CN108230162B - Insurance service recommendation method and device, storage medium and electronic equipment - Google Patents
Insurance service recommendation method and device, storage medium and electronic equipment Download PDFInfo
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- CN108230162B CN108230162B CN201711483269.XA CN201711483269A CN108230162B CN 108230162 B CN108230162 B CN 108230162B CN 201711483269 A CN201711483269 A CN 201711483269A CN 108230162 B CN108230162 B CN 108230162B
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Abstract
The embodiment of the invention discloses a method and a device for recommending insurance services, a storage medium and electronic equipment. The method comprises the following steps: matching the type of the insurance service to be recommended with the primary label of the family portrait to obtain a target family, determining the insurance service for each family according to the secondary label of each family in the target family, and recommending the insurance service corresponding to each family. According to the embodiment of the invention, the user requirements can be analyzed based on the primary label and the secondary label, so that the insurance service for each family is obtained from the insurance service to be recommended, blind marketing is avoided, the conflict emotion of the user is reduced, the user experience is improved, and efficient, accurate and personalized recommendation of the insurance service is realized.
Description
Technical Field
The invention relates to the technical field of computers, in particular to a method and a device for recommending insurance services, a storage medium and electronic equipment.
Background
With the deepening of the socialist market economy, like most commodities, insurance services, a special "commodity" has also distinguished the shortage period and started to compete in the market. In the past, the marketing idea of 'producing' and 'providing' products is concentrated on, the marketing idea cannot adapt to the changed operation environment, and the marketing is gradually paid attention to by the insurance boundary as a brand-new theory and method of operation management and is introduced into the new field.
At present, each insurance company feels the fierce market competition, gives a global solution, and actively recommends insurance services to users from the aspects of operation diversification (group operation such as production insurance, life insurance, investment and the like), channel diversification (expansion of organization networks, rapid development of agents, bank insurance, online marketing and the like), means modernization (television advertisement, public welfare activities, the internet and the like) and the like.
In the process of implementing the invention, the inventor finds that the blindly popular insurance service recommendation method in the prior art cannot implement targeted and flexible recommendation of insurance services, and reduces the effectiveness of insurance service recommendation.
Therefore, a new insurance service recommendation method, apparatus, storage medium and electronic device are needed to implement personalized recommendation of insurance services.
It is to be noted that the information disclosed in the above background section is only for enhancement of understanding of the background of the embodiments of the present invention and therefore may include information that does not constitute prior art known to a person of ordinary skill in the art.
Disclosure of Invention
In view of this, the invention provides a method, an apparatus, a storage medium and an electronic device for recommending insurance services, which realize efficient, accurate and personalized recommendation of insurance services.
Additional features and advantages of the invention will be set forth in the detailed description which follows, or may be learned by practice of the invention.
According to a first aspect of the embodiments of the present invention, there is provided a method for insurance service recommendation, wherein the method includes:
matching the type of insurance service to be recommended with a primary label of the family portrait to obtain a target family;
determining insurance services for each family in the target family according to the secondary label of each family;
and recommending insurance services corresponding to the families.
According to some embodiments, the method further comprises:
generating family relations of a plurality of families according to insurance data in the big data platform;
a plurality of families are generated according to the information of the members in each family, and a family representation of at least one primary label included in each family is constructed.
According to some embodiments, generating family relationships for a plurality of households from insurance data in a big data platform includes:
generating family relations of a plurality of families according to first insurance policy data from the WeChat client accessed by using a web service mode in the big data platform; and/or the presence of a gas in the gas,
generating family relations of a plurality of families according to second policy data from a service database accessed by using an sqoop technology in a big data platform;
wherein the first keep-alive data comprises: insurance policy data for transaction at the wechat client and sharing interaction data for insurance policies at the wechat client;
the second policy data includes: policy data for committed policies offline or online, in addition to policy data committed by the WeChat client, and customer data.
According to some embodiments, generating a plurality of families based on information about members in each family, and constructing a family representation of at least one primary tag included in each family, comprises:
according to the similarity of the information of the members in each family, a plurality of families are generated, and family representations of at least one primary label included in each family are constructed based on the similarity.
According to some embodiments, matching the type of insurance service to be recommended with the primary label of the family portrait to obtain the target family comprises:
setting a matching relation between the insurance service type and a primary label of the family portrait;
after the insurance service type to be recommended is obtained, the primary label of the family portrait matched with the insurance service type to be recommended is found, and a target family is obtained.
According to some embodiments, the secondary label includes at least one of basic information, insurance dimension information, and network behavior information;
wherein the network behavior information comprises network behavior information for a specified website.
According to some embodiments, when the secondary label includes basic information, determining an insurance service for each household in the target family from the secondary label of the respective household includes:
and determining insurance services for each family from the types of the insurance services to be recommended according to at least one of age information, gender information, region information, occupation information and marital information of each member in the basic information of each family.
According to some embodiments, when the secondary label includes insurance dimension information, determining an insurance service for each household in the target family from the secondary label for the respective household includes:
and determining the insurance service for each family from the type of the insurance service to be recommended according to at least one of policy type information, policy number information and insurance amount information of each policy of each family in the insurance dimension information of each family.
According to some embodiments, when the secondary label includes network behavior information, determining an insurance service for each household in the target family from the secondary label for the respective household includes:
and determining insurance services for each family from the types of the insurance services to be recommended according to at least one of the page stay information, the browsing product information, the accumulated health test information, the date information concerning the specified website and the date bound with the specified website of each member in each family.
According to some embodiments, recommending, to the respective households, insurance services corresponding to the respective households includes:
determining a mode of recommending insurance services for each family according to the secondary label of each family in the target family;
and recommending the insurance service corresponding to each family in the mode.
According to some embodiments, after recommending the insurance service corresponding to each family, the method further comprises:
and recommending the insurance service to be recommended to other families according to the interpersonal relationship information of each family in the target family.
According to a second aspect of the embodiments of the present invention, there is provided an insurance service recommendation apparatus, wherein the apparatus includes:
the matching module is used for matching the type of the insurance service to be recommended with the primary label of the family portrait to obtain a target family;
the determining module is used for determining insurance services aiming at each family according to the secondary label of each family in the target family;
and the recommending module is used for recommending the insurance service corresponding to each family.
There is provided a computer readable storage medium having a computer program stored thereon, wherein the program realizes the method steps according to the first aspect when executed by a processor.
According to a fourth aspect of the present invention, an electronic device is provided, comprising: one or more processors; storage means for storing one or more programs which, when executed by the one or more processors, cause the one or more processors to carry out the method steps as described in the first aspect.
In the embodiment of the invention, the insurance service corresponding to each family is recommended to each family by matching the type of the insurance service to be recommended with the primary label of the family portrait to obtain the target family and determining the insurance service for each family according to the secondary label of each family in the target family. The user requirements can be analyzed based on the first-level label and the second-level label, and then the insurance service for each family is obtained from the insurance service to be recommended, so that blind marketing is avoided, the conflict emotion of the user is reduced, the user experience is improved, and efficient, accurate and personalized recommendation of the insurance service is realized.
Drawings
The above and other objects, features and advantages of the present invention will become more apparent by describing in detail exemplary embodiments thereof with reference to the attached drawings.
FIG. 1 is a flow chart illustrating a method for insurance service recommendation in accordance with an embodiment of the present invention;
FIG. 2 is a schematic representation of a family provided by embodiments of the present invention;
FIG. 3 is a diagram of dimensions of a secondary label provided by an embodiment of the invention;
FIG. 4 is a flow chart of a method for generating a family according to an embodiment of the present invention;
FIG. 5 is a block diagram of an insurance service recommendation apparatus according to an embodiment of the present invention;
fig. 6 is a schematic structural diagram of an electronic device according to an exemplary embodiment.
Detailed Description
Example embodiments will now be described more fully with reference to the accompanying drawings. Example embodiments may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of example embodiments to those skilled in the art. The same reference numerals denote the same or similar parts in the drawings, and thus, a repetitive description thereof will be omitted.
Furthermore, the described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments. In the following description, numerous specific details are provided to provide a thorough understanding of embodiments of the invention. One skilled in the relevant art will recognize, however, that the invention may be practiced without one or more of the specific details, or with other methods, components, devices, steps, and so forth. In other instances, well-known methods, devices, implementations or operations have not been shown or described in detail to avoid obscuring aspects of the invention.
The block diagrams shown in the figures are functional entities only and do not necessarily correspond to physically separate entities. I.e. these functional entities may be implemented in the form of software, or in one or more hardware modules or integrated circuits, or in different networks and/or processor means and/or microcontroller means.
The flow charts shown in the drawings are merely illustrative and do not necessarily include all of the contents and operations/steps, nor do they necessarily have to be performed in the order described. For example, some operations/steps may be decomposed, and some operations/steps may be combined or partially combined, so that the actual execution sequence may be changed according to the actual situation.
Although the terms of first/second, etc. are used to describe the policy data in the embodiment of the present invention, these terms are only used to distinguish the policy data from each other, and do not limit the policy data.
Fig. 1 is a flowchart illustrating a method for insurance service recommendation according to an embodiment of the present invention. As shown in fig. 1, the method may include, but is not limited to, the following steps:
and S110, matching the insurance type to be recommended with the primary label of the family portrait to obtain the target family.
According to the embodiment of the invention, after acquiring the insurance service to be recommended, acquiring the type of the insurance service to be recommended, for example, if an insurance company needs to organize a promotion activity about a product of a child series, the type of the series of insurance service to be recommended can be acquired as child insurance.
According to the embodiment of the invention, a plurality of families can be preset, each family comprises at least one family, and the family representation of each family comprises at least one primary label. The primary labels are for a family, which may include but are not limited to: economic status, insurance coverage, presence of children, presence of elderly, age span, major distribution cities, and family medical history. For example, FIG. 2 is a schematic diagram of a family representation of a family provided by an embodiment of the present invention, the family representation of the family including: the old people and children have the first-level labels.
According to the embodiment of the invention, after the family portrait is set for each family, the matching relationship between the insurance service type and the primary label of the family portrait can be set, and after the insurance service type to be recommended is obtained, the primary label of the family portrait matched with the insurance service type to be recommended is searched to obtain the target family.
For example, when the acquired insurance service type to be recommended is children insurance, a family matched with the children insurance can be found from the matching relationship between the preset insurance service type and the primary label of the family portrait, and the family is a target family.
And S120, determining insurance services aiming at each family according to the secondary label of each family in the target family.
According to an embodiment of the present invention, the secondary label is for a family, and may include: at least one of basic information, insurance dimension information, and network behavior information. The basic information refers to the basic information of each member in the family, the insurance dimension information refers to policy information of the family committed, and the network behavior information comprises the basic information of the network behavior information aiming at the specified website. For example, fig. 3 is a schematic diagram of various dimensions of a secondary label provided by an embodiment of the present invention.
According to the embodiment of the invention, when the secondary label comprises the basic information, the insurance service for each family can be determined from the type of the insurance service to be recommended according to at least one of age information, sex information, region information, occupation information and marital information of each member in the basic information of each family in the target family.
For example, the type of insurance service to be recommended is children insurance, and is matched with a target family including a primary label of children in the family portrait, and the target family includes family a and family B. According to the basic information of each member of the family A and the basic information of each member of the family B, the life condition of the family A is better than that of the family B, so that the children education risk in the children risk is recommended for the family A (the children education risk needs quota payment, more returns, is saved and is guaranteed, and is suitable for the family with stronger household manager strength), and the accidental injury risk in the children risk is recommended for the family B (the accidental injury risk is a consumption type risk, and is cheap in guarantee and high in guarantee).
According to the embodiment of the present invention, when the secondary label includes insurance dimension information, the insurance service for each family can be determined from the type of the insurance service to be recommended according to at least one of policy type information, number of policies information, and premium information of each policy of each family in the insurance dimension information of each family.
For example, the type of insurance service to be recommended is children insurance, and is matched with a target family including a primary label of children in the family portrait, and the target family includes family a and family B. According to the insurance dimension information of the family A, the family A can be known to buy the children accidental injury insurance and not buy the children education insurance, so that the children education insurance can be recommended for the family A. According to insurance dimension information of the family B, the family B can know that the family B does not purchase the children accidental injury danger, and therefore the children accidental injury danger can be recommended for the family B.
According to the embodiment of the invention, when the secondary label comprises network behavior information, insurance services for each family can be determined from the types of the insurance services to be recommended according to at least one of page stay information, browsing product information, accumulated health test information, date information concerning the specified website and date information bound with the specified website of each member in each family.
For example, the type of insurance service to be recommended is children insurance, and is matched with a target family including a primary label of children in the family portrait, and the target family includes family a and family B. Wherein, the members in family A often browse the children education risks released by the insurance company, thereby recommending the children education risks in the children risks for family A, and the members in family B often browse the children accident risks released by the insurance company, thereby recommending the children accident risks for family B.
According to the embodiment of the invention, when the secondary label comprises multiple types of basic information, insurance dimension information and network behavior information, the insurance service for each family in the target family can be comprehensively determined according to the multiple types of secondary labels at the same time. For example, the priority of each secondary label may be set so that insurance services for a home are determined according to the secondary label with the higher priority. Or according to a few majority-compliant principle, for example, when the frequency of certain insurance service in all the secondary labels is determined to be the highest, the insurance service can be determined to be the insurance service for the family, or the insurance services determined by all the secondary labels for the family can be directly recommended to the family.
And S130, recommending insurance services corresponding to the families.
According to the embodiment of the invention, the method for recommending the insurance service for each family can be determined according to the secondary label of each family in the target family, and then the insurance service corresponding to each family is recommended to each family through the method.
For example, the way of recommending insurance services for the family can be determined by age information in the basic information in the secondary label. When the main purchasing member in the family is the old person whose old legs and feet are not convenient, the determined insurance service can be recommended to the member by the way of the WeChat public number after the WeChat related data of the member is acquired.
For another example, the determined insurance service can be recommended for the family by the purchase mode of the established insurance policy in the guarantee dimension information in the secondary label.
For another example, certain insurance services may be recommended for the family members through a specified website in the network behavior information in the secondary label.
It should be noted that, when the secondary label includes multiple types of basic information, insurance dimension information, and network behavior information, the manner of recommending insurance services for each family can be determined comprehensively according to the multiple types of secondary labels at the same time.
In the embodiment of the invention, the insurance service corresponding to each family is recommended to each family by matching the type of the insurance service to be recommended with the primary label of the family portrait to obtain the target family and determining the insurance service for each family according to the secondary label of each family in the target family. The user requirements can be analyzed based on the first-level label and the second-level label, and then the insurance service for each family is obtained from the insurance service to be recommended, so that blind marketing is avoided, the conflict emotion of the user is reduced, the user experience is improved, and efficient, accurate and personalized recommendation of the insurance service is realized.
It should be noted that after the insurance service corresponding to each family is recommended to each family in the target family, the insurance service to be recommended may be further recommended to other families according to the interpersonal relationship information of each family in the target family.
In the embodiment of the invention, the type of the insurance service to be recommended is recommended to other families according to the interpersonal relationship information of each family, so that the trusted social network of the interpersonal relationship information can be utilized, the conflict emotion of the user is reduced, the user experience is improved, and the high-efficiency, accurate and personalized recommendation of the insurance service is realized.
The method for presetting multiple families is described in detail below with reference to specific application scenarios.
Fig. 4 is a flowchart of a method for generating a family according to an embodiment of the present invention. As shown in fig. 4, the method may include, but is not limited to, the following steps:
and S410, generating the family relations of a plurality of families according to the insurance data in the big data platform.
According to the embodiment of the invention, the family relations of a plurality of families can be generated according to the first policy data from the WeChat client accessed by using the web service mode in the big data platform, and/or the family relations of a plurality of families can be generated according to the second policy data from the service database accessed by using the sqoop technology in the big data platform. Wherein the first keep-alive data comprises: insurance policy data for transaction at the wechat client and shared interaction data for insurance policies at the wechat client. The second policy data includes: policy data for committed policies offline or online, in addition to policy data committed by the WeChat client, and customer data.
It should be noted that insurance policy data committed at the wechat client and shared interactive data for the insurance policy at the wechat client can be accessed to the big data platform from the Tencent cloud server in a Web Service mode. And the policy data (comprising various risk types such as life insurance, financial insurance and vehicle insurance) and the customer data of the online or offline committed insurance policy, which are except the policy data committed by the WeChat client, can be accessed to the big data platform from the business database through the sqoop technology.
According to the first policy data and/or the second policy data, a family relationship of a plurality of families can be generated. For example, family relationships may be mined based on the policy's (applicant's) and (beneficiary's) invested (insured) relationships in the first policy data. For example, family relationships may be mined based on the relationship of the applicant (applicant) to the beneficiary (beneficiary) in the second policy data. It should be noted that, according to the policy adding and sharing and message leaving interaction behavior data for the policy in the second policy data, the family relationship can be further improved and the interpersonal relationship information of each family can be obtained.
It should be noted that after the family relations of a plurality of families are generated, the basic information and insurance dimension information in the secondary label of each family can be further generated according to the first insurance policy data and/or the second insurance policy data of each family. And the network behavior information aiming at the specified website can be generated into the network behavior information in the secondary label of each family by using the network behavior data aiming at the specified website accessed by a front-end page js interpolation code and a Nginx server log acquisition technology in a big data platform.
And S420, generating a plurality of families according to the information of the members in each family, and constructing a family portrait of at least one primary label included in each family.
According to the embodiment of the invention, a plurality of families can be generated according to the similarity of the information of the members in each family, and the family portrait of at least one primary label included in each family is constructed based on the similarity.
For example, family a includes a child aged 10, family B includes a child aged 9, family a and family B include members with high similarity, family a and family B may be used to generate a family, the family representation of which includes a primary label: there are children.
It is noted that each family includes at least one primary label, and each family may belong to multiple families. Assuming that family A and family B have family representations that include a primary label for a child, and family A and family B also each include a member aged over 60, family A and family B also have a primary label in their family representations: there are old people. Assuming family A and family B have family representations that include a primary label for a child, and family A also includes a member aged over 60, family A may create a family with family members including family C aged over 60, the family representation of the family including a primary label: there are old people.
It should be clearly understood that the present disclosure describes how to make and use particular examples, but the principles of the present disclosure are not limited to any details of these examples. Rather, these principles can be applied to many other embodiments based on the teachings of the present disclosure.
The following are embodiments of the apparatus of the present invention that may be used to perform embodiments of the method of the present invention. In the following description of the apparatus, the same parts as those of the foregoing method will not be described again.
Fig. 5 is a block diagram of an insurance service recommendation apparatus according to an embodiment of the present invention, and as shown in fig. 5, the apparatus 500 includes:
the matching module 510 is used for matching the type of the insurance service to be recommended with the primary label of the family portrait to obtain a target family;
a determining module 530, configured to determine, according to the secondary labels of the respective households in the target family, insurance services for the respective households;
a recommending module 530, configured to recommend the insurance service corresponding to each family.
In the embodiment of the invention, the insurance service corresponding to each family is recommended to each family by matching the type of the insurance service to be recommended with the primary label of the family portrait to obtain the target family and determining the insurance service for each family according to the secondary label of each family in the target family. The user requirements can be analyzed based on the first-level label and the second-level label, and then the insurance service for each family is obtained from the insurance service to be recommended, so that blind marketing is avoided, the conflict emotion of the user is reduced, the user experience is improved, and efficient, accurate and personalized recommendation of the insurance service is realized.
As another aspect, the present application also provides a computer-readable medium, which may be contained in the apparatus described in the above embodiments; or may be separate and not incorporated into the device. The computer readable medium carries one or more programs which, when executed by a device, cause the device to perform: matching the type of insurance service to be recommended with a primary label of the family portrait to obtain a target family; determining insurance services for each family in the target family according to the secondary label of each family; and recommending insurance services corresponding to the families.
Fig. 6 is a schematic structural diagram of an electronic device according to an exemplary embodiment. It should be noted that the electronic device shown in fig. 6 is only an example, and should not bring any limitation to the functions and the use range of the embodiment of the present application.
As shown in fig. 6, the computer system 600 includes a Central Processing Unit (CPU)601 that can perform various appropriate actions and processes according to a program stored in a Read Only Memory (ROM)602 or a program loaded from a storage section 608 into a Random Access Memory (RAM) 603. In the RAM 603, various programs and data necessary for the operation of the system 600 are also stored. The CPU601, ROM 602, and RAM 603 are connected to each other via a bus 604. An input/output (I/O) interface 605 is also connected to bus 604.
The following components are connected to the I/O interface 605: an input portion 606 including a keyboard, a mouse, and the like; an output portion 607 including a display such as a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and the like, and a speaker; a storage section 608 including a hard disk and the like; and a communication section 609 including a network interface card such as a LAN card, a modem, or the like. The communication section 609 performs communication processing via a network such as the internet. The driver 610 is also connected to the I/O interface 605 as needed. A removable medium 611 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is mounted on the drive 610 as necessary, so that a computer program read out therefrom is mounted in the storage section 608 as necessary.
In particular, according to an embodiment of the present disclosure, the processes described above with reference to the flowcharts may be implemented as computer software programs. For example, embodiments of the present disclosure include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising program code for performing the method illustrated in the flow chart. In such an embodiment, the computer program may be downloaded and installed from a network through the communication section 609, and/or installed from the removable medium 611. The above-described functions defined in the system of the present application are executed when the computer program is executed by the Central Processing Unit (CPU) 601.
It should be noted that the computer readable medium shown in the present application may be a computer readable signal medium or a computer readable storage medium or any combination of the two. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of the computer readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the present application, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In this application, however, a computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, fiber optic cable, RF, etc., or any suitable combination of the foregoing.
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present application. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. 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 involved. It will also be noted that each block of the block diagrams or flowchart illustration, and combinations of blocks in the block diagrams or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The units described in the embodiments of the present application may be implemented by software or hardware. The described modules may also be provided in a processor, which may be described as: a processor includes a matching module, a determination module, and a recommendation module. Wherein the names of the modules do not in some cases constitute a limitation of the module itself.
Exemplary embodiments of the present invention are specifically illustrated and described above. It is to be understood that the invention is not limited to the precise construction, arrangements, or instrumentalities described herein; on the contrary, the invention is intended to cover various modifications and equivalent arrangements included within the spirit and scope of the appended claims.
Claims (11)
1. A method for insurance service recommendation, the method comprising:
generating family relations of a plurality of families according to insurance data in the big data platform;
generating a plurality of families according to the similarity of the information of each member in each family, and constructing a family portrait of at least one primary label included in each family based on the similarity;
setting a matching relation between the insurance service type and a primary label of the family portrait;
after acquiring the insurance service type to be recommended, finding a primary label of the family portrait matched with the insurance service type to be recommended so as to acquire a target family;
determining insurance services for each family in the target family according to the secondary label of each family; when each family comprises a plurality of secondary labels, setting the priority of each secondary label, and determining the insurance service for each family according to the secondary label with high priority;
and recommending insurance services corresponding to the families.
2. The method of claim 1, wherein generating family relationships for a plurality of households based on insurance data in a big data platform comprises:
generating family relations of a plurality of families according to first insurance policy data from the WeChat client accessed by using a web service mode in the big data platform; and/or the presence of a gas in the gas,
generating family relations of a plurality of families according to second policy data from a service database accessed by using an sqoop technology in a big data platform;
wherein the first keep-alive data comprises: insurance policy data for transaction at the wechat client and sharing interaction data for insurance policies at the wechat client;
the second policy data includes: policy data for committed policies offline or online, in addition to policy data committed by the WeChat client, and customer data.
3. The method of claim 1, wherein the secondary label comprises at least one of basic information, insurance dimension information, and network behavior information;
wherein the network behavior information comprises network behavior information for a specified website.
4. The method of claim 3, wherein determining insurance services for each household in the target family from the secondary label for the respective household when the secondary label includes basic information comprises:
and determining insurance services for each family from the types of the insurance services to be recommended according to at least one of age information, gender information, region information, occupation information and marital information of each member in the basic information of each family.
5. The method of claim 3, wherein when the secondary label includes insurance dimension information, determining insurance services for each household in the target family from the secondary label for the respective household comprises:
and determining the insurance service for each family from the type of the insurance service to be recommended according to at least one of policy type information, policy number information and insurance amount information of each policy of each family in the insurance dimension information of each family.
6. The method of claim 3, wherein determining the insurance service for each household in the target family based on the secondary label for the respective household when the secondary label includes network behavior information comprises:
and determining insurance services for each family from the types of the insurance services to be recommended according to at least one of the page stay information, the browsing product information, the accumulated health test information, the date information concerning the specified website and the date bound with the specified website of each member in each family.
7. The method of claim 1, wherein recommending insurance services for the respective households to the respective households comprises:
determining a mode of recommending insurance services for each family according to the secondary label of each family in the target family;
and recommending the insurance service corresponding to each family in the mode.
8. The method of claim 1, wherein after recommending the insurance service corresponding to the respective household, the method further comprises:
and recommending the insurance service to be recommended to other families according to the interpersonal relationship information of each family in the target family.
9. An apparatus for insurance service recommendation, the apparatus comprising:
the matching module is used for generating the family relations of a plurality of families according to the insurance data in the big data platform;
generating a plurality of families according to the similarity of the information of each member in each family, and constructing a family portrait of at least one primary label included in each family based on the similarity;
setting a matching relation between the insurance service type and a primary label of the family portrait;
after acquiring the insurance service type to be recommended, finding a primary label of the family portrait matched with the insurance service type to be recommended so as to acquire a target family;
the determining module is used for determining insurance services aiming at each family according to the secondary label of each family in the target family; when each family comprises a plurality of secondary labels, setting the priority of each secondary label, and determining the insurance service for each family according to the secondary label with high priority;
and the recommending module is used for recommending the insurance service corresponding to each family.
10. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the method steps of any one of claims 1 to 8.
11. An electronic device, comprising:
one or more processors;
storage means for storing one or more programs which, when executed by the one or more processors, cause the one or more processors to carry out the method steps of any one of claims 1-8.
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