CN110310145B

CN110310145B - Product multi-dimensional configuration method, device, computer equipment and storage medium

Info

Publication number: CN110310145B
Application number: CN201910432713.8A
Authority: CN
Inventors: 袁佳
Original assignee: Ping An Life Insurance Company of China Ltd
Current assignee: Ping An Life Insurance Company of China Ltd
Priority date: 2019-05-23
Filing date: 2019-05-23
Publication date: 2024-05-24
Anticipated expiration: 2039-05-23
Also published as: CN110310145A

Abstract

The invention discloses a method, a device, computer equipment and a storage medium for multi-dimension configuration of products, wherein the method comprises the steps of dividing each product management mechanism according to a hierarchy, configuring corresponding mechanism codes for each product management mechanism, and determining mechanism authorized products corresponding to the mechanism codes; determining an agent authorization product of each agent identifier corresponding to the mechanism code according to the mechanism authorization product corresponding to the mechanism code; acquiring a to-be-recommended client list, performing group division on client information in the to-be-recommended client list, and determining a client group corresponding to the client information; searching a database according to a customer group, and acquiring a product to be recommended corresponding to the customer group; matching the product to be recommended with the seat authorized product to obtain a matching result; if the matching result is that the matching is successful, distributing the customer information in the product to be recommended and the corresponding customer group to the seat terminal corresponding to the seat authorized product, so as to solve the problem of low efficiency of selling the product by the current seat.

Description

Product multi-dimensional configuration method, device, computer equipment and storage medium

Technical Field

The present invention relates to the field of data processing, and in particular, to a method and apparatus for multidimensional configuration of a product, a computer device, and a storage medium.

Background

Along with the development of science and technology, the competition of each company is more and more vigorous, and each company communicates with clients through manual agents for dialing out calls, so that the sales efficiency of products of the company is improved. Typically, each company will provide a large number of telephone numbers for each agent that recommends products by dialing out telephone numbers. But the mass-market products in different areas are different, and the agents in each area recommend the products by dialing out the telephone, so that the productivity is not high. Meanwhile, the sales of each agent is different due to different conditions, products which are good for sales or recommended by each agent are different, if the agents recommend products which are not good for sales, the problems of unclear and the like can occur, in a large number of telephone numbers, products which are required by different customers are different, and the agents have no pertinence in product sales, so that the sales efficiency is low.

Disclosure of Invention

The embodiment of the invention provides a method, a device, computer equipment and a storage medium for multi-dimension configuration of a product, which are used for solving the problem of low product selling efficiency of the current seat.

A method of multi-dimensional configuration of a product, comprising:

Dividing each product management mechanism according to a hierarchy, configuring corresponding mechanism codes for each product management mechanism, and determining mechanism authorized products corresponding to the mechanism codes;

determining an agent authorization product of each agent identifier corresponding to the mechanism code according to the mechanism authorization product corresponding to the mechanism code;

acquiring a to-be-recommended client list, performing group division on client information in the to-be-recommended client list, and determining a client group corresponding to each client information;

searching a database according to the customer group, and acquiring a product to be recommended corresponding to the customer group;

matching the product to be recommended with the seat authorization product to obtain a matching result;

and if the matching result is that the matching is successful, distributing the customer information in the product to be recommended and the corresponding customer group to the seat terminal corresponding to the seat authorized product.

A product multi-dimensional configuration apparatus comprising:

The mechanism authorized product determining module is used for dividing each product management mechanism according to the hierarchy, configuring corresponding mechanism codes for each product management mechanism and determining mechanism authorized products corresponding to the mechanism codes;

The seat authorization product determining module is used for determining the seat authorization product of each seat identifier corresponding to the mechanism code according to the mechanism authorization product corresponding to the mechanism code;

The client group determining module is used for acquiring a to-be-recommended client list, dividing the client information in the to-be-recommended client list into groups, and determining a client group corresponding to each client information;

The product to be recommended acquisition module is used for searching a database according to the client group and acquiring the product to be recommended corresponding to the client group;

The matching result acquisition module is used for matching the product to be recommended with the seat authorized product to acquire a matching result;

And the customer information distribution module is used for distributing the customer information in the product to be recommended and the corresponding customer group to the seat terminal corresponding to the seat authorized product if the matching result is that the matching is successful.

A computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, the processor implementing the product multi-dimensional configuration method described above when executing the computer program.

A computer readable storage medium storing a computer program which when executed by a processor implements the product multi-dimensional configuration method described above.

The method, the device, the computer equipment and the storage medium for multi-dimension configuration of the product are provided, and the corresponding organization codes are configured for each product management organization to determine the organization authorized product corresponding to the organization codes so as to realize the determination of the product which can be sold by each organization code, avoid blind sales and improve the productivity. And determining the seat authorized products of each seat mark corresponding to the organization codes according to the organization authorized products corresponding to the organization codes, so that the seats sell or recommend the good products, and the sales efficiency is improved. The method comprises the steps of obtaining a to-be-recommended client list, determining a client group corresponding to each client information in the to-be-recommended client list, obtaining to-be-recommended products corresponding to the client group, determining products required by each client information, avoiding blind recommending of the products by an agent, enabling the agent to sell or recommend good products, and improving recommending and selling efficiency; matching the product to be recommended with the seat authorized product, distributing the product to be recommended and the client information in the corresponding client group to the seat terminal corresponding to the seat authorized product, so that the recommended product is the product required by the client, the recommended product is the product good at being recommended or sold by the seat, and the sales success rate is improved.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are needed in the description of the embodiments of the present invention will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.

FIG. 1 is a schematic diagram of an application environment of a method for multi-dimensional configuration of a product according to an embodiment of the present invention;

FIG. 2 is a flow chart of a method of multi-dimensional configuration of a product in an embodiment of the invention;

FIG. 3 is a flow chart of a method of multi-dimensional configuration of a product in an embodiment of the invention;

FIG. 4 is a flow chart of a method of multi-dimensional configuration of a product in an embodiment of the invention;

FIG. 5 is a flow chart of a method of multi-dimensional configuration of a product in an embodiment of the invention;

FIG. 6 is a flow chart of a method of multi-dimensional configuration of a product in an embodiment of the invention;

FIG. 7 is a flow chart of a method of multi-dimensional configuration of a product in an embodiment of the invention;

FIG. 8 is a flow chart of a method of multi-dimensional configuration of a product in an embodiment of the invention;

FIG. 9 is a functional block diagram of a product multi-dimensional configuration device in accordance with one embodiment of the present invention;

FIG. 10 is a schematic diagram of a computer device in accordance with an embodiment of the invention.

Detailed Description

The following description of the embodiments of the present invention will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are some, but not all embodiments of the invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.

The product multidimensional configuration method provided by the embodiment of the invention can be applied to an application environment as shown in fig. 1, and is applied to a product recommendation system, wherein the product recommendation system comprises a client and a server, and the client communicates with the server through a network. The method comprises the steps of firstly determining the organization authorized products of each product management organization, then determining the agent authorized products corresponding to each agent, and finally matching the products to be recommended corresponding to the customer information with the agent authorized products, so that the products recommended by the agents are smooth sales products in the area, are good-quality recommended products and are required by customers. The clients may be, but are not limited to, various personal computers, notebook computers, smart phones, tablet computers, and portable wearable devices. The server may be implemented by an independent server or a server cluster formed by a plurality of servers.

In an embodiment, as shown in fig. 2, a method for configuring multiple dimensions of a product is provided, and the method is applied to the server in fig. 1 for illustration, and specifically includes the following steps:

s10: dividing each product management organization according to the hierarchy, configuring corresponding organization codes for each product management organization, and determining organization authorized products corresponding to the organization codes.

The organization codes refer to identifiers configured by the server for each product management organization according to preset rules, different product management organizations correspond to different organization codes, and unique product management organizations can be found through the organization codes. The preset rules refer to rules for generating corresponding identifications for each level of product management mechanism. The authorized product of the organization refers to an authorized product configured for the product management organization and capable of being sold or recommended, and the authorized product can be determined by the authorized product, so that the authorized product, namely the product management organization, can be sold or recommended.

Specifically, the hierarchy of each product management mechanism is determined, wherein the hierarchy can be specifically divided into 4 classes of headquarters, branch centers, business departments, business groups and the like, and the service end configures corresponding mechanism codes for each product management mechanism according to preset rules and the hierarchy corresponding to each product management mechanism. And determining the authorized products of the corresponding institutions of each product management institution according to the data values of the products of each product management institution within a certain period of time. For example, if the data value corresponding to the good luck and easy execution of the Guangzhou product management agency reaches the product threshold, the good luck and easy execution is used as the agency authorized product corresponding to the Guangzhou product management agency, wherein the product threshold is a preset value for determining whether a single product can be used as the agency authorized product corresponding to the agency code, and it is understood that the product threshold corresponding to each product in each product management agency can be different.

Further, the upper tier includes a corresponding institution authorization product for each lower tier. For example, the business department comprises a business 1 part and a business 2 part, and the authorized products corresponding to the business 1 part are A and B; the authorized products corresponding to business 2 are A and C, and the authorized products corresponding to business can be A, B and C. By determining the corresponding mechanism code and the authorized products of the mechanisms of each product management mechanism, the phenomenon that different product management mechanisms recommend or sell the same products is avoided, so that the sales of the products are not targeted, the seat time is wasted, the seat productivity is not high, and the performance is influenced.

S20: and determining the seat authorization product of each seat identifier corresponding to the organization code according to the organization authorization product corresponding to the organization code.

The agent identifiers are identifiers which are configured for the agents in advance by the server side and are used for distinguishing each agent. The agent authorized product refers to a product which corresponds to the agent identifier and can be sold or recommended.

Specifically, the server side obtains all the seat identifiers and data information (i.e. seat sales information) corresponding to each organization code in advance, wherein the data information can include a data value (sales amount) in a certain time period (the last quarter), and then configures a corresponding seat authorization product for the seat identifier corresponding to the organization code according to the organization authorization product and the data information corresponding to the organization code. It should be noted that, the agent authorized product corresponding to the agent identifier may be an organization authorized product corresponding to an organization code, or may be an authorized product not corresponding to an organization code, for example, the organization authorized products corresponding to a certain organization code may be A, B and C products, and then the agent identifier may be a and B products, or may be other products belonging to the same class with the a and B products. And determining the seat authorized product corresponding to the seat identifier through the mechanism authorized product, so that the seat corresponding to the seat identifier sells or recommends the mass-market product in the area, and the productivity of the seat is improved. Because the sales products corresponding to each agent are different, for example, some agents are good at sales accidents, some agents are good at sales health, the sales products good at the agents are determined according to the data information, so as to determine the agent sales permission, the agent authorized products corresponding to each agent identification are obtained, the good products are recommended or sold through the agents corresponding to the agent identification, and the sales efficiency is improved. And determining the seat authorized product through the data value in a certain time period so as to periodically update the products which can be sold or recommended by the seat, thereby avoiding long-term sale or recommendation of the same products.

Further, each organization code includes a particular authorized product. And configuring corresponding specific authorized products for each organization code according to the organization authorized products corresponding to the organization codes, so that the agents newly added into the company recommend or sell the specific authorized products. The specific authorized product may be a product with more customer demands or a product with lower premium, etc.

S30: and obtaining a to-be-recommended client list, dividing the client information in the to-be-recommended client list into groups, and determining the client group corresponding to each client information.

The to-be-recommended client list refers to a list formed by client information that an agent calls out to recommend or sell. The list of clients to be recommended contains at least one client information, wherein the client information comprises, but is not limited to, client personal information and telephone numbers. The customer group refers to a group formed by dividing customers in advance according to actual conditions, for example, a 'high-quality customer group', 'child risk group', 'endowment insurance group', a 'car risk group' and the like.

In particular, customer information for each agent may be issued by a particular product authority, as the division criteria for the customer group varies for each particular product authority. After the specific product management mechanism obtains the to-be-recommended client list, grouping each client in the to-be-recommended client list according to the decision tree model corresponding to the specific product management mechanism, and determining the client group corresponding to each client information in the to-be-recommended client list. The customer group corresponding to each piece of customer information is determined by dividing the group of each piece of customer information in the customer list to be recommended, so that products required by the customer group can be determined later, and the products can be conveniently issued to corresponding seats for product sales or recommendation, and the sales or recommendation efficiency is improved.

The decision tree is also called a decision tree, and is a tree structure applied to classification, wherein each internal node represents a test on a certain attribute, each edge represents a test result, and each leaf node represents a certain class or distribution of classes. The decision tree model can make decisions on a large amount of client information in the client list to be recommended in a relatively short time, the client group corresponding to each client information is obtained, the accuracy of client group classification is improved, the decision tree is only required to be built once and used repeatedly, and the efficiency of client group division is improved.

S40: and searching a database according to the customer group, and acquiring the products to be recommended corresponding to the customer group.

The product to be recommended refers to a preset product corresponding to a customer group. The database stores the corresponding relation between each customer group and the product to be recommended. For example, a juvenile risk product corresponding to a juvenile risk group; the vehicle insurance customer group corresponds to vehicle insurance products; a high quality customer group may correspond to a particular authorized product.

Specifically, a database is searched according to customer groups, and products to be recommended corresponding to each customer group are obtained. By determining the products to be recommended corresponding to each customer group, the corresponding products to be recommended can be recommended to the customers in the customer group recommendation, the sales efficiency is improved, and the recommended products are more targeted.

S50: and matching the product to be recommended with the seat authorized product to obtain a matching result.

The matching result is obtained by matching the product to be recommended with the agent authorized product, and comprises matching success and matching failure.

Specifically, because the agent authorized products corresponding to each agent are different, the server needs to match the to-be-recommended products corresponding to the client group with the agent authorized products corresponding to the agent identifier, and a matching result is obtained. By matching the product to be recommended with the agent authorized product, the agent identifier is then allocated with the product which is good for recommendation or sales and is required by the customer corresponding to the customer information.

Further, when matching is performed, determining whether the product to be recommended and the agent authorized product are of the same type, wherein the types can be text type and code type (for example, the code A1000 represents xx risk), and different codes correspond to different products; if the types of the product to be recommended and the seat authorized product are different, invoking a preset conversion rule to convert the product into a unified type, wherein the conversion rule refers to the corresponding relation between the codes and the characters; and matching the product to be recommended and the seat authorization product according to a matching algorithm corresponding to the type. Specifically, when the type is literal, the DFA algorithm and KMP (Knuth-Morris-Pratt, knoop-Morris-Pratt) algorithm may be employed, but are not limited to. In the embodiment, the KMP algorithm is selected for keyword matching, so that time is saved, and matching efficiency is improved. When the type is the coding type, a regular matching algorithm can be adopted for matching, so that the matching efficiency is improved.

S60: if the matching result is that the matching is successful, distributing the to-be-recommended products and the client information in the corresponding client groups to the agent terminals corresponding to the agent authorized products.

Specifically, if the product to be recommended is successfully matched with the agent authorized product, the server side determines the issued agent for each customer group, then the product to be recommended and the customer information in the corresponding customer group are distributed to the agent terminal corresponding to the agent authorized product, the product to be recommended is the product of which the agent is good at recommending or selling, and the agent recommends the product to the customer according to the product to be recommended, so that the selling efficiency is improved. The customer information in the product to be recommended and the corresponding customer groups is distributed to the seat terminal corresponding to the seat authorized product, the seat authorized product is a product which is popular in the area, the seat is good at selling or recommending the product to be recommended, and the product to be recommended is a product required by the customer, so that the productivity is improved.

And S10-S60, determining the organization authorized products corresponding to the organization codes by configuring the corresponding organization codes for each product management organization so as to realize the determination of the products which can be sold by each organization code, avoiding blind sales and improving the productivity of the seat. And determining the seat authorized products of each seat mark corresponding to the organization codes according to the organization authorized products corresponding to the organization codes, so that the seats sell or recommend the good products, and the sales efficiency is improved. The method comprises the steps of obtaining a to-be-recommended client list, determining a client group corresponding to each client information in the to-be-recommended client list, obtaining to-be-recommended products corresponding to the client group, determining products required by each client information, avoiding blind recommending of the products by an agent, enabling the agent to sell or recommend good products, and improving recommending and selling efficiency; matching the product to be recommended with the seat authorized product, distributing the product to be recommended and the client information in the corresponding client group to the seat terminal corresponding to the seat authorized product, so that the recommended product is the product required by the client, the recommended product is the product good at being recommended or sold by the seat, and the sales success rate is improved.

In one embodiment, as shown in fig. 3, step S10, namely, dividing each product management organization according to a hierarchy, configuring a corresponding organization code for each product management organization, and determining an organization authorized product corresponding to the organization code, specifically includes the following steps:

S11: and acquiring the organization information of all the product management organizations, determining the hierarchy corresponding to the product management organizations according to the organization information, and configuring corresponding organization codes for the product management organizations according to the hierarchy.

The organization information refers to information of each product management organization. The organization information includes organization names, affiliated departments, geographical position information, and the like. The hierarchy is determined based on the institution information corresponding to each product administration.

Specifically, the server obtains the organization information of all the product management organizations of the company, and performs hierarchical division on each product management organization according to the organization information, for example, the organization information is classified into 4 classes such as headquarters, branch centers, business departments, business groups and the like according to the hierarchy. And configuring corresponding organization codes for each product management organization, wherein the organization codes can contain the hierarchy identification corresponding to the product management organization.

S12: and obtaining the mechanism data value corresponding to the single product of each mechanism code, and comparing the mechanism data value with the product threshold.

The organization data value refers to a data total value (sales total) corresponding to each product corresponding to the organization code in a certain period of time. For example, the organization code corresponds to the data value of the A product of the last quarter. It should be noted that, each product type includes a plurality of individual products, and in this embodiment, the institution data value corresponding to each individual product is obtained. For example, the pediatric risk class contains U, V and W individual products, and the institution data value corresponding to each individual product is obtained. The product threshold value refers to a preset value for determining whether a single product can be used as an authorized product of an organization corresponding to the organization code. The product threshold may be determined in a plurality of ways, and one way is to calculate an average value according to the institution data value of the individual product of each product management institution, and use the average value as the product threshold. Another way is to determine a cost corresponding to a single product for each product management mechanism in a certain period of time for each product management mechanism, determine a product threshold corresponding to each product management mechanism according to the formula cost x (1+ profit ratio) based on the cost and the profit ratio, for example, the cost of U products is 5 ten thousand, the profit ratio is twenty percent, and then the product threshold is 6 ten thousand.

Specifically, the mechanism data value corresponding to the single product corresponding to each mechanism code is firstly obtained, and the product threshold value corresponding to each mechanism code configuration can be predetermined because the geographic position, the level and the economic environment of each selling mechanism are different, and technical support is provided for the authorized product of the subsequent determining mechanism by comparing the mechanism data value with the corresponding product threshold value.

S13: and if the institution data value is larger than the product threshold, determining the single product corresponding to the institution data value as an institution authorized product.

Specifically, the product threshold may be understood as a sales expected value, and if the institution data value is greater than the product threshold, the institution data value corresponding to the institution code reaches the sales expected value, and then a single product corresponding to the institution data value greater than the product threshold is taken as an institution authorized product corresponding to the institution code.

In the steps S11-S13, the mechanism data value corresponding to the single product of each mechanism code is obtained, the mechanism data value is compared with the product threshold, the single product corresponding to the mechanism data value larger than the product threshold is determined to be the mechanism authorized product, the purposes that the free selling product in the area where the mechanism code is located is determined according to the mechanism data value corresponding to the mechanism code and the free selling product is taken as the mechanism authorized product are achieved, so that the agent can sell or recommend the free selling product, and the selling efficiency is improved.

In one embodiment, as shown in fig. 4, after step S12, that is, after comparing the mechanism data value with the product threshold, the product multidimensional configuration method further includes the following steps:

S121: and if the data value of the mechanism is not greater than the product threshold value, determining the total value of the same-class data corresponding to the same-class product of the mechanism code.

Specifically, if the organization data value is not greater than the product threshold, the organization data value corresponding to the organization code does not reach the sales expected value, and the like data total value of the like products to which the single products belong is counted, wherein the like data total value refers to the sum of the organization data values of the single products in the same class. For example, the child risk class includes U, V and W, and if the corresponding organization data value of the U product is not greater than the product threshold, the similar data total value of the child risk class, that is, the similar data total value of U, V and W, is counted.

S122: and calculating the data proportion between the data value of the mechanism and the total value of the similar data, and if the data proportion is larger than the proportion threshold value, determining the single product corresponding to the data value of the mechanism as the authorized product of the mechanism.

The data proportion is the proportion of the mechanism data value corresponding to the single product in the similar data value corresponding to the similar product. The ratio threshold is a predetermined ratio of corresponding institutional authorized products used to determine whether an individual product may act as an institutional code. It will be appreciated that the proportion threshold is less than the proportion of the average value to the total value of the data of the same class.

Specifically, after the mechanism data value and the similar data total value are obtained, calculating the data proportion occupied by the mechanism sales in the similar data total value, comparing the data proportion with a proportion threshold value, and if the data proportion is larger than the proportion threshold value, determining a single product corresponding to the mechanism data value as a mechanism authorized product.

Further, based on the organization authorized product corresponding to the organization code of the last level, the organization authorized product corresponding to the organization code of the next level is updated. Specifically, according to the organization authorized products of the previous level, the trial sales products of each lower level are determined, if the data value of the trial sales products of a certain lower level reaches a certain proportion, the organization authorized products corresponding to the organization codes of the next level are updated, and the trial sales products are taken as the organization authorized products of the next level. For example, the authorized products of the mechanism corresponding to a certain upper level are A, B, C, D and E, the authorized products of the mechanism corresponding to a certain lower level are A, B and C, the authorized product D is taken as a trial sales product, if the data value of the D product corresponding to the lower level reaches a certain proportion in a certain period of time, the D product is taken as the authorized product of the mechanism of the lower level, so that trial sales of each product of the lower level is realized, and the product management mechanism of the lower level is prevented from selling the same authorized product of the mechanism throughout the year.

In step S121-S122, if the mechanism data value is not greater than the product threshold, determining a generic data total value corresponding to the generic product of the mechanism code, calculating a data ratio between the mechanism data value and the generic data total value, and if the data ratio is greater than the ratio threshold, determining a single product corresponding to the mechanism data value as a mechanism authorized product, thereby realizing the determination of the mechanism authorized product.

In one embodiment, as shown in fig. 5, in step S20, an agent authorization product of each agent identifier corresponding to an organization code is determined according to the organization authorization product corresponding to the organization code, and specifically includes the following steps:

S21: and acquiring the seat information to be configured, wherein the seat information to be configured comprises a seat identifier, a seat grade and data information.

The agent information to be configured refers to data information of an agent authorized product corresponding to the agent identifier. The agent level refers to a level corresponding to the agent identifier determined according to the agent sales capability. The data information refers to a data value (sales) corresponding to each product corresponding to the agent identifier in a certain period of time (the last quarter).

Specifically, corresponding agent authorized products are configured for the agent identifiers corresponding to the codes of each mechanism in advance, so that the distribution of subsequent client information is facilitated. The method comprises the steps of firstly, obtaining authority configuration requests of all product management institutions sent by team members on the basis of clients, and obtaining seat information to be configured according to the authority configuration requests, wherein the seat information to be configured comprises seat identifiers, seat grades and data information, and the authority configuration requests refer to requests of the team members of the product management institutions on the basis of the clients, wherein the requests are used for configuring seat authorized products corresponding to the seat identifiers.

S22: and determining the affiliated mechanism code according to the agent identification, and acquiring a data threshold value corresponding to each agent level in the mechanism code.

The data threshold value is a preset value for determining whether a single product can be used as an agent authorized product corresponding to the agent identifier. Specifically, determining an organization code to which the agent identification is determined, determining an average value according to data information corresponding to each agent identification in the same organization code, taking the average value as a data threshold value of which the agent level is a middle level, and finally determining the data threshold value corresponding to each agent level by an equal ratio array or an equal difference array. The data threshold corresponding to different seat levels in each product management mechanism can be different because the region in which each product management mechanism is responsible is different and the environment in which each product management mechanism is located is different.

Specifically, the correspondence between the agent level and the data threshold is configured for each organization code in advance, and stored in the database. The method comprises the steps of firstly determining an organization code to which an agent identifier belongs according to the agent identifier, and then determining the corresponding relation between each agent grade corresponding to the organization code and a data threshold according to the organization code. And determining which authorized products are allocated for the agent identification through the mechanism authorized products corresponding to the mechanism codes, and providing technical support for the follow-up determination of the agent authorized products through determining the corresponding relation between the agent level and the data threshold. It will be appreciated that the higher the agent level, the higher the corresponding data threshold, and conversely, the lower the agent level, the lower the corresponding data threshold.

S23: and counting personal data values of the single products corresponding to the agent identifiers according to the data information, and comparing the personal data values corresponding to the agent identifiers with data thresholds corresponding to the agent grades.

Wherein the personal data value refers to the data value of a single product within a certain period of time (such as the last quarter) corresponding to the agent identification. Specifically, after the corresponding relation between the agent level and the data threshold is obtained, according to the data information corresponding to each agent identifier, a personal data value of a single product corresponding to the agent identifier is obtained, and the personal data value is compared with the data threshold corresponding to the agent level corresponding to the agent identifier. For example, the seat class corresponding to a certain seat mark is the first class, the personal data value is 100 ten thousand in a certain time period, the data threshold value corresponding to the first class in the organization code corresponding to the seat mark is 200 ten thousand, and the personal data value is 100 ten thousand and the data threshold value corresponding to the first class are compared with 200 ten thousand.

S24: and if the personal data value is larger than the data threshold value, taking the single product corresponding to the personal data value and the specific authorized product as the agent authorized product corresponding to the agent identifier.

Wherein, the specific authorized product refers to a product which can be sold or recommended by each agent corresponding to the organization code.

Specifically, if the personal sales data value is greater than the data threshold, that is, the personal data value corresponding to the agent identifier reaches a preset expected value and can be authorized, the single product corresponding to the personal data value is used as the agent authorized product corresponding to the agent identifier, that is, the product with the agent good at sales is used as the agent authorized product. Because each organization code is preset with a specific authorized product, namely, a product which can be sold or recommended by each agent, the specific authorized product corresponding to the organization code to which the agent identifier belongs is also used as the authorized product corresponding to the agent identifier.

S25: and if the personal data values are not greater than the data threshold value, taking the specific authorized product as the agent authorized product corresponding to the agent identifier.

Specifically, each personal data value corresponding to the agent identifier is compared with a corresponding data threshold, if each personal data value is not larger than the corresponding data threshold, it is indicated that in a certain period of time, the personal data value corresponding to the agent identifier does not reach a preset expected value and authorization cannot be performed, and then a specific authorized product corresponding to an institution code to which the agent identifier belongs is taken as an authorized product corresponding to the agent identifier.

And S21-S25, determining the affiliated mechanism code according to the seat identification, and acquiring the data threshold value corresponding to each seat grade in the mechanism code, so that the affiliated mechanism code is different according to different seat grades, and the corresponding data threshold value is different. According to the data information, the personal data value of the single product corresponding to the agent identifier is counted, the personal data value corresponding to the agent identifier is compared with the data threshold corresponding to the agent level, the corresponding data threshold is determined according to the agent level corresponding to the agent, the situation that the agent authorized products are unevenly distributed due to the fact that different agent levels correspond to the same data threshold is avoided, and accordingly the accuracy of configuration of the agent authorized products is improved. If the personal data value is larger than the data threshold value, taking the single product corresponding to the personal data value and the specific authorized product as the seat authorized product corresponding to the seat identifier; if the personal data value is not greater than the data threshold value, the specific authorized product is used as the agent authorized product corresponding to the agent identifier, so that the configuration of the agent authorized product is realized, the product required by the customer information distributed for the agent identifier later is the product which is good at selling or recommending for the agent identifier, and the productivity is improved.

In an embodiment, as shown in fig. 6, after step S23, that is, after comparing the personal data value corresponding to the agent identifier with the data threshold corresponding to the agent level, the product multidimensional configuration method specifically further includes the following steps:

S231: and counting the total personal data value corresponding to the similar products of each seat mark according to the data information, and comparing the total personal data value with the threshold value of the similar products.

The personal data total value refers to the sum of personal data values of like products in a certain period of time corresponding to the seat mark. The similar product threshold is a preset value for evaluating whether the similar product is used as an agent authorized product corresponding to the agent identifier according to different levels corresponding to the product management mechanism.

Specifically, according to the data information corresponding to the seat identifications, the sum of the data values of the like products, namely the total personal data value, in a certain period of time corresponding to each seat identification is counted. It should be noted that, the threshold value of the similar product corresponding to each type of product is preset, so that the subsequently determined seat authorized product is more accurate. If the total value of the personal data is the sum of the data values of the last quarter, the threshold value of the similar products is set for the last quarter; and comparing the personal data total value with a threshold value of a similar product, for example, the juvenile insurance class comprises U, V and W and other single products, the agency authorized product corresponding to a certain agency code comprises part of products of the juvenile insurance class, for example, only comprises U products and V products, and according to data information, counting the sum of the personal data values of the U products and the V products corresponding to the seat identification within a certain period (such as the last quarter) to obtain the personal data total value, and comparing the personal data total value with the threshold value of the similar product.

S232: and if the total value of the personal data is larger than the threshold value of the similar products, taking all the products of the similar products and the specific authorized products as the seat authorized products corresponding to the seat identifications.

Specifically, if the total value of the personal data is larger than the threshold value of the similar products, namely the agents corresponding to the agent identifiers are good at selling the similar products, all the products and the specific authorized products of the similar products are used as the agent authorized products corresponding to the agent identifiers. For example, in the embodiment of step S31, if the total personal data value of the U product and the V product corresponding to the seat identifier is greater than the similar product threshold, products such as U, V and W of the child risk class and the specific authorized product corresponding to the organization code of the seat identifier are used as the seat authorized product corresponding to the seat identifier.

In one embodiment, as shown in fig. 7, in step S30, a to-be-recommended client list is obtained, and each client information in the to-be-recommended client list is grouped to determine a client group corresponding to each client information, which specifically includes the following steps:

s31: and acquiring a to-be-recommended client list, wherein the to-be-recommended client list comprises at least one client information and a specific organization code.

Wherein the customer information includes, but is not limited to, name, identification number, asset status, marital status, whether there is a child, health status, phone number, etc. The specific organization code refers to the organization code to which the list of clients to be recommended belongs.

Specifically, since the agents require outgoing calls for product sales or recommendation, a public will generally assign telephone numbers of a large number of clients to the agents by a specific product management organization, and the specific product management organization obtains a list of clients to be recommended through various channels, where the list of clients to be recommended includes at least one client information and a specific organization code.

S32: and searching a database according to the specific organization codes, and acquiring a decision tree model corresponding to the specific organization codes.

Specifically, because the authorized products of the institutions corresponding to each specific institution are different, the required classification standards are different, for example, the Shenyang branch center and the Guangzhou branch center are high-income customers, and the Shenyang may be ten thousands of months and the Guangzhou needs to be ten thousands of months due to the economic condition difference. Thus, if the classification criteria corresponding to a particular organization code is different, the decision tree model corresponding to each particular organization code is also different. The product management mechanism corresponding to each specific mechanism code adopts a decision tree algorithm to train historical client data in the database according to the classification standard of the product management mechanism, so as to obtain a decision tree model corresponding to the specific mechanism code.

Decision tree algorithms include, but are not limited to, ID3 (ITERATIVE DICHOTOMISER, iterative decision tree) algorithms, C4.5 algorithms, CART (Classification and Regression Tree ) algorithms, and the like. In this embodiment, the historical customer data in the database is trained specifically by using a C4.5 algorithm, where the C4.5 algorithm is an algorithm for constructing a decision tree, and performs attribute selection according to the information gain rate. And training historical customer data in the database through a C4.5 algorithm, namely, the growth process of the decision tree, until the construction of the decision tree is completed, so as to obtain a decision tree model corresponding to a specific organization code.

S33: and carrying out decision processing on each piece of client information through a decision tree model, and determining a client group corresponding to each piece of client information in a to-be-recommended client list.

Specifically, after a decision tree model corresponding to a specific organization code is obtained, decision processing is performed on each piece of client information in a list to be recommended through a decision data model, a client group corresponding to each piece of client information is obtained, and the client information belonging to the same client group is classified.

In steps S31-S33, a database is searched according to the specific organization codes, and a decision tree model corresponding to the specific organization codes is obtained, so that the subsequently obtained customer groups are quicker and more accurate. And carrying out decision processing on each piece of customer information through a decision tree model, determining a customer group corresponding to each piece of customer information in a to-be-recommended customer list, and determining the customer group so as to determine the to-be-recommended products which can be recommended according to the customer group later.

In one embodiment, as shown in fig. 8, in step S60, client information in a product to be recommended and a corresponding client group is distributed to a seat terminal corresponding to a seat authorized product, and the method specifically includes the following steps:

S61: and determining the assignable quantity corresponding to the seat identifiers according to the seat grade of each seat identifier.

Wherein the allocable quantity refers to the receivable quantity corresponding to the seat mark.

Specifically, the seat level corresponding to each seat identifier can be determined according to the data information. Because the allocable number corresponding to each agent level is different, the database can be searched according to the agent level to determine the allocable number corresponding to the agent identification.

S62: and counting the number of incomplete positions corresponding to the seat marks.

The unfinished number refers to the number of client information which corresponds to the seat identifier and is not recommended correspondingly. Specifically, according to the seat identification, the number of incomplete sets corresponding to the seat identification is counted.

S63: and according to the allocable quantity and the unfinished quantity, acquiring the quantity to be allocated, and distributing the to-be-recommended products matched with the quantity to be allocated and the client information in the corresponding client group to the seat terminal corresponding to the seat authorized product.

The number to be allocated refers to the difference between the allocable number and the unfinished number, and it is understood that the number to be allocated refers to the number of client information allocated to the agent identifier.

Specifically, after the distributable quantity and the unfinished quantity are obtained, the quantity to be distributed corresponding to the seat identifier is calculated according to the distributable quantity and the quantity to be completed, and the customer information in the product to be recommended and the corresponding customer group matched with the quantity to be distributed is distributed to the seat terminal corresponding to the seat authorized product.

And S61-S63, determining the assignable quantity corresponding to the seat marks according to the seat grade of each seat mark so that the seats can carry out task bearing in the bearing range. Counting the number of incomplete positions corresponding to the seat marks; and according to the allocable quantity and the unfinished quantity, acquiring the quantity to be allocated, and distributing the customer information matched with the quantity to be allocated to the seat terminal corresponding to the seat authorized product, so as to realize the allocation of the proper quantity of customer information for the seat.

It should be understood that the sequence number of each step in the foregoing embodiment does not mean that the execution sequence of each process should be determined by the function and the internal logic, and should not limit the implementation process of the embodiment of the present invention.

In an embodiment, a product multi-dimensional configuration device is provided, where the product multi-dimensional configuration device corresponds to the product multi-dimensional configuration method in the above embodiment one by one. As shown in fig. 9, the product multi-dimensional configuration apparatus includes an organization authorized product determination module 10, an agent authorized product determination module 20, a customer group determination module 30, a product to be recommended acquisition module 40, a matching result acquisition module 50, and a customer information distribution module 60. The functional modules are described in detail as follows:

And the mechanism authorized product determining module 10 is used for dividing each product management mechanism according to the hierarchy, configuring corresponding mechanism codes for each product management mechanism, and determining the mechanism authorized products corresponding to the mechanism codes.

The agent authorized product determining module 20 is configured to determine an agent authorized product of each agent identifier corresponding to the organization code according to the organization authorized product corresponding to the organization code.

The client group determining module 30 is configured to obtain a to-be-recommended client list, divide the client information in the to-be-recommended client list into groups, and determine a client group corresponding to each client information.

The product to be recommended obtaining module 40 is configured to search a database according to the customer group, and obtain a product to be recommended corresponding to the customer group.

The matching result obtaining module 50 is configured to match a product to be recommended with an agent authorized product, and obtain a matching result.

And the customer information distribution module 60 is configured to distribute the customer information in the product to be recommended and the corresponding customer group to the agent terminal corresponding to the agent authorized product if the matching result is that the matching is successful.

In one embodiment, the institution authorized product determination module 10 includes an institution code configuration unit, a first comparison unit, and a first institution authorized product determination unit.

And the mechanism code configuration unit is used for acquiring the mechanism information of all the product management mechanisms, determining the hierarchy corresponding to the product management mechanisms according to the mechanism information, and configuring the corresponding mechanism codes for the product management mechanisms according to the hierarchy.

And the first comparison unit is used for acquiring the mechanism data value corresponding to the single product of each mechanism code and comparing the mechanism data value with the product threshold value.

And the first institution authorized product determining unit is used for determining the single product corresponding to the institution data value as the institution authorized product if the institution data value is larger than the product threshold value.

In an embodiment, after the first comparing unit, the product multidimensional configuring apparatus further comprises a generic data total value obtaining unit and a second institution authorization product determining unit.

And the similar data total value acquisition unit is used for determining the similar data total value corresponding to the similar product of the mechanism code if the mechanism data value is not greater than the product threshold value.

And the second mechanism authorized product determining unit is used for calculating the data proportion between the mechanism data value and the similar data total value, and determining the single product corresponding to the mechanism data value as the mechanism authorized product if the data proportion is larger than the proportion threshold value.

In an embodiment, the agent authorized product determining module 20 includes an agent information obtaining unit to be configured, a data threshold obtaining unit, a second comparing unit, a first agent authorized product determining unit, and a second agent authorized product determining unit.

The to-be-configured seat information acquisition unit is used for acquiring to-be-configured seat information, wherein the to-be-configured seat information comprises seat identification, seat grade and data information.

The data threshold value acquisition unit is used for determining the affiliated mechanism code according to the seat identification and acquiring the data threshold value corresponding to each seat grade in the mechanism code.

And the second comparison unit is used for counting personal data values of the single products corresponding to the agent identifiers according to the data information and comparing the personal data values corresponding to the agent identifiers with the data threshold values corresponding to the agent grades.

And the first agent authorized product determining unit is used for taking the single product corresponding to the personal data value and the specific authorized product as the agent authorized product corresponding to the agent identifier if the personal data value is larger than the data threshold value.

And the second agent authorized product determining unit is used for taking the specific authorized product as the agent authorized product corresponding to the agent identifier if the personal data value is not larger than the data threshold value.

In an embodiment, after the second comparing unit, the product multidimensional configuring apparatus further includes a third comparing unit and a third agent authorized product determining unit.

And the third comparison unit is used for counting the personal data total value corresponding to the similar product of each seat mark according to the data information and comparing the personal data total value with the similar product threshold.

And the third agent authorized product determining unit is used for taking all products of the similar products and the specific authorized products as agent authorized products corresponding to the agent identification if the total value of the personal data is larger than the threshold value of the similar products.

In one embodiment, the customer group determination module 30 includes a to-be-recommended customer list acquisition unit, a decision tree model acquisition unit, and a customer group determination unit.

The to-be-recommended client list acquisition unit is used for acquiring a to-be-recommended client list, and the to-be-recommended client list comprises at least one client information and a specific organization code.

And the decision tree model acquisition unit is used for searching the database according to the specific organization codes and acquiring the decision tree model corresponding to the specific organization codes.

And the client group determining unit is used for carrying out decision processing on each piece of client information through the decision tree model and determining a client group corresponding to each piece of client information in the to-be-recommended client list.

In one embodiment, the customer information distribution module 60 includes an allocatable number determination unit, an unfinished number determination unit, and a customer information distribution unit.

And the allocable quantity determining unit is used for determining the allocable quantity corresponding to the seat identifiers according to the seat grade of each seat identifier.

The incomplete number determining unit is used for counting the number of the incomplete corresponding to the seat identifier.

The customer information distribution unit is used for acquiring the quantity to be distributed according to the quantity which can be distributed and the quantity which is not completed, and distributing the customer information in the products to be recommended and the corresponding customer groups matched with the quantity to be distributed to the seat terminals corresponding to the seat authorized products.

For specific limitations of the product multi-dimensional configuration device, reference may be made to the above limitation of the product multi-dimensional configuration method, and no further description is given here. The modules in the multi-dimensional configuration device of the product can be realized in whole or in part by software, hardware and a group of the modules. The above modules may be embedded in hardware or may be independent of a processor in the computer device, or may be stored in software in a memory in the computer device, so that the processor may call and execute operations corresponding to the above modules.

In one embodiment, a computer device is provided, which may be a server, and the internal structure of which may be as shown in fig. 10. The computer device includes a processor, a memory, a network interface, and a database connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The database of the computer equipment is used for data and the like generated or acquired in the process of the multidimensional configuration method of the product, such as the corresponding relation between the customer group and the product to be recommended, a decision tree model and the like. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to implement a method of product multi-dimensional configuration.

In an embodiment, a computer device is provided, including a memory, a processor, and a computer program stored on the memory and executable on the processor, where the processor executes the computer program to implement the steps of the method for multi-dimensional configuration of a product in the above embodiment, for example, the steps S10 to S60 shown in fig. 2, or the steps shown in fig. 3 to 8. Or the processor, when executing the computer program, implements the functions of each module in the product multi-dimensional configuration apparatus in the above embodiment, for example, the functions of the modules 10 to 60 shown in fig. 9. To avoid repetition, no further description is provided here.

In an embodiment, a computer readable storage medium is provided, on which a computer program is stored, which when executed by a processor implements the product multi-dimensional configuration method in the above method embodiment, for example, steps S10 to S60 shown in fig. 2, or steps shown in fig. 3 to 8. Or the computer program when executed by a processor, implements the functions of each module in the product multi-dimensional configuration apparatus in the above embodiment, for example, the functions of the modules 10 to 60 shown in fig. 9. To avoid repetition, no further description is provided here.

Those skilled in the art will appreciate that implementing all or part of the above-described methods may be accomplished by way of a computer program, which may be stored on a non-transitory computer readable storage medium and which, when executed, may comprise the steps of the above-described embodiments of the methods. Any reference to memory, storage, database, or other medium used in embodiments provided herein may include non-volatile and/or volatile memory. The nonvolatile memory can include Read Only Memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double Data Rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (SYNCHLINK) DRAM (SLDRAM), memory bus (RambuS) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), among others.

It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-described division of the functional units and modules is illustrated, and in practical application, the above-described functional distribution may be performed by different functional units and modules according to needs, i.e. the internal structure of the apparatus is divided into different functional units or modules to perform all or part of the above-described functions.

The above embodiments are only for illustrating the technical solution of the present invention, and are not limiting; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention, and are intended to be included in the scope of the present invention.

Claims

1. A method for multi-dimensional configuration of a product, comprising:

obtaining a to-be-recommended client list, dividing groups of client information in the to-be-recommended client list according to a decision tree model corresponding to each product management mechanism, and determining client groups corresponding to each client information;

2. The method for multidimensional allocation of products according to claim 1, wherein said dividing each product management organization by hierarchy, allocating a corresponding organization code for each said product management organization, and determining an organization authorized product corresponding to said organization code comprises:

obtaining the mechanism information of all the product management mechanisms, determining a hierarchy corresponding to the product management mechanisms according to the mechanism information, and configuring corresponding mechanism codes for the product management mechanisms according to the hierarchy;

obtaining a mechanism data value corresponding to a single product of each mechanism code, and comparing the mechanism data value with a product threshold;

and if the institution data value is larger than the product threshold, determining the single product corresponding to the institution data value as an institution authorized product.

3. The product multi-dimensional configuring method of claim 2, wherein after said comparing said institution data values to product thresholds, said product multi-dimensional configuring method further comprises:

If the mechanism data value is not greater than the product threshold, determining a similar data total value corresponding to similar products of the mechanism code;

And calculating the data proportion between the mechanism data value and the similar data total value, and if the data proportion is larger than a proportion threshold value, determining a single product corresponding to the mechanism data value as a mechanism authorized product.

4. The method for multidimensional configuration of products according to claim 1, wherein determining an agent authorization product for each agent identifier corresponding to the agent code based on the agent authorization product corresponding to the agent code comprises:

acquiring seat information to be configured, wherein the seat information to be configured comprises a seat identifier, a seat grade and data information;

determining the affiliated mechanism code according to the agent identification, and acquiring a data threshold value corresponding to each agent level in the mechanism code;

According to the data information, counting personal data values of single products corresponding to the agent identifiers, and comparing the personal data values corresponding to the agent identifiers with data thresholds corresponding to the agent grades;

if the personal data value is larger than the data threshold value, taking a single product corresponding to the personal data value and a specific authorized product as an agent authorized product corresponding to the agent identifier;

and if the personal data values are not larger than the data threshold value, taking the specific authorized product as an agent authorized product corresponding to the agent identifier.

5. The method of multi-dimensional configuration of a product of claim 4, wherein after said comparing the personal data value corresponding to the agent identifier with the data threshold corresponding to the agent level, the method of multi-dimensional configuration of a product further comprises:

according to the data information, counting the total personal data value corresponding to the similar products of each seat mark, and comparing the total personal data value with the similar product threshold;

and if the personal data total value is larger than the similar product threshold value, taking all products of the similar product and the specific authorized product as the seat authorized product corresponding to the seat identifier.

6. The method for multidimensional allocation of products according to claim 1, wherein said obtaining a list of clients to be recommended, grouping each client information in said list of clients to be recommended, determining a client group corresponding to each client information, comprises:

acquiring a to-be-recommended client list, wherein the to-be-recommended client list comprises at least one client information and a specific mechanism code;

searching a database according to the specific organization code, and acquiring a decision tree model corresponding to the specific organization code;

and carrying out decision processing on each piece of client information through the decision tree model, and determining a client group corresponding to each piece of client information in the to-be-recommended client list.

7. The method for multidimensional allocation of products according to claim 1, wherein said distributing the customer information in the product to be recommended and the corresponding customer group to the agent terminal corresponding to the agent authorized product comprises:

determining the assignable quantity corresponding to the seat identifiers according to the seat grade of each seat identifier;

Counting the number of incomplete positions corresponding to the seat identifiers;

and acquiring the quantity to be distributed according to the distributable quantity and the unfinished quantity, and distributing the customer information in the product to be recommended and the corresponding customer group matched with the quantity to be distributed to the seat terminal corresponding to the seat authorized product.

8. A product multi-dimensional configuring apparatus, comprising:

the client group determining module is used for acquiring a to-be-recommended client list, dividing groups of client information in the to-be-recommended client list according to a decision tree model corresponding to each product management mechanism, and determining client groups corresponding to each client information;

9. A computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that the processor implements the method of multi-dimensional configuration of the product according to any of claims 1 to 7 when executing the computer program.

10. A computer readable storage medium storing a computer program, wherein the computer program when executed by a processor implements the method of multi-dimensional configuration of the product of any one of claims 1 to 7.