CN116703525A - Recommendation method and system of vehicle brands, storage medium and electronic equipment - Google Patents
Recommendation method and system of vehicle brands, storage medium and electronic equipment Download PDFInfo
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Abstract
The application provides a recommendation method and system of a vehicle brand, a storage medium and electronic equipment. The recommendation method of the vehicle brands comprises the following steps: acquiring browsing data of a user in a driving training application program; determining a target vehicle brand according to the browsing data; pushing the vehicle purchasing information of the target vehicle brand to a user according to the target vehicle brand; personal information authorized by a user and reserved in a driving training application program is obtained; the personal information is sent to a sales enterprise of the target vehicle brand.
Description
Technical Field
The present application relates to the field of computer technology, and in particular, to a vehicle brand recommendation method, a vehicle brand recommendation system, a storage medium, and an electronic device.
Background
Currently, the vehicle industry faces challenges of increasing lead acquisition costs and decreasing conversion. Taking a certain head vertical media cue product as an example, the rise per year of the periodical price is about 20% within 5 years; meanwhile, according to the data published by the vertical media at the end of 2021, the cue quantity ring ratio is increased by 12%, and the whole market sales quantity ring ratio is increased by only 10%; thread conversion shows a trend of decreasing year by year. Therefore, the key point of future vehicle-enterprise marketing is on-line digital marketing, so on the basis of a large amount of on-line data, improving the accuracy of recommending vehicle brands to users is a technical problem to be solved urgently.
Disclosure of Invention
The present application aims to solve at least one of the technical problems existing in the prior art or related art.
For this purpose, a first object of the present application is to propose a method for recommending a brand of a vehicle.
A second object of the application is to propose a recommendation system for a brand of vehicle.
A third object of the present application is to propose a storage medium.
A fourth object of the present application is to propose an electronic device.
In view of the above, according to a first object of the present application, there is provided a recommendation method of a brand of a vehicle, wherein the method includes acquiring browsing data of a user in a driving training application; determining a target vehicle brand according to the browsing data; pushing the vehicle purchasing information of the target vehicle brand to a user according to the target vehicle brand; personal information authorized by a user and reserved in a driving training application program is obtained; the personal information is sent to a sales enterprise of the target vehicle brand.
According to the recommendation method of the vehicle brands, browsing data of a user in a driving training application program is obtained, the target vehicle brands of the user heart instrument are determined according to the browsing data of the user by utilizing a big data algorithm, and then vehicle purchasing information of the target vehicle brands, such as preferential promotion activities, personalized vehicle purchasing schemes and the like of the target vehicle brands, of the user are pushed to the user according to the target vehicle brands of the user heart instrument, so that the vehicle purchasing will of the user and the enthusiasm of online reservation are improved. If the user has a intention of purchasing the vehicle, the driving training application program is authorized, and then personal information reserved in the driving training application program by the user is acquired and sent to a sales enterprise of the target vehicle brand. And the vehicle brand of the cardiometer of the user is determined according to the browsing data of the user by acquiring the browsing data of the user, so that the accuracy of recommending the vehicle brand to the user is improved.
In addition, the recommendation method of the brand of the vehicle provided by the technical scheme of the application has the following additional technical characteristics:
in some embodiments, optionally, the step of acquiring browsing data of the user in the driving training application includes: acquiring relevant information of a plurality of vehicle brands; and pushing the related information of the plurality of vehicle brands to a user through the driving training application program.
In the technical scheme, the method and the system also cooperate with sales enterprises or 4S stores of a plurality of vehicle brands to acquire related information of the plurality of vehicle brands, such as related information of recently new vehicle types, interior decorations and the like of the vehicle brands, and then the related information of the plurality of vehicle brands is pushed to a user through a driving training application program. Further, the relevant information of a plurality of vehicle brands is sent to the user, so that more choices are provided for the user, and the accuracy of recommendation is improved.
In some embodiments, optionally, the step of determining the brand of the target vehicle according to the browsing data includes: determining the most data information in the browsing data according to the browsing data; matching the data information with the related information of a plurality of vehicle brands, and determining the related information of the vehicle brands opposite to the data information; and determining the brand of the target vehicle according to the related information of the brand of the vehicle.
In this technical solution, the step of determining the brand of the target vehicle according to the browsing data includes: firstly, browsing data of a user is acquired, and then, the most data information in the browsing data is determined according to the browsing data by utilizing an algorithm. By determining the most data information in the browsing data, the user can find out which type of information is interested in, then the data information is matched with the related information of a plurality of vehicle brands, the related information of the vehicle brands opposite to the data information is determined, namely the related information of which vehicle brand the data information belongs to is determined, and then the target vehicle brand, namely the vehicle brand of the user's heart instrument, is determined according to the related information of the vehicle brands. The target vehicle brand interested by the user is determined by analyzing and calculating the browsing data of the user, so that the accuracy of recommendation is further improved.
In some embodiments, optionally, the recommendation method of the vehicle brand further includes: associating the user with the driving school based on the user after finishing registration of the driving training application program; and generating a digital clue follow-up billboard according to the purchase progress of the user and sending the digital clue follow-up billboard to a driving school.
In the technical scheme, the vehicle brand recommendation method can also cooperate with a driving school. The user may register the driving school through the driving training application or the driving school may recommend the driving training application to the user after logging the user. After the registration of the driving training application program is completed, the user is associated with the driving school, so that the user can learn the driving theory in the driving training application program, and the user can conduct operations such as reservation driving exercise, time and fee payment, reservation examination and the like in the driving training application program due to the fact that the user is associated with the driving school in the driving training application program, and the use experience of the user is improved. Further, because the driving training application program is recommended to the user by the driving school, the digital clue follow-up sign is generated according to the vehicle purchasing progress of the user and sent to the driving school, namely, the driving school can check the follow-up state of the clue of the vehicle purchasing user recommended by the driving school through the digital clue follow-up sign. The effective combination of online and offline is realized by establishing a cooperative relationship with a driving school, so that the user satisfaction is improved.
According to a second object of the present application, there is provided a recommendation system for a brand of vehicle, wherein the system comprises: the first acquisition module is used for acquiring browsing data of a user in the driving training application program; the first determining module is used for determining a brand of the target vehicle according to the browsing data; the first pushing module is used for pushing the purchasing information of the target vehicle brand to the user according to the target vehicle brand; the second acquisition module is used for acquiring personal information authorized by a user and reserved in the driving training application program; and the sending module is used for sending the personal information to a sales enterprise of the target vehicle brand.
According to the recommendation system for the vehicle brands, disclosed by the application, the sales enterprises of the vehicle brands and the Internet driving training enterprises are combined together, so that information related to the vehicle brands can be displayed in the driving training application program generated by the Internet driving training enterprises. The recommendation system of the vehicle brand specifically comprises: the device comprises a first acquisition module, a first determination module, a first pushing module, a second acquisition module and a sending module. Specifically, the first acquisition module acquires browsing data of a user in the driving training application program, the first determination module determines a target vehicle brand of the user heart instrument according to the browsing data of the user by utilizing a big data algorithm, and then the first pushing module pushes the driving training application program of the target vehicle brand to the user according to the target vehicle brand of the user heart instrument, such as preferential promotion activities of the target vehicle brand, personalized purchasing schemes and the like, so that the purchase intention of the user and the enthusiasm of online reservation are improved. If the user has a willingness to purchase the vehicle, the vehicle is authorized, so that the second acquisition module acquires personal information reserved in the driving training application program by the user after the user is authorized, and sends the personal information to a sales enterprise of a target vehicle brand through the sending module, and the vehicle brand of the heart meter of the user is determined according to the browsing data of the user by acquiring the browsing data of the user, so that accuracy of recommending the vehicle brand to the user is improved.
In some embodiments, optionally, the recommendation system for a vehicle brand further includes: the third acquisition module is used for acquiring the related information of a plurality of vehicle brands; the second pushing module is used for pushing the relevant information of the plurality of vehicle brands to the user through the driving training application program.
In this technical solution, the recommendation system for a brand of vehicle further includes: a third acquisition module and a second pushing module. The third obtaining module obtains relevant information of a plurality of vehicle brands, such as relevant information of a vehicle model, an interior trim and the like which are recently updated by the vehicle brands, and then the second pushing module pushes the relevant information of the plurality of vehicle brands to a user through a driving training application program. Further, the relevant information of a plurality of vehicle brands is sent to the user, so that more choices are provided for the user, and the accuracy of recommendation is improved.
In some embodiments, optionally, the first determining module includes: the second determining module is used for determining the most data information in the browsing data according to the browsing data; a third determining module for determining relevant information of a vehicle brand opposite to the data information according to the data information and the relevant information of the plurality of vehicle brands; and the fourth determining module is used for determining the brand of the target vehicle according to the related information of the brand of the vehicle.
In this technical solution, the first determining module includes: the system comprises a second determining module, a third determining module and a fourth determining module. Firstly, acquiring browsing data of a user, and then determining the most data information in the browsing data by a second determining module according to the browsing data by using an algorithm. By determining the most data information in the browsing data, the user can find out which type of information is interested in, and then the third determining module matches the data information with the related information of a plurality of vehicle brands, determines the related information of the vehicle brands opposite to the data information, namely determines which vehicle brand the data information belongs to, and then the fourth determining module determines the target vehicle brand, namely the vehicle brand of the user heart instrument, according to the related information of the vehicle brands, so that the recommendation accuracy is further improved.
In some embodiments, optionally, the recommendation system for a vehicle brand further includes: the association module is used for associating the user with the driving school based on the fact that the user finishes registering the driving training application program; the generation module is used for generating a digital clue follow-up billboard according to the purchasing progress of the user and sending the digital clue follow-up billboard to the driving school.
In this technical solution, it is also possible to cooperate with driving schools in a recommendation system of the brand of the vehicle. The user may register the driving school through the driving training application or the driving school may recommend the driving training application to the user after logging the user. The recommendation system of the vehicle brand further includes: the association module is used for associating the user with the driving school after the user finishes registration of the driving training application program, so that the user can learn the driving theory in the driving training application program, and the user can conduct operations such as reservation driving, time and fee payment, reservation examination and the like on the driving school in the driving training application program due to the fact that the user associates the user with the driving school in the driving training application program, and therefore the use experience of the user is improved. Further, because the driving training application program is recommended to the user by the driving school, the generating module generates a digital clue follow-up billboard according to the vehicle purchasing progress of the user and sends the digital clue follow-up billboard to the driving school, namely the driving school can check the follow-up state of the clue of the vehicle purchasing user recommended by the driving school through the digital clue follow-up billboard. The on-line and off-line effective combination is realized by establishing a cooperative relationship with a driving school, so that a perfect on-line and off-line sales system is constructed, and the user satisfaction is improved by combining an on-line platform with a driving school entity store.
According to a third object of the present application, there is provided a storage medium having stored thereon a computer program which, when executed by a processor, implements the steps of the method of recommending a brand of a vehicle as defined in any of the above-mentioned claims.
The storage medium provided by the application realizes the steps of the method for recommending the vehicle brand according to any one of the above-mentioned technical schemes when the computer program is executed by the processor, so that the storage medium comprises all the beneficial effects of the method for recommending the vehicle brand according to any one of the above-mentioned technical schemes.
According to a fourth object of the present application, there is provided an electronic device comprising: the system comprises a memory, a processor and a computer program stored in the memory and capable of running on the processor, wherein the processor realizes the recommendation method of the brand of the vehicle according to any one of the technical schemes when executing the computer program.
The electronic equipment provided by the application realizes the steps of the vehicle brand recommendation method according to any one of the technical schemes when the computer program is executed by the processor, so that the electronic equipment has all the beneficial effects of the vehicle brand recommendation method according to any one of the technical schemes.
Additional aspects and advantages of the application will be set forth in part in the description which follows, or may be learned by practice of the application.
Drawings
The foregoing and/or additional aspects and advantages of the application will become apparent and may be better understood from the following description of embodiments taken in conjunction with the accompanying drawings in which:
FIG. 1 illustrates one of the flow diagrams of a method of recommending a brand of a vehicle in accordance with one embodiment of the present application;
FIG. 2 illustrates a second flow diagram of a method of recommending a brand of a vehicle in accordance with an embodiment of the present application;
FIG. 3 is a flowchart illustrating steps for determining a target vehicle brand based on browsing data in a method for recommending a vehicle brand according to an embodiment of the present application;
FIG. 4 illustrates a third flow diagram of a method of recommending a brand of a vehicle in accordance with an embodiment of the present application;
FIG. 5 shows a fourth flow diagram of a method of recommending a brand of a vehicle, according to an embodiment of the present application;
FIG. 6 shows a schematic block diagram of a recommendation system for a brand of vehicle, according to an embodiment of the present application;
FIG. 7 shows a schematic block diagram of a first determination module in a recommendation system for a brand of vehicle, according to one embodiment of the present application;
fig. 8 shows a schematic block diagram of an electronic device according to an embodiment of the application.
Detailed Description
In order that the above-recited objects, features and advantages of the present application will be more clearly understood, a more particular description of the application will be rendered by reference to the appended drawings and appended detailed description. It should be noted that, without conflict, the embodiments of the present application and features in the embodiments may be combined with each other.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present application, however, the present application may be practiced otherwise than as described herein, and therefore the scope of the present application is not limited to the specific embodiments disclosed below.
Fig. 1 shows one of the flow diagrams of a recommendation method for a brand of a vehicle according to one embodiment of the present application. As shown in fig. 1, the method includes:
s102: acquiring browsing data of a user in a driving training application program;
s104: determining a target vehicle brand according to the browsing data;
s106: pushing the vehicle purchasing information of the target vehicle brand to a user according to the target vehicle brand;
s108: personal information authorized by a user and reserved in a driving training application program is obtained;
s110: the personal information is sent to a sales enterprise of the target vehicle brand.
According to the recommendation method for the vehicle brands, the sales enterprises of the vehicle brands and the Internet driving training enterprises are combined together, so that information related to the vehicle brands can be displayed in driving training application programs generated by the Internet driving training enterprises. And then acquiring browsing data of the user in the driving training application program, determining a target vehicle brand of the user heart instrument according to the browsing data of the user by utilizing a big data algorithm, and pushing the vehicle purchasing information of the target vehicle brand to the user according to the target vehicle brand of the user heart instrument, such as preferential promotion activities of the target vehicle brand, personalized vehicle purchasing schemes and the like, so as to improve the vehicle purchasing will of the user and the enthusiasm of online reservation. If the user is authorized to purchase the vehicle, personal information reserved in the driving training application program by the user is obtained after the user is authorized and is sent to a sales enterprise of a target vehicle brand, and the vehicle brand of the heart meter of the user is determined according to the browsing data of the user by obtaining the browsing data of the user, so that accuracy of recommending the vehicle brand to the user is improved.
FIG. 2 illustrates a second flow diagram of a method of recommending a brand of a vehicle in accordance with an embodiment of the present application. As shown in fig. 2, the method further includes:
s202: acquiring relevant information of a plurality of vehicle brands;
s204: and pushing the related information of the plurality of vehicle brands to a user through the driving training application program.
In this embodiment, it is also necessary to cooperate with sales enterprises or 4S stores of multiple vehicle brands to acquire relevant information of multiple vehicle brands, such as relevant information of recently new vehicle types, interior decorations, and the like of the vehicle brands, and then push the relevant information of the multiple vehicle brands to a user through a driving training application program. Further, the relevant information of a plurality of vehicle brands is sent to the user, so that more choices are provided for the user, and the accuracy of recommendation is improved.
Fig. 3 is a flowchart illustrating a step of determining a target vehicle brand according to browsing data in a recommendation method of a vehicle brand according to an embodiment of the present application. As shown in fig. 3, this step includes:
s302: determining the most data information in the browsing data according to the browsing data;
s304: matching the data information with the related information of a plurality of vehicle brands, and determining the related information of the vehicle brands opposite to the data information;
s306: and determining the brand of the target vehicle according to the related information of the brand of the vehicle.
In this embodiment, the step of determining the brand of the target vehicle from the browsing data includes: firstly, browsing data of a user is acquired, and then, the most data information in the browsing data is determined according to the browsing data by utilizing an algorithm. By determining the most data information in the browsing data, the user can find out which type of information is interested in, then the data information is matched with the related information of a plurality of vehicle brands, the related information of the vehicle brands opposite to the data information is determined, namely the related information of which vehicle brand the data information belongs to is determined, and then the target vehicle brand, namely the vehicle brand of the user's heart instrument, is determined according to the related information of the vehicle brands. The target vehicle brand interested by the user is determined by analyzing and calculating the browsing data of the user, so that the accuracy of recommendation is further improved.
FIG. 4 illustrates a third flow chart of a method of recommending a brand of a vehicle in accordance with an embodiment of the present application. As shown in fig. 4, the method further includes:
s402: associating the user with the driving school based on the user after finishing registration of the driving training application program;
s404: and generating a digital clue follow-up billboard according to the purchase progress of the user and sending the digital clue follow-up billboard to a driving school.
In this embodiment, it is also possible to cooperate with a driving school in the recommendation method of the brand of the vehicle. The user may register the driving school through the driving training application or the driving school may recommend the driving training application to the user after logging the user. After the registration of the driving training application program is completed, the user is associated with the driving school, so that the user can learn the driving theory in the driving training application program, and the user can conduct operations such as reservation driving exercise, time and fee payment, reservation examination and the like in the driving training application program due to the fact that the user is associated with the driving school in the driving training application program, and the use experience of the user is improved. Further, because the driving training application program is recommended to the user by the driving school, the digital clue follow-up sign is generated according to the vehicle purchasing progress of the user and sent to the driving school, namely, the driving school can check the follow-up state of the recommended vehicle purchasing user through the digital clue follow-up sign. The effective combination of online and offline is realized by establishing a cooperative relationship with a driving school, so that the user satisfaction is improved.
FIG. 5 shows a fourth flow diagram of a method of recommending a brand of a vehicle, according to an embodiment of the present application; according to the recommendation method of the vehicle brands, which is shown in fig. 5, the Internet driving training application program, the vehicle purchasing careless cue platform, the cooperative driving school and the cooperative vehicle enterprise are combined together, and as shown in fig. 5, a user selects the driving school to conduct driving examination registration on the driving training application program or a coach recommends the driving training application program to the user after the driving school registration, and further, the driving school and the user are associated on the driving training application program, so that the user can conduct first-class brushing in the driving training application program, and can conduct reservation examination on the driving training application program after the learning reaches the standard. After the first test of the department passes, the driving school is associated with the user in the driving training application program, so that the user can directly conduct the second reservation driving exercise in the driving training application program and pay the time and expense of the class on line. Further, after the time and fee payment is completed, the user can sign in or sign out the second training vehicle on the driving training application program, so that the driving training application program can record whether the second training time meets the standard, and after the second training time meets the standard, the second training examination can be reserved. After the examination of the second department passes, the reservation driving exercise, the on-site check-in and the on-site check-out of the third department can be performed. And the driver license is taken until the user finishes the whole driving test process. By combining the driving school with the driving training application program, the user is facilitated, and the learning effect of the user is improved.
Further, the vehicle purchasing careless cue platform determines the heart instrument target vehicle brand of the user according to the browsing data of the user, and pushes the vehicle purchasing information of the target vehicle brand to the user, such as preferential promotion activities, personalized vehicle purchasing schemes and the like, if the user has intent to purchase vehicles, a light cue management system in the vehicle purchasing careless cue platform can acquire personal information authorized by the user and then send the personal information to a service system of the cooperative vehicle enterprise, and then after the user obtains a driving license, sales personnel of the cooperative vehicle enterprise follow up according to cues, thereby completing sales. The follow-up condition of the clue is fed back to the careless clue purchasing platform through an application programming interface (Appliacation Programming Interface, API), and then the careless clue purchasing platform generates a digital clue follow-up billboard according to the follow-up condition fed back by the cooperative vehicle enterprise and sends the digital clue follow-up billboard to a cooperative driving school, so that the driving school can check the follow-up state of the recommended purchasing user through the digital clue follow-up billboard.
Further, the user can obtain the point rewards when using the driving training application program, and the point rewards are sent to the user when the user performs operations such as first registration, driving school registration, daily card punching, sharing and giving, exercise and question brushing, appointment driving, class time stage, driving sign-in, driving sign-out, subject achievement, license taking rewards, vehicle browsing and the like. The user can use the points to participate in point activities or point exchange, and the point activities can comprise point lottery, point second killing, point treasuring and point guessing; the point exchange can include car tickets, electronic coupons, life payments, physical goods, and the like. The use interest of the user is improved by issuing points to the user. And further, the vehicle purchase intention of the user and the on-line resource reservation enthusiasm can be improved.
The application realizes the data intercommunication of the vehicle purchasing careless cue platform, the user and the off-line driving school with various large vehicle brands, the vehicle purchasing careless cue platform is fused with the Internet driving training application program, and the user can easily accept and memorize information while providing easy and pleasant learning experience for the driving training student, and the propaganda of the vehicle enterprise products can be accepted more easily. Further, the user can also check on-line reservation information through the shopping cart carefree cue platform, and enjoy preferential to store by sweeping the code. The driving school can check the new vehicle recommendation potential passenger clue follow-up state through the vehicle purchasing careless clue platform, the vehicle purchasing careless clue platform is linked with the vehicle brand system, and the user clue is directly transmitted to the vehicle brand system in real time through encryption so as to be followed by the consultant in time.
FIG. 6 shows a schematic block diagram of a recommendation system for a brand of vehicle, according to an embodiment of the present application. Wherein the recommendation system 60 of the vehicle brand comprises:
a first obtaining module 602, configured to obtain browsing data of a user in a driving training application program;
a first determining module 604, configured to determine a brand of the target vehicle according to the browsing data;
a first pushing module 606, configured to push, to a user, vehicle purchase information of a target vehicle brand according to the target vehicle brand;
a second obtaining module 608, configured to obtain personal information authorized by the user and reserved in the driving training application;
a transmitting module 610 for transmitting the personal information to a sales enterprise of the target vehicle brand.
The recommendation system 60 for the vehicle brand combines a sales enterprise of the vehicle brand with an internet driving training enterprise, so that information related to the vehicle brand can be displayed in a driving training application program generated by the internet driving training enterprise. The recommendation system 60 for a brand of vehicle specifically includes: a first acquisition module 602, a first determination module 604, a first push module 606, a second acquisition module 608, and a transmission module 610. Specifically, the first obtaining module 602 obtains browsing data of the user in the driving training application program, the first determining module 604 determines a target vehicle brand of the user's cardiology according to the browsing data of the user by using a big data algorithm, and the first pushing module 606 pushes vehicle purchasing information of the target vehicle brand to the user according to the target vehicle brand of the user's cardiology, such as preferential promotion activities of the target vehicle brand, personalized vehicle purchasing schemes, and the like, so as to improve the purchase intention of the user and the enthusiasm of online reservation. If the user has a desire to purchase the vehicle, the second obtaining module 608 obtains personal information reserved in the driving training application program by the user after authorization, and sends the personal information to a sales enterprise of the target vehicle brand through the sending module 610, and determines the vehicle brand of the cardiology instrument of the user according to the browsing data of the user by obtaining the browsing data of the user, thereby improving the accuracy of recommending the vehicle brand to the user.
In some embodiments, optionally, the recommendation system 60 for a brand of vehicle further comprises: a third obtaining module, configured to obtain relevant information of a plurality of vehicle brands; and the second pushing module is used for pushing the relevant information of the plurality of vehicle brands to the user through the driving training application program.
In this embodiment, the recommendation system 60 for a brand of vehicle further includes: a third acquisition module and a second pushing module. The third obtaining module obtains relevant information of a plurality of vehicle brands, such as relevant information of a vehicle model, an interior trim and the like which are recently updated by the vehicle brands, and then the second pushing module pushes the relevant information of the plurality of vehicle brands to a user through a driving training application program. Further, the relevant information of a plurality of vehicle brands is sent to the user, so that more choices are provided for the user, and the accuracy of recommendation is improved.
FIG. 7 shows a schematic block diagram of a first determination module in a recommendation system for a brand of vehicle, according to one embodiment of the present application. Wherein the first determining module 604 includes:
a second determining module 6042, configured to determine, according to the browsing data, the most data information in the browsing data;
a third determining module 6044 for determining related information of a vehicle brand opposite to the data information based on the data information and the related information of the plurality of vehicle brands;
fourth determination module 6046 is configured to determine a target vehicle brand according to the related information of the vehicle brand.
In this embodiment, the first determination module 604 includes: the second determination module 6042, the third determination module 6044, and the fourth determination module 6046. First, browsing data of the user is acquired, and then the second determining module 6042 determines the most data information in the browsing data according to the browsing data by using an algorithm. By determining the most data information in the browsing data, it can be found which kind of information is interested by the user, and then the third determining module 6044 matches the data information with the relevant information of a plurality of vehicle brands, determines the relevant information of the vehicle brand opposite to the data information, that is, determines which vehicle brand the data information belongs to, and then the fourth determining module 6046 determines the target vehicle brand, that is, the vehicle brand of the user's heart instrument, according to the relevant information of the vehicle brand. The target vehicle brand interested by the user is determined by analyzing and calculating the browsing data of the user, so that the accuracy of recommendation is further improved.
In some embodiments, optionally, the recommendation system 60 for a brand of vehicle further comprises: the association module is used for associating the user with the driving school based on the fact that the user finishes registering the driving training application program; and the generation module is used for generating a digital clue follow-up billboard according to the vehicle purchasing progress of the user and sending the digital clue follow-up billboard to a driving school.
In this embodiment, it is also possible to cooperate with a driving school in a recommendation system of a vehicle brand. The user may register the driving school through the driving training application or the driving school may recommend the driving training application to the user after logging the user. The recommendation system of the vehicle brand further includes: the association module is used for associating the user with the driving school after the user finishes registration of the driving training application program, so that the user can learn the driving theory in the driving training application program, and the user can conduct operations such as reservation driving, time and fee payment, reservation examination and the like on the driving school in the driving training application program due to the fact that the user associates the user with the driving school in the driving training application program, and therefore the use experience of the user is improved. Further, because the driving training application program is recommended to the user by the driving school, the generating module generates a digital clue follow-up billboard according to the vehicle purchasing progress of the user and sends the digital clue follow-up billboard to the driving school, namely the driving school can check the follow-up state of the clue of the vehicle purchasing user recommended by the driving school through the digital clue follow-up billboard. The effective combination of online and offline is realized by establishing a cooperative relationship with a driving school, so that the user satisfaction is improved.
According to a third object of the present application, there is provided a storage medium having stored thereon a computer program which, when executed by a processor, implements a method of recommending a brand of a vehicle according to any of the embodiments described above.
The storage medium provided by the application realizes the steps of the method for recommending the vehicle brand according to any of the embodiments when the computer program is executed by the processor, so that the storage medium comprises all the beneficial effects of the method for recommending the vehicle brand according to any of the embodiments.
FIG. 8 shows a schematic block diagram of an electronic device in accordance with one embodiment of the application; wherein the electronic device 80 comprises: the present application provides a vehicle brand recommendation method according to any of the embodiments described above, comprising a memory 802, a processor 804, and a computer program stored on the memory 802 and executable on the processor 804, wherein the processor 804 executes the computer program.
The electronic device 80 provided by the present application, when the computer program is executed by the processor 804, implements the steps of the method for recommending a vehicle brand according to any of the above embodiments, so that the electronic device 80 includes all the advantages of the method for recommending a vehicle brand according to any of the above embodiments.
In the description of the present application, it should be understood that the terms "upper", "lower", "front", "rear", "horizontal", "top", "bottom", "inner", "outer", "axial", "radial", "circumferential", etc. indicate orientations or positional relationships based on the positional relationships shown in the drawings, are merely for convenience in describing the present application and simplifying the description, and do not indicate or imply that the devices or elements referred to must have a specific orientation, be configured and operated in a specific orientation, and thus should not be construed as limiting the present application.
In the description of the present specification, the terms "connected," "mounted," "secured," and the like are to be construed broadly, and for example, "connected" may be a fixed connection, a removable connection, or an integral connection; can be directly connected or indirectly connected through an intermediate medium. The specific meaning of the above terms in the present application can be understood by those of ordinary skill in the art according to the specific circumstances.
In the description of the present specification, the terms "one embodiment," "some embodiments," "particular embodiments," and the like, mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present application. In this specification, schematic representations of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
The above is only a preferred embodiment of the present application, and is not intended to limit the present application, but various modifications and variations can be made to the present application by those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the protection scope of the present application.
Claims (10)
1. A method of recommending a brand of a vehicle, the method comprising:
acquiring browsing data of a user in a driving training application program;
determining a target vehicle brand according to the browsing data;
pushing the purchase information of the target vehicle brand to the user according to the target vehicle brand;
acquiring personal information authorized by the user and reserved in the driving training application program;
the personal information is sent to a sales enterprise of the target vehicle brand.
2. The method for recommending a brand of a vehicle according to claim 1, wherein the step of acquiring browsing data of the user in the driving training application comprises the steps of:
acquiring relevant information of a plurality of vehicle brands;
and pushing the relevant information of a plurality of vehicle brands to the user through the driving training application program.
3. The recommendation method of a vehicle brand according to claim 2, wherein the step of determining the target vehicle brand from the browsing data comprises:
determining the most data information in the browsing data according to the browsing data;
matching the data information with the relevant information of a plurality of vehicle brands, and determining the relevant information of the vehicle brands opposite to the data information;
and determining the target vehicle brand according to the related information of the vehicle brand.
4. A method of recommending a brand of a vehicle according to any one of claims 1 to 3, further comprising:
associating the user with a driving school based on the user after the driving training application program is registered;
and generating a digital clue follow-up billboard according to the vehicle purchasing progress of the user and sending the digital clue follow-up billboard to the driving school.
5. A recommendation system for a brand of a vehicle, comprising:
the first acquisition module is used for acquiring browsing data of a user in a driving training application program;
the first determining module is used for determining a brand of a target vehicle according to the browsing data;
the first pushing module is used for pushing the vehicle purchasing information of the target vehicle brand to the user according to the target vehicle brand;
the second acquisition module is used for acquiring personal information authorized by the user and reserved in the driving training application program;
and the sending module is used for sending the personal information to a sales enterprise of the target vehicle brand.
6. The vehicle brand recommendation system of claim 5, further comprising:
the third acquisition module is used for acquiring the related information of a plurality of vehicle brands;
and the second pushing module is used for pushing the relevant information of the plurality of vehicle brands to the user through the driving training application program.
7. The vehicle brand recommendation system of claim 5, wherein the first determination module comprises:
the second determining module is used for determining the most data information in the browsing data according to the browsing data;
a third determining module configured to determine relevant information of the vehicle brand opposite to the data information according to the data information and relevant information of a plurality of vehicle brands;
and the fourth determining module is used for determining the target vehicle brand according to the related information of the vehicle brand.
8. The recommendation system for a brand of a vehicle according to any one of claims 5 to 7, further comprising:
the association module is used for associating the user with a driving school based on the fact that the user finishes registration of the driving training application program;
and the generation module is used for generating a digital clue follow-up billboard according to the vehicle purchasing progress of the user and sending the digital clue follow-up billboard to the driving school.
9. A storage medium having stored thereon a computer program, which when executed by a processor, implements the steps of the vehicle brand recommendation method of any one of claims 1 to 4.
10. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the steps of the recommended method of branding a vehicle according to any of claims 1 to 4 when the computer program is executed by the processor.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310814498.4A CN116703525A (en) | 2023-07-04 | 2023-07-04 | Recommendation method and system of vehicle brands, storage medium and electronic equipment |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310814498.4A CN116703525A (en) | 2023-07-04 | 2023-07-04 | Recommendation method and system of vehicle brands, storage medium and electronic equipment |
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| CN116703525A true CN116703525A (en) | 2023-09-05 |
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| Application Number | Title | Priority Date | Filing Date |
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| CN202310814498.4A Pending CN116703525A (en) | 2023-07-04 | 2023-07-04 | Recommendation method and system of vehicle brands, storage medium and electronic equipment |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116894570A (en) * | 2023-09-11 | 2023-10-17 | 杭州及凌网络科技有限公司 | Salesman recommending method, device and equipment based on automobile sales platform |
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2023
- 2023-07-04 CN CN202310814498.4A patent/CN116703525A/en active Pending
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116894570A (en) * | 2023-09-11 | 2023-10-17 | 杭州及凌网络科技有限公司 | Salesman recommending method, device and equipment based on automobile sales platform |
| CN116894570B (en) * | 2023-09-11 | 2023-12-05 | 杭州及凌网络科技有限公司 | Salesman recommending method, device and equipment based on automobile sales platform |
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