Shopping mall operation method and device based on vehicle networking user behavior

Abstract

Embodiments of the present application relate to a kind of based on the operation method and device of commercial center of vehicle networking user behavior, comprising: based on the preset rule, the entire user of using vehicle networking user end is carried out basic user group, obtain multiple basic user groups;The multiple behavior parameter information of each user of the basic user group in historical time period is counted;Based on the multiple behavior parameter information, user group division is carried out for each user, obtain multiple target operation groups;Corresponding operation strategy is formulated for the multiple target operation groups, and target user in the multiple target operation groups is maintained based on the operation strategy.Thereby, group is carried out to user, group division is carried out according to user behavior, corresponding operation strategy is formulated for different groups to carry out user maintenance, can reach the effect of fine operation and maintenance user, improve user experience.

Description

E-commerce operation method and device based on vehicle-to-everything (V2X) user behavior Technical Field

[0001] The embodiments of the present invention relate to the field of data processing, and in particular to a method and apparatus for operating an e-commerce platform based on user behavior in the Internet of Vehicles. Background Technology

[0002] With the continuous development of internet technology, merchants are focusing on developing online platforms to meet current user needs. When users use these platforms, they can accumulate points through activities such as check-ins, which can then be redeemed for goods in a points mall.

[0003] However, the products are displayed in the same way to all users, without any targeting; the products are configured uniformly by the backend, so all users see the same products, without any user segmentation based on user behavior; and the operation strategy is the same for all users, without adopting different activation strategies for different users. Summary of the Invention

[0004] In view of this, in order to solve the above-mentioned technical problems or some of the technical problems, the present invention provides a method and apparatus for operating an e-commerce platform based on the behavior of Internet of Vehicles users.

[0005] In a first aspect, embodiments of the present invention provide a method for operating an online marketplace based on user behavior in the Internet of Vehicles (IoV), comprising:

[0006] Based on preset rules, all users using the vehicle-to-everything (V2X) user terminal will be divided into basic user groups to obtain multiple basic user groups.

[0007] Collect multiple behavioral parameter information for each user in the basic user group within the historical time period;

[0008] Based on the aforementioned multiple behavioral parameter information, each user is segmented into multiple target operational groups;

[0009] Develop corresponding operational strategies for the multiple target operational groups, and maintain target users within the multiple target operational groups based on the operational strategies.

[0010] In one possible implementation, the method further includes:

[0011] Obtain basic information of all users using the vehicle-to-everything (V2X) user terminal;

[0012] Based on the aforementioned basic information and multiple preset grouping parameters, all users are divided into basic user groups, resulting in multiple basic user groups. The multiple grouping parameters include at least region, age, gender, and preferences.

[0013] In one possible implementation, the method further includes:

[0014] The multiple behavioral parameter information includes at least: behavior frequency, behavior value, and the interval between the most recent behaviors;

[0015] The frequency of key actions for each user within a historical time period is statistically analyzed. These key actions include at least remote control of the vehicle, checking vehicle status, checking vehicle information, sharing the vehicle, Bluetooth operation, and checking information on new vehicles.

[0016] The number of points earned by each user within a historical time period is used as behavioral value.

[0017] The time interval between each user's most recent use of the vehicle connectivity function and the current time is statistically analyzed within a historical period.

[0018] In one possible implementation, the method further includes:

[0019] Based on each user's behavior frequency, behavior value, and recent behavior interval, a preset user behavior segmentation model is used to divide each user into user groups, resulting in multiple target operation groups.

[0020] In one possible implementation, the method further includes:

[0021] Preset average behavior frequency, average behavior value, and average interval between recent behaviors;

[0022] Based on the difference between behavior frequency and average behavior frequency, the difference between behavior value and average behavior value, and the difference between the most recent behavior interval and the average most recent behavior interval, each user is divided into user groups to obtain multiple target operation groups.

[0023] Secondly, embodiments of the present invention provide an e-commerce operation device based on vehicle network user behavior, comprising:

[0024] The segmentation module is used to divide all users using the vehicle-to-everything (V2X) user terminal into basic user groups based on preset rules, resulting in multiple basic user groups.

[0025] The statistics module is used to collect multiple behavioral parameter information for each user in the basic user group within a historical time period.

[0026] The segmentation module is also used to segment each user group based on the multiple behavioral parameter information to obtain multiple target operation groups;

[0027] The operation and maintenance module is used to formulate corresponding operation strategies for the multiple target operation groups and maintain the target users within the multiple target operation groups based on the operation strategies.

[0028] Thirdly, embodiments of the present invention provide a server, including a processor and a memory, wherein the processor is configured to execute an e-commerce operation program based on vehicle network user behavior stored in the memory, so as to implement the e-commerce operation method based on vehicle network user behavior described in the first aspect above.

[0029] Fourthly, embodiments of the present invention provide a storage medium, comprising: the storage medium storing one or more programs, the one or more programs being executable by one or more processors to implement the e-commerce operation method based on vehicle network user behavior described in the first aspect above.

[0030] The e-commerce operation solution based on vehicle-to-everything (V2X) user behavior provided in this invention involves: segmenting all users of the V2X user terminal into multiple basic user groups based on preset rules; statistically analyzing multiple behavioral parameters of each user in each basic user group over a historical period; further dividing each user into multiple target operation groups based on these behavioral parameters; and developing corresponding operation strategies for each target operation group and maintaining target users within those groups based on these strategies. Compared to existing e-commerce operation methods that apply the same operation strategy to all users without tailoring activation strategies for different users, this solution segments users, divides them into groups based on user behavior, and develops corresponding operation strategies for different groups to maintain user engagement. This achieves refined operation and user retention, improving the user experience. Attached Figure Description

[0031] Figure 1 is a flowchart illustrating a method for operating an online marketplace based on user behavior in the Internet of Vehicles, according to an embodiment of the present invention.

[0032] Figure 2 is a flowchart illustrating another method for operating an online marketplace based on user behavior in the Internet of Vehicles, provided by an embodiment of the present invention.

[0033] Figure 3 is a schematic diagram of the structure of an e-commerce operation device based on vehicle network user behavior provided in an embodiment of the present invention;

[0034] Figure 4 is a schematic diagram of the structure of a server provided in an embodiment of the present invention. Detailed Implementation

[0035] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0036] To facilitate understanding of the embodiments of the present invention, further explanations and descriptions will be provided below with reference to the accompanying drawings and specific embodiments. These embodiments do not constitute a limitation on the embodiments of the present invention.

[0037] Figure 1 is a flowchart illustrating a method for operating an online marketplace based on user behavior in the Internet of Vehicles (IoV) according to an embodiment of the present invention. As shown in Figure 1, the method specifically includes:

[0038] S11. Based on preset rules, all users using the vehicle network user terminal will be divided into basic user groups to obtain multiple basic user groups.

[0039] In this embodiment of the invention, the preset rule, namely the basic user segmentation rule, can be used to segment users based on basic information filled in by users in the vehicle-to-everything (V2X) user terminal APP. This basic information includes, but is not limited to, user location, age, gender, and preferences. Users are assigned different tags based on their location, age, gender, and preferences. Users with the highest degree of similarity in tag categories are grouped into a basic user group. This segmentation is the most basic user segmentation. Different purchase push strategies can be applied when pushing or purchasing points-based goods to different basic user groups.

[0040] For example, user Zhang San is located in city A, is 30 years old, male, likes sports, and prefers B-class car models; user Li Si is located in city A, is 32 years old, male, likes sports, and prefers B-class car models; user Wang Wu is located in city C, is 45 years old, male, likes chess, and prefers B-class car models. Therefore, Zhang San and Li Si have 5 common tag categories, Zhang San and Wang Wu have 2 common tag categories, and Li Si and Wang Wu have 2 common tag categories. Thus, Zhang San and Li Si are grouped into a basic user group, while Wang Wu is further grouped by comparing him with other users.

[0041] It should be noted that the age difference can be set to no more than 3 years, which means they are considered to have the same label. The age difference setting is determined according to the actual situation, and this invention does not impose any specific limitations.

[0042] S12. Collect multiple behavioral parameter information of each user in the basic user group within the historical time period.

[0043] Furthermore, multiple behavioral parameter information can be obtained by statistically analyzing the behavioral parameters of each user in each basic user group over a historical period of time through multiple dimensions.

[0044] S13. Based on the multiple behavioral parameter information, each user is divided into user groups to obtain multiple target operation groups.

[0045] S14. Formulate corresponding operation strategies for the multiple target operation groups, and maintain target users within the multiple target operation groups based on the operation strategies.

[0046] Based on the statistically obtained behavioral parameters for each user, each user is regrouped. These regrouped groups constitute the target operational groups. When conducting user operations and maintenance, product recommendations or other operational maintenance can be tailored to the attributes of the target groups, including but not limited to displaying targeted products, pushing activity information, and promoting preferential policies. Specific operational maintenance methods are detailed in the embodiment shown in Figure 2.

[0047] The e-commerce operation method based on vehicle-to-everything (V2X) user behavior provided in this invention involves: segmenting all users using V2X user terminals into multiple basic user groups based on preset rules; statistically analyzing multiple behavioral parameters for each user in each basic user group over a historical period; further dividing each user into multiple target operation groups based on these behavioral parameters; formulating corresponding operation strategies for each target operation group; and maintaining target users within each target operation group based on these operation strategies. Compared to existing e-commerce operation methods that apply the same operation strategy to all users without tailoring activation strategies for different users, this method segments users, divides them into groups based on user behavior, and formulates corresponding operation strategies for different groups to maintain users. This achieves refined operation and user maintenance, improving the user experience.

[0048] Figure 2 is a flowchart illustrating another method for operating an online marketplace based on user behavior in the Internet of Vehicles, as provided in an embodiment of the present invention. As shown in Figure 2, the method specifically includes:

[0049] S21. Obtain basic information of all users using the vehicle networking user terminal.

[0050] S22. Based on the basic information and multiple preset grouping parameters, all users are divided into basic user groups to obtain multiple basic user groups. The multiple grouping parameters include at least region, age, gender, and preferences.

[0051] In this embodiment of the invention, users are first categorized based on basic information entered by the user in the vehicle-to-everything (V2X) user app. This basic information includes, but is not limited to, the user's location, age, gender, and preferences. Users are then tagged based on these factors, and those with the most similar tag categories are grouped into a basic user group. This is the most fundamental user group. Different purchasing strategies can be implemented for different basic user groups when pushing or purchasing points-based goods.

[0052] S23. Statistically analyze the frequency of key actions for each user within a historical time period. The key actions include at least remote control of the vehicle, viewing vehicle status, viewing vehicle information, sharing the vehicle, Bluetooth operation, and viewing information on new vehicles.

[0053] In this embodiment of the invention, the user's multiple behavioral parameter information includes at least: behavior frequency, behavior value, and the interval between recent behaviors; wherein, behavior frequency refers to the frequency of key actions of the user in the vehicle network user terminal APP within a historical time period, and key actions include the frequency of behaviors such as remote control of the vehicle (unlocking, locking, finding the vehicle, turning on the air conditioner, turning on the seat heating, closing the windows, controlling the tailgate, controlling the sunroof, etc.), checking vehicle status, checking vehicle information, sharing the vehicle, Bluetooth-related operations, and checking information on new vehicles.

[0054] S24. Calculate the number of points each user earns within a historical time period as behavioral value.

[0055] Behavioral value refers to the number of points a user earns within a historical period, and it is the number of points each user earns within a historical period.

[0056] S25. Calculate the time interval between each user's most recent use of the vehicle networking function and the current time within the historical time period.

[0057] The most recent behavior interval refers to the time interval between a user's most recent use of the vehicle networking function within a historical time period and the current time. The most recent behavior of each user within a historical time period and the current time are counted.

[0058] S26. Preset average behavior frequency, average behavior value, and average interval between recent behaviors.

[0059] In this embodiment of the invention, average behavior frequency, average behavior value, and average recent behavior interval can be preset for comparison with actual user behavior parameter information.

[0060] S27. Based on the difference between behavior frequency and average behavior frequency, the difference between behavior value and average behavior value, and the difference between the most recent behavior interval and the average most recent behavior interval, each user is divided into user groups to obtain multiple target operation groups.

[0061] In this embodiment of the invention, a pre-defined vehicle network user behavior segmentation model table can be used, as shown in Table 1:

[0062] Table 1

[0063]

[0064]

[0065] As shown in Table 1, key value customers are those whose recent opening frequency, number of openings within a historical time period, and behavioral value are all higher than the average, and can be identified as core users.

[0066] Key customer retention: Recent open time is below average, but the number of open times and behavioral value in the historical period are above average. This indicates that this is a loyal customer who has not visited for some time and needs to be proactively contacted.

[0067] Key customers to develop: Users whose recent page view time and behavioral value are above average, but whose page view frequency is below average over a historical period, have low loyalty, and are high-potential users who must be prioritized for development.

[0068] Key customers to retain: Users whose recent opening time and number of openings within a historical time period are lower than the average, but whose behavioral value is higher than the average, may be users who are about to churn or have already churned. We should actively develop retention measures.

[0069] For the different user groups mentioned above, the operational strategy is to send targeted content related to car products to key value customers to maintain user engagement.

[0070] Maintaining key customers: A small campaign can be planned for these users in the near future to reactivate them.

[0071] For key customer development: Consider increasing push notifications to re-engage users.

[0072] Key customer retention strategies include offering specific incentives, such as limited-time discounts.

[0073] Optionally, corresponding operational strategies can also be developed for secondary users in the table to attract and develop users.

[0074] The e-commerce operation method based on vehicle-to-everything (V2X) user behavior provided in this invention involves: segmenting all users using V2X user terminals into multiple basic user groups based on preset rules; statistically analyzing multiple behavioral parameters for each user in each basic user group over a historical period; further dividing each user into multiple target operation groups based on these behavioral parameters; formulating corresponding operation strategies for each target operation group; and maintaining target users within each target operation group based on these operation strategies. This method, by segmenting users, dividing them into groups based on user behavior, and formulating corresponding operation strategies for different groups to maintain user engagement, achieves refined operation and user retention, thereby improving user experience.

[0075] Figure 3 is a schematic diagram of the structure of an e-commerce operation device based on vehicle network user behavior provided in an embodiment of the present invention, specifically including:

[0076] The segmentation module 301 is used to perform basic user grouping on all users using the vehicle network user terminal based on preset rules, resulting in multiple basic user groups.

[0077] The statistics module 302 is used to collect multiple behavioral parameter information of each user in the basic user group during a historical time period;

[0078] The segmentation module 301 is also used to segment each user group based on the multiple behavioral parameter information to obtain multiple target operation groups;

[0079] The operation and maintenance module 303 is used to formulate corresponding operation strategies for the multiple target operation groups and maintain target users within the multiple target operation groups based on the operation strategies.

[0080] In one possible implementation, the segmentation module 301 is specifically used to obtain basic information of all users using the vehicle network user terminal; based on the basic information and multiple preset segmentation parameter information, all users are segmented into basic user groups to obtain multiple basic user groups, wherein the multiple segmentation parameter information includes at least region, age, gender, and preferences.

[0081] In one possible implementation, the statistics module 302 is specifically used to count the frequency of key actions of each user within a historical time period. The key actions include at least remote control of the vehicle, checking vehicle status, checking vehicle information, sharing the vehicle, Bluetooth operation, and checking information on new vehicles. The module also counts the number of points earned by each user within the historical time period as behavioral value, and counts the time interval between each user's most recent use of the vehicle networking function and the current time within the historical time period.

[0082] In one possible implementation, the segmentation module 301 is further configured to divide each user into multiple target operation groups based on the frequency, value, and recent behavior interval of each user's behavior using a preset user behavior segmentation model.

[0083] In one possible implementation, the segmentation module 301 is further configured to preset the average behavior frequency, average behavior value, and average recent behavior interval; based on the difference between the behavior frequency and the average behavior frequency, the difference between the behavior value and the average behavior value, and the difference between the recent behavior interval and the average recent behavior interval, each user is segmented into user groups to obtain multiple target operation groups.

[0084] The e-commerce operation device based on vehicle network user behavior provided in this embodiment can be the e-commerce operation device based on vehicle network user behavior shown in Figure 3. It can execute all the steps of the e-commerce operation method based on vehicle network user behavior shown in Figure 1-2, thereby achieving the technical effect of the e-commerce operation method based on vehicle network user behavior shown in Figure 1-2. For details, please refer to the relevant descriptions in Figure 1-2. For the sake of brevity, it will not be elaborated here.

[0085] Figure 4 is a schematic diagram of a server structure provided in an embodiment of the present invention. The server 500 shown in Figure 4 includes: at least one processor 501, a memory 502, at least one network interface 504, and other user interfaces 503. The various components in the server 500 are coupled together through a bus system 505. It is understood that the bus system 505 is used to realize the connection and communication between these components. In addition to a data bus, the bus system 505 also includes a power bus, a control bus, and a status signal bus. However, for clarity, all buses are labeled as bus system 505 in Figure 4.

[0086] The user interface 503 may include a display, keyboard, or clicking device (e.g., mouse, trackball, touchpad, or touchscreen).

[0087] It is understood that the memory 502 in the embodiments of the present invention can be volatile memory or non-volatile memory, or may include both volatile and non-volatile memory. The non-volatile memory can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. The volatile memory can be random access memory (RAM), which is used as an external cache. By way of example, but not limitation, many forms of RAM are available, such as Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDRSDRAM), Enhanced Synchronous DRAM (ESDRAM), Synchronous Link DRAM (SLDRAM), and Direct Rambus RAM (DRRAM). The memory 502 described herein is intended to include, but is not limited to, these and any other suitable types of memory.

[0088] In some implementations, memory 502 stores elements, executable units or data structures, or subsets thereof, or extended sets thereof: operating system 5021 and application program 5022.

[0089] The operating system 5021 includes various system programs, such as the framework layer, core library layer, and driver layer, used to implement various basic business functions and handle hardware-based tasks. The application program 5022 includes various applications, such as a media player and a browser, used to implement various application functions. The program implementing the method of this embodiment can be included in the application program 5022.

[0090] In this embodiment of the invention, by calling the program or instructions stored in memory 502, specifically the program or instructions stored in application program 5022, processor 501 executes the method steps provided in each method embodiment, including, for example:

[0091] Based on preset rules, all users using the vehicle-to-everything (V2X) user terminal are divided into basic user groups to obtain multiple basic user groups; multiple behavioral parameter information of each user in the basic user groups is collected during historical time periods; based on the multiple behavioral parameter information, each user is further divided into user groups to obtain multiple target operation groups; corresponding operation strategies are formulated for the multiple target operation groups, and target users within the multiple target operation groups are maintained based on the operation strategies.

[0092] In one possible implementation, basic information of all users using the vehicle-to-everything (V2X) user terminal is obtained; based on the basic information and multiple preset grouping parameters, all users are divided into basic user groups, wherein the multiple grouping parameters include at least region, age, gender, and preferences.

[0093] In one possible implementation, the multiple behavioral parameter information includes at least: behavior frequency, behavior value, and the interval between recent behaviors; the frequency of key actions of each user within a historical time period is statistically analyzed, and the key actions include at least remote control of the vehicle, viewing vehicle status, viewing vehicle information, vehicle sharing, Bluetooth operation, and viewing information on new vehicles; the number of points obtained by each user within a historical time period is statistically analyzed as the behavior value; and the time interval between each user's most recent use of the vehicle networking function and the current time is statistically analyzed.

[0094] In one possible implementation, a preset user behavior segmentation model is used to divide each user into user groups based on the frequency, value, and recent behavior interval of each user, resulting in multiple target operation groups.

[0095] In one possible implementation, the average behavior frequency, average behavior value, and average recent behavior interval are preset; based on the difference between behavior frequency and average behavior frequency, the difference between behavior value and average behavior value, and the difference between recent behavior interval and average recent behavior interval, each user is divided into user groups to obtain multiple target operation groups.

[0096] The methods disclosed in the above embodiments of the present invention can be applied to or implemented by processor 501. Processor 501 may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above method can be completed by the integrated logic circuit of the hardware in processor 501 or by instructions in the form of software. The processor 501 may be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. It can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of the present invention. The general-purpose processor may be a microprocessor or any conventional processor. The steps of the methods disclosed in the embodiments of the present invention can be directly embodied in the execution of a hardware decoding processor, or executed by a combination of hardware and software units in the decoding processor. The software units may be located in random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, or other mature storage media in the art. The storage medium is located in memory 502. Processor 501 reads the information in memory 502 and, in conjunction with its hardware, completes the steps of the above method.

[0097] It is understood that the embodiments described herein can be implemented in hardware, software, firmware, middleware, microcode, or a combination thereof. For hardware implementation, the processing unit can be implemented in one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field-programmable gate arrays (FPGAs), general-purpose processors, controllers, microcontrollers, microprocessors, other electronic units for performing the functions described herein, or combinations thereof.

[0098] For software implementation, the techniques described herein can be implemented by units that perform the functions described herein. The software code can be stored in memory and executed by a processor. The memory can be implemented in the processor or external to the processor.

[0099] The server provided in this embodiment can be the server shown in Figure 4, which can execute all the steps of the e-commerce operation method based on vehicle network user behavior in Figure 1-2, thereby achieving the technical effect of the e-commerce operation method based on vehicle network user behavior shown in Figure 1-2. For details, please refer to the relevant descriptions in Figure 1-2. For the sake of brevity, the details will not be elaborated here.

[0100] This invention also provides a storage medium (computer-readable storage medium). This storage medium stores one or more programs. The storage medium may include volatile memory, such as random access memory; the memory may also include non-volatile memory, such as read-only memory, flash memory, hard disk, or solid-state drive; the memory may also include combinations of the above types of memory.

[0101] When one or more programs in the storage medium can be executed by one or more processors to implement the above-mentioned e-commerce operation method based on vehicle network user behavior executed on the server side.

[0102] The processor is used to execute the e-commerce operation program based on vehicle network user behavior stored in the memory, so as to implement the following steps of the e-commerce operation method based on vehicle network user behavior executed on the server side:

[0103] Based on preset rules, all users using the vehicle-to-everything (V2X) user terminal are divided into basic user groups to obtain multiple basic user groups; multiple behavioral parameter information of each user in the basic user groups is collected during historical time periods; based on the multiple behavioral parameter information, each user is further divided into user groups to obtain multiple target operation groups; corresponding operation strategies are formulated for the multiple target operation groups, and target users within the multiple target operation groups are maintained based on the operation strategies.

[0104] In one possible implementation, basic information of all users using the vehicle-to-everything (V2X) user terminal is obtained; based on the basic information and multiple preset grouping parameters, all users are divided into basic user groups, wherein the multiple grouping parameters include at least region, age, gender, and preferences.

[0105] In one possible implementation, the multiple behavioral parameter information includes at least: behavior frequency, behavior value, and the interval between recent behaviors; the frequency of key actions of each user within a historical time period is statistically analyzed, and the key actions include at least remote control of the vehicle, viewing vehicle status, viewing vehicle information, vehicle sharing, Bluetooth operation, and viewing information on new vehicles; the number of points obtained by each user within a historical time period is statistically analyzed as the behavior value; and the time interval between each user's most recent use of the vehicle networking function and the current time is statistically analyzed.

[0106] In one possible implementation, a preset user behavior segmentation model is used to divide each user into user groups based on the frequency, value, and recent behavior interval of each user, resulting in multiple target operation groups.

[0107] In one possible implementation, the average behavior frequency, average behavior value, and average recent behavior interval are preset; based on the difference between behavior frequency and average behavior frequency, the difference between behavior value and average behavior value, and the difference between recent behavior interval and average recent behavior interval, each user is divided into user groups to obtain multiple target operation groups.

[0108] Those skilled in the art will further recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0109] The steps of the methods or algorithms described in conjunction with the embodiments disclosed herein can be implemented in hardware, a software module executed by a processor, or a combination of both. The software module can be located in random access memory (RAM), main memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, removable disk, CD-ROM, or any other form of storage medium known in the art.

[0110] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for operating an e-commerce platform based on user behavior in the Internet of Vehicles (IoV), characterized in that, include: Based on preset rules, all users using the vehicle-to-everything (V2X) user terminal will be divided into basic user groups to obtain multiple basic user groups. Collect multiple behavioral parameter information for each user in the basic user group within the historical time period; The multiple behavioral parameters include at least: behavior frequency, behavior value, and the interval between recent behaviors. Based on these multiple behavioral parameters, each user is segmented into multiple target operational groups. Corresponding operational strategies are formulated for each of the multiple target operational groups, and target users within each target operational group are maintained based on these strategies. The multiple behavioral parameters of each user in the basic user group within the statistical historical time period include: the frequency of each user's key actions within the statistical historical time period, where key actions include at least remote vehicle control, checking vehicle status, checking vehicle information, vehicle sharing, Bluetooth operation, and checking information on new vehicles; the number of points each user earns within the statistical historical time period is used as the behavior value; and the time interval between each user's most recent use of the vehicle networking function and the current time within the statistical historical time period. The remote vehicle control includes at least one of unlocking, locking, locating the vehicle, turning on the air conditioning, turning on the seat heating, closing the windows, controlling the tailgate, and controlling the sunroof.

2. The method according to claim 1, characterized in that, The process of performing basic user grouping on all users using the vehicle-to-everything (V2X) user terminal based on preset rules to obtain multiple basic user groups includes: obtaining basic information of all users using the V2X user terminal; and performing basic user grouping on all users based on the basic information and multiple preset grouping parameter information to obtain multiple basic user groups, wherein the multiple grouping parameter information includes at least region, age, gender, and preferences.

3. The method according to claim 1, characterized in that, The step of dividing each user into multiple target operational groups based on the multiple behavioral parameter information includes: using a preset user behavior grouping model based on the frequency, value, and recent behavior interval of each user to divide each user into multiple target operational groups.

4. The method according to claim 3, characterized in that, The method employs a preset user behavior segmentation model based on each user's corresponding behavior frequency, behavior value, and recent behavior interval to divide each user into multiple target operation groups, including: preset average behavior frequency, average behavior value, and average recent behavior interval. Based on the difference between behavior frequency and average behavior frequency, the difference between behavior value and average behavior value, and the difference between recent behavior interval and average recent behavior interval, each user is further divided into multiple target operation groups.

5. A shopping mall operation device based on vehicle network user behavior, characterized in that, include: The segmentation module is used to divide all users using the vehicle-to-everything (V2X) user terminal into basic user groups based on preset rules, resulting in multiple basic user groups. The statistics module is used to collect multiple behavioral parameter information for each user in the basic user group within a historical time period. The multiple behavioral parameter information includes at least: behavior frequency, behavior value, and the interval between the most recent behaviors; The segmentation module is further configured to segment users into multiple target operation groups based on the multiple behavioral parameter information; the operation and maintenance module is configured to formulate corresponding operation strategies for the multiple target operation groups and maintain target users within the multiple target operation groups based on the operation strategies; the statistics module is configured to: count the frequency of key actions of each user within a historical time period, wherein the key actions include at least remote control of the vehicle, checking vehicle status, checking vehicle information, sharing the vehicle, Bluetooth operation, and checking information on new vehicles; count the number of points obtained by each user within a historical time period as behavioral value; and count the time interval between each user's most recent use of the vehicle networking function and the current time within a historical time period; the remote control of the vehicle includes at least one of unlocking, locking, locating the vehicle, turning on the air conditioning, turning on the seat heating, closing the windows, controlling the tailgate, and controlling the sunroof.

6. A server, characterized in that, include: A processor and a memory, the processor being configured to execute an e-commerce operation program based on vehicle-to-everything (V2X) user behavior stored in the memory, to implement the e-commerce operation method based on V2X user behavior as described in any one of claims 1 to 4.

7. A storage medium, characterized in that, The storage medium stores one or more programs, which can be executed by one or more processors to implement the e-commerce operation method based on vehicle network user behavior as described in any one of claims 1 to 4.

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