User group identification method, device, electronic device and storage medium

Abstract

The present embodiment discloses a user group identification method, apparatus, electronic device, and storage medium. The method comprises: obtaining first online data for each of a plurality of users, the first online data comprising the number of target webpages browsed by each user and the duration of their browsing of the target webpage; determining a first target user from the plurality of users based on the number of target webpages browsed by each user and the duration of their browsing of the target webpage; and adding the first target user to a first database as a target user. The present embodiment is conducive to improving the accuracy of online marketing.

Description

Technical Field

[0001] The present application relates to the field of marketing technology, and in particular to a method, device, electronic device and storage medium for identifying a user group. Background Art

[0002] With the advancement of information technology, online marketing has become a crucial means for businesses to promote their brands and boost sales. In recent years, the rapid development of big data technology and its applications has profoundly transformed the operational model of online marketing, from budget allocation to campaign adjustments and post-campaign performance evaluation. One of the key impacts of big data on online marketing is its ability to integrate and analyze user data from multiple sources, creating accurate profiles of users' natural attributes, interests, purchasing power, and consumption intentions through profiling. This allows for precise insights into users and the market, enabling personalized information push, targeted advertising, and programmatic buying.

[0003] Despite the rapid development of big data technology, its impact on online sales has been minimal. Existing online sales models rely on human agents to communicate with users, understand their purchasing intentions, and then recommend suitable products. However, this model, which relies heavily on manual experience, struggles to accurately determine whether a user has purchasing intent, resulting in low marketing success rates and a poor user experience. Summary of the Invention

[0004] The embodiments of the present application provide a user group identification method, device, electronic device, and storage medium to improve the accuracy of online marketing by acquiring multi-dimensional data.

[0005] Another object of the present application is to provide a user group identification method, device, electronic device and storage medium, which have the advantage of automatically screening target users based on the number of times users browse the target web page and the duration of their browsing.

[0006] Another object of the present application is to provide a user group identification method, device, electronic device and storage medium, which have the advantage of being able to automatically screen out users with purchasing power by combining user fusion data, making the screened target users more accurate.

[0007] Another object of the present application is to provide a user group identification method, device, electronic device and storage medium, which have the advantage of being able to combine user interaction data to screen out target users from the user group and improve the accuracy of target user screening.

[0008] Another object of the present application is to provide a user group identification method, device, electronic device and storage medium, which have the advantage of being able to combine the characteristic attributes of matched purchased users to recommend purchase information for each target user, recommend items that users may need to purchase, and improve the user's shopping experience.

[0009] To achieve the above objectives, in a first aspect, embodiments of the present application provide a method for identifying a user group, comprising:

[0010] Acquiring first online data of each of the plurality of users, the first online data including the number of pages browsed by each user on a target webpage and a browsing time of the target webpage;

[0011] Determining a first target user among the multiple users based on the number of pages browsed by each user on the target webpage and the browsing time of the target webpage; and

[0012] The first target user is added to the first database as a target user.

[0013] It can be seen that based on the number of times users browse the target web page and the length of time they browse the web page, target users, i.e. users with purchasing intentions, can be automatically screened out. This way, when subsequently marketing products to these target users, the success rate of product marketing can be improved.

[0014] In some possible implementations, before adding the first target user to the first database as a target user, the method further includes:

[0015] Acquiring financial data of the first target user;

[0016] determining the economic level of the first target user based on the financial data of the first target user; and

[0017] Determine whether the economic level of the first target user meets the purchasing needs.

[0018] It can be seen that by combining the user's financial data, target users with purchasing intentions are screened out, making the screened target users more accurate.

[0019] In some possible implementations, after adding the first target user to the first database as a target user, the method further includes:

[0020] Obtaining second online data of each of the multiple users except the first user, the second online data including one or more of the number of interactions, message data, and appointment requests, wherein the number of interactions is the number of interactions between the user and the online customer service on the target webpage, and the appointment request is for booking an offline activity;

[0021] If the second online data includes the number of interactions and the number of interactions is greater than a fourth threshold; and / or if the second online data includes the message data and the message data indicates that the user has a purchase intention; and / or if the second online data includes the reservation request, determining that the user is a second target user; and

[0022] The second target user is added to the first database as the target user.

[0023] It can be seen that the target users can also be screened out by combining the user's second-line data, that is, the interactive data, which broadens the channels for screening target users and improves the comprehensiveness of determining target users.

[0024] In some possible implementations, the method further includes:

[0025] Obtain first characteristic attribute information of each purchased user in the second database;

[0026] Obtaining second characteristic attribute information of each target user in the first data;

[0027] Matching the second characteristic attribute information of each target user with the first characteristic attribute information of each target user in the second database to obtain a purchased user corresponding to each target user;

[0028] Acquire the purchase information of the purchasing user corresponding to each target user from the second database; and

[0029] Push the purchase information of the purchasing users corresponding to each target user to each target user.

[0030] It can be seen that it is also possible to combine the characteristic attributes of matched users who have purchased to recommend purchase information to each target user, recommend items that the user may need to purchase, and improve the user's purchasing experience.

[0031] In a second aspect, an embodiment of the present application provides a user group identification device, comprising:

[0032] a transceiver unit, configured to obtain first online data of each of a plurality of users, wherein the first online data includes the number of pages browsed by each user on a target webpage and a browsing time of the target webpage;

[0033] a determining unit, configured to determine a first target user among the plurality of users based on the number of pages browsed by each user on the target webpage and the browsing time of the target webpage; and

[0034] An adding unit is configured to add the first target user to the first database as a target user.

[0035] In some possible implementations, before adding the first target user to the database as a target user, the transceiver unit is further configured to obtain financial data of the first target user;

[0036] The determining unit is further configured to determine the economic level of the first target user based on the financial data of the first target user; and

[0037] The determining unit is further configured to determine whether the economic level of the first target user meets the purchasing needs.

[0038] In some possible implementations, after the first target user is added to the first database as a target user, the transceiver unit is further configured to obtain second online data of each of the multiple users other than the first user, where the second online data includes one or more of the number of interactions, message data, and appointment requests, wherein the number of interactions is the number of interactions between the user and online customer service on the target webpage, and the appointment request is used to schedule an offline activity;

[0039] The determining unit is further configured to determine that the user is a second target user if the second online data includes the number of interactions and the number of interactions is greater than a fourth threshold; and / or if the second online data includes the message data and the message data indicates that the user has a purchase intention; and / or if the second online data includes the reservation request; and

[0040] The adding unit is further configured to add the second target user to the database as the target user.

[0041] In some possible implementations, the transceiver unit is further configured to obtain third online data of the purchasing user before purchase from the second database;

[0042] The transceiver unit is further configured to obtain first characteristic attribute information of each purchased user from the second database;

[0043] The transceiver unit is further configured to obtain second characteristic attribute information of each target user in the first data;

[0044] The determining unit is further configured to match the second characteristic attribute information of each target user with the first characteristic attribute information of each target user in the second database to obtain a purchased user corresponding to each target user;

[0045] The transceiver unit is further configured to obtain purchase information of a purchasing user corresponding to each target user from the second database; and

[0046] The transceiver unit is further configured to push purchase information of the purchasing user corresponding to each target user to each target user.

[0047] In a third aspect, an embodiment of the present application provides an electronic device comprising a processor, a memory, a communication interface, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the processor, and the program includes instructions for executing the steps in the method described in the first aspect.

[0048] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and the computer program enables a computer to execute the method described in the first aspect.

[0049] In a fifth aspect, an embodiment of the present application provides a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program, and the computer is operable to enable the computer to execute the method described in the first aspect.

[0050] The implementation of the embodiments of the present application has the following beneficial effects:

[0051] As can be seen, in the embodiment of the present application, the number of pages visited by a user on a target webpage and the duration of the visit to the target page are obtained. Based on the number of pages visited and the duration of the visit, a first target user with purchase intention is screened out from multiple users, and the first target user is used as the target user. In this way, target users can be screened out intelligently, quickly, and accurately, achieving targeted marketing without manual intervention and improving marketing accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following briefly introduces the drawings required for use in the description of the embodiments. 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.

[0053] Figure 1 A schematic diagram of the architecture of a user group identification system provided in an embodiment of the present application;

[0054] Figure 2 A flowchart of a user group identification method provided in an embodiment of the present application;

[0055] Figure 3A flowchart of another method for identifying user groups provided in an embodiment of the present application;

[0056] Figure 4 A flowchart of another method for identifying user groups provided in an embodiment of the present application;

[0057] Figure 5 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application;

[0058] Figure 6 This is a block diagram of the functional units of a user group identification device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0059] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are part of the embodiments of this application, not all of them. 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.

[0060] The terms "first," "second," "third," and "fourth," etc., in the specification and claims of this application and the accompanying drawings are used to distinguish between different objects, rather than to describe a specific order. In addition, the terms "including," "having," and any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, system, product, or apparatus comprising a series of steps or elements is not limited to the listed steps or elements, but may optionally include steps or elements not listed, or may optionally include other steps or elements inherent to the process, method, product, or apparatus.

[0061] References herein to "embodiments" mean that a particular feature, result, or characteristic described in connection with the embodiments may be included in at least one embodiment of the present application. The appearance of this phrase in various places in the specification does not necessarily refer to the same embodiment, nor does it constitute an independent or alternative embodiment that is mutually exclusive of other embodiments. It is understood, both explicitly and implicitly, by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0062] It should be understood that the target users of this application can be users with purchasing intentions in various marketing scenarios. For example, in a car purchase scenario, the target users can be users who are interested in purchasing a car; in an insurance recommendation scenario, the target users can be users who are interested in purchasing insurance, etc. This application uses the car purchase scenario as an example to illustrate how to determine target users. Other scenarios are similar and will not be described here.

[0063] See Figure 1 , Figure 1 The user group identification system provided in the embodiment of the present application is a schematic diagram of the architecture of the user group identification system. The user group entity system includes a user group identification device 10, a terminal device 20 and a first database 30.

[0064] like Figure 1 As shown, when a user uses a terminal device 20 to browse a target web page, for example, browsing a car purchase web page, the terminal device 20 can send the number of pages browsed by the user on the target web page and the browsing time of the target web page to the user group identification device 10; then, the user group identification device 10 determines that the user is a first target user based on the number of pages browsed by the user on the target web page and the browsing time of the target web page; finally, the user group identification device 10 adds the user to the first database 30 and marks the user as a target user in the first database 30.

[0065] As can be seen, in this embodiment of the present application, the user group identification device 10 screens out a first target user with car purchase intention from multiple users based on the number of pages visited by the user on the target webpage and the duration of the user's browsing of the target page, and uses the first target user as the target user. This allows for intelligent, rapid, and accurate screening of target users, enabling targeted marketing without manual intervention and improving marketing accuracy.

[0066] See Figure 2 , Figure 2 A user group identification method is provided in an embodiment of the present application. The method is applied to a user group identification device. The method of this embodiment includes the following steps:

[0067] 201: A user group identification device obtains first online data of each user among a plurality of users.

[0068] The first online data includes the number of pages viewed by each user on a target webpage and the duration of the user's browsing of the target webpage. The target webpage may be a car purchase webpage or an electronic article. For example, the car purchase webpage may be the official webpage of a car company or the official webpage of a flagship store. The electronic article may be a marketing article of the car company or a marketing article on an official WeChat account.

[0069] 202: The user group identification device determines a first target user among the multiple users according to the number of pages browsed by each user on the target webpage and the browsing time of the target webpage.

[0070] Exemplarily, based on the number of pages of the target webpage browsed by each user and the duration of their browsing of the target webpage, the average duration of each page browsed by the user is determined, that is, the average duration of the user's browsing of the pages browsed is determined; then, based on the number of pages of the target webpage browsed by each user and the average duration of their browsing of each page of the target webpage, the first target user of the multiple users is determined. Exemplarily, the user whose page count of the target webpage browsed by the multiple users is greater than a first threshold and whose average duration of their browsing of each page of the target webpage is greater than a second threshold can be determined as the first target user.

[0071] Exemplarily, the browsing time of the target web page is the effective browsing time of the user on the target web page. In one possible embodiment of the present application, during the process of the user browsing the target web page, the user's eye data can be obtained, and it is determined based on the eye data whether the user is browsing the target web page, that is, based on the eye data obtained each time, the eye's rest position on the current page is determined. If the difference between the two adjacent eye rest positions is greater than the position threshold, it is determined that the user is browsing the target web page, and the time interval between the two adjacent acquisitions of eye data is used as a valid duration. All valid durations in the browsing process are combined to obtain the effective browsing time of the target web page; in another embodiment of the present application, it is also possible to detect whether the user's eyes are focused on the current page. If so, it is determined that the user is browsing the current page, and the display duration of browsing the current page is used as a valid duration. If not, it is determined that the user is not browsing the current page, and the display duration of the current page cannot be used as a valid duration. In another possible implementation of the present application, the time interval for the user to operate the current page can be obtained. If the time interval is less than or equal to the interval threshold, it is determined that the user is browsing the current page, and the browsing time of the current page is used as a valid browsing time; if the operation time is greater than the time threshold, it is determined that the user has not operated the current page (for example, the user has left the current page), and the browsing time of the current page cannot be used as a valid browsing time.

[0072] In actual applications, multiple browsing records of the user can be obtained, each of which includes the user's first online data. The multiple browsing records are used to comprehensively determine whether the user is the first target user. The determination method is similar to the above determination method and will not be described again.

[0073] 203: The user group identification device adds the first target user to the first database as a target user.

[0074] The first target user is added to the first database as a target user (i.e., a user who is looking to purchase a car). The first database is used to store the target user's information. Subsequently, car purchase information can be pushed to any one or more users in the first database. For example, when a new car is released, information related to the new car can be pushed preferentially to users in the first database.

[0075] It should be understood that the target users and users to purchase cars involved later are essentially the same and will not be described in detail.

[0076] As can be seen, in this embodiment of the present application, the number of pages visited by a user on a target webpage and the duration of the visit to the target page are obtained. Based on the number of pages visited and the duration of the visit, a first target user with car purchase intention is screened out from multiple users and the first target user is selected as the target user. In this way, target users can be screened intelligently, quickly, and accurately, achieving targeted marketing without manual intervention and improving the success rate of marketing.

[0077] In some possible implementations, before adding the first target user to the first database as a target user, the method further includes:

[0078] Obtaining financial data of the first target user, wherein the financial data includes the first target user's consumption data, savings, salary flow, assets and liabilities data, etc.; determining the first target user's economic level based on the first target user's financial data, wherein the economic level can be used to reflect the user's annual income, etc.; and determining whether the first target user's economic level satisfies the need to purchase a car. That is, after determining that the first target user's economic level satisfies the need to purchase a car, the first target user is added to the first database, thereby preventing the addition of users who have a need to purchase a car but lack the financial ability, such as car enthusiasts (e.g., those who enjoy browsing web pages for car-related information and currently have a need to purchase a car but lack the financial ability) who frequently browse official websites. This ensures that the first database is populated with users who have both a need to purchase a car and the financial ability to purchase a car, thereby improving marketing targeting and conversion rates.

[0079] In some possible implementations, after adding the first target user to the first database as a target user, the method further includes:

[0080] Obtaining second online data of each user among the multiple users other than the first user, the second online data including one or more of interaction times, message data, and appointment requests, wherein the interaction times are the number of interactions between the user and online customer service on the target webpage, and the appointment requests are for booking offline activities, illustratively, the offline activities include offline visits to physical stores, offline test drives, or offline learning about car purchase policies, etc.;

[0081] If the second online data includes the number of interactions and the number of interactions is greater than a fourth threshold; and / or if the second online data includes the message data and the message data indicates that the user has a purchase intention; and / or if the second online data includes the reservation request, determining that the user is a second target user;

[0082] The second target user is added to the first database as the target user.

[0083] Specifically, some users may have a particular vehicle in mind and therefore may not spend much time browsing the target webpage, perhaps only using it to make a reservation or seek assistance from online customer service. Alternatively, some users are not accustomed to browsing the web and prefer to learn about products online. Therefore, secondary online data can be obtained for each user. If this secondary online data indicates that the user is a target user, the user is added to the primary database. This allows for the screening of target users from multiple dimensions, thereby acquiring more users with vehicle purchasing intentions and improving the success rate of marketing.

[0084] In some possible implementations, after adding the first target user to the first database as a target user, the method further includes:

[0085] Obtain second online data of each user among the multiple users other than the first user, the second online data including multiple interaction data of the user with the online customer service within a preset time period; use the RFM model to analyze the multiple interaction data to obtain the RFM value of the user, the RFM value is used to characterize the interaction heat of the user with the online customer service. Exemplarily, the RFM parameters R, parameter F and parameter R of the RFM model can be predefined, the parameter M is used to represent the last interaction time of the user with the online customer service, the parameter F is used to represent the interaction frequency of the user with the online customer service within the preset time period, and the parameter M is used to represent the user's involvement in the online interaction within the preset time period; then, set the interaction heat weight corresponding to the multiple interaction data to obtain a weight table, and obtain the RFM model based on the RFM parameters and the weight table; then, calculate the RFM value through the RFM according to the existing technology and will not be described again; finally, when the RFM value is greater than the third threshold, determine the user as the second target user, and add the second target user to the second database.

[0086] In some possible implementations, the method further includes:

[0087] Obtaining first characteristic attribute information of each car-purchasing user in the second database, wherein the first characteristic attribute information includes information such as interests, economic status, consumption habits, number of family members, etc. of each car-purchasing user that is used to characterize the characteristics of the car-purchasing user;

[0088] Obtaining second characteristic attribute information of each target user in the first data. Similarly, the second characteristic attribute information includes each target user's interests, economic level, consumption habits, number of family members, and other information used to characterize the target user's characteristics;

[0089] Matching the second characteristic attribute information of each target user with the first characteristic attribute information of each target user in the second database to obtain a user who has purchased a car corresponding to each target user;

[0090] Obtaining the car purchase information of the user who has purchased the car corresponding to each target user from the second database;

[0091] Push the car purchase information of the users who have purchased the car corresponding to each target user to each target user.

[0092] Specifically, the characteristic attribute information of the target user is matched with the characteristic attribute information of the user who has purchased the car, so as to obtain the matched user who has purchased the car, and the car purchase information of the user who has purchased the car is pushed to the target user to achieve targeted recommendations and improve the marketing success rate.

[0093] In some possible implementations, the method further includes:

[0094] Obtaining the geographic location of each target user in the first database;

[0095] Clustering the target users in the first database according to the geographic location of each target user to obtain multiple clustering results;

[0096] Determining a target physical store corresponding to each cluster according to the geographical location corresponding to each cluster result in the plurality of cluster results, wherein the target physical store is the physical store closest to the cluster result;

[0097] The information of all users corresponding to the clustering result is pushed to the terminal device of the target physical store, so that the corresponding marketing personnel are dispatched according to the clustering result to conduct car purchase marketing for all users.

[0098] It can be seen that in this embodiment, clustering is performed based on geographic location, so that the nearest offline physical store can be found for each clustering result. In this way, the marketing personnel of the physical store can be notified to carry out targeted marketing for the users corresponding to the clustering result, such as door-to-door marketing or special marketing in the physical store, which can also improve the accuracy of marketing.

[0099] See Figure 3 , Figure 3 Another user group identification method provided in an embodiment of the present application is applied to a user group identification device. The method of this embodiment includes the following steps:

[0100] 301: The user group identification device obtains first online data of each user among a plurality of users, where the first online data includes the number of pages browsed by each user on a target webpage and the browsing time of the target webpage.

[0101] 302: The user group identification device determines a first target user among the multiple users according to the number of pages browsed by each user on the target webpage and the browsing time of the target webpage.

[0102] 303: The user group identification device obtains the financial data of the first target user.

[0103] 304: The user group identification device determines the economic level of the first target user based on the financial data of the first target user.

[0104] 305: The user group identification device determines that the economic level of the first target user meets the demand for car purchase.

[0105] 306: The user group identification device adds the first target user to the first database as a target user.

[0106] It should be noted that Figure 3 The specific implementation process of each step of the method shown can be found in the above Figure 2 The specific implementation process of the method will not be described here.

[0107] As can be seen, in this embodiment of the present application, the number of pages visited by a user on a target webpage and the duration of their browsing of that target page are obtained. Based on this number of pages and the duration of their browsing, a first target user with car purchasing intention is screened from multiple users and designated as the target user. This allows for intelligent, rapid, and accurate screening of target users, enabling targeted marketing without manual intervention and improving marketing accuracy, i.e., success rate. Furthermore, before designating the first target user as a target user, the user's financial data can be obtained to determine whether the first target user has the ability to purchase a car, thereby avoiding misidentification and further improving the accuracy of the target user identification.

[0108] See Figure 4 , Figure 4 Another user group identification method provided in an embodiment of the present application is applied to a user group identification device. The method of this embodiment includes the following steps:

[0109] 401: The user group identification device obtains first online data of each user among a plurality of users, where the first online data includes the number of pages browsed by each user on a target webpage and the browsing time of the target webpage.

[0110] 402: The user group identification device determines a first target user among the multiple users according to the number of pages browsed by each user on the target webpage and the browsing time of the target webpage.

[0111] 403: The user group identification device obtains the financial data of the first target user.

[0112] 404: The user group identification device determines the economic level of the first target user based on the financial data of the first target user.

[0113] 405: The user group identification device determines that the economic level of the first target user meets the demand for car purchase.

[0114] 406: The user group identification device adds the first target user to the first database as a target user.

[0115] 407: The user group identification device obtains second online data of each user among the multiple users except the first user, where the second online data includes one or more of the number of interactions, message data, and appointment requests, wherein the number of interactions is the number of interactions between the user and the online customer service on the target webpage, and the appointment request is used to schedule an offline activity.

[0116] 408: The user group identification device determines that the user is a second target user when the second online data includes the number of interactions and the number of interactions is greater than a fourth threshold; and / or when the second online data includes the message data and the message data indicates that the user has a purchase intention; and / or when the second online data includes the reservation request.

[0117] 409: The user group identification device adds the second target user to the first database as the target user.

[0118] It should be noted that Figure 4 The specific implementation process of each step of the method shown can be found in the above Figure 2 The specific implementation process of the method will not be described here.

[0119] As can be seen, in the embodiment of the present application, the number of pages visited by the user on the target web page and the browsing time of the target page are obtained. Based on the number of pages and the browsing time, a first target user with the intention to purchase a car is screened out from multiple users, and the first target user is used as the target user. In this way, the target users can be screened out intelligently, quickly, and accurately, and targeted marketing can be achieved without manual intervention, thereby improving the accuracy of marketing. In addition, before the first target user is used as the target user, the financial data of the first target user can also be obtained. The financial data can be used to determine whether the first target user has the ability to purchase a car, thereby avoiding misidentification and further improving the accuracy of the determined target user. In addition, users whose second online data meets the requirements are also used as target users, so that the target users can be determined from multiple dimensions, thereby improving the richness of the target users.

[0120] See Figure 5 , Figure 5 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. Figure 5 As shown, the electronic device 500 includes a processor, a memory, a communication interface, and one or more programs. The processor, the memory, and the communication interface are connected via electrical signals. The one or more programs are stored in the memory and configured to be executed by the processor. The programs include instructions for performing the following steps:

[0121] Acquiring first online data of each of the plurality of users, the first online data including the number of pages browsed by each user on a target webpage and a browsing time of the target webpage;

[0122] Determining a first target user among the multiple users based on the number of pages browsed by each user on the target webpage and the browsing time of the target webpage; and

[0123] The first target user is added to the first database as a target user.

[0124] In some possible implementations, in determining the first target user among the multiple users based on the number of pages browsed by each user on the target webpage and the browsing time of the target webpage, the program is specifically configured to execute instructions for the following steps:

[0125] Determining an average browsing time for each page of the target webpage based on the number of pages browsed by each user and the browsing time of the target webpage; and

[0126] A first target user among the multiple users is determined according to the number of pages browsed by each user on the target webpage and the average browsing time of each page of the target webpage.

[0127] In some possible implementations, in determining the first target user among the multiple users based on the number of pages browsed by each user on the target webpage and the average browsing time of each page of the target webpage, the program is specifically configured to execute the following steps:

[0128] It is determined that a user among the multiple users whose number of pages browsed the target webpage is greater than a first threshold and whose average browsing time for each page of the target webpage is greater than a second threshold is the first target user.

[0129] In some possible implementations, before adding the first target user to the first database and using it as a target user, the program is further configured to execute instructions for the following steps:

[0130] Acquiring financial data of the first target user;

[0131] determining the economic level of the first target user based on the financial data of the first target user; and

[0132] Determine whether the economic level of the first target user meets the needs of purchasing a car.

[0133] In some possible implementations, after the first target user is added to the first database as a target user, the program is further configured to execute instructions for the following steps:

[0134] Obtaining second online data of each of the multiple users except the first user, the second online data including one or more of the number of interactions, message data, and appointment requests, wherein the number of interactions is the number of interactions between the user and the online customer service on the target webpage, and the appointment request is for booking an offline activity;

[0135] If the second online data includes the number of interactions and the number of interactions is greater than a fourth threshold; and / or if the second online data includes the message data and the message data indicates that the user has a purchase intention; and / or if the second online data includes the reservation request, determining that the user is a second target user; and

[0136] The second target user is added to the first database as the target user.

[0137] In some possible implementations, the above program is further used to execute instructions for the following steps:

[0138] Obtain first characteristic attribute information of each user who has purchased a car in the second database;

[0139] Obtaining second characteristic attribute information of each target user in the first data;

[0140] Matching the second characteristic attribute information of each target user with the first characteristic attribute information of each target user in the second database to obtain a user who has purchased a car corresponding to each target user;

[0141] Obtaining the car purchase information of the user who has purchased the car corresponding to each target user from the second database; and

[0142] Push the car purchase information of the users who have purchased the car corresponding to each target user to each target user.

[0143] See Figure 6 , Figure 6 The present invention provides a functional unit block diagram of a user group identification device. The user group identification device 600 includes: a transceiver unit 610, a determination unit 620 and an addition unit 630, wherein:

[0144] The transceiver unit 610 is configured to obtain first online data of each user among a plurality of users, wherein the first online data includes the number of pages browsed by each user on a target webpage and the browsing time of the target webpage;

[0145] a determining unit 620 configured to determine a first target user among the plurality of users based on the number of pages browsed by each user on the target webpage and the browsing time of the target webpage; and

[0146] The adding unit 630 is configured to add the first target user to the first database as a target user.

[0147] In some possible implementations, in determining the first target user among the multiple users based on the number of pages browsed by each user on the target webpage and the browsing time of the target webpage, the determining unit 620 is specifically configured to:

[0148] Determining an average browsing time for each page of the target webpage based on the number of pages browsed by each user and the browsing time of the target webpage; and

[0149] A first target user among the multiple users is determined according to the number of pages browsed by each user on the target webpage and the average browsing time of each page of the target webpage.

[0150] In some possible implementations, in determining the first target user among the multiple users based on the number of pages browsed by each user on the target webpage and the average browsing time of each page of the target webpage, the determining unit 620 is specifically configured to:

[0151] It is determined that a user among the multiple users whose number of pages browsed the target webpage is greater than a first threshold and whose average browsing time for each page of the target webpage is greater than a second threshold is the first target user.

[0152] In some possible implementations, before adding the first target user to the database as a target user, the transceiver unit is further configured to obtain financial data of the first target user;

[0153] The determining unit 620 is further configured to determine the economic level of the first target user based on the financial data of the first target user; and

[0154] The determining unit 620 is further configured to determine whether the economic level of the first target user meets the demand for purchasing a car.

[0155] In some possible implementations, after the first target user is added to the first database as a target user, the transceiver unit 610 is further configured to obtain second online data of each of the multiple users other than the first user, where the second online data includes one or more of the number of interactions, message data, and appointment requests, wherein the number of interactions is the number of interactions between the user and the online customer service on the target webpage, and the appointment request is used to schedule an offline activity;

[0156] The determining unit 620 is further configured to determine that the user is a second target user if the second online data includes the number of interactions and the number of interactions is greater than a fourth threshold; and / or if the second online data includes the message data and the message data indicates that the user has a purchase intention; and / or if the second online data includes the reservation request; and

[0157] The adding unit 630 is further configured to add the second target user to the database as the target user.

[0158] In some possible implementations, the transceiver unit 610 is further configured to obtain third online data of the vehicle-purchasing user before purchasing the vehicle from the second database;

[0159] The transceiver unit 610 is further configured to obtain first characteristic attribute information of each user who has purchased a car in the second database;

[0160] The transceiver unit 610 is further configured to obtain second characteristic attribute information of each target user in the first data;

[0161] The determining unit 620 is further configured to match the second characteristic attribute information of each target user with the first characteristic attribute information of each target user in the second database to obtain a user who has purchased a car corresponding to each target user;

[0162] The transceiver unit 610 is further configured to obtain the car purchase information of the user who has purchased the car corresponding to each target user from the second database; and

[0163] The transceiver unit 610 is further configured to push the car purchase information of the user who has purchased the car corresponding to each target user to each target user.

[0164] It should be understood that the user group identification devices in this application may include smartphones (such as Android phones, iOS phones, Windows Phone phones, etc.), tablet computers, PDAs, laptops, mobile Internet devices (MIDs), or wearable devices. The above user group identification devices are merely examples and are not exhaustive, and include but are not limited to the above user group identification devices. In actual applications, user group identification devices may also include: smart vehicle terminals, computer equipment, etc.

[0165] An embodiment of the present application further provides a computer storage medium, wherein the computer-readable storage medium stores a computer program, and the computer program is executed by a processor to implement part or all of the steps of any user group identification method described in the above method embodiments.

[0166] An embodiment of the present application further provides a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program, and the computer program is operable to cause a computer to execute some or all of the steps of any user group identification method described in the above method embodiments.

[0167] It should be noted that for the aforementioned method embodiments, for the sake of simplicity, they are all expressed as a series of action combinations, but those skilled in the art should be aware that this application is not limited by the order of the actions described, because according to this application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in this specification are all optional embodiments, and the actions and modules involved are not necessarily required by this application.

[0168] In the above embodiments, the description of each embodiment has its own focus. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0169] In the several embodiments provided in this application, it should be understood that the disclosed devices can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the units is merely a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, and the indirect coupling or communication connection of devices or units can be electrical or other forms.

[0170] 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 these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0171] In addition, the functional units in the various embodiments of the present application may be integrated into a single processing unit, or each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or in the form of software program modules.

[0172] If the integrated unit is implemented in the form of a software program module and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, which is stored in a memory and includes a number of instructions for enabling a computer device (which can be a personal computer, a server or a network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned memory includes various media that can store program codes, such as a USB flash drive, a read-only memory (ROM), a random access memory (RAM), a mobile hard disk, a magnetic disk or an optical disk.

[0173] Those skilled in the art will appreciate that all or part of the steps in the various methods of the above embodiments can be completed by instructing related hardware through a program. The program can be stored in a computer-readable memory, and the memory can include: a flash drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, etc.

[0174] The above is a detailed introduction to the embodiments of the present application. Specific examples are used herein to illustrate the principles and implementation methods of the present application. The description of the above embodiments is only used to help understand the method and core idea of ​​the present application. At the same time, for those skilled in the art, according to the idea of ​​the present application, there may be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as a limitation on the present application.

Claims

1. A method for identifying user groups, characterized in that: The following steps are involved: Acquiring first online data of each of the plurality of users, the first online data including the number of pages browsed by each user on a target webpage and a browsing time of the target webpage; The browsing time of the target webpage is the effective browsing time of the user on the target webpage, including: Obtaining eyeball data of each user browsing the target webpage; Determine the position of each user's eyeball on the current page of the target webpage based on the eyeball data obtained each time; If the difference between two consecutive eyeball rest positions is greater than the position threshold, it is determined that the user is browsing the target webpage, and the time interval between the two consecutive acquisitions of eyeball data is used as an effective duration. All effective durations during the browsing process are combined to obtain the user's effective browsing time for the target webpage; Determining a first target user among the multiple users based on the number of pages browsed by each user on the target webpage and the browsing time of the target webpage; and The first target user is added to the first database as a target user.

2. The method according to claim 1, wherein The method of determining a first target user among the plurality of users according to the number of pages browsed by each user on the target webpage and the browsing time of the target webpage comprises the following steps: Determining an average browsing time for each page of the target webpage based on the number of pages browsed by each user and the browsing time of the target webpage; and A first target user among the multiple users is determined according to the number of pages browsed by each user on the target webpage and the average browsing time of each page of the target webpage.

3. The method according to claim 2, wherein: The method of determining a first target user among the plurality of users according to the number of pages browsed by each user on the target webpage and the average browsing time of each page of the target webpage comprises the following steps: It is determined that a user among the multiple users whose number of pages browsed the target webpage is greater than a first threshold and whose average browsing time for each page of the target webpage is greater than a second threshold is the first target user.

4. The method according to any one of claims 1 to 3, wherein Before adding the first target user to the first database as a target user, the method further includes the following steps: Acquiring financial data of the first target user; determining the economic level of the first target user based on the financial data of the first target user; and Determine whether the economic level of the first target user meets the purchasing needs.

5. The method according to any one of claims 1 to 4, wherein After adding the first target user to the first database as a target user, the method further includes the following steps: Obtaining second online data of each user among the multiple users other than the first target user, the second online data including one or more of interaction times, message data, and appointment requests, wherein the interaction times are the number of interactions between the user and online customer service on the target webpage, and the appointment requests are for booking offline activities; If the second online data includes the number of interactions and the number of interactions is greater than a fourth threshold; and / or if the second online data includes the message data and the message data indicates that the user has a purchase intention; and / or if the second online data includes the reservation request, determining that the user is a second target user; and The second target user is added to the first database as the target user.

6. The method according to claim 5, wherein: The method further comprises the following steps: Obtain first characteristic attribute information of each purchased user in the second database; Obtaining second characteristic attribute information of each target user in the first data; Matching the second characteristic attribute information of each target user with the first characteristic attribute information of each target user in the second database to obtain a purchased user corresponding to each target user; Acquire the purchase information of the purchasing user corresponding to each target user from the second database; and Push the purchase information of the purchasing users corresponding to each target user to each target user.

7. A user group identification device, characterized in that: include: a transceiver unit, configured to obtain first online data of each of a plurality of users, wherein the first online data includes the number of pages browsed by each user on a target webpage and a browsing time of the target webpage; The browsing time of the target webpage is the effective browsing time of the user on the target webpage, including: Obtaining eyeball data of each user browsing the target webpage; Determine the position of each user's eyeball on the current page of the target webpage based on the eyeball data obtained each time; If the difference between two consecutive eyeball rest positions is greater than the position threshold, it is determined that the user is browsing the target webpage, and the time interval between the two consecutive acquisitions of eyeball data is used as an effective duration. All effective durations during the browsing process are combined to obtain the user's effective browsing time for the target webpage; a determining unit, configured to determine a first target user among the plurality of users based on the number of pages browsed by each user on the target webpage and the browsing time of the target webpage; and An adding unit is configured to add the first target user to the first database as a target user.

8. The device according to claim 7, wherein In determining the first target user among the multiple users based on the number of pages browsed by each user on the target webpage and the browsing time of the target webpage, the determining unit is specifically configured to: Determining an average browsing time for each page of the target webpage based on the number of pages browsed by each user and the browsing time of the target webpage; as well as A first target user among the multiple users is determined according to the number of pages browsed by each user on the target webpage and the average browsing time of each page of the target webpage.

9. The device according to claim 7 or 8, wherein In determining the first target user among the multiple users based on the number of pages browsed by each user on the target webpage and the average browsing time of each page of the target webpage, the determining unit is specifically configured to: It is determined that a user among the multiple users whose number of pages browsed the target webpage is greater than a first threshold and whose average browsing time for each page of the target webpage is greater than a second threshold is the first target user.

10. The device according to any one of claims 7 to 9, wherein: Before adding the first target user to the first database and using it as a target user, the transceiver unit is further configured to obtain financial data of the first target user; The determining unit is further configured to determine the economic level of the first target user based on the financial data of the first target user; and The determining unit is further configured to determine whether the economic level of the first target user meets the purchasing needs.

11. The device according to any one of claims 7 to 10, wherein: After adding the first target user to the first database as the target user, the transceiver unit is further configured to obtain second online data of each of the multiple users other than the first user, the second online data including one or more of the number of interactions, message data, and appointment requests, wherein the number of interactions is the number of interactions between the user and the online customer service on the target webpage, and the appointment request is used to schedule an offline activity; The determining unit is further configured to determine that the user is a second target user if the second online data includes the number of interactions and the number of interactions is greater than a fourth threshold; and / or if the second online data includes the message data and the message data indicates that the user has a purchase intention; and / or if the second online data includes the reservation request; and The adding unit is further configured to add the second target user to the database as the target user.

12. The device according to claim 11, wherein The transceiver unit is further configured to obtain first characteristic attribute information of each purchased user from the second database; The transceiver unit is further configured to obtain second characteristic attribute information of each target user in the first data; The determining unit is further configured to match the second characteristic attribute information of each target user with the first characteristic attribute information of each target user in the second database to obtain a purchased user corresponding to each target user; The transceiver unit is further configured to obtain purchase information of a purchasing user corresponding to each target user from the second database; as well as The transceiver unit is further configured to push purchase information of the purchasing user corresponding to each target user to each target user.

13. An electronic device, characterized in that: The method comprises a processor, a memory, a communication interface, and one or more programs, wherein the processor, the memory, and the communication interface are connected via electrical signals, wherein the one or more programs are stored in the memory and configured to be executed by the processor, and the programs include instructions for executing the steps in any one of the methods of claims 1 to 6.

14. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, and the computer program is executed by a processor to implement the method according to any one of claims 1 to 6.

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