Product information push method and related products

Abstract

The embodiment of the present application discloses a method for pushing product information and related products, the method comprising: determining a first correlation between the basic information of the first user and the basic information of the second user according to the basic information of the first user in the first scenario and the basic information of the second user in the second scenario; integrating the first user information of the first user in the first scenario and the second user information of the second user in the second scenario according to the first correlation to obtain the third user information of the first user; determining the demand score of the first user for the first product according to the third user information; and pushing the product information of the first product to the first user according to the demand score. The embodiment of the present application determines the demand score of the first user for the first product according to the integrated first user information, pushes the product information to the first user according to the demand score, improves the first user information, and improves the efficiency of pushing products.

Description

Technical Field

[0001] The present application relates to the field of computer technology, and in particular to a product information push method and related products. Background Art

[0002] With the development of China's economy, the increase of national wealth and income, and the gradual strengthening of people's insurance awareness, residents' financial management and insurance needs are becoming more urgent and diversified. However, due to the large number and complexity of financial management and insurance information products, and the different needs of users for financial management and insurance, when we want to recommend suitable financial management products and insurance products to users, we usually adopt manual query methods, which require huge manpower and material resources and are inefficient. Summary of the invention

[0003] The main purpose of the embodiments of the present application is to provide a product information push method and related products, which can effectively solve the problem of low recommendation efficiency when recommending financial products and insurance products suitable for users.

[0004] In a first aspect, an embodiment of the present application provides a product information push method, which is applied to an electronic device, and the method includes:

[0005] Obtaining first user basic information of the first user in the first scenario and second user basic information of the second user in the second scenario, where the user basic information refers to the user's personal information and the personal information of the first contact associated with the user in the scenario;

[0006] Identifying the first user basic information and the second user basic information to obtain a first association between the first user basic information and the second user basic information;

[0007] Integrate the first user information of the first user in the first scenario and the second user information of the second user in the second scenario according to the first correlation to obtain the third user information of the first user, where the user information includes: basic user information, user value information, user behavior information, and user historical purchase information;

[0008] Determining a demand score of the first user for the first product according to the third user information;

[0009] Product information of the first product is pushed to the first user according to the demand score.

[0010] Optionally, before determining the demand score of the first user for the first product according to the third user information, the method further includes: establishing a demand score model of the first user for the first product.

[0011] Optionally, establishing a demand scoring model for the first user's demand for the first product includes:

[0012] The user information of the first user is used as a prediction variable, converted into a target variable, and the demand scoring model is constructed, wherein the demand scoring model is a scoring model for the first user's demand for the first product.

[0013] Optionally, determining the demand score of the first user for the first product based on the third user information includes: using a demand scoring model to determine the demand score of the first user for the first product based on the third user information of the first user.

[0014] Optionally, the demand scoring model includes a logistic regression prediction model.

[0015] Optionally, pushing the product information of the first product to the first user according to the demand score includes: determining the progress of the first user according to the demand score of the first user; and pushing the product information of the first product to the first user according to the progress of the first user.

[0016] Optionally, the logistic regression prediction model is: ,in Represents the model score of customer conversion rate under known label conditions, is the label weight value of the third user information, A label for third-party user information.

[0017] In a second aspect, an embodiment of the present application provides a product information push device, the device comprising:

[0018] An acquisition unit, configured to acquire first user basic information of a first user in a first scenario and second user basic information of a second user in a second scenario;

[0019] an identification unit, configured to identify the first user basic information and the second user basic information, and obtain a first association between the first user basic information and the second user basic information;

[0020] An integration unit, configured to integrate the first user information of the first user in the first scenario and the second user information of the second user in the second scenario according to the first association, to obtain third user information of the first user;

[0021] A determining unit, configured to determine a demand score of the first user for the first product according to the third user information;

[0022] A push unit is used to push the product information of the first product to the first user according to the demand score.

[0023] Optionally, before determining the demand score of the first user for the first product according to the third user information, the determining unit 504 is further specifically configured to: establish a demand score model of the first user for the first product.

[0024] Optionally, in terms of establishing the demand scoring model for the first user's demand for the first product, the determination unit 504 is further specifically used to: use the user information of the first user as a prediction variable, convert it into a target variable, and construct the demand scoring model, wherein the demand scoring model is a scoring model for the first user's demand for the first product.

[0025] Optionally, in determining the demand score of the first user for the first product based on the third user information, the determination unit 504 is further specifically used to: determine the demand score of the first user for the first product based on the third user information of the first user by using a demand scoring model.

[0026] Optionally, the demand scoring model includes a logistic regression prediction model.

[0027] Optionally, in terms of pushing the product information of the first product to the first user according to the demand score, the pushing unit 505 is specifically used to: determine the progress of the first user according to the demand score of the first user; and push the product information of the first product to the first user according to the progress of the first user.

[0028] Optionally, the logistic regression prediction model is: ,in Represents the model score of customer conversion rate under known label conditions, is the label weight value of the third user information, A label for third-party user information.

[0029] In a third aspect, an embodiment of the present application provides an electronic device, comprising a processor, a memory, a communication interface, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the processor, and the program includes instructions for executing the steps of any method in the first aspect of the embodiment of the present application.

[0030] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program for electronic data exchange, wherein the computer program enables a computer to execute part or all of the steps described in any method of the first aspect of the embodiment of the present application.

[0031] In a fifth aspect, an embodiment of the present application provides a computer program product, wherein the computer program product includes a non-transitory computer-readable storage medium storing a computer program, and the computer program is operable to cause a computer to execute some or all of the steps described in any method of the first aspect of the embodiment of the present application. The computer program product may be a software installation package.

[0032] It can be seen that the embodiment of the present application obtains the first user basic information of the first user in the first scenario and the second user basic information of the second user in the second scenario, where the user basic information refers to the user's personal information and the personal information of the first contact associated with the user in the scenario; identifies the first user basic information and the second user basic information to obtain the first association between the first user basic information and the second user basic information; integrates the first user information of the first user in the first scenario and the second user information of the second user in the second scenario according to the first association to obtain the third user information of the first user, where the user information includes: user basic information, user value information, user behavior information, and user historical purchase information; determines the first user's demand score for the first product according to the third user information; and pushes the product information of the first product to the first user according to the demand score. The embodiment of the present application determines the first user's demand score for the first product according to the integrated first user information, pushes the product information to the first user according to the demand score, improves the first user information, improves the accuracy of the first user information, and improves the accuracy and efficiency of pushing product information to the first user. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0034] Figure 1 A flowchart of a method for pushing product information provided in an embodiment of the present application;

[0035] Figure 2 A schematic diagram of a process for determining a first user's demand score for a first product provided in an embodiment of the present application;

[0036] Figure 3 A flowchart of a method for pushing product information provided in an embodiment of the present application;

[0037] Figure 4It is a structural schematic diagram of an electronic device provided in an embodiment of the present application;

[0038] Figure 5 It is a block diagram of the functional units of a product information push device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0039] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0040] The terms "first", "second", etc. in the specification and claims of this application and the above-mentioned drawings are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but optionally includes steps or units that are not listed, or optionally includes other steps or units inherent to these processes, methods, products or devices.

[0041] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0042] The collection and processing of user information and other related data in the embodiments of the present application must comply with relevant national and regional laws and regulations, and obtaining user information requires the permission or consent of the relevant user.

[0043] The following is a detailed description of the embodiments of the present application.

[0044] In order to solve the problem of low efficiency in recommending financial products and insurance products suitable for users, the present application provides a product information push method, which is applied to electronic devices, specifically, Figure 1 As shown, the method may include but is not limited to the following steps:

[0045] S101, the electronic device obtains first user basic information of a first user in a first scenario and second user basic information of a second user in a second scenario;

[0046] The basic user information refers to the user's personal information and the personal information of the first contact associated with the user in a scenario.

[0047] Among them, the basic information of the user may include the following information: the user's name, gender, birthday, contact information, certificate information, and personal information of the first contact associated with the user in the scenario. The certificate information includes the certificate type and certificate number. The user's contact information may be common contact information such as mobile phone number, landline number, instant messaging account, email address, etc. The personal information of the first contact associated with the user in the scenario includes: the first contact's name, work number, and contact information. The contact information of the first contact includes any of the following: the first contact's mobile phone number, email account, instant messaging account, etc. The first contact may be the salesperson associated with the user in the scenario.

[0048] The first user and the second user may be the same user or different users. The first user is a user in a preset scenario in the database. The preset scenario may be any one of an insurance product scenario and a financial scenario, for example, a life insurance scenario (life insurance product purchase scenario), a property insurance scenario (auto insurance, travel insurance, home property insurance, accident insurance, etc. purchase scenarios), a banking scenario (such as the purchase of financial products, etc.), and a fund scenario (fund product purchase scenario). No excessive restrictions are imposed on the preset scenarios.

[0049] Among them, the first scenario can be any one of the insurance product scenarios and financial scenarios, for example, life insurance scenarios (life insurance product purchase scenarios), property insurance scenarios (auto insurance, travel insurance, home insurance, accident insurance, etc. purchase scenarios), banking scenarios (such as financial product purchase scenarios, etc.), fund scenarios (fund product purchase scenarios), and the first scenario can also be other scenarios, and there are no excessive restrictions here.

[0050] The second scenario can be any of the insurance product scenarios and financial scenarios, for example, life insurance scenarios (life insurance product purchase scenarios), property insurance scenarios (auto insurance, travel insurance, home property insurance, accident insurance, etc. purchase scenarios), banking scenarios (such as financial product purchase scenarios), fund scenarios (fund product purchase scenarios). The second scenario can also be other scenarios, and there is no excessive restriction here.

[0051] Among them, the first scene is different from the second scene.

[0052] S102: The electronic device identifies the first user basic information and the second user basic information to obtain a first correlation between the first user basic information and the second user basic information;

[0053] The first correlation is the correlation that the basic information of the first user and the basic information of the second user are the same user. The first correlation can be divided into strong correlation and weak correlation. The strong correlation means that the first user and the second user are the same user, and the weak correlation means that the first user and the second user are different users.

[0054] As shown in Table 1 below, Table 1 is a table of association between the basic information of the first user and the second user.

[0055]

[0056] The conditions corresponding to strong correlation include any of the following situations:

[0057] 1. Condition 1: The ID type and ID number in the basic information of the first user and the basic information of the second user are consistent, the name is consistent, the gender is consistent, the birthday is consistent, the contact information is consistent, and there is no restriction on the corresponding salesperson information;

[0058] 2. Condition 2: The ID type and ID number in the basic information of the first user and the basic information of the second user are missing, the name is present and consistent, the gender is present and consistent, the birthday is present and consistent, the contact information is present and consistent, and there is no restriction on the corresponding salesperson information;

[0059] 3. Condition 3: The certificate type and certificate number in the basic information of the first user and the basic information of the second user are both available and consistent, the name is not restricted, the gender is not restricted, the birthday is not restricted, the contact information is available and consistent, and there is no restriction on the corresponding salesperson information.

[0060] The conditions corresponding to weak correlation include the following situations:

[0061] Condition 4: The certificate type and certificate number in the basic information of the first user and the second user are missing, the name is not restricted, the gender is not restricted, the birthday is not restricted, the contact information is available and consistent, and the corresponding salesperson information is available and consistent.

[0062] The personal information of the first contact person is the user's corresponding order-issuing salesperson information or the user's corresponding product service manager information.

[0063] It needs to be further supplemented that: in other cases except for the cases corresponding to strong correlation and weak correlation, it is deemed that the first user cannot be matched with the second user, that is, the first user and the second user are not the same user, and a new identity identification number (Identity document, ID) needs to be created for the first user's basic information, where the ID number is the user number in the user basic information in the preset scenario.

[0064] In one possible example, first user information of a first user in a first scenario and second user information of a second user in a second scenario are identified to obtain a first correlation, including: comparing the name, gender, birthday, mobile phone number, ID information, and corresponding salesperson information of the first user in the first user information with the name, gender, birthday, mobile phone number, ID information, and corresponding salesperson information of the second user in the second user information to obtain a first correlation between the first user and the second user.

[0065] For example, if there are two users: the first user A and the second user B, they come from two different scenarios (such as life insurance and property insurance). If they both have the same ID number, the same name, the same gender, the same birthday, and no restrictions on mobile phone numbers, then the first correlation between the first user A and the second user B is judged to be the condition 1 in the strong correlation, that is, the first correlation between the first user A and the second user B is a strong correlation, that is, the first user A and the second user B are the same user.

[0066] S103. The electronic device integrates the first user information of the first user in the first scenario and the second user information of the second user in the second scenario according to the first correlation to obtain third user information of the first user.

[0067] Among them, user information includes: user basic information, user value information, user behavior information,

[0068] Among them, the basic information of the user may include the following information: the user's name, gender, birthday, contact information, certificate information, and personal information of the first contact associated with the user in the scenario. The certificate information includes the certificate type and certificate number. The user's contact information may be common contact information such as mobile phone number, landline number, instant messaging account, email address, etc. The personal information of the first contact associated with the user in the scenario includes: the first contact's name, work number, and contact information. The contact information of the first contact includes any of the following: the first contact's mobile phone number, email account, instant messaging account, etc. The first contact may be the salesperson associated with the user in the scenario.

[0069] The user's value information may be value information determined based on the user's own deposit information, historical consumption information, and historical information on the purchase of insurance and financial products.

[0070] The user's behavior information includes the duration and time points of the user's browsing of insurance products and financial products on the application APP within a preset time period, and the user's behavior information also includes the user's historical purchase information. The user's historical purchase information can be: the type, amount, and time of purchase of insurance and financial products purchased by the user, without excessive restrictions here. The application APP can be an APP related to financial products, an APP related to insurance products, or an APP of payment type.

[0071] In a specific implementation, the electronic device integrates the first user information of the first user in the first scenario and the second user information of the second user in the second scenario according to the first correlation to obtain the third user information of the first user, including but not limited to: the electronic device determines whether the first user and the second user are the same user according to the first correlation, and if so, the electronic device integrates the first user information of the first user in the first scenario and the second user information of the second user in the second scenario to obtain the third user information of the first user.

[0072] It should be noted that the electronic device integrates the first user information of the first user in the first scenario and the second user information of the second user in the second scenario, including but not limited to: the electronic device compares the first user information and the second user information, and integrates the information in the second user information that is different from the first user information into the first user information.

[0073] In a specific implementation, the electronic device integrates the first user information of the first user in the first scenario and the second user information of the second user in the second scenario according to the first correlation to obtain the third user information of the first user, which also includes but is not limited to: the electronic device determines whether the first user and the second user are the same user according to the first correlation, if not, the electronic device numbers the second user, creates a new identity document (ID) for the second user basic information of the second user, where the ID number is the user number in the user basic information in the preset scenario; and saves the second user information of the second user in the database. The preset scenario is consistent with the description of the preset scenario in the above embodiment, and will not be repeated here.

[0074] S104, the electronic device determines the first user's demand score for the first product according to the third user information;

[0075] In a possible example, before the electronic device determines the demand score of the first user for the first product according to the third user information, the process further includes: the electronic device establishing a demand score model for the first user's demand for the first product.

[0076] In a specific implementation, the electronic device establishes a demand scoring model for the first user's demand for the first product, including: the electronic device uses the user information of the first user as a prediction variable, converts it into a target variable, and constructs a demand scoring model, wherein the demand scoring model is a scoring model for the first user's demand for the first product.

[0077] In a possible example, determining the first user's demand score for the first product based on the third user information includes: the electronic device uses a demand scoring model to determine the first user's demand score for the first product based on the third user information of the first user.

[0078] Among them, the demand scoring model includes a logistic regression prediction model.

[0079] Among them, the logistic regression prediction model is: , where Score(y=1│X) represents the model score of customer conversion rate under known label conditions, β_n is the label weight value of the third user information, is a label of the third user information, and the third user information includes multiple labels.

[0080] It needs to be explained that Figure 2 As shown, Figure 2 A flow chart of a process for determining a first user's demand score for a first product is provided, wherein the electronic device uses a demand score model to determine the first user's demand score for the first product based on the first user's third user information, including but not limited to: the electronic device uses a logistic regression prediction model and a demand score calculation formula to calculate the first user's demand score for the first product based on the first user's third user information.

[0081] Among them, the calculation formula for the first user's demand score is:

[0082] Ip;

[0083] Among them, Standard is the demand score of the first user, Score is Score(y=1│X), C is a constant, SPmin is the minimum conversion rate, SPmax is the maximum conversion rate, and Ip is a weight value.

[0084] S105. The electronic device pushes product information of the first product to the first user according to the demand score.

[0085] In one possible example, the electronic device pushes product information of the first product to the first user based on the demand score, including: the electronic device determines the progress of the first user based on the demand score of the first user; and the electronic device pushes the product information of the first product to the first user based on the progress of the first user.

[0086] It needs to be further explained that the electronic device determines the progress of the first user according to the demand score of the first user, including but not limited to: the electronic device divides the first user according to the demand score of the first user to determine the progress of the first user.

[0087] The rules for dividing the stages of the process of the first user are as follows:

[0088] 1. P3: The conversion rate corresponding to the demand score is above 35%

[0089] 2. P2: Standardize the demand score line with a conversion rate of 35% corresponding to the demand score, and select the first 25% of the standardized score range of 0-35% to enter P2

[0090] 3. P1: Standardize the demand score line of 35% conversion rate corresponding to the demand score, and take 50%-75% of the standardized score range of 0-35% to enter P1.

[0091] Among them, the P1 stage refers to the user being in the cognitive stage; the P2 stage refers to the user being in the operational stage; and the P3 stage refers to the user being in the precision marketing stage.

[0092] It needs to be further explained that the electronic device pushes product information to the first user according to the progress of the first user, including but not limited to:

[0093] When the first user's process is at the P1 stage, in this stage, relevant questionnaires, materials and information are recommended according to the label weight information in the user rating model to obtain the first user's demand information to improve the understanding of the first user;

[0094] When the first user's process is at the P2 stage, at this stage, a user demand tendency model is constructed to obtain the user's major product tendency information, and based on the product tendency information, some information about savings products is recommended or participation in product presentations for savings products is recommended. For example, there are only seven major demand categories for personal insurance products, namely education (E06), non-health protection (E02), savings (E05), pension (E00), major disease protection (E04), medical insurance (E03), and long-term care (E01). Seven binary classification models are constructed (such as the lightGBM model) to predict that the first user A is interested in the savings category of personal insurance products. If the user is interested in savings products, some information about savings products can be recommended to him or he can participate in product presentations for savings products, etc.;

[0095] When the first user's process is at the P3 stage, at this stage, the specific products that the user is interested in are predicted. First, the user's premium model will be constructed, which predicts the premium range that the user can afford in the future. The premium segmentation is as follows: a multi-classification logistic regression model with the premium segmentation interval as the target variable is constructed to predict the premium range that the user is most likely to bear, assuming it is 4000-6000. Then, based on the user's demand tendency in the P2 stage, such as E05, savings type, by querying the product system for products in the savings type and with an annual premium in the range of 4000-6000, and combining the user's multi-product recommendation model (the result of multi-product logistic regression recommendation), it is recommended to the user.

[0096] Among them, the premium segments are divided according to the following results:

[0097] 0-2000, 2000-4000, 4000-6000, 6000-8500, and above 8500.

[0098] It can be seen that the embodiment of the present application obtains the first user's basic information in the first scenario and the second user's basic information in the second scenario, where the user basic information refers to the user's personal information and the personal information of the first contact person associated with the user in the scenario; identifies the first user's basic information and the second user's basic information to obtain the first correlation between the first user's basic information and the second user's basic information; integrates the first user's information in the first scenario and the second user's information in the second scenario according to the first correlation to obtain the first user's third user information, where the user information includes: user basic information, user value information, user behavior information, and user historical purchase information; determines the first user's demand score for the first product according to the third user information; and pushes the product information of the first product to the first user according to the demand score. The embodiment of the present application determines the first user's demand score for the first product according to the integrated first user information, pushes the product information to the first user according to the demand score, improves the first user information, improves the accuracy of the first user information, and improves the accuracy and efficiency of pushing product information to the first user.

[0099] The following is a detailed description of the embodiments of the present application through a specific example.

[0100] With the above Figure 1 The embodiment shown is consistent with that shown in FIG. Figure 3 , Figure 3 : is a flow chart of a product information push method provided in an embodiment of the present application, which is applied to an electronic device, and the method includes:

[0101] S301, the electronic device obtains first user basic information of a first user in a first scenario and second user basic information of a second user in a second scenario;

[0102] The above basic user information refers to the user's personal information and the personal information of the first contact person associated with the user in the scenario;

[0103] S302: The electronic device identifies the first user basic information and the second user basic information to obtain a first correlation between the first user basic information and the second user basic information;

[0104] S303: The electronic device integrates the first user information of the first user in the first scenario and the second user information of the second user in the second scenario according to the first correlation to obtain the third user information of the first user.

[0105] The above user information includes: basic user information, user value information, user behavior information, and user purchase history information;

[0106] S304, the electronic device uses the user information of the first user as a prediction variable, converts it into a target variable, and constructs a demand scoring model;

[0107] S305, the electronic device determines the demand score of the first user for the first product according to the third user information using the demand score model;

[0108] S306, the electronic device determines the progress of the first user according to the demand score of the first user;

[0109] S307: The electronic device pushes product information of the first product to the first user according to the progress of the first user.

[0110] It can be seen that the embodiment of the present application obtains the first user's basic information in the first scenario and the second user's basic information in the second scenario, where the user basic information refers to the user's personal information and the personal information of the first contact person associated with the user in the scenario; identifies the first user's basic information and the second user's basic information to obtain the first correlation between the first user's basic information and the second user's basic information; integrates the first user's information in the first scenario and the second user's information in the second scenario according to the first correlation to obtain the first user's third user information, where the user information includes: user basic information, user value information, user behavior information, and user historical purchase information; determines the first user's demand score for the first product according to the third user information; and pushes the product information of the first product to the first user according to the demand score. The embodiment of the present application determines the first user's demand score for the first product according to the integrated first user information, pushes the product information to the first user according to the demand score, improves the first user information, improves the accuracy of the first user information, improves the accuracy of pushing appropriate product information to the first user, and improves the efficiency of pushing product information to the first user.

[0111] See also Figure 4 , Figure 4 4 is a structural diagram of an electronic device 400 provided in an embodiment of the present application. As shown in the figure, the electronic device 400 includes an application processor 410, a memory 420, a communication interface 430, and one or more programs 421, wherein the one or more programs 421 are stored in the above-mentioned memory 420 and are configured to be executed by the above-mentioned application processor 410, and the one or more programs 421 include for performing the following steps:

[0112] Obtaining first user basic information of the first user in the first scenario and second user basic information of the second user in the second scenario, where the user basic information refers to the user's personal information and the personal information of the first contact associated with the user in the scenario;

[0113] Identifying the first user basic information and the second user basic information to obtain a first association between the first user basic information and the second user basic information;

[0114] Integrate the first user information of the first user in the first scenario and the second user information of the second user in the second scenario according to the first correlation to obtain the third user information of the first user, where the user information includes: basic user information, user value information, user behavior information, and user historical purchase information;

[0115] Determining a demand score of the first user for the first product according to the third user information;

[0116] Product information of the first product is pushed to the first user according to the demand score.

[0117] It can be seen that the embodiment of the present application obtains the first user's basic information in the first scenario and the second user's basic information in the second scenario, where the user basic information refers to the user's personal information and the personal information of the first contact person associated with the user in the scenario; identifies the first user's basic information and the second user's basic information to obtain the first correlation between the first user's basic information and the second user's basic information; integrates the first user's information in the first scenario and the second user's information in the second scenario according to the first correlation to obtain the first user's third user information, where the user information includes: user basic information, user value information, user behavior information, and user historical purchase information; determines the first user's demand score for the first product according to the third user information; and pushes the product information of the first product to the first user according to the demand score. The embodiment of the present application determines the first user's demand score for the first product according to the integrated first user information, pushes the product information to the first user according to the demand score, improves the first user information, improves the accuracy of the first user information, and improves the accuracy and efficiency of pushing product information to the first user.

[0118] In a possible embodiment, before determining the first user's demand score for the first product according to the third user information, the one or more programs 421 further include executing the following steps:

[0119] A demand scoring model for the first user's demand for the first product is established.

[0120] In a possible embodiment, the demand scoring model for the first user's demand for the first product is established, and the one or more programs 421 include a method for performing the following steps: using the user information of the first user as a predictive variable, converting it into a target variable, and constructing the demand scoring model, wherein the demand scoring model is a scoring model for the first user's demand for the first product.

[0121] In one possible embodiment, the demand score of the first user for the first product is determined based on the third user information, and the one or more programs 421 include a program for performing the following steps: using a demand scoring model to determine the demand score of the first user for the first product based on the third user information of the first user.

[0122] In a possible embodiment, the demand scoring model includes a logistic regression prediction model.

[0123] In a possible embodiment, the product information of the first product is pushed to the first user based on the demand score, and the one or more programs 421 include functions for performing the following steps: determining the progress of the first user based on the demand score of the first user; and pushing the product information of the first product to the first user based on the progress of the first user.

[0124] In a possible embodiment, the logistic regression prediction model is: ,in Represents the model score of customer conversion rate under known label conditions, is the label weight value of the third user information, A label for third-party user information.

[0125] The above mainly introduces the scheme of the embodiment of the present application from the perspective of the execution process on the method side. It is understandable that, in order to realize the above functions, the electronic device includes a hardware structure and / or software module corresponding to the execution of each function. It should be easily appreciated by those skilled in the art that, in combination with the units and algorithm steps of each example described in the embodiments provided herein, the present application can be implemented in the form of hardware or a combination of hardware and computer software. Whether a function is executed in the form of hardware or computer software driving hardware depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present application.

[0126] The embodiment of the present application can divide the electronic device into functional units according to the above method example. For example, each functional unit can be divided according to each function, or two or more functions can be integrated into one processing unit. The above integrated unit can be implemented in the form of hardware or in the form of software functional units. It should be noted that the division of units in the embodiment of the present application is schematic and is only a logical function division. There may be other division methods in actual implementation.

[0127] Figure 5 1 is a block diagram of the functional units of the product information push device 500 involved in the embodiment of the present application. The product information push device 500 includes:

[0128] An acquisition unit 501 is used to acquire first user basic information of a first user in a first scenario and second user basic information of a second user in a second scenario;

[0129] An identification unit 502 is used to identify the first user basic information and the second user basic information to obtain a first association between the first user basic information and the second user basic information;

[0130] An integration unit 503 is configured to integrate the first user information of the first user in the first scenario and the second user information of the second user in the second scenario according to the first correlation to obtain third user information of the first user;

[0131] A determining unit 504 is configured to determine a demand score of the first user for the first product according to the third user information;

[0132] The push unit 505 is configured to push the product information of the first product to the first user according to the demand score.

[0133] The product information push device 500 may further include a storage unit 506 for storing program codes and data of the electronic device. The storage unit 506 may be a memory.

[0134] It can be seen that the embodiment of the present application obtains the first user's basic information in the first scenario and the second user's basic information in the second scenario, where the user basic information refers to the user's personal information and the personal information of the first contact person associated with the user in the scenario; identifies the first user's basic information and the second user's basic information to obtain the first correlation between the first user's basic information and the second user's basic information; integrates the first user's information in the first scenario and the second user's information in the second scenario according to the first correlation to obtain the first user's third user information, where the user information includes: user basic information, user value information, user behavior information, and user historical purchase information; determines the first user's demand score for the first product according to the third user information; and pushes the product information of the first product to the first user according to the demand score. The embodiment of the present application determines the first user's demand score for the first product according to the integrated first user information, pushes the product information to the first user according to the demand score, improves the first user information, improves the accuracy of the first user information, and improves the accuracy and efficiency of pushing product information to the first user.

[0135] In a possible embodiment, before determining the demand score of the first user for the first product according to the third user information, the determining unit 504 is further specifically configured to: establish a demand score model of the first user for the first product.

[0136] In a possible embodiment, in terms of establishing a demand scoring model for the first user's demand for the first product, the determination unit 504 is further specifically used to: use the user information of the first user as a prediction variable, convert it into a target variable, and construct a demand scoring model, wherein the demand scoring model is a scoring model for the first user's demand for the first product.

[0137] In a possible embodiment, in terms of determining the first user's demand score for the first product based on the third user information, the determination unit 504 is further specifically used to: determine the first user's demand score for the first product based on the third user information of the first user using a demand scoring model.

[0138] In one possible embodiment, the demand scoring model includes a logistic regression prediction model.

[0139] In a possible embodiment, in terms of pushing product information of the first product to the first user according to the demand score, the pushing unit 505 is specifically used to: determine the progress of the first user according to the demand score of the first user; and push the product information of the first product to the first user according to the progress of the first user.

[0140] In one possible embodiment, the logistic regression prediction model is: ,in Represents the model score of customer conversion rate under known label conditions, is the label weight value of the third user information, A label for third-party user information.

[0141] An embodiment of the present application also provides a computer storage medium, wherein the computer storage medium stores a computer program for electronic data exchange, wherein the computer program enables a computer to execute part or all of the steps of any method described in the above method embodiments, and the above computer includes an electronic device.

[0142] The embodiment of the present application also provides a computer program product, the computer program product includes a non-transitory computer-readable storage medium storing a computer program, the computer program is operable to cause a computer to execute some or all of the steps of any method described in the method embodiment. The computer program product may be a software installation package, and the computer includes an electronic device.

[0143] It should be noted that, for the aforementioned method embodiments, for the sake of simplicity, they are all expressed as a series of action combinations, but those skilled in the art should be aware that the present application is not limited by the described order of actions, because according to the present application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required by the present application.

[0144] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0145] In the several embodiments provided in the present application, it should be understood that the disclosed device can be implemented in other ways. For example, the device embodiments described above are only schematic, such as the division of the above-mentioned units, which is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, and the indirect coupling or communication connection of devices or units can be electrical or other forms.

[0146] The units described above as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0147] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0148] If the above-mentioned integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a memory, including a number of instructions to enable a computer device (which can be a personal computer, server or network device, etc.) to execute all or part of the steps of the above-mentioned methods in each embodiment of the present application. The aforementioned memory includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, disk or optical disk and other media that can store program codes.

[0149] Those skilled in the art will appreciate that all or part of the steps in the various methods of the above embodiments may be completed by instructing related hardware through a program, and the program may be stored in a computer-readable memory, which may include a flash drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, etc.

[0150] The embodiments of the present application are introduced in detail above. Specific examples are used in this article to illustrate the principles and implementation methods of the present application. The description of the above embodiments is only used to help understand the method and core idea of ​​the present application. At the same time, for general technical personnel in this field, according to the idea of ​​the present application, there will be changes in the specific implementation method and application scope. In summary, the content of this specification should not be understood as a limitation on the present application.

Claims

1. A product information push method, characterized in that: Applied to electronic equipment, the method comprises: Obtaining first user basic information of a first user in a first scenario and second user basic information of a second user in a second scenario, where the user basic information refers to the user's personal information and the personal information of a first contact associated with the user in a scenario; the first scenario and the second scenario are any one of an insurance product scenario and a financial scenario, and the first scenario is different from the second scenario; Identifying the first user basic information and the second user basic information to obtain a first association between the first user basic information and the second user basic information; Determine whether the first user and the second user are the same user according to the first correlation, and if so, integrate the first user information of the first user in the first scenario and the second user information of the second user in the second scenario to obtain the third user information of the first user, wherein the user information includes: basic user information, user value information, user behavior information, and user historical purchase information; the integration includes: comparing the first user information and the second user information, and integrating the information in the second user information that is different from the first user information into the first user information; Determine the first user's demand score for the first product based on the third user information; the first user's demand score calculation formula is: ; Where Standard is the demand score of the first user, C is a constant, SPmin is the minimum conversion rate, SPmax is the maximum conversion rate, and Ip is a weight value; Score is ,in Represents the model score of customer conversion rate under known label conditions, is the label weight value of the third user information, A label for third-party user information; determining the progress of the first user according to the demand score of the first user; Pushing product information of the first product to the first user according to the progress of the first user; wherein the product information pushed at different progress stages is different; If the process of the first user is at the P1 stage, information is recommended according to the label weight information in the user rating model, and the demand information of the first user is obtained to improve the understanding degree information of the first user; If the first user's process is at the P2 stage, a demand tendency model of the first user is constructed to obtain the first user's major product tendency information, and information is recommended to the first user based on the product tendency information; If the first user's progress is at the P3 stage, a premium model is constructed to predict the premium range that the user can afford in the future, and the target premium range that the first user can afford is predicted based on the premium model, and product recommendations are made based on the target premium range and the first user's product preference information at the P2 stage; wherein the P1 stage is the cognitive stage, the P2 stage is the operational stage, and the P3 stage is the precision marketing stage.

2. A product information push device, characterized in that: The device comprises: an acquisition unit, configured to acquire first user basic information of a first user in a first scenario and second user basic information of a second user in a second scenario; the first scenario and the second scenario are any one of an insurance product scenario and a financial scenario, and the first scenario is different from the second scenario; an identification unit, configured to identify the first user basic information and the second user basic information, and obtain a first association between the first user basic information and the second user basic information; an integration unit, configured to determine whether the first user and the second user are the same user according to the first association, and if so, integrate the first user information of the first user in the first scenario and the second user information of the second user in the second scenario to obtain the third user information of the first user; the integration comprises: comparing the first user information and the second user information, and integrating the information in the second user information that is different from the first user information into the first user information; A determination unit is used to determine the demand score of the first user for the first product according to the third user information; the demand score calculation formula of the first user is: ; Where Standard is the demand score of the first user, C is a constant, SPmin is the minimum conversion rate, SPmax is the maximum conversion rate, and Ip is a weight value; Score is ,in Represents the model score of customer conversion rate under known label conditions, is the label weight value of the third user information, A label for third-party user information; A push unit is used to determine the progress of the first user according to the demand score of the first user; push product information of the first product to the first user according to the progress of the first user; wherein the product information pushed at different progress stages is different; wherein, if the progress of the first user is at the P1 stage, recommend information according to the label weight information in the user scoring model, and obtain the demand information of the first user to improve the information on the degree of understanding of the first user; if the progress of the first user is at the P2 stage, construct a demand tendency model of the first user to obtain the product tendency information of the major categories of the first user, and recommend information to the first user according to the product tendency information; if the progress of the first user is at the P3 stage, construct a premium model for predicting the premium range that the user can afford in the future, and predict the target premium range that the first user can afford based on the premium model, and make product recommendations based on the target premium range and the product tendency information of the first user at the P2 stage; wherein the P1 stage is the cognitive stage, the P2 stage is the operating stage, and the P3 stage is the precision marketing stage.

3. An electronic device, characterized in that: The method comprises a processor, a memory, a communication interface, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the processor, and the programs include instructions for executing the steps in the method according to claim 1.

4. A computer-readable storage medium, characterized in that: It stores a computer program for electronic data exchange, wherein the computer program causes a computer to execute the method as claimed in claim 1.

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