CN117312400A - Intelligent customer management system and method based on artificial intelligence - Google Patents

Abstract

The invention discloses an intelligent customer management system and method based on artificial intelligence, and belongs to the technical field of customer management. The system comprises a client data acquisition module, a service pushing module, a service follow-up module and a client feedback module; the client data acquisition module acquires client identity information, stores the information and updates the information periodically; the business pushing module pushes business to the client according to the client intention and intelligent analysis; the business follow-up module obtains corresponding business information by inquiring customer information, and predicts the signing possibility of the business by visualizing business signing data; the customer feedback module analyzes customer satisfaction degree through feedback data of customers on the service and performs secondary classification on the customers; the invention realizes the whole-course instant tracking and updating of the customer signing business through the modules, and realizes the careful division of the customers through the feedback condition of the customers so as to ensure the important attention of high-quality customers and the cultivation of potential customers.

Description

Intelligent customer management system and method based on artificial intelligence

Technical Field

The invention relates to the technical field of customer management, in particular to an intelligent customer management system and method based on artificial intelligence.

Background

The client management system is a software system for centrally managing and maintaining client related information; the method helps enterprises effectively track and manage interactions with clients, provides comprehensive client views, helps enterprises identify client demands, improves client relationships, and improves sales and enhances client satisfaction;

in the intelligent era, signing and expanding of cooperative business between enterprises and clients requires more flexible and real-time response, and a plurality of enterprises develop more and more business fields for clients to select in order to adapt to the social development requirement; under such circumstances, the conventional customer management mode of information entry, manual service and service tracking has been difficult to meet the needs of enterprises and customers, and the conventional customer management mode cannot grasp the dynamic situation of customers and services in time, and the feedback of customers to services is basically only performed by people or groups interfacing with customers, which may result in the enterprise having insufficient knowledge of customers themselves, and in case of personnel change, there is a high possibility of causing loss of good quality customers.

Disclosure of Invention

The invention aims to provide an intelligent customer management system and method based on artificial intelligence so as to solve the problems in the background technology.

In order to solve the technical problems, the invention provides the following technical scheme:

an intelligent client management system based on artificial intelligence comprises a client data acquisition module, a service pushing module, a service follow-up module and a client feedback module;

the client data acquisition module acquires personal information or enterprise information of a client through a mobile terminal, updates the client information according to a period, and stores the information after the client information is collected; the business pushing module judges the primary category of the client through the information of the client, and pushes proper business items according to the judging result and the client intention analysis; the service follow-up module determines a target client by inquiring the identity information reserved by the client, inquires corresponding service items of the target client, and predicts the completion degree of the service by analyzing the progress of the service; the customer feedback module acquires feedback according to the completion result of the customer on the business and the service satisfaction degree of the customer, performs secondary division and definition on the current customer according to the feedback, and stores the customer information in a classified manner;

the client data acquisition module is connected with the service pushing module; the business pushing module is connected with the business follow-up module; the business follow-up module is connected with the client feedback module;

the client data acquisition module comprises a client data acquisition unit, a client data updating unit and a client data storage unit; the client data acquisition unit acquires identity data of a client under the authorization of the client through a remote mobile terminal or a manual terminal, wherein the data of the client comprises a client name, a birth date, an age, a contact way, a company name, a company address and a home address; the customer data updating unit is used for periodically inquiring and updating customer identity information and service information; the client data storage unit is used for storing the identity information and the service information of the client.

The data storage unit generates a unique identification code for each piece of customer identity information when storing the customer identity information; after the customer identity information or the service information is updated, the updated information does not cover old data and is stored in the form of new data.

The business pushing module comprises a customer primary classifying unit, a customer intention analyzing unit and an intelligent business pushing unit; the primary classification unit of the client carries out primary level assessment on the client according to the identity information of the client, and the level of the primary classification unit of the client is divided into primary clients and senior clients; the customer intent analysis unit combines the requirements set by customers to introduce the required business fields to the customers; the intelligent service pushing unit is used for intelligently screening specific service items for the clients according to the service fields of classification and intent analysis of the users, and pushing service information to the clients through priority intelligent sequencing.

The business follow-up module comprises a customer information inquiry unit, a business progress analysis unit and a business completion degree prediction unit; the client information inquiry unit retrieves the detailed identity information of the client by inputting the initial information of the client, confirms the identity of the client according to the retrieval result, acquires an identity identification code and inquires service information corresponding to the client through the identification code; the business progress analysis unit performs visualization processing on the signing progress of the current business according to the approval degree by analyzing the approval degree of the client on the pushing business; and the business completion degree prediction unit analyzes the signing completion possibility of the current business according to the business signing progress analysis result and with the development trend after data visualization.

The client feedback module comprises a client satisfaction analysis unit and a client secondary classification unit; the customer satisfaction analysis unit analyzes feedback data of the customers after signing and expanding the business, and judges the satisfaction degree of the customers on the current business according to analysis results; the client secondary classification unit judges the secondary class of the client through the feedback condition of the client in the whole business service flow; the secondary categories include premium customers and potential customers.

An intelligent customer management method based on artificial intelligence, the method comprising the following steps:

s100, acquiring identity information and enterprise information of a client through a mobile terminal or a manual terminal, setting a period to update and store the client information and the service information, and primarily classifying the client according to the client information;

s200, determining the service field required by the client according to the intention proposed by the client, screening an optimal service set for the client through intelligent analysis, and sequencing service priorities through the matching rate;

s300, analyzing the business signing progress by inquiring customer information, and predicting the possibility of business signing; and analyzing the satisfaction degree of the customer after business signing, and carrying out secondary classification on the customer according to the satisfaction degree and feedback data in the business signing flow.

In the step S100, the mobile terminal or the manual terminal collects identity information and enterprise information of the client, the setting period updates the client information and the service information, and the specific steps of primary classification of the client according to the client information are as follows:

s101, acquiring identity information and enterprise information of a client by adopting a mobile terminal app, off-line business equipment and a manual mode; the information acquisition comprises a customer name, a birth date, an age, a contact way, a company name, a company address and a family address, and the acquired customer information is stored in a database and a unique identity code is generated;

s102, setting a time period T, inquiring client information and service information at a time interval of T, updating the changed client information and service information, and storing the updated data as new data;

s103, performing primary category judgment on the client according to the identity data of the client which is logged in for the first time; if the client is an individual client, inquiring transaction data disclosed by the individual client through a network as a basis, if the transaction value of the client is smaller than a, judging that the current client is a primary individual client, otherwise, judging that the current client is a senior individual client; if the client is an enterprise client, inquiring transaction data disclosed by the enterprise client through a network, if the enterprise transaction limit is smaller than b, judging the current enterprise client as a primary enterprise client, otherwise, judging the current enterprise client as a deep enterprise client, wherein a and b are constants.

In the step S200, the service domain required by the client is determined according to the intention proposed by the client, the optimal service set is screened for the client through intelligent analysis, and the specific steps of service priority ranking through the matching rate are as follows:

s201, collecting M= { M in the service field under the guidance of a system or a person through a mobile terminal or off-line equipment or person ₁ ,M ₂ ,M ₃ ...M _i Selecting a service area M required by a customer _i In the selection of the corresponding service field, the functions to be realized by n clients are input, the keywords of the functions to be realized by the n clients are extracted, and the collaborative filtering algorithm and the cosine similarity algorithm are combined in the service field M _i Middle screening of specific service set N= { N meeting customer requirements ₁ ,N ₂ ,N ₃ ...N _i -a }; wherein i is N ^* ，n∈N ^* ；

S202, dividing each function required by a customer into b sub-functions, wherein the single function capability realized by a single service is thatWherein m is the number of sub-functions in a single function implemented by a single service, m is N ^* ，b∈N ^* The method comprises the steps of carrying out a first treatment on the surface of the The function of the single service implements the total capability p _{Total (S)} ＝k ₁ *p ₁ +k ₂ *p ₂ +k ₃ *p ₃ +...+k _n *p _n Wherein k is a proportion coefficient corresponding to a single function; calculating the capacity degree of the current service for realizing the functions required by the clients according to the ratios of the capacities of different functions realized by the single service and the functions required by the clients occupied by the corresponding functions; by curve f (n) =e ^-n Substituting the position of the function input by the customer into the curve to obtain a set { e } of f (n) ^-1 ,e ^-2 ,e ^-3 ,...,e ^-n Then the duty factor of the corresponding function in the total functions of the client->The order of the positions of the functions input by the clients is sequentially the proportion of the functions in the service required by the clients, and the proportion occupied by the functions in the previous order is large, and the functions are gradually decreased; calculating the duty ratio coefficient by using a mirror image curve of the exponential curve; according to p _{Total (S)} The number of (2) pushes traffic information to the customer from a big to a small order.

In the step S300, the possibility of business signing is predicted by inquiring the customer information and analyzing the business signing progress; the customer satisfaction after business signing is analyzed, and the specific steps of carrying out secondary classification on the customer according to the satisfaction and feedback data in the business signing flow are as follows:

s301, inquiring a unique identity code corresponding to the identity information by utilizing the identity information logged in by the client, and inquiring corresponding service information by the identity code; for the business in personnel contact, collecting the customer contact business to the current day T; the method comprises the steps of calling the times g and the query time t of corresponding days for inquiring service information by a client in an enterprise server in the days; collecting interview times f and interview times h of corresponding days between the contact person and the client; the interviews include online interviews and offline interviews; respectively taking T as an x axis, g as a y axis and T as a z axis to establish three types of customer query service informationA dimensional coordinate system; establishing a three-dimensional coordinate system of client interview service information by taking T as an x axis, taking f as a y axis and taking h as a z axis; two space curves obtained by a three-dimensional coordinate system are respectively a customer query service curve r ₁ And client interview curve r ₂ The method comprises the steps of carrying out a first treatment on the surface of the Mapping points in space to a bottom surface of the coordinate system in the coordinate system to obtain plane coordinates (T, g) and (T, f) at the bottom surface; triangle is formed by using the origin, the mapping point of the bottom surface of the coordinate system and the point in space as vertexes, and the triangle is formed according to the formulaCalculating the new knowledge degree of the customer service; according to the formula->Calculating the newly added degree of engagement of the client interview; by calculating the mapped triangle area on the curve, the understanding degree of the business by the client and the interview degree with sales personnel can be obtained when the corresponding days T are obtained; with T as x-axis, e=u ₁ +U ₁ Constructing a customer business signing development curve for a y axis; point e on curve e at its maximum _max Taking the curve before the point as a sample to carry out mirror image overturning operation; in a mirror image curve +.>T is the maximum day threshold T _max If the current service contacts with the client at time T _{To date} ＞T _max Judging that the client does not sign the current service, and finally confirming the client by a contact person; if T _{To date} ＜T _max Judging that the customer has possibility of signing a service, and normally performing a service signing process; when the curve reaches the maximum value, the mirror image turning operation is adopted, an ideal business signing flow is adopted as a standard, a customer starts to inquire by himself from unfamiliar business, and then contacts with salesperson, after the business is comprehensively known through interviews with salesperson and business data inquiry, the long-time data inquiry and long-time interview consultation of the business are reduced, and finally, a business contract is signed;

S302、the method comprises the steps of soliciting service satisfaction from clients in a service after-sale questionnaire mode, wherein questionnaire content is divided into signing process satisfaction, service development service satisfaction and next intention of collaboration; the questionnaire comprises s pieces of selection questions, and answers are set as 'good', 'medium', 'bad', 'poor'; by the formulaCalculating the duty ratio degree of the answer being 'good', wherein the duty ratio degree is the business after-sale satisfaction degree of the customer; wherein v is the number of questions with answer "good"; if the questionnaire result w is larger than the threshold value L, judging that the user is satisfied with the business service flow, and if the user is a primary user at the moment, classifying the user as a potential user for the second time; if the client is a senior client at this time, the client is classified as a high-quality client.

Compared with the prior art, the invention has the following beneficial effects: the system comprises a client data acquisition module, a service pushing module, a service follow-up module and a client feedback module; the client data acquisition module can realize instant update and redundant storage of the identity information and service information of the client; the service pushing module can carry out optimal matching service pushing according to subjective function requirements of clients; the business follow-up module can correlate the customer with the business and display the progress and possibility of the customer signing the business in real time; the customer feedback module can accurately classify customer groups through the business satisfaction degree of customer feedback; the invention can realize the real-time supervision and guidance of the signing period between the client and the business and the accurate positioning of the client group market through the modules, is beneficial to the promotion of business signing and expanding service for enterprises, and is suitable for the targeted cultivation of high-quality clients and potential clients.

Drawings

The accompanying drawings are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate the invention and together with the embodiments of the invention, serve to explain the invention. In the drawings:

FIG. 1 is a schematic diagram of an artificial intelligence based intelligent customer management system according to the present invention;

FIG. 2 is a schematic diagram of steps of an artificial intelligence based intelligent customer management method of the present invention.

Detailed Description

The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. 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.

Referring to fig. 1-2, the present invention provides the following technical solutions:

an intelligent client management system based on artificial intelligence comprises a client data acquisition module, a service pushing module, a service follow-up module and a client feedback module;

the client data acquisition module acquires personal information or enterprise information of a client through a mobile terminal, updates the client information according to a period, and stores the information after the client information is collected; the business pushing module judges the primary category of the client through the information of the client, and pushes proper business items according to the judging result and the client intention analysis; the service follow-up module determines a target client by inquiring the identity information reserved by the client, inquires corresponding service items of the target client, and predicts the completion degree of the service by analyzing the progress of the service; the customer feedback module acquires feedback according to the completion result of the customer on the business and the service satisfaction degree of the customer, performs secondary division and definition on the current customer according to the feedback, and stores the customer information in a classified manner;

the client data acquisition module is connected with the service pushing module; the business pushing module is connected with the business follow-up module; the business follow-up module is connected with the client feedback module;

the client data acquisition module comprises a client data acquisition unit, a client data updating unit and a client data storage unit; the client data acquisition unit acquires identity data of a client under the authorization of the client through a remote mobile terminal or a manual terminal, wherein the data of the client comprises a client name, a birth date, an age, a contact way, a company name, a company address and a home address; the customer data updating unit is used for periodically inquiring and updating customer identity information and service information; the client data storage unit is used for storing the identity information and the service information of the client.

The data storage unit generates a unique identification code for each piece of customer identity information when storing the customer identity information; after the customer identity information or the service information is updated, the updated information does not cover old data and is stored in the form of new data.

The business pushing module comprises a customer primary classifying unit, a customer intention analyzing unit and an intelligent business pushing unit; the primary classification unit of the client carries out primary level assessment on the client according to the identity information of the client, and the level of the primary classification unit of the client is divided into primary clients and senior clients; the customer intent analysis unit combines the requirements set by customers to introduce the required business fields to the customers; the intelligent service pushing unit is used for intelligently screening specific service items for the clients according to the service fields of classification and intent analysis of the users, and pushing service information to the clients through priority intelligent sequencing.

The business follow-up module comprises a customer information inquiry unit, a business progress analysis unit and a business completion degree prediction unit; the client information inquiry unit retrieves the detailed identity information of the client by inputting the initial information of the client, confirms the identity of the client according to the retrieval result, acquires an identity identification code and inquires service information corresponding to the client through the identification code; the business progress analysis unit performs visualization processing on the signing progress of the current business according to the approval degree by analyzing the approval degree of the client on the pushing business; and the business completion degree prediction unit analyzes the signing completion possibility of the current business according to the business signing progress analysis result and with the development trend after data visualization.

The client feedback module comprises a client satisfaction analysis unit and a client secondary classification unit; the customer satisfaction analysis unit analyzes feedback data of the customers after signing and expanding the business, and judges the satisfaction degree of the customers on the current business according to analysis results; the client secondary classification unit judges the secondary class of the client through the feedback condition of the client in the whole business service flow; the secondary categories include premium customers and potential customers.

An intelligent customer management method based on artificial intelligence, the method comprising the following steps:

s100, acquiring identity information and enterprise information of a client through a mobile terminal or a manual terminal, setting a period to update and store the client information and the service information, and primarily classifying the client according to the client information;

s200, determining the service field required by the client according to the intention proposed by the client, screening an optimal service set for the client through intelligent analysis, and sequencing service priorities through the matching rate;

s300, analyzing the business signing progress by inquiring customer information, and predicting the possibility of business signing; and analyzing the satisfaction degree of the customer after business signing, and carrying out secondary classification on the customer according to the satisfaction degree and feedback data in the business signing flow.

In the step S100, the mobile terminal or the manual terminal collects identity information and enterprise information of the client, the setting period updates the client information and the service information, and the specific steps of primary classification of the client according to the client information are as follows:

s101, acquiring identity information and enterprise information of a client by adopting a mobile terminal app, off-line business equipment and a manual mode; the information acquisition comprises a customer name, a birth date, an age, a contact way, a company name, a company address and a family address, and the acquired customer information is stored in a database and a unique identity code is generated;

s102, setting a time period T, inquiring client information and service information at a time interval of T, updating the changed client information and service information, and storing the updated data as new data;

s103, performing primary category judgment on the client according to the identity data of the client which is logged in for the first time; if the client is an individual client, inquiring transaction data disclosed by the individual client through a network as a basis, if the transaction value of the client is smaller than a, judging that the current client is a primary individual client, otherwise, judging that the current client is a senior individual client; if the client is an enterprise client, inquiring transaction data disclosed by the enterprise client through a network, if the enterprise transaction limit is smaller than b, judging the current enterprise client as a primary enterprise client, otherwise, judging the current enterprise client as a deep enterprise client, wherein a and b are constants.

In the step S200, the service domain required by the client is determined according to the intention proposed by the client, the optimal service set is screened for the client through intelligent analysis, and the specific steps of service priority ranking through the matching rate are as follows:

s201, collecting M= { M in the service field under the guidance of a system or a person through a mobile terminal or off-line equipment or person ₁ ,M ₂ ,M ₃ ...M _i Selecting a service area M required by a customer _i In the selection of the corresponding service field, the functions to be realized by n clients are input, the keywords of the functions to be realized by the n clients are extracted, and the collaborative filtering algorithm and the cosine similarity algorithm are combined in the service field M _i Middle screening of specific service set N= { N meeting customer requirements ₁ ,N ₂ ,N ₃ ...N _i -a }; wherein i is N ^* ，n∈N ^* ；

S202, dividing each function required by a customer into b sub-functions, wherein the single function capability realized by a single service is thatWherein m is the number of sub-functions in a single function implemented by a single service, m is N ^* ，b∈N ^* The method comprises the steps of carrying out a first treatment on the surface of the The function of the single service implements the total capability p _{Total (S)} ＝k ₁ *p ₁ +k ₂ *p ₂ +k ₃ *p ₃ +...+k _n *p _n Wherein k is the corresponding singleThe ratio of the functions; calculating the capacity degree of the current service for realizing the functions required by the clients according to the ratios of the capacities of different functions realized by the single service and the functions required by the clients occupied by the corresponding functions; by curve f (n) =e ^-n Substituting the position of the function input by the customer into the curve to obtain a set { e } of f (n) ^-1 ,e ^-2 ,e ^-3 ,...,e ^-n Then the duty factor of the corresponding function in the total functions of the client->The order of the positions of the functions input by the clients is sequentially the proportion of the functions in the service required by the clients, and the proportion occupied by the functions in the previous order is large, and the functions are gradually decreased; calculating the duty ratio coefficient by using a mirror image curve of the exponential curve; according to p _{Total (S)} The number of (2) pushes traffic information to the customer from a big to a small order.

In the step S300, the possibility of business signing is predicted by inquiring the customer information and analyzing the business signing progress; the customer satisfaction after business signing is analyzed, and the specific steps of carrying out secondary classification on the customer according to the satisfaction and feedback data in the business signing flow are as follows:

s301, inquiring a unique identity code corresponding to the identity information by utilizing the identity information logged in by the client, and inquiring corresponding service information by the identity code; for the business in personnel contact, collecting the customer contact business to the current day T; the method comprises the steps of calling the times g and the query time t of corresponding days for inquiring service information by a client in an enterprise server in the days; collecting interview times f and interview times h of corresponding days between the contact person and the client; the interviews include online interviews and offline interviews; respectively taking T as an x axis, g as a y axis and T as a z axis to establish a three-dimensional coordinate system of customer query service information; establishing a three-dimensional coordinate system of client interview service information by taking T as an x axis, taking f as a y axis and taking h as a z axis; two space curves obtained by a three-dimensional coordinate system are respectively a customer query service curve r ₁ And client interview curve r ₂ The method comprises the steps of carrying out a first treatment on the surface of the Mapping points in space to a bottom surface of the coordinate system in the coordinate system to obtain plane coordinates (T, g) and (T, f) at the bottom surface; to be used forThe origin, the mapping points of the bottom surface of the coordinate system and the points in the space are vertexes to form a triangle, and the triangle is formed according to the formulaCalculating the new knowledge degree of the customer service; according to the formula->Calculating the newly added degree of engagement of the client interview; by calculating the mapped triangle area on the curve, the understanding degree of the business by the client and the interview degree with sales personnel can be obtained when the corresponding days T are obtained; with T as x-axis, e=u ₁ +U ₁ Constructing a customer business signing development curve for a y axis; point e on curve e at its maximum _max Taking the curve before the point as a sample to carry out mirror image overturning operation; in a mirror image curve +.>T is the maximum day threshold T _max If the current service contacts with the client at time T _{To date} ＞T _max Judging that the client does not sign the current service, and finally confirming the client by a contact person; if T _{To date} ＜T _max Judging that the customer has possibility of signing a service, and normally performing a service signing process; when the curve reaches the maximum value, the mirror image turning operation is adopted, an ideal business signing flow is adopted as a standard, a customer starts to inquire by himself from unfamiliar business, and then contacts with salesperson, after the business is comprehensively known through interviews with salesperson and business data inquiry, the long-time data inquiry and long-time interview consultation of the business are reduced, and finally, a business contract is signed;

s302, soliciting service satisfaction from clients in a service after-sale questionnaire mode, wherein the questionnaire content is divided into signing process satisfaction, service development service satisfaction and next intention; the questionnaire comprises s pieces of selection questions, and answers are set as 'good', 'medium', 'bad', 'poor'; by the formulaCalculating the duty ratio degree of the answer being 'good', wherein the duty ratio degree is the business after-sale satisfaction degree of the customer; wherein v is the number of questions with answer "good"; if the questionnaire result w is larger than the threshold value L, judging that the user is satisfied with the business service flow, and if the user is a primary user at the moment, classifying the user as a potential user for the second time; if the client is a senior client at this time, the client is classified as a high-quality client.

In an embodiment:

an existing enterprise device is provided with an intelligent customer management system based on artificial intelligence as a customer business signing and customer management system; the existing client accesses an enterprise service interface through a mobile terminal and queries the service through an enterprise management system; firstly, a client management system solicits identity information and company information of a client from the client, after the client is authorized to input, a system background judges that the client is the enterprise query service of the client through public information of the client in a network, and the specific value of the historical transaction limit of the enterprise where the client is located is 2000 ten thousand;

after the customer inputs the identity information, a service selection query interface is opened to the customer, the customer selects the required service field, and after the customer selects the service field, the customer is solicited that 3 functional contents to be realized by the required service are { function 1, function 2, function 3}; the system screens in the corresponding service field according to the function limit input by the client to obtain the specific service item result which meets the client requirement as { service 1, service 2, service 3};

the system divides functions required by clients into sub-functions, and each function is divided into 5 sub-functions; calculating the function realization capability of a single service according to the specific realization condition of the function of the screened specific service; wherein, service 1 can realize 4 sub-functions in function 1, 3 sub-functions in function 2, 1 sub-function in function 3; service 2 can realize 2 sub-functions in function 1, 2 sub-functions in function 23 sub-functions in function 3; service 3 can realize 5 sub-functions in function 1, 2 sub-functions in function 2, 2 sub-functions in function 3; according to the formulaThe value of the single service to realize the single function can be calculated, wherein the capability value of service 1 is +.>And->The capability values of service 2 are +.>And->The capability values of service 3 are 1, < >, respectively>And->Determining the occupation proportion of the function in the service according to the sequential position of the client input function by the curve f (n) =e ^-n Substituting the position of the function input by the customer into the curve to obtain a set { e } of f (n) ^-1 ,e ^-2 ,e ^-3 -a }; by the formula->Can calculate the proportion coefficient k corresponding to the function 1 ₁ =0.66, the duty factor k corresponding to function 2 ₂ =0.24, the duty factor k corresponding to function 3 ₃ =0.1; then according to formula p _{Total (S)} ＝k ₁ *p ₁ +k ₂ *p ₂ +k ₃ *p ₃ +...+k _n *p _n Calculate total capability of service 1 to be 0.692, total capability of service 2 to be 0.42, total of service 3Capacity of 0.796; sorting the services according to the total capacity into { service 3, service 1, service 2} and pushing service information to the client;

under intelligent pushing, a client selects a service 3, and the number of considered days after the client selects the service 3 is collected to be 3 days; collecting service information of 5 times of clients on the first day within 3 days, wherein the total access time is 3 hours, the interviews of clients and sales personnel are 0, and the total interview time is 0; the next day the customer accesses the business information for 3 times, the total access time for 1h, the number of interviews of the customer and sales personnel for 3 times, and the total interview time for 4h; the number of times of the client accessing the service information is 1 in the third day, the total access time is 1h, the number of interviews of the client and sales personnel is 2, and the total interview time is 2h; by collecting information and establishing a space coordinate system, a query service curve r of a client can be obtained ₁ And client interview curve r ₂ The method comprises the steps of carrying out a first treatment on the surface of the A point is obtained by mapping the space coordinates on the bottom surface, and the origin, the mapped point and the space point can form a triangle according to the formulaThe new knowledge degree of the business of the customer every day is calculated as follows: 7.65,1.8,1.6; according to the formula->The newly added degree of engagement for the client interview is calculated as: 0,7.2,3.6; then the number of days passed and e=u ₁ +U ₁ Constructing a customer business signing development curve; take maximum value e on e _max =9, the curve before this point is taken as a sample to perform the mirror-image flipping operation; in a mirror image curve +.>T is the maximum day threshold T _max Because the current t=3 is smaller than the maximum threshold value, judging that the current customer has possibility of signing a service, and normally performing the service signing flow;

after the business signing is unfolded, questionnaires are used for soliciting satisfaction of the service from the clients, the questionnaires comprise 30 option questions, and the answer situation is filled out according to the clientsWherein the number of answers "good" is 25, according to the formulaCalculating the duty ratio degree of 'good' answer to be 0.83, wherein the duty ratio degree is the business after-sale satisfaction degree of the customer; since the satisfaction degree of the current customer is 0.83 and is greater than the threshold value set by the system by 0.8, and the current user is rated as the primary enterprise user for the first time, the current user is rated as the potential enterprise customer for the second time.

It is noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.

Finally, it should be noted that: the foregoing description is only a preferred embodiment of the present invention, and the present invention is not limited thereto, but it is to be understood that modifications and equivalents of some of the technical features described in the foregoing embodiments may be made by those skilled in the art, although the present invention has been described in detail with reference to the foregoing embodiments. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims (10)

1. An intelligent customer management system based on artificial intelligence, which is characterized in that: the intelligent customer management system based on artificial intelligence comprises a customer data acquisition module, a service pushing module, a service follow-up module and a customer feedback module;

the client data acquisition module acquires personal information or enterprise information of a client through a mobile terminal, updates the client information according to a period, and stores the information after the client information is collected; the business pushing module judges the primary category of the client through the information of the client, and pushes proper business items according to the judging result and the client intention analysis; the service follow-up module determines a target client by inquiring the identity information reserved by the client, inquires corresponding service items of the target client, and predicts the completion degree of the service by analyzing the progress of the service; the customer feedback module acquires feedback according to the completion result of the customer on the business and the service satisfaction degree of the customer, performs secondary division and definition on the current customer according to the feedback, and stores the customer information in a classified manner;

the client data acquisition module is connected with the service pushing module; the business pushing module is connected with the business follow-up module; the business follow-up module is connected with the customer feedback module.

2. An artificial intelligence based intelligent customer management system according to claim 1 wherein: the client data acquisition module comprises a client data acquisition unit, a client data updating unit and a client data storage unit; the client data acquisition unit acquires identity data of a client under the authorization of the client through a remote mobile terminal or a manual terminal, wherein the data of the client comprises a client name, a birth date, an age, a contact way, a company name, a company address and a home address; the customer data updating unit is used for periodically inquiring and updating customer identity information and service information; the client data storage unit is used for storing the identity information and the service information of the client.

3. An artificial intelligence based intelligent customer management system according to claim 2 wherein: the data storage unit generates a unique identification code for each piece of customer identity information when storing the customer identity information; after the customer identity information or the service information is updated, the updated information does not cover old data and is stored in the form of new data.

4. An artificial intelligence based intelligent customer management system according to claim 3 wherein: the business pushing module comprises a customer primary classifying unit, a customer intention analyzing unit and an intelligent business pushing unit; the primary classification unit of the client carries out primary level assessment on the client according to the identity information of the client, and the level of the primary classification unit of the client is divided into primary clients and senior clients; the customer intent analysis unit combines the requirements set by customers to introduce the required business fields to the customers; the intelligent service pushing unit is used for intelligently screening specific service items for the clients according to the service fields of classification and intent analysis of the users, and pushing service information to the clients through priority intelligent sequencing.

5. An artificial intelligence based intelligent customer management system according to claim 4 wherein: the business follow-up module comprises a customer information inquiry unit, a business progress analysis unit and a business completion degree prediction unit; the client information inquiry unit retrieves the detailed identity information of the client by inputting the initial information of the client, confirms the identity of the client according to the retrieval result, acquires an identity identification code and inquires service information corresponding to the client through the identification code; the business progress analysis unit performs visualization processing on the signing progress of the current business according to the approval degree by analyzing the approval degree of the client on the pushing business; and the business completion degree prediction unit analyzes the signing completion possibility of the current business according to the business signing progress analysis result and with the development trend after data visualization.

6. An artificial intelligence based intelligent customer management system according to claim 5 wherein: the client feedback module comprises a client satisfaction analysis unit and a client secondary classification unit; the customer satisfaction analysis unit analyzes feedback data of the customers after signing and expanding the business, and judges the satisfaction degree of the customers on the current business according to analysis results; the client secondary classification unit judges the secondary class of the client through the feedback condition of the client in the whole business service flow; the secondary categories include premium customers and potential customers.

7. An intelligent customer management method based on artificial intelligence is characterized in that: the method comprises the following steps:

s100, acquiring identity information and enterprise information of a client through a mobile terminal or a manual terminal, setting a period to update and store the client information and the service information, and primarily classifying the client according to the client information;

s200, determining the service field required by the client according to the intention proposed by the client, screening an optimal service set for the client through intelligent analysis, and sequencing service priorities through the matching rate;

s300, analyzing the business signing progress by inquiring customer information, and predicting the possibility of business signing; and analyzing the satisfaction degree of the customer after business signing, and carrying out secondary classification on the customer according to the satisfaction degree and feedback data in the business signing flow.

8. The intelligent client management method based on artificial intelligence according to claim 7, wherein: in the step S100, the mobile terminal or the manual terminal collects identity information and enterprise information of the client, the setting period updates the client information and the service information, and the specific steps of primary classification of the client according to the client information are as follows:

s101, acquiring identity information and enterprise information of a client by adopting a mobile terminal app, off-line business equipment and a manual mode; the information acquisition comprises a customer name, a birth date, an age, a contact way, a company name, a company address and a family address, and the acquired customer information is stored in a database and a unique identity code is generated;

s102, setting a time period T, inquiring client information and service information at a time interval of T, updating the changed client information and service information, and storing the updated data as new data;

s103, performing primary category judgment on the client according to the identity data of the client which is logged in for the first time; if the client is an individual client, inquiring transaction data disclosed by the individual client through a network as a basis, if the transaction value of the client is smaller than a, judging that the current client is a primary individual client, otherwise, judging that the current client is a senior individual client; if the client is an enterprise client, inquiring transaction data disclosed by the enterprise client through a network, if the enterprise transaction limit is smaller than b, judging the current enterprise client as a primary enterprise client, otherwise, judging the current enterprise client as a deep enterprise client, wherein a and b are constants.

9. The intelligent client management method based on artificial intelligence according to claim 8, wherein: in the step S200, the service domain required by the client is determined according to the intention proposed by the client, the optimal service set is screened for the client through intelligent analysis, and the specific steps of service priority ranking through the matching rate are as follows:

s201, collecting M= { M in the service field under the guidance of a system or a person through a mobile terminal or off-line equipment or person ₁ ,M ₂ ,M ₃ ...M _i Selecting a service area M required by a customer _i In the selection of the corresponding service field, the functions to be realized by n clients are input, the keywords of the functions to be realized by the n clients are extracted, and the collaborative filtering algorithm and the cosine similarity algorithm are combined in the service field M _i Middle screening of specific service set N= { N meeting customer requirements ₁ ,N ₂ ,N ₃ ...N _i -a }; wherein i is N ^* ，n∈N ^* ；

S202, dividing each function required by a customer into b sub-functions, wherein the single function capability realized by a single service is thatWherein m is the number of sub-functions in a single function implemented by a single service, m is N ^* ，b∈N ^* The method comprises the steps of carrying out a first treatment on the surface of the The function of the single service implements the total capability p _{Total (S)} ＝k ₁ *p ₁ +k ₂ *p ₂ +k ₃ *p ₃ +...+k _n *p _n Wherein k is a proportion coefficient corresponding to a single function; using curve f (n) =e ^-n Substituting the position of the function input by the customer into the curve to obtain a set { e } of f (n) ^-1 ,e ^-2 ,e ^-3 ,...,e ^-n Then the duty factor of the corresponding function in the total functions of the client->According to p _{Total (S)} The number of (2) pushes traffic information to the customer from a big to a small order.

10. The intelligent client management method based on artificial intelligence according to claim 9, wherein: in the step S300, the possibility of business signing is predicted by inquiring the customer information and analyzing the business signing progress; the customer satisfaction after business signing is analyzed, and the specific steps of carrying out secondary classification on the customer according to the satisfaction and feedback data in the business signing flow are as follows:

s301, inquiring a unique identity code corresponding to the identity information by utilizing the identity information logged in by the client, and inquiring corresponding service information by the identity code; for the business in personnel contact, collecting the customer contact business to the current day T; the method comprises the steps of calling the times g and the query time t of corresponding days for inquiring service information by a client in an enterprise server in the days; collecting interview times f and interview times h of corresponding days between the contact person and the client; the interviews include online interviews and offline interviews; respectively taking T as an x axis, g as a y axis and T as a z axis to establish a three-dimensional coordinate system of customer query service information; establishing a three-dimensional coordinate system of client interview service information by taking T as an x axis, taking f as a y axis and taking h as a z axis; two space curves obtained by a three-dimensional coordinate system are respectively a customer query service curve r ₁ And client interview curve r ₂ The method comprises the steps of carrying out a first treatment on the surface of the Mapping points in space to a bottom surface of the coordinate system in the coordinate system to obtain plane coordinates (T, g) and (T, f) at the bottom surface; triangle is formed by using the origin, the mapping point of the bottom surface of the coordinate system and the point in space as vertexes, and the triangle is formed according to the formulaCalculating the new knowledge degree of the customer service; according to the formula->Calculating the newly added degree of engagement of the client interview; with T as x-axis, e=u ₁ +U ₁ Constructing a customer business signing development curve for a y axis; point e on curve e at its maximum _max Taking the curve before the point as a sample to carry out mirror image overturning operation; in a mirror image curve +.>T is the maximum day threshold T _max If the current service contacts with the client at time T _{To date} ＞T _max Judging that the client does not sign the current service, and finally confirming the client by a contact person; if T _{To date} ＜T _max Judging that the customer has possibility of signing a service, and normally performing a service signing process;

s302, soliciting service satisfaction from clients in a service after-sale questionnaire mode, wherein the questionnaire content is divided into signing process satisfaction, service development service satisfaction and next intention; the questionnaire comprises s pieces of selection questions, and answers are set as 'good', 'medium', 'bad', 'poor'; by the formulaCalculating the duty ratio degree of the answer being 'good', wherein the duty ratio degree is the business after-sale satisfaction degree of the customer; wherein v is the number of questions with answer "good"; if the questionnaire result w is larger than the threshold value L, judging that the user is satisfied with the business service flow, and if the user is a primary user at the moment, classifying the user as a potential user for the second time; if the client is a senior client at this time, the client is classified as a high-quality client.