Method and device for generating insurance product sales suggestions

Abstract

The invention provides a method and a device for generating insurance product sales suggestions. The method comprises the following steps: displaying a front-end interface; in response to the operation of the sales user on the front-end interface, determining a to-be-promoted insurance product and a to-be-promoted user; obtaining product information of a to-be-promoted insurance product, and obtaining user information of a to-be-promoted user; according to the product information of the to-be-promoted insurance product and the user information of the to-be-promoted user, generating a prompt word; and inputting the cue word into a large model obtained by pre-training for analysis to obtain an insurance product sales suggestion which is output by the large model, aims at the to-be-promoted user and corresponds to the to-be-promoted insurance product. In the scheme, the cue word is generated according to the product information of the to-be-promoted insurance product and the user information of the to-be-promoted user, and the generated graph cue word is input into the large model for analysis, so that the insurance product sales suggestion corresponding to the to-be-promoted insurance product for the to-be-promoted user is obtained; and the insurance product analysis efficiency and the customer experience are improved.

Description

Technical Field

[0001] The present invention relates to the field of large model technology, and in particular to a method and device for generating insurance product sales recommendations. Background Art

[0002] As competition in the insurance market intensifies, insurance salespeople need to more accurately grasp customer needs and provide personalized sales recommendations. Currently, insurance salespeople typically analyze customer needs and insurance product features manually. However, with so many insurance product categories, manual analysis is difficult to conduct. Consequently, personalized sales recommendations cannot be provided, resulting in inefficient insurance product analysis and a poor customer experience. Summary of the Invention

[0003] In view of this, an embodiment of the present invention provides a method and apparatus for generating insurance product sales recommendations to solve the problems of low insurance product analysis efficiency and poor customer experience in manual analysis of insurance product characteristics.

[0004] To achieve the above objectives, the embodiments of the present invention provide the following technical solutions:

[0005] A first aspect of an embodiment of the present invention discloses a method for generating an insurance product sales proposal, the method comprising:

[0006] Display the front-end interface;

[0007] In response to the sales user's operation on the front-end interface, determining the insurance products to be promoted and the users to be promoted;

[0008] Acquiring product information of the insurance product to be promoted, and acquiring user information of the user to be promoted;

[0009] generating prompt words based on the product information of the insurance product to be promoted and the user information of the user to be promoted;

[0010] The prompt words are input into a pre-trained large model for analysis, and an insurance product sales suggestion corresponding to the insurance product to be promoted and targeted at the user to be promoted is obtained from the large model.

[0011] Preferably, obtaining product information of the insurance product to be promoted and obtaining user information of the user to be promoted include:

[0012] Acquiring product information of the insurance product to be promoted from a backend, wherein the backend includes product information of a plurality of pre-configured insurance products;

[0013] Capture basic information and behavior data of the users to be marketed from multiple designated business systems;

[0014] The basic information and behavior data of the user to be marketed are integrated to obtain the user information of the user to be marketed.

[0015] Preferably, generating prompt words based on the product information of the insurance product to be promoted and the user information of the user to be promoted includes:

[0016] Data cleaning and integration are performed on the product information of the insurance product to be promoted and the user information of the user to be promoted to generate prompt words.

[0017] Preferably, the product information at least includes demand background, product positioning, product advantages and sales philosophy; the insurance product sales recommendations at least include personalized sales talk and strategy recommendations.

[0018] Preferably, after obtaining the insurance product sales suggestion output by the large model for the user to be marketed and corresponding to the insurance product to be marketed, the method further includes:

[0019] An insurance product sales suggestion corresponding to the insurance product to be promoted is displayed in the front-end interface for the user to be promoted.

[0020] A second aspect of an embodiment of the present invention discloses a device for generating a sales proposal for an insurance product, the device comprising:

[0021] A display unit, used for displaying a front-end interface;

[0022] A determination unit, configured to determine the insurance products to be promoted and the users to be promoted in response to the sales user's operation on the front-end interface;

[0023] an acquiring unit, configured to acquire product information of the insurance product to be promoted, and user information of the user to be promoted;

[0024] a generating unit, configured to generate prompt words based on the product information of the insurance product to be promoted and the user information of the user to be promoted;

[0025] An analysis unit is used to input the prompt word into a pre-trained large model for analysis, and obtain an insurance product sales suggestion corresponding to the insurance product to be promoted and targeted at the user to be promoted, output by the large model.

[0026] Preferably, the acquisition unit includes:

[0027] A first acquisition module is configured to acquire product information of the insurance product to be promoted from a backend, wherein the backend contains product information of a plurality of pre-configured insurance products;

[0028] A second acquisition module is used to capture the basic information and behavior data of the user to be marketed from multiple designated business systems;

[0029] The integration module is used to integrate the basic information and behavior data of the user to be marketed to obtain the user information of the user to be marketed.

[0030] Preferably, the generating unit is specifically configured to perform data cleaning and integration on the product information of the insurance product to be promoted and the user information of the user to be promoted, so as to generate prompt words.

[0031] Preferably, the product information at least includes demand background, product positioning, product advantages and sales philosophy; the insurance product sales recommendations at least include personalized sales talk and strategy recommendations.

[0032] Preferably, it also includes:

[0033] An output unit is used to display, in the front-end interface, insurance product sales recommendations corresponding to the insurance product to be promoted and targeted at the user to be promoted.

[0034] Based on the above-mentioned embodiment of the present invention, a method and device for generating insurance product sales recommendations are provided. The method comprises the following steps: displaying a front-end interface; determining the insurance product to be promoted and the user to be promoted in response to the sales user's operation on the front-end interface; obtaining product information of the insurance product to be promoted and user information of the user to be promoted; generating prompt words based on the product information of the insurance product to be promoted and the user information of the user to be promoted; inputting the prompt words into a pre-trained large model for analysis, and obtaining an insurance product sales recommendation for the user to be promoted and corresponding to the insurance product to be promoted, output by the large model. In this solution, prompt words are generated based on the product information of the insurance product to be promoted and the user information of the user to be promoted, and the generated prompt words are input into the large model for analysis, thereby obtaining an insurance product sales recommendation for the user to be promoted and corresponding to the insurance product to be promoted, thereby improving the efficiency of insurance product analysis and the customer experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are merely embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying any creative work.

[0036] Figure 1 A flowchart of a method for generating insurance product sales recommendations provided by an embodiment of the present invention;

[0037] Figure 2 Another flow chart of a method for generating insurance product sales recommendations provided by an embodiment of the present invention;

[0038] Figure 3 An architectural diagram of an insurance sales system provided by an embodiment of the present invention;

[0039] Figure 4 A structural block diagram of a device for generating insurance product sales recommendations provided by an embodiment of the present invention;

[0040] Figure 5 Another structural block diagram of an apparatus for generating insurance product sales recommendations provided by an embodiment of the present invention;

[0041] Figure 6 Another structural block diagram of an apparatus for generating insurance product sales recommendations provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0042] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0043] In this application, the terms "comprises," "comprising," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, article, or apparatus that includes a list of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or apparatus. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not preclude the presence of additional identical elements in the process, method, article, or apparatus that includes the element.

[0044] As competition in the insurance market intensifies, insurance salespeople need to more accurately grasp customer needs and provide personalized sales recommendations. Currently, insurance salespeople typically analyze customer needs and insurance product features manually. However, with so many insurance product categories and individual customer needs, insurance salespeople spend a significant amount of time learning about insurance products. Manual analysis of insurance product features and individual customer needs is difficult, making it difficult to provide personalized sales recommendations. This results in inefficient insurance product analysis and a poor customer experience.

[0045] Research has found that there are currently insurance sales assistance systems that assist in insurance sales. These insurance sales assistance systems generate general sales recommendations based on simple rules, such as recommending common insurance products based solely on the customer's age and gender. However, these insurance sales assistance systems lack semantic understanding capabilities and are unable to accurately capture the customer's personalized needs and the core advantages of insurance products. As a result, the sales recommendations they provide are often not precise and personalized enough.

[0046] To solve the above problems, this solution proposes a method and device for generating insurance product sales recommendations, which generates prompt words based on the product information of the insurance product to be promoted and the user information of the user to be promoted. The generated graphic prompt words are input into a large model for analysis, thereby obtaining insurance product sales recommendations corresponding to the insurance product to be promoted for the user to be promoted, thereby improving the efficiency of insurance product analysis and customer experience.

[0047] See also Figure 1 , which shows a flow chart of a method for generating insurance product sales suggestions provided by an embodiment of the present invention, including:

[0048] Step S101: Display the front-end interface.

[0049] During the specific implementation of step S101, the operation of the sales user opening the client (APP) is detected, and the front-end interface of the client is displayed. The front-end interface includes multiple controls. The sales user (such as an insurance account manager or an insurance product manager) can select the insurance product to be promoted and the user to be promoted by operating in the front-end interface. Among them, the insurance product to be promoted is any insurance product, and the user to be promoted is the target object to which the insurance product needs to be promoted, that is, the sales user needs to introduce the insurance product to the user to be promoted.

[0050] Step S102: In response to the sales user's operation on the front-end interface, determine the insurance products to be promoted and the users to be promoted.

[0051] In the specific implementation of step S102, in response to the sales user's operation on the front-end interface, the insurance products to be promoted and the users to be promoted are determined.

[0052] For example: in response to the selection operation of the sales user on the front-end interface, the insurance product to be promoted and the user to be promoted selected by the sales user are determined.

[0053] Step S103: Acquire product information of the insurance product to be promoted, and acquire user information of the user to be promoted.

[0054] It should be noted that the product information of multiple insurance products is pre-configured in the background. The product information of insurance products at least includes demand background, product positioning, product advantages and sales concept; among them, demand background and product positioning are equivalent to the characteristic information of insurance products; the product information of insurance products can accurately and comprehensively reflect the core advantages and sales concept of insurance products.

[0055] In the specific implementation of step S103, product information of the insurance product to be promoted is obtained from the background; basic information and behavioral data of the user to be promoted are captured from multiple designated business systems; and the basic information and behavioral data of the user to be promoted are integrated to obtain user information of the user to be promoted.

[0056] It should be noted that the basic information of the user to be marketed includes but is not limited to: name, age, gender, occupation and income;

[0057] The behavioral data of users to be marketed include but are not limited to: insurance product purchase history, insurance product browsing history, insurance product consultation history, etc.

[0058] For example: obtain the name of the user to be marketed from a designated system, and obtain the age, gender, occupation, income, insurance product purchase history, insurance product browsing history, insurance product consultation history, etc. of the user to be marketed from a customer relationship system (such as CRM).

[0059] It should be further explained that, before obtaining the basic information and behavioral data of the user to be marketed, a specified prompt message is sent to the user to be marketed, and the specified prompt message is used to request the user to be marketed to authorize the collector to obtain the basic information and behavioral data of the user to be marketed; after receiving the authorization instruction from the user to be marketed, the basic information and behavioral data of the user to be marketed are obtained;

[0060] That is, this solution obtains the basic information and behavior data of the user to be marketed only after the user authorizes and agrees to collect personal information.

[0061] Step S104: Generate prompt words based on the product information of the insurance product to be promoted and the user information of the user to be promoted.

[0062] In the specific implementation of step S104, data cleaning (e.g., data deduplication) and integration are performed on the product information of the insurance product to be promoted and the user information of the user to be promoted to generate a prompt word, which at least includes the product information of the insurance product to be promoted and the user information of the user to be promoted.

[0063] Specifically, the prompt word project cleans and integrates the product information of the insurance product to be promoted and the user information of the user to be promoted, extracts the sales analysis information required for the insurance product to be promoted from the product information and the user information, and then combines the extracted sales analysis information to generate prompt words.

[0064] For example, the prompt word project cleans and integrates the product information of the insurance product to be promoted and the user information of the target user to be promoted. The generated prompt words are as follows:

[0065] "You are now an insurance account manager, and you have a client named Zhang San, gender: male, age: 34, annual income: 100,000 yuan; 1. Content of demand background; 2. Content related to product positioning; 3. Content related to product advantages; 4. Content related to sales philosophy; Words that need to be avoided when answering."

[0066] Step S105: Input the prompt word into the pre-trained large model for analysis, and obtain the insurance product sales recommendation output by the large model for the user to be promoted and corresponding to the insurance product to be promoted.

[0067] It should be noted that a large neural network model with deep learning capabilities is pre-trained to obtain a large model that can process and understand natural language text and perform complex information extraction and analysis.

[0068] In the specific implementation of step S105, after generating prompt words based on the product information of the insurance product to be promoted and the user information of the user to be promoted, the prompt words are input into the big model for analysis, so that the big model uses deep learning capabilities and natural semantic understanding capabilities to extract the correlation information between the product information and the user information (equivalent to the analysis results of the big model), and then automatically generates insurance product sales recommendations corresponding to the insurance product to be promoted for the user to be promoted based on the analysis results.

[0069] That is to say, the prompt words are input into the big model, and the big model outputs an insurance product sales suggestion corresponding to the insurance product to be promoted and targeted at the user to be promoted. The insurance product sales suggestion is also a personalized insurance product sales suggestion generated for the user to be promoted.

[0070] Insurance product sales recommendations include at least personalized sales pitches and strategic recommendations; among which, the strategic recommendations include the product features of the insurance product to be promoted and the part related to the needs of the insurance product to be promoted and the users to whom the insurance product to be promoted is to be promoted.

[0071] In some embodiments, after generating an insurance product sales suggestion for the user to be marketed, the insurance product sales suggestion corresponding to the insurance product to be marketed for the user to be marketed is displayed in the front-end interface to show the insurance product sales suggestion to the salesperson.

[0072] In an embodiment of the present invention, prompt words are generated based on the product information of the insurance product to be promoted and the user information of the user to be promoted, and the generated graphic prompt words are input into a large model for analysis, so as to obtain insurance product sales recommendations corresponding to the insurance product to be promoted for the user to be promoted, thereby improving the efficiency of insurance product analysis and customer experience.

[0073] To better explain the above embodiments of the present invention Figure 1 The following is from the perspective of practical application. Figure 2 Another flow chart of a method for generating insurance product sales recommendations is shown as an example. Figure 2 The steps include:

[0074] Step S201: The sales user opens the front-end interface of the client.

[0075] Step S202: Select the insurance product to be promoted.

[0076] Step S203: Select users to be marketed.

[0077] Step S204: Acquire product information of the insurance product to be promoted, and acquire user information of the user to be promoted.

[0078] Step S205: Generate prompt words by combining product information and user information using the prompt word project; input the prompt words into the macro model.

[0079] Step S206: Obtain the insurance product sales suggestion output by the large model; and display the insurance product sales suggestion in the front-end interface.

[0080] In practical applications, insurance product sales recommendations can be generated through the insurance sales system. The architecture of the insurance sales system is as follows: Figure 3 As shown; Figure 3 The insurance sales system shown includes at least a front end, an API access layer, a business service layer, and several other layers.

[0081] Among them, the front end provides a front-end interface, and sales users can open the front-end interface through mobile phones or PCs to select insurance products to be promoted and users to be promoted.

[0082] The API access layer is used to call the large model. The API access layer includes the proxy server (nginx proxy), API, and other contents.

[0083] The business service layer includes an official WeChat system (Mwp), AI system, customer relationship system (CRM), etc.; the AI ​​system is the prompt word project.

[0084] The data layer includes databases such as Oracle and Redis, which are used to save logs and records.

[0085] From the above embodiments, it can be seen that this solution has the following beneficial effects:

[0086] High Precision: Through deep learning and natural semantic understanding of large models, it can accurately capture customers' personalized needs and the core advantages of insurance products, generating precise insurance sales recommendations.

[0087] Strong adaptability: The large model can continuously learn and adapt to market changes and changes in customer needs, improving the work efficiency of insurance account managers;

[0088] Good user experience: Accurate insurance sales recommendations can improve customer satisfaction and enhance customer trust in insurance products and purchase willingness.

[0089] Corresponding to the method for generating insurance product sales suggestions provided by the above embodiment of the present invention, see Figure 4 , an embodiment of the present invention also provides a structural block diagram of a device for generating insurance product sales suggestions, the device comprising: a display unit 100, a determination unit 200, an acquisition unit 300, a generation unit 400 and an analysis unit 500;

[0090] The display unit 100 is used to display the front-end interface.

[0091] The determination unit 200 is used to determine the insurance products to be promoted and the users to be promoted in response to the sales user's operation on the front-end interface.

[0092] The acquisition unit 300 is used to acquire product information of the insurance product to be promoted and user information of the user to be promoted.

[0093] In some embodiments, the product information includes at least demand background, product positioning, product advantages, and sales concept.

[0094] The generating unit 400 is configured to generate prompt words based on the product information of the insurance product to be promoted and the user information of the user to be promoted.

[0095] In a specific implementation, the generating unit 400 is specifically used to clean and integrate the product information of the insurance product to be promoted and the user information of the user to be promoted, so as to generate prompt words.

[0096] The analysis unit 500 is used to input the prompt word into the pre-trained large model for analysis, and obtain the insurance product sales recommendation output by the large model for the user to be promoted and corresponding to the insurance product to be promoted.

[0097] In some embodiments, insurance product sales recommendations include at least personalized sales pitches and strategic recommendations.

[0098] In an embodiment of the present invention, prompt words are generated based on the product information of the insurance product to be promoted and the user information of the user to be promoted, and the generated graphic prompt words are input into a large model for analysis, so as to obtain insurance product sales recommendations corresponding to the insurance product to be promoted for the user to be promoted, thereby improving the efficiency of insurance product analysis and customer experience.

[0099] Preferably, combined Figure 4 , see Figure 5 , an embodiment of the present invention provides another structural block diagram of an apparatus for generating insurance product sales suggestions, wherein the acquisition unit 300 includes: a first acquisition module 301, a second acquisition module 302 and a synthesis module 303;

[0100] The first acquisition module 301 is used to acquire product information of the insurance product to be promoted from the background, which contains product information of multiple pre-configured insurance products.

[0101] The second acquisition module 302 is used to capture basic information and behavior data of users to be marketed from multiple designated business systems.

[0102] The integration module 303 is used to integrate the basic information and behavior data of the user to be marketed to obtain the user information of the user to be marketed.

[0103] Preferably, combined Figure 4 , see Figure 6 , an embodiment of the present invention provides another structural block diagram of an apparatus for generating insurance product sales recommendations, the apparatus further comprising:

[0104] The output unit 600 is used to display insurance product sales recommendations corresponding to the insurance product to be promoted to the user to be promoted in the front-end interface.

[0105] In summary, the embodiments of the present invention provide a method and device for generating insurance product sales recommendations, generating prompt words based on the product information of the insurance product to be promoted and the user information of the user to be promoted, and inputting the generated graphic prompt words into a large model for analysis, thereby obtaining insurance product sales recommendations corresponding to the insurance product to be promoted for the user to be promoted, thereby improving the efficiency of insurance product analysis and customer experience.

[0106] Each embodiment in this specification is described in a progressive manner. The same or similar parts between the embodiments can be referred to each other. Each embodiment focuses on the differences from other embodiments. In particular, for system or system embodiments, since they are basically similar to method embodiments, the description is relatively simple. For relevant parts, refer to the partial description of the method embodiment. The system and system embodiments described above are merely schematic, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment. A person of ordinary skill in the art can understand and implement it without expending creative work.

[0107] Professionals may further appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the above description has generally described the components and steps of each example according to their functions. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professionals and technicians may use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the present invention.

[0108] The above description of the disclosed embodiments is intended to enable one skilled in the art to implement or use the present invention. Various modifications to these embodiments will be readily apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the scope of the present invention. Therefore, the present invention is not limited to the embodiments shown herein, but is intended to conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for generating a sales proposal for an insurance product, characterized in that: The method comprises: Display the front-end interface; In response to the sales user's operation on the front-end interface, determining the insurance products to be promoted and the users to be promoted; Acquire product information of the insurance product to be promoted, and acquire user information of the user to be promoted; Generate prompt words according to the product information of the insurance product to be promoted and the user information of the user to be promoted; The prompt words are input into a pre-trained large model for analysis, and an insurance product sales suggestion corresponding to the insurance product to be promoted and targeted at the user to be promoted is obtained from the large model.

2. The method according to claim 1, characterized in that Acquiring product information of the insurance product to be promoted and acquiring user information of the user to be promoted includes: Acquire product information of the insurance product to be promoted from a background, wherein the background includes product information of a plurality of pre-configured insurance products; Capture basic information and behavior data of the users to be marketed from multiple designated business systems; The basic information and behavior data of the user to be marketed are integrated to obtain the user information of the user to be marketed.

3. The method according to claim 1, characterized in that: Generate prompt words according to the product information of the insurance product to be promoted and the user information of the user to be promoted, including: Data cleaning and integration are performed on the product information of the insurance product to be promoted and the user information of the user to be promoted to generate prompt words.

4. The method according to any one of claims 1 to 3, characterized in that: The product information at least includes demand background, product positioning, product advantages and sales philosophy; the insurance product sales recommendations at least include personalized sales scripts and strategic recommendations.

5. The method according to any one of claims 1 to 3, characterized in that: After obtaining the insurance product sales suggestion output by the large model for the insurance product to be promoted to the user to be promoted, the method further includes: An insurance product sales suggestion corresponding to the insurance product to be promoted is displayed in the front-end interface for the user to be promoted.

6. A device for generating insurance product sales suggestions, characterized in that: The device comprises: A display unit, used for displaying a front-end interface; A determination unit, configured to determine the insurance products to be promoted and the users to be promoted in response to the operation of the sales user on the front-end interface; An acquisition unit, used to acquire product information of the insurance product to be promoted, and to acquire user information of the user to be promoted; A generating unit, configured to generate prompt words according to the product information of the insurance product to be promoted and the user information of the user to be promoted; The analysis unit is used to input the prompt word into a pre-trained large model for analysis, and obtain an insurance product sales suggestion corresponding to the insurance product to be promoted and targeted at the user to be promoted, output by the large model.

7. The device according to claim 6, characterized in that The acquisition unit comprises: A first acquisition module is used to acquire product information of the insurance product to be promoted from a background, wherein the background contains product information of a plurality of pre-configured insurance products; A second acquisition module is used to capture the basic information and behavior data of the user to be marketed from multiple designated business systems; The integration module is used to integrate the basic information and behavior data of the user to be marketed to obtain the user information of the user to be marketed.

8. The device according to claim 6, characterized in that The generating unit is specifically used for: performing data cleaning and integration on the product information of the insurance product to be promoted and the user information of the user to be promoted, so as to generate prompt words.

9. The device according to any one of claims 6 to 8, characterized in that: The product information at least includes demand background, product positioning, product advantages and sales philosophy; the insurance product sales recommendations at least include personalized sales scripts and strategic recommendations.

10. The device according to any one of claims 6 to 8, characterized in that: Also includes: The output unit is used to display the insurance product sales suggestion corresponding to the insurance product to be promoted for the user to be promoted in the front-end interface.

Images