operation management method, characterized in that: include: Obtain at least one merchant operation parameter corresponding to the merchant; Obtaining an associated merchant layer corresponding to the merchant, wherein the associated merchant layer refers to a merchant layer that has an associated relationship with the merchant, and the merchant layer refers to a layer structure obtained by layering all merchants in the same industry to which the merchant belongs; Determining a layer indicator parameter corresponding to the associated merchant layer, wherein the layer indicator parameter refers to an indicator statistical result obtained by performing indicator statistics on the associated merchant layer; Determining the layer indicator parameter as the associated parameter, wherein the associated parameter is used to maintain or improve the operating effect of the merchant; Determining at least one target negative indicator corresponding to the merchant based on the association parameter and the at least one merchant operation parameter, wherein the target negative indicator is determined based on the association parameter and the at least one negative operation parameter, the negative operation parameter being a merchant operation parameter having a contribution less than zero, the contribution being used to identify the degree of influence of the merchant operation parameter on the merchant's operations; The merchant is operated and managed based on the target negative indicator.

2. The method according to claim 1, characterized in that Obtain the associated merchant layer corresponding to the merchant, including: Obtaining an upper merchant layer corresponding to the merchant, wherein the lifetime value of merchants in the upper merchant layer is greater than the lifetime value of the merchant; The upper merchant layer is determined as the associated merchant layer.

3. The method according to claim 1, characterized in that Before obtaining the associated merchant layer corresponding to the merchant, the method further includes: Obtain operational data of other merchants in the same industry as the merchant; All merchants in the same industry are layered based on other merchant operation data and the merchant operation parameters to obtain at least two merchant layers, where different merchant layers include merchants with different values.

4. The method according to claim 3, characterized in that All merchants in the same industry are layered based on other merchant operation data and the merchant operation parameters to obtain at least two merchant layers, including: Determine the corresponding life cycle value of each merchant based on the operating data of other merchants and the merchant operating parameters, where the life cycle value is used to identify the value created by the merchant for the platform; All merchants are layered based on their respective lifetime values ​​to obtain at least two merchant layers.

5. The method according to claim 1, wherein Determining at least one target negative indicator corresponding to the merchant based on the association parameter and the at least one merchant operation parameter includes: determining at least one negative operating parameter included in the at least one merchant operating parameter; At least one target negative indicator corresponding to the merchant is determined based on the association parameter and the at least one negative operating parameter.

6. The method according to claim 5, characterized in that Determining at least one negative operating parameter included in the at least one merchant operating parameter includes: Obtaining a contribution degree corresponding to each of the at least one merchant operation parameters, where the contribution degree is used to identify the degree of influence of the merchant operation parameter on the merchant operation; When the contribution is less than zero, the merchant operation parameter corresponding to the contribution is determined as a negative operation parameter.

7. The method according to claim 5, characterized in that Determining at least one target negative indicator corresponding to the merchant based on the association parameter and the at least one negative operating parameter includes: determining at least one indicator offset based on the correlation parameter and the at least one negative operating parameter; At least one target negative indicator corresponding to the merchant is determined based on the at least one indicator offset.

8. The method according to claim 7, characterized in that The correlation parameters include: a correlation indicator mean and a correlation indicator standard deviation; and determining at least one indicator offset based on the correlation parameters and the at least one negative operating parameter, including: Obtaining the difference between each negative operating parameter and the mean value of the associated indicator; The indicator offset is determined based on a ratio between the difference and the association indicator standard deviation.

9. The method according to claim 7, characterized in that Determining at least one target negative indicator corresponding to the merchant based on the at least one indicator offset includes: determining a minimum indicator offset among the at least one indicator offset; At least one negative operating parameter corresponding to the minimum indicator offset is determined as at least one target negative indicator corresponding to the merchant.

10. The method according to any one of claims 1 to 9, characterized in that Conducting operations management on merchants based on the target negative indicators, including: Acquire at least one hierarchical causal indicator corresponding to the target negative indicator; determining target operating parameters corresponding to the merchant; Determining an operation management parameter corresponding to the merchant based on the target operation parameter and at least one hierarchical causal indicator; The merchant is operated and managed based on the operation management parameters.

11. The method according to claim 10, characterized in that Determining operation management parameters corresponding to the merchant based on the target operation parameters and at least one hierarchical causal indicator includes: Determine the degree of influence of causal indicators at each level on the negative indicators of the target; Determining at least one key causal indicator among the at least one hierarchical causal indicator based on the impact degree; Based on the at least one key causal indicator and the target operating parameter, an operation management parameter corresponding to the merchant is determined.

12. The method according to claim 11, characterized in that Determining at least one key causal indicator based on the impact level includes: Determine the current indicator layer to which the causal indicators at each level belong; When the current indicator layer has an associated cause indicator layer, obtaining a first influence degree of the hierarchical causal indicator in the current indicator layer and a second influence degree of the hierarchical causal indicator in the cause indicator layer, wherein the cause indicator layer includes other hierarchical causal indicators that have an influence on the hierarchical causal indicator in the current indicator layer; When the first influence degree is greater than the second influence degree, determining the hierarchical causal indicator in the current indicator layer as at least one key causal indicator; When the first impact degree is smaller than the second impact degree, the cause indicator layer is used as a new current indicator layer, and at least one key causal indicator is determined based on the new current indicator layer.

13. An electronic device, characterized in that: include: A memory and a processor; wherein the memory is used to store one or more computer instructions, wherein when the one or more computer instructions are executed by the processor, the operation management method according to any one of claims 1 to 12 is implemented.

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