CN113761370A - Insurance product recommendation method, system, device and storage medium - Google Patents

Insurance product recommendation method, system, device and storage medium Download PDF

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CN113761370A
CN113761370A CN202111048214.2A CN202111048214A CN113761370A CN 113761370 A CN113761370 A CN 113761370A CN 202111048214 A CN202111048214 A CN 202111048214A CN 113761370 A CN113761370 A CN 113761370A
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user
insurance product
browsing
user terminal
recommendation
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CN113761370B (en
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陈远
范文杰
李廷威
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Guangdong Baijia Information Technology Co ltd
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Guangdong Baijia Investment Consulting Co ltd
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/90—Details of database functions independent of the retrieved data types
    • G06F16/95—Retrieval from the web
    • G06F16/953—Querying, e.g. by the use of web search engines
    • G06F16/9535—Search customisation based on user profiles and personalisation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00—Commerce
    • G06Q30/06—Buying, selling or leasing transactions
    • G06Q30/0601—Electronic shopping [e-shopping]
    • G06Q30/0631—Item recommendations
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q40/00—Finance; Insurance; Tax strategies; Processing of corporate or income taxes
    • G06Q40/08—Insurance
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D10/00—Energy efficient computing, e.g. low power processors, power management or thermal management

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Abstract

The invention discloses a method, a system, a device and a storage medium for recommending insurance products, which can be widely applied to the technical field of recommendation. The method comprises the following steps: acquiring a plurality of browsing process nodes of the insurance product; setting data acquisition points on the plurality of browsing process nodes; acquiring browsing information of the user terminal acquired by the data acquisition point in real time; determining a user tag of the user terminal according to the browsing information; and determining recommendation times by adopting a preset recommendation model according to the user tag, and recommending insurance products to the user terminal according to the recommendation times. The invention can effectively recommend insurance products to the user and control the recommendation times without depending on a large amount of user behavior data so as to improve the user experience.

Description

Insurance product recommendation method, system, device and storage medium
Technical Field
The invention relates to the technical field of recommendation, in particular to an insurance product recommendation method, system, device and storage medium.
Background
In the related art, the recommendation algorithm is to use some mathematical algorithms to infer the things that the user may like by using some behaviors of the user, and send the things that the user may like to the user terminal for displaying. The current recommendation algorithm can effectively recommend the insurance product depending on a large amount of user behavior data, most users in the insurance product do not see or hardly see information about insurance, and the information is searched only when the information is needed, so that the accuracy of the existing recommendation method in the recommendation of the insurance product is lower. And the contents recommended by the recommendation algorithms of multiple types are mostly the same, so that the recommendation information seen by the user in different webpages or software is the same, and the user experience is reduced.
Disclosure of Invention
The present invention is directed to solving at least one of the problems of the prior art. Therefore, the invention provides an insurance product recommendation method, system, device and storage medium, which can improve insurance recommendation accuracy and user experience.
In one aspect, an embodiment of the present invention provides an insurance product recommendation method, including the following steps:
acquiring a plurality of browsing process nodes of the insurance product;
setting data acquisition points on the plurality of browsing process nodes;
acquiring browsing information of the user terminal acquired by the data acquisition point in real time;
determining a user tag of the user terminal according to the browsing information;
and determining recommendation times by adopting a preset recommendation model according to the user tag, and recommending insurance products to the user terminal according to the recommendation times.
In some embodiments, the recommendation method further comprises the steps of:
acquiring recommendation effect information and feedback information of the recommended product;
and adjusting the model parameters of the preset recommendation model according to the recommendation effect information and the feedback information.
In some embodiments, the process steps of the insurance product include sub-steps including a user entering an advertisement page, a user clicking on an advertisement, entering a pickup page, filling in personal information, picking up a gift insurance, jumping to a pay insurance, forming a first payment, paying a public account, and completing an operation, the browsing process node being a start node of each of the sub-steps.
In some embodiments, the determining the user tag of the user terminal according to the browsing information includes:
acquiring a browsing flow node of the user terminal jumping out of the insurance product in the browsing information;
and determining the user label of the user terminal according to the browsing flow node jumping out of the insurance product.
In some embodiments, the determining the user tag of the user terminal according to the browsing flow node jumping out of the insurance product includes:
determining a jump-out type of a browsing flow node for jumping out and browsing the insurance product;
and determining the user label of the user terminal according to the jumping-out type.
In some embodiments, when the step of acquiring browsing information of the user terminal acquired by the data acquisition point in real time is performed, the method further includes the following steps:
acquiring personal information of the user terminal acquired by the data acquisition point in real time;
and determining the insurance products to be recommended according to the personal information.
In some embodiments, the recommending an insurance product to the user terminal includes:
and recommending the insurance product to be recommended to the user terminal.
In another aspect, an embodiment of the present invention provides an insurance product recommendation system, including:
the first acquisition module is used for acquiring a plurality of browsing process nodes of the insurance product;
the setting module is used for setting data acquisition points on the browsing process nodes;
the second acquisition module is used for acquiring the browsing information of the user terminal acquired by the data acquisition point in real time;
the determining module is used for determining a user label of the user terminal according to the browsing information;
and the recommending module is used for determining the recommending times by adopting a preset recommending model according to the user tags and recommending insurance products to the user terminal according to the recommending times.
In another aspect, an embodiment of the present invention provides an insurance product recommendation apparatus, including:
at least one memory for storing a program;
at least one processor for loading the program to perform the insurance product recommendation method described above.
In another aspect, an embodiment of the present invention provides a storage medium in which a computer-executable program is stored, and the computer-executable program is executed by a processor to implement the insurance product recommendation method described above.
The embodiment of the invention provides an insurance product recommendation method, which has the following beneficial effects:
according to the method, the plurality of browsing process nodes of the insurance product are obtained firstly, the data acquisition points are arranged on the plurality of browsing process nodes, the browsing information of the user terminal acquired by the data acquisition points in real time is obtained, the user label of the user terminal is determined according to the browsing information, the recommendation times are determined by adopting the preset recommendation model according to the user label, and the insurance product is recommended to the user terminal according to the recommendation times, so that the insurance product can be effectively recommended to the user and the recommendation times are controlled without depending on a large amount of user behavior data, and the user experience is improved.
Additional aspects and advantages of the invention will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the invention.
Drawings
The invention is further described with reference to the following figures and examples, in which:
FIG. 1 is a flow chart of an insurance product recommendation method according to an embodiment of the present invention;
FIG. 2 is a flow chart of the process steps of an insurance product according to an embodiment of the invention;
FIG. 3 is a general flow chart of a recommendation process of an embodiment of the present invention.
Detailed Description
Reference will now be made in detail to embodiments of the present invention, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the accompanying drawings are illustrative only for the purpose of explaining the present invention, and are not to be construed as limiting the present invention.
In the description of the present invention, the meaning of a plurality is one or more, the meaning of a plurality is two or more, and the above, below, exceeding, etc. are understood as excluding the present numbers, and the above, below, within, etc. are understood as including the present numbers. If the first and second are described for the purpose of distinguishing technical features, they are not to be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated or implicitly indicating the precedence of the technical features indicated.
In the description of the present invention, unless otherwise explicitly defined, terms such as set, etc. should be broadly construed, and those skilled in the art can reasonably determine the specific meanings of the above terms in the present invention in combination with the detailed contents of the technical solutions.
In the description of the present invention, reference to the description of the terms "one embodiment," "some embodiments," "an illustrative embodiment," "an example," "a specific example," or "some examples," etc., means that a particular feature or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
Referring to fig. 1, an embodiment of the present invention provides an insurance product recommendation method, which may be applied to a background control end of recommendation software or a server. The background control end and the server can interact with each terminal, and the terminals comprise mobile phones, tablets and other terminal equipment of users.
In the application process, the embodiment includes the following steps:
and S11, acquiring a plurality of browsing flow nodes of the insurance product.
In the embodiment of the present application, as shown in fig. 2, the process of the insurance product of the embodiment includes several sub-steps, where the several sub-steps include a user entering an advertisement page, a user clicking an advertisement, entering a pickup page, filling in personal information, picking up a gift insurance, jumping to a pay insurance, forming a first payment, paying a public number, and completing operations. The browsing flow node is the starting node of each sub-step. For example, when a user terminal wants to browse an advertisement, the user terminal can enter an advertisement page by clicking software of a certain webpage, and a corresponding node is a starting node of the user when the user terminal clicks the software of the certain webpage; for another example, when the terminal wants to view the corresponding advertisement, the user can enter the advertisement viewing page by clicking the link of the corresponding advertisement, and the node corresponding to the link of the corresponding advertisement is the node for the user to view the advertisement, that is, the user terminal jumps from the starting node to the node between the advertisement nodes to define the node for the user to view the advertisement. By analogy, the starting node of each sub-step is defined as the node of each step.
And S12, setting data acquisition points on the plurality of browsing flow nodes.
In the embodiment, data acquisition points are arranged on the nodes of each sub-step so as to acquire each sub-step through the data acquisition points, thereby improving the accuracy of the result of the subsequent step. For example, in FIG. 2, a data acquisition Point A is set between the beginning and the user clicking on an advertisement, and a data acquisition Point B is set between the user clicking on an advertisement and entering a pickup page; and setting data acquisition points C between the entering of the getting page and the filling of the personal information, and sequentially operating until the setting of the data acquisition points corresponding to all the nodes is completed.
And S13, acquiring the browsing information of the user terminal acquired by the data acquisition point in real time.
In the embodiment of the application, the browsing information includes browsing duration of each node corresponding to a page by a user, a target node in a jumping-out browsing process, a jumping-out type in the jumping-out browsing process, and the like, that is, the browsing information includes behavior information of the user terminal. In order to improve the recommendation accuracy of insurance products, when browsing information of a user terminal is acquired, personal information uploaded by the user terminal is also required to be acquired, so that the types of the insurance products which are relatively interested by the corresponding users are determined according to the personal information of the users, and the types of the insurance products which are relatively interested by the users are taken as the insurance products to be recommended.
And S14, determining the user label of the user terminal according to the browsing information.
In the embodiment of the application, the interest degree of the user corresponding to the terminal of the user in the insurance product is analyzed according to the behavior information of the user in the browsing process, and the label of the user is determined according to the interest degree obtained through analysis, for example, if the user is interested in the insurance product A through analysis, the label of the user in the insurance product A is a potential customer.
Specifically, a browsing flow node for jumping out of the browsing insurance product by the user terminal in the browsing information is obtained, and then the user tag of the user terminal is determined according to the browsing flow node for jumping out of the browsing insurance product. For example, in fig. 2, after entering the page displaying the insurance advertisement link, i.e., jumping out of the browsing process, the user terminal may determine that the user does not want to browse the advertisement information about insurance. For another example, when the user jumps out of the browsing process when entering the jump payment risk, it can be determined that the user has a certain demand for the insurance product. The user terminal can determine the user label of the user terminal according to the jumping type by determining the jumping type of the browsing flow node for jumping and browsing the insurance product. For example, when the user terminal browses the node filling in the personal information and directly jumps out of the current browsing process, the user is determined to have little interest in the insurance product. For another example, when the user browses to the node forming the first payment, the payment process is not completed within 30 seconds of completing the payment, so that the browsing process is automatically jumped out, and the user is determined to have a greater interest in the current insurance product, possibly based on the problem of the payment, and does not want to purchase the insurance product.
And S15, determining the recommendation times by adopting a preset recommendation model according to the user label, and recommending the insurance product to the user terminal according to the recommendation times.
In the embodiment of the application, the recommendation frequency of the insurance product of the current user is determined according to the label of the user, so that the experience effect of the user on the insurance product is improved. For example, it is determined that the current user has only a little interest in insurance products, but recommending the user with insurance products many times greatly reduces the user's experience of the insurance products. If it is determined that the current user has a great interest in insurance products, but the user is rarely sent a recommended link for the insurance products, the user's experience of the insurance products may be reduced, or even lost. In the implementation, when the user is determined to have little interest in the insurance product, less recommendation times are set to recommend the insurance product to the user, so that the impression of the user on the insurance product is improved, and the experience effect of the user on the insurance product is improved; when the user's interest in the insurance product is determined to be strong, the relatively frequent recommendation times are set to send the recommendation link of the insurance product to the user, so that the user experience is improved. In this embodiment, the insurance products recommended to the user terminal are all the insurance products to be recommended which are predetermined.
In some embodiments, when it is determined that the reason for the user to give up the insurance product is the purchase amount, the product recommendation link may be sent to the user after setting a relatively low fee before sending the insurance product recommendation link to the user; or when the user sends the current insurance product link, the link of other similar products with relatively low price is attached, so that the user screening is facilitated, and the user experience is improved.
In some embodiments, a plurality of recommendation modes are preset in the preset recommendation model, for example, a weighted recommendation mode: weighting the multiple recommendation results and then determining a final recommendation result; and (3) converting a recommendation mode: determining to change different recommendation technologies according to the problem background and the actual situation or requirement; and (3) mixed recommendation mode: meanwhile, various recommendation techniques are adopted to give various recommendation results, so that reference is provided for the user; feature Combination (Feature Combination) combining features from different recommended data sources is employed by another recommendation algorithm; stacking (Cascade): firstly, a coarse recommendation result is generated by using a recommendation technology, and a second recommendation technology further makes more accurate recommendation on the basis of the recommendation result; feature Augmentation (Feature Augmentation): embedding additional feature information generated by one technique into the feature input of another recommended technique; meta-level (Meta-Ievel) a model generated with one recommendation method is used as input for another recommendation method.
In some embodiments, after the recommendation method completes the recommendation of the insurance product, the recommendation effect information and the feedback information of the recommended product are obtained, and the model parameters of the preset recommendation model are adjusted according to the recommendation effect information and the feedback information. After the recommendation effect information can be sent to the user terminal through the insurance link, the click times of the link by the user terminal are obtained; the feedback information may be obtained by a query reply message sent by the user to the recommender regarding the insurance product recommendation link after the user receives the link. According to the method and the device, parameters of the recommendation model are adjusted through the recommendation effect information and the feedback information, so that the recommendation model can be recommended in a recommendation mode which is more in line with the actual situation in the subsequent recommendation process.
In summary, in the recommendation process of the embodiment, as shown in fig. 3, information submitted by a user is acquired, meanwhile, background data is acquired and data is processed, then, the recommendation times of insurance products and products to be recommended are determined according to the data processing result, the products to be checked are intelligently pushed to a user terminal, the users can receive and check the products conveniently, data feedback sent by the user terminal is received, and parameters of a recommendation model are adjusted according to the data feedback, so that the recommendation model is closer to actual requirements of the users in a subsequent recommendation process, and user experience is improved.
The embodiment of the invention provides an insurance product recommendation system, which comprises:
the first acquisition module is used for acquiring a plurality of browsing process nodes of the insurance product;
the setting module is used for setting data acquisition points on the browsing process nodes;
the second acquisition module is used for acquiring the browsing information of the user terminal acquired by the data acquisition point in real time;
the determining module is used for determining a user label of the user terminal according to the browsing information;
and the recommending module is used for determining the recommending times by adopting a preset recommending model according to the user tags and recommending insurance products to the user terminal according to the recommending times.
The content of the embodiment of the method of the invention is all applicable to the embodiment of the system, the function of the embodiment of the system is the same as the embodiment of the method, and the beneficial effect achieved by the embodiment of the system is the same as the beneficial effect achieved by the method.
The embodiment of the invention provides an insurance product recommending device, which comprises:
at least one memory for storing a program;
at least one processor configured to load the program to perform the insurance product recommendation method shown in FIG. 1.
The content of the method embodiment of the present invention is applicable to the apparatus embodiment, the functions specifically implemented by the apparatus embodiment are the same as those of the method embodiment, and the beneficial effects achieved by the apparatus embodiment are also the same as those achieved by the method.
An embodiment of the present invention provides a storage medium in which a computer-executable program is stored, which, when being executed by a processor, is used to implement the insurance product recommendation method shown in fig. 1.
Embodiments of the present invention also provide a computer program product or computer program comprising computer instructions stored in a computer readable storage medium. The computer instructions may be read by a processor of a computer device from a computer-readable storage medium, and executed by the processor to cause the computer device to perform the method illustrated in fig. 1.
In alternative embodiments, the functions/acts noted in the block diagrams may occur out of the order noted in the operational illustrations. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality/acts involved. Furthermore, the embodiments presented and described in the flow charts of the present invention are provided by way of example in order to provide a more thorough understanding of the technology. The disclosed methods are not limited to the operations and logic flows presented herein. Alternative embodiments are contemplated in which the order of various operations is changed and in which sub-operations described as part of larger operations are performed independently.
Furthermore, although the present invention is described in the context of functional modules, it should be understood that, unless otherwise stated to the contrary, one or more of the described functions and/or features may be integrated in a single physical device and/or software module, or one or more functions and/or features may be implemented in a separate physical device or software module. It will also be appreciated that a detailed discussion of the actual implementation of each module is not necessary for an understanding of the present invention. Rather, the actual implementation of the various functional modules in the apparatus disclosed herein will be understood within the ordinary skill of an engineer, given the nature, function, and internal relationship of the modules. Accordingly, those skilled in the art can, using ordinary skill, practice the invention as set forth in the claims without undue experimentation. It is also to be understood that the specific concepts disclosed are merely illustrative of and not intended to limit the scope of the invention, which is defined by the appended claims and their full scope of equivalents.
The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
The logic and/or steps represented in the flowcharts or otherwise described herein, e.g., an ordered listing of executable instructions that can be considered to implement logical functions, can be embodied in any computer-readable medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, processor-containing system, or other system that can fetch the instructions from the instruction execution system, apparatus, or device and execute the instructions. For the purposes of this description, a "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device.
More specific examples (a non-exhaustive list) of the computer-readable medium would include the following: an electrical connection (electronic device) having one or more wires, a portable computer diskette (magnetic device), a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). Additionally, the computer-readable medium could even be paper or another suitable medium upon which the program is printed, as the program can be electronically captured, via for instance optical scanning of the paper or other medium, then compiled, interpreted or otherwise processed in a suitable manner if necessary, and then stored in a computer memory.
It should be understood that portions of the present invention may be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, the various steps or methods may be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, any one or combination of the following techniques, which are known in the art, may be used: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application specific integrated circuit having an appropriate combinational logic gate circuit, a Programmable Gate Array (PGA), a Field Programmable Gate Array (FPGA), or the like.
The embodiments of the present invention have been described in detail with reference to the accompanying drawings, but the present invention is not limited to the above embodiments, and various changes can be made within the knowledge of those skilled in the art without departing from the gist of the present invention. Furthermore, the embodiments of the present invention and the features of the embodiments may be combined with each other without conflict.

Claims (10)

1. An insurance product recommendation method, comprising the steps of:
acquiring a plurality of browsing process nodes of the insurance product;
setting data acquisition points on the plurality of browsing process nodes;
acquiring browsing information of the user terminal acquired by the data acquisition point in real time;
determining a user tag of the user terminal according to the browsing information;
and determining recommendation times by adopting a preset recommendation model according to the user tag, and recommending insurance products to the user terminal according to the recommendation times.
2. The insurance product recommendation method of claim 1, further comprising the steps of:
acquiring recommendation effect information and feedback information of the recommended product;
and adjusting the model parameters of the preset recommendation model according to the recommendation effect information and the feedback information.
3. The insurance product recommendation method according to claim 1, wherein the process step of the insurance product comprises a plurality of sub-steps, the plurality of sub-steps comprises user entering an advertisement page, user clicking an advertisement, entering a pickup page, filling personal information, picking up a gift insurance, jumping to a payment insurance risk, forming a first payment, paying a public number and completing operation, and the browsing process node is a start node of each sub-step.
4. The insurance product recommendation method according to claim 1, wherein said determining a user tag of said user terminal based on said browsing information comprises:
acquiring a browsing flow node of the user terminal jumping out of the insurance product in the browsing information;
and determining the user label of the user terminal according to the browsing flow node jumping out of the insurance product.
5. The insurance product recommendation method according to claim 4, wherein the determining the user tag of the user terminal according to the browsing flow node jumping out of browsing the insurance product comprises:
determining a jump-out type of a browsing flow node for jumping out and browsing the insurance product;
and determining the user label of the user terminal according to the jumping-out type.
6. The insurance product recommendation method according to claim 1, further comprising the following steps when performing the step of acquiring the browsing information of the user terminal collected by the data collection point in real time:
acquiring personal information of the user terminal acquired by the data acquisition point in real time;
and determining the insurance products to be recommended according to the personal information.
7. The insurance product recommendation method according to claim 6, wherein said recommending an insurance product to the user terminal comprises:
and recommending the insurance product to be recommended to the user terminal.
8. An insurance product recommendation system, comprising:
the first acquisition module is used for acquiring a plurality of browsing process nodes of the insurance product;
the setting module is used for setting data acquisition points on the browsing process nodes;
the second acquisition module is used for acquiring the browsing information of the user terminal acquired by the data acquisition point in real time;
the determining module is used for determining a user label of the user terminal according to the browsing information;
and the recommending module is used for determining the recommending times by adopting a preset recommending model according to the user tags and recommending insurance products to the user terminal according to the recommending times.
9. An insurance product recommendation device, comprising:
at least one memory for storing a program;
at least one processor configured to load the program to perform the insurance product recommendation method of any one of claims 1 to 7.
10. A storage medium having stored therein a computer-executable program for implementing the insurance product recommendation method according to any one of claims 1 to 7 when executed by a processor.
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