A target user screening method and device, electronic equipment and storage medium

Abstract

The application discloses a target user screening method and device, electronic equipment and a storage medium. The method comprises the following steps: obtaining front-end behavior data and back-end storage data of a candidate user; screening the front-end behavior data and the back-end storage data according to candidate influencing factors to obtain target behavior data and target storage data; determining a comprehensive influence degree according to the target behavior data and the target storage data; and judging whether the candidate user is a target user according to the comprehensive influence degree. The technical scheme of the application improves the data operation efficiency, reduces the operation pressure of the operation equipment, avoids the error caused by determining the influence degree only according to the target behavior data or only according to the target storage data, improves the accuracy of the final operation result, improves the accuracy of selecting the target user, avoids the influence on non-target users in subsequent marketing, and reduces the marketing cost.

Description

Technical Field

[0001] This invention relates to the field of e-commerce technology, and in particular to a method, apparatus, electronic device, and storage medium for screening target users. Background Technology

[0002] In the more than two decades of internet development, mobile internet has deeply penetrated various industries and groups in China. With the increase in users and the expanding coverage, the internet industry has entered a red ocean phase. Simply relying on increasing users to drive GMV growth is increasingly unable to meet the company's development needs.

[0003] In the next phase, more and more internet companies are seeking to develop value-added business products among existing users and increase revenue and profits from existing users. Among these, marketing and conversion of disconnected users will be the focus of development for various companies in the future, but how to identify target users among disconnected users remains a major challenge. Summary of the Invention

[0004] This invention provides a target user screening method, device, electronic device, and storage medium to solve the problem of wasted marketing resources when marketing to non-target users during the breakpoint marketing process.

[0005] According to one aspect of the present invention, a method for screening target users is provided, the method comprising:

[0006] Acquire front-end behavioral data and back-end stored data of candidate users;

[0007] Based on the candidate influencing factors, the front-end behavioral data and back-end storage data are filtered to obtain the target behavioral data and target storage data;

[0008] The overall impact level is determined based on target behavior data and target storage data;

[0009] Whether a candidate user is a target user is determined based on the overall degree of influence.

[0010] According to another aspect of the present invention, a target user screening device is provided, the device comprising:

[0011] The data acquisition module is used to acquire front-end behavioral data and back-end stored data of candidate users;

[0012] The data filtering module is used to filter front-end behavioral data and back-end stored data based on candidate influencing factors to obtain target behavioral data and target stored data.

[0013] The impact determination module is used to determine the overall impact based on target behavior data and target stored data.

[0014] The target user identification module is used to determine whether a candidate user is a target user based on the overall impact.

[0015] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising:

[0016] At least one processor; and

[0017] A memory that is communicatively connected to at least one processor; wherein,

[0018] The memory stores a computer program that can be executed by at least one processor, such that the at least one processor is able to perform the target user screening method of any embodiment of the present invention.

[0019] According to another aspect of the present invention, a computer-readable storage medium is provided, which stores computer instructions for causing a processor to execute and implement the target user screening method of any embodiment of the present invention.

[0020] According to the technical solution of this invention, by filtering front-end behavioral data and back-end stored data based on candidate influencing factors, target behavioral data and target stored data are obtained, improving the efficiency of data processing and reducing the computational burden on computing devices. By determining the comprehensive influence level based on the target behavioral data and target stored data, errors arising from determining the influence level of candidate users solely based on target behavioral data or solely based on target stored data are avoided, improving the accuracy of the final calculation results. Determining whether a candidate user is a target user based on the comprehensive influence level improves the accuracy of target user selection. By adopting the above technical solution, the accuracy of target user selection is improved, ensuring that subsequent remarketing does not negatively impact non-target users, thus reducing marketing costs.

[0021] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0022] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0023] Figure 1 This is a flowchart of a target user screening method provided in Embodiment 1 of the present invention;

[0024] Figure 2 This is a flowchart of another target user screening method provided in Embodiment 2 of the present invention.

[0025] Figure 3 This is a schematic diagram of a target user screening device according to Embodiment 3 of the present invention;

[0026] Figure 4 This is a schematic diagram of the structure of an electronic device that implements the target user screening method of the present invention. Detailed Implementation

[0027] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0028] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0029] Example 1

[0030] Figure 1 This is a flowchart illustrating a target user screening method provided in Embodiment 1 of the present invention. This embodiment is applicable to situations where candidate users are precisely screened during breakpoint marketing. This method can be executed by a target user screening device, which can be implemented in hardware and / or software and can be configured in an electronic device with data processing capabilities. Figure 1 As shown, the method includes:

[0031] S110: Obtain front-end behavior data and back-end storage data of candidate users.

[0032] Candidate users can be all users registered with the software. Front-end behavioral data can be the user's actions during front-end operations. Back-end stored data can be user information stored on the back-end server, including registration time, account membership level, and account membership duration.

[0033] After a candidate user registers, the backend storage data of the candidate user stored in the backend server is read. The account information includes registration time, account membership level, and account membership time. In addition, the frontend behavior data generated by the candidate user during frontend operations is also read.

[0034] In one alternative approach, obtaining the front-end behavior data of candidate users may include:

[0035] Based on the components included in the software used by candidate users, obtain the candidate users' usage information;

[0036] The usage information includes at least the interface access time and component operation information.

[0037] When reading the front-end behavior data of candidate users, it is not possible to directly obtain the user's front-end behavior data. It is necessary to use the components embedded in the software used by the candidate users to report the user's operation process and obtain the candidate user's front-end behavior data.

[0038] The obtained front-end behavior data of candidate users includes at least interface access time and component operation information. Interface access time refers to the time a candidate user spends on different software interfaces during front-end operations. Component operation information refers to the components triggered by the candidate user's actions within the front-end software. Components can be user-interactive parts of the front-end software, including but not limited to account input boxes, login buttons, and checkboxes.

[0039] In one alternative approach, obtaining the backend storage data of candidate users may include steps A1-A2:

[0040] Step A1: Obtain the change information generated by the database.

[0041] The change information includes at least the data record change field and the data record change content corresponding to the data record change field;

[0042] Step A2: Parse the change information to obtain the backend storage data.

[0043] Change information can be the content of changes when the information of a candidate user stored in the backend server changes. The change information includes at least the data record change field and the data record change content corresponding to the data record change field.

[0044] When retrieving candidate user backend storage data, it is necessary to obtain the candidate user change information stored in the candidate server's database, identify the data that has changed among the candidate users, and parse the data to obtain backend storage data with the same data structure as the frontend behavior data.

[0045] S120. Based on the candidate influencing factors, filter the front-end behavioral data and back-end storage data to obtain the target behavioral data and target storage data.

[0046] Target behavioral data can be obtained by filtering invalid data from the front-end behavioral data of candidate users. Invalid data can include meaningless actions triggered by candidate users while using the front-end software, such as clicking on background information with no feedback, or pre-defined action information by operators. Target stored data can be obtained by filtering irrelevant information from the back-end stored data of candidate users. Irrelevant information can be pre-defined data by operators. Candidate influencing factors are determined by operators based on their operational experience and are used to filter user front-end behavioral data and back-end stored data related to operational needs. Operational needs can be requirements determined by operators based on the data needed during the operational process.

[0047] Since the front-end behavior data and back-end storage data of candidate users contain a large amount of information that is not of interest to the operators, directly calculating the obtained front-end behavior data and back-end storage data will affect the efficiency of the operation and put a lot of pressure on the computing equipment. Therefore, after obtaining the front-end behavior data and back-end storage data of candidate users, it is necessary to filter the front-end behavior data and back-end storage data to obtain target behavior data and target storage data with smaller data volume that are of interest to the operators.

[0048] S130. Determine the overall impact level based on target behavior data and target storage data.

[0049] The overall impact level can be used to determine the extent to which a candidate user can be influenced.

[0050] After obtaining the target behavior data and target storage data, the differences between the target behavior data and the target storage data may lead to the final determination of the degree of impact being difficult to meet the actual needs and produce certain errors. Therefore, it is necessary to conduct a comprehensive analysis of the target behavior data and the target storage data to obtain the comprehensive degree of impact.

[0051] By determining the comprehensive degree of influence based on target behavior data and target storage data, the error that occurs when determining the degree of influence of candidate users is avoided when relying solely on target behavior data or target storage data, thus improving the accuracy of the final calculation results.

[0052] In one alternative approach, determining the comprehensive impact based on target behavioral data and target stored data may include steps B1-B3:

[0053] Step B1: Identify the interfering factors between the target behavior data and the target stored data, and determine the degree of interference corresponding to the interfering factors.

[0054] Step B2: Determine the degree of influence of the behavior based on the target behavior data, and determine the degree of influence of the storage based on the target storage data.

[0055] Step B3: Determine the overall impact level based on the degree of behavioral impact, the degree of storage impact, and the degree of interference.

[0056] Interference factors can be data that mutually influences the target behavioral data and the target stored data. The degree of interference refers to the magnitude of the interference factor's impact on the overall influence. The degree of behavioral influence can be determined based on the target behavioral data, and its impact on candidate users. The degree of storage influence can be determined based on the storage influence, and its impact on candidate users.

[0057] For example, if the target behavior data shows that a candidate user clicks on a certain fixed content 10 times a day, it can be determined that the candidate user has a high interest in the content, and in this case, it can be determined that the behavior determined by the target behavior data of the candidate user has a high degree of influence.

[0058] If the target storage data shows that the candidate user's membership has been continuously renewed for a year, it can be determined that the candidate user is highly likely to continue to renew the membership, and the storage impact determined by the target storage data of the candidate user is high.

[0059] After obtaining the target behavior data and the target storage data, it is necessary to identify the interfering factors that influence the target behavior data and the target storage data, and determine the degree of influence of the interfering factors.

[0060] For example, the target behavioral data is that the user stays on the membership renewal interface for 3 seconds, and the target stored data is that the user has continuously renewed their membership for more than 1 year. If only the target behavioral data is judged, it may be concluded that the user will not renew their membership. If only the target stored data is judged, it may be concluded that the user will continue to renew their membership. At this time, the conclusions are contradictory. Therefore, it is necessary to determine the data that influences each other between the target behavioral data and the target stored data, and to determine the degree of interference of this interfering factor.

[0061] After obtaining the target behavior data and the target storage data, it is necessary to determine the degree of influence of each of the target behavior data and the target storage data on the user, so as to obtain the degree of influence of behavior and the degree of influence of storage.

[0062] By obtaining the degree of behavioral impact, storage impact, and interference, we can determine the degree of impact of the analysis results obtained after analyzing the target behavioral data, target storage data, and interference factors on candidate users, and fit the final comprehensive impact degree according to different impact degrees.

[0063] In one alternative approach, determining the degree of impact of the behavior based on the target behavior data may include steps C1-C3:

[0064] Step C1: Determine the impact of the candidate user's first action based on the interface access time.

[0065] Step C2: Determine the degree of influence of the candidate user's second action based on the component operation information.

[0066] Step C3: Fit the influence degree of the first behavior and the influence degree of the second behavior to obtain the influence degree of the behavior.

[0067] The degree of influence of the first behavior can be the degree of influence of the interface access time on candidate users.

[0068] The second behavior's degree of influence can be the degree of influence of component operation information on candidate users.

[0069] After obtaining the target behavior data, since the target behavior data contains interface access time and component operation information, it is also necessary to determine the degree of influence of interface access time and component operation information.

[0070] After determining the interface access time, the influence of a candidate user's first action can be determined based on the length of the interface access time. However, the magnitude of the first action's influence is not directly related to the length of the interface access time. A direct relationship, however, is that a longer interface access time generally results in a greater influence of the first action.

[0071] For example, if a candidate user's interface access time is 10 minutes, it is difficult to determine whether the candidate user entered the interface by accident or browsed the interface for a long time.

[0072] After obtaining the component operation information, since triggering different operations may represent different meanings for different components, it is necessary to determine the degree of influence of the second behavior based on the component operation information.

[0073] For example, if a candidate user clicks the membership renewal page and then quickly clicks the back button to cancel the page, it can be determined that the candidate user does not intend to renew their membership.

[0074] After obtaining the influence levels of the first and second behaviors, since there may be large errors in the data fitting results when fitting multiple data, it is necessary to fit the influence levels of the first and second behaviors to obtain the influence level of the behavior in order to reduce the error when fitting the comprehensive influence level.

[0075] In one alternative approach, the storage impact is determined based on the target stored data, including:

[0076] The extent of storage impact is determined based on the data record change fields and the corresponding data record change content.

[0077] A data record change field can be a field in the user data stored on the backend server that has been modified. The data record change content can be the data in the data record where the change field has changed.

[0078] After obtaining the target storage data, it is necessary to determine whether the data in the target storage data has changed, and in order to determine whether it is necessary to determine the degree of storage impact based on the target storage data.

[0079] For example, if a candidate user has 180 days remaining on their membership, it can be determined that the user does not need to renew. However, if only 3 days remain, renewal may be necessary, requiring a assessment of the impact on storage based on the target storage data. Furthermore, if a second check of the candidate user's target storage data reveals that the data remains unchanged, the impact on storage will be reassessed.

[0080] After the target storage data of a candidate user changes, it is necessary to determine the changed fields of the target storage data of the candidate user and the changes that have occurred in those fields. Therefore, it is necessary to determine the data record change fields and the data record change content corresponding to the data record change fields, and determine the final storage impact based on the changes.

[0081] S140. Determine whether a candidate user is a target user based on the overall impact.

[0082] After obtaining the combined impact determined by the target behavior data and the target storage data, candidate users can be judged to determine whether the candidate user is the target user.

[0083] According to the technical solution of this invention, by filtering front-end behavioral data and back-end stored data based on candidate influencing factors, target behavioral data and target stored data are obtained, improving the efficiency of data processing and reducing the computational burden on computing devices. By determining the comprehensive influence level based on the target behavioral data and target stored data, errors arising from determining the influence level of candidate users solely based on target behavioral data or solely based on target stored data are avoided, improving the accuracy of the final calculation results. Determining whether a candidate user is a target user based on the comprehensive influence level improves the accuracy of target user selection. By adopting the above technical solution, the accuracy of target user selection is improved, ensuring that subsequent remarketing does not negatively impact non-target users, thus reducing marketing costs.

[0084] Example 2

[0085] Figure 2 This invention provides a flowchart of another target user screening method. Based on the above embodiments, this embodiment further optimizes the process of determining whether a candidate user is a target user according to the comprehensive influence degree in the aforementioned embodiments. This embodiment can be combined with various optional solutions in one or more of the above embodiments. Figure 2 As shown, the target user screening method in this embodiment may include the following steps:

[0086] S210: Obtain front-end behavior data and back-end storage data of candidate users.

[0087] S220. Based on the candidate influencing factors, filter the front-end behavioral data and back-end storage data to obtain the target behavioral data and target storage data.

[0088] S230. Determine the overall impact level based on target behavior data and target storage data.

[0089] S240. Match the overall impact of candidate users with the preset impact.

[0090] S250. If the overall influence of the candidate user meets the preset influence level, then the candidate user is determined as the target user.

[0091] The target users can be candidate users whose overall influence reaches a preset threshold.

[0092] The preset level of influence can be predetermined, representing the minimum number of users that a candidate user can be influenced.

[0093] After obtaining the overall influence level of the candidate users, the overall influence level is matched with the preset influence level to determine whether the overall influence level of the candidate users reaches the preset influence level of the candidate users.

[0094] If the overall influence of a candidate user reaches the preset influence level for that candidate user, then that candidate user is determined to be the target user.

[0095] Optionally, after determining the overall influence of candidate users and identifying them as target users, the preset threshold for candidate users is reduced by a certain step to obtain a first preset threshold. This first preset threshold is then used as the threshold for judging the overall influence of the target user in the next evaluation. The step value can be data determined based on historical data and the operational experience of staff, and its size is smaller than the preset threshold. The first preset threshold can be the threshold obtained by reducing the preset threshold by one step.

[0096] For example, when the preset threshold is 80, the stage value is 5, and the overall influence of the candidate user is 90, it can be determined that the overall influence of the candidate user is greater than the preset threshold, indicating that the candidate user is the target user. At this time, the preset threshold will be reduced by one stage value to obtain the first preset threshold, which is 75.

[0097] By employing the technical solution of this invention, the comprehensive influence of candidate users is matched with the preset influence level to determine the candidate users as target users, thereby making the determination process of target users clear and improving the accuracy of the final determination result.

[0098] Example 3

[0099] Figure 3 This invention provides a structural block diagram of a target user screening device, applicable to situations requiring precise screening of candidate users during breakpoint marketing. This target user screening device can be implemented in hardware and / or software and can be configured in an electronic device with data processing capabilities. Figure 3 As shown, the target user screening device of this embodiment may include: a data acquisition module 310, a data screening module 320, an influence degree determination module 330, and a target user determination module 340. Wherein:

[0100] Data acquisition module 310 is used to acquire front-end behavior data and back-end storage data of candidate users;

[0101] The data filtering module 320 is used to filter front-end behavioral data and back-end stored data based on candidate influencing factors to obtain target behavioral data and target stored data.

[0102] The impact degree determination module 330 is used to determine the overall impact degree based on the target behavior data and the target storage data;

[0103] The target user identification module 340 is used to determine whether a candidate user is a target user based on the degree of comprehensive influence.

[0104] Based on the above embodiments, optionally, the influence degree determination module 330 includes:

[0105] The interference level determination unit is used to determine the interference factors between the target behavior data and the target stored data, and to determine the interference level corresponding to the interference factors;

[0106] The impact degree determination unit is used to determine the degree of impact of the behavior based on the target behavior data and to determine the degree of impact of the storage based on the target storage data.

[0107] The comprehensive impact determination unit is used to determine the comprehensive impact based on the degree of behavioral impact, the degree of storage impact, and the degree of interference.

[0108] Based on the above embodiments, optionally, the data acquisition module 310 includes:

[0109] The information acquisition unit is used to acquire the usage information of candidate users based on the components contained in the software used by the candidate users;

[0110] The usage information includes at least the interface access time and component operation information.

[0111] Based on the above embodiments, optionally, the influence degree determination module 330 includes:

[0112] The first influence determination unit is used to determine the influence of the candidate user's first behavior based on the interface access time.

[0113] The second influence degree determination unit is used to determine the influence degree of the candidate user's second behavior based on the component operation information;

[0114] The influence degree fitting unit is used to fit the influence degree of the first behavior and the influence degree of the second behavior to obtain the influence degree of the behavior.

[0115] Based on the above embodiments, optionally, the data acquisition module 310 includes:

[0116] The change information acquisition unit is used to acquire change information generated by the database; wherein, the change information includes at least the data record change field and the data record change content corresponding to the data record change field;

[0117] The change information parsing unit is used to parse the change information to obtain the data stored in the backend.

[0118] Based on the above embodiments, optionally, the influence degree determination module 330 includes:

[0119] The storage impact determination unit is used to determine the storage impact based on the data record change fields and the corresponding data record change content.

[0120] Based on the above embodiments, optionally, the target user determination module 340 includes:

[0121] The matching unit is used to match the overall influence of candidate users with the preset influence level;

[0122] The target user selection unit is used to determine the candidate user as the target user if the overall influence of the candidate user meets the preset influence level.

[0123] The target user screening device provided in this embodiment of the invention can execute the target user screening method provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the method execution.

[0124] Example 4

[0125] Figure 4 A schematic diagram of an electronic device 10 that can be used to implement embodiments of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0126] like Figure 4 As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12 or a random access memory (RAM) 13, communicatively connected to the at least one processor 11. The memory stores computer programs executable by the at least one processor. The processor 11 can perform various appropriate actions and processes based on the computer program stored in the ROM 12 or loaded from storage unit 18 into the RAM 13. The RAM 13 may also store various programs and data required for the operation of the electronic device 10. The processor 11, ROM 12, and RAM 13 are interconnected via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0127] Multiple components in electronic device 10 are connected to I / O interface 15, including: input unit 16, such as keyboard, mouse, etc.; output unit 17, such as various types of displays, speakers, etc.; storage unit 18, such as disk, optical disk, etc.; and communication unit 19, such as network card, modem, wireless transceiver, etc. Communication unit 19 allows electronic device 10 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0128] Processor 11 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 11 performs the various methods and processes described above, such as target user screening methods.

[0129] In some embodiments, the target user screening method may be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on electronic device 10 via ROM 12 and / or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the target user screening method described above may be performed. Alternatively, in other embodiments, processor 11 may be configured to perform the target user screening method by any other suitable means (e.g., by means of firmware).

[0130] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0131] Computer programs used to implement the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0132] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0133] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0134] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or computing systems that include middleware components (e.g., application servers), or computing systems that include frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0135] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0136] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0137] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A method for selecting target users, characterized in that, include: Acquire front-end behavioral data and back-end stored data of candidate users; The front-end behavior data and back-end storage data are filtered based on candidate influencing factors to obtain target behavior data and target storage data. The overall impact level is determined based on the target behavior data and the target storage data; Determine whether the candidate user is the target user based on the overall degree of influence. Among them, the candidate influencing factors are determined by the operations staff based on the degree of influence of front-end behavioral data and back-end stored data on the target users; The determination of the comprehensive impact degree based on the target behavior data and the target stored data includes: Identify the interfering factors between the target behavior data and the target stored data, and determine the degree of interference corresponding to the interfering factors; The degree of influence of the behavior is determined based on the target behavior data, and the degree of influence of the storage is determined based on the target storage data; The overall impact level is determined based on the degree of impact of the behavior, the degree of impact of the storage, and the degree of interference.

2. The method according to claim 1, characterized in that, The acquisition of candidate user front-end behavior data includes: Based on the components included in the software used by the candidate user, obtain the candidate user's usage information; The usage information includes at least the interface access time and component operation information.

3. The method according to claim 2, characterized in that, Determining the degree of influence of a behavior based on the target behavior data includes: The degree of influence of the candidate user's first action is determined based on the interface access time. Based on the component operation information, determine the degree of influence of the candidate user's second behavior; The degree of influence of the first behavior and the degree of influence of the second behavior are fitted together to obtain the degree of influence of the behavior.

4. The method according to claim 1, characterized in that, The process of obtaining the backend storage data of candidate users includes: Obtain change information generated by the database; wherein, the change information includes at least a data record change field and the data record change content corresponding to the data record change field; The change information is parsed to obtain the backend stored data.

5. The method according to claim 4, characterized in that, Determining the storage impact level based on the target stored data includes: The degree of impact on storage is determined based on the data record change field and the corresponding data record change content.

6. The method according to claim 1, characterized in that, The step of determining whether a candidate user is a target user based on the overall influence includes: The overall influence level of the candidate users is matched with the preset influence level; If the overall influence of the candidate user meets the preset influence level, then the candidate user is determined to be the target user.

7. A target user screening device, characterized in that, include: The data acquisition module is used to acquire front-end behavioral data and back-end stored data of candidate users; The data filtering module is used to filter the front-end behavioral data and back-end stored data according to candidate influencing factors to obtain target behavioral data and target stored data. The impact degree determination module is used to determine the overall impact degree based on the target behavior data and the target storage data; The target user determination module is used to determine whether the candidate user is a target user based on the overall influence level. The module for determining the degree of impact includes: Identify the interfering factors between the target behavior data and the target stored data, and determine the degree of interference corresponding to the interfering factors; The degree of influence of the behavior is determined based on the target behavior data, and the degree of influence of the storage is determined based on the target storage data; The overall impact level is determined based on the degree of impact of the behavior, the degree of impact of the storage, and the degree of interference.

8. An electronic device, characterized in that, The electronic device includes: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the target user screening method according to any one of claims 1-6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that cause a processor to execute the target user screening method according to any one of claims 1-6.

Images