CN112163887A - Electric sales system, electric sales list management method, device, equipment and storage medium - Google Patents
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Abstract
The invention discloses an electric sales system, an electric sales list management method, an electric sales list management device, electric sales list management equipment and a storage medium. The method comprises the following steps: acquiring basic information data of N target clients; the basic information data includes at least one of: gender, occupation, age, related product purchase; predicting the characteristics of each target client by using a trained client characteristic prediction model according to the basic information data of the N target clients to obtain the predicted characteristics of the target clients; acquiring sales capability characteristics of M agents; and distributing the N target clients to the M agents according to the prediction characteristics of the target clients and the sales capability characteristics of the agents and preset rules. According to the scheme, the characteristics of the target customers are predicted and matched with the sales capability characteristics of the seat staff, and each target customer is distributed to the corresponding seat staff according to the matching degree. Therefore, the client data can be objectively distributed, and the distribution process is more efficient.
Description
Technical Field
The invention relates to the field of data processing, in particular to an electric sales system, an electric sales list management method, an electric sales list management device, electric sales list management equipment and a storage medium.
Background
Sales of products may be involved in many industries, such as the sale of credit or loan transactions by financial institutions, the renting or selling of houses in the real estate industry, the sale of training courses in the educational training industry, and the like. For the sales scenes with large number of target customer groups of various types, among a plurality of sales means, telephone sales is one of relatively efficient modes.
The existing telephone sales typically collects customer data through channels such as offline promotion and online advertisement, and stores the customer data in a customer data management system. The customer data management system can complement and perfect the collected customer data and then send the customer data to the power distribution system. And the person in charge of the telepin seat establishes a telepin task and sends the telepin task to the telepin seat to carry out final call dialing.
In the process, the person in charge of the electricity sales seat creates and distributes the electricity sales task based on own experience. This approach is inefficient in distributing the customer material.
Disclosure of Invention
The invention mainly aims to provide an electric sales system, an electric sales list management method, an electric sales list management device, electric sales list management equipment and a storage medium, and aims to improve the distribution efficiency of customer data.
In order to achieve the above object, the present invention provides an electric sales list management method, including:
acquiring basic information data of N target clients; the basic information data includes at least one of: gender, occupation, age, related product purchase;
predicting the characteristics of each target client by using a trained client characteristic prediction model according to the basic information data of the N target clients to obtain the predicted characteristics of the target clients;
acquiring sales capability characteristics of M agents;
and distributing the N target customers to the M agents according to the prediction characteristics of the target customers and the sales capability characteristics of the agents and preset rules.
In one embodiment, the target customer's predictive features include: a conversion success rate for indicating a prediction probability of successful conversion of the target customer to a real customer;
the sales capability features of the agent include: a customer conversion rate indicating a prediction probability that the agent successfully converts the target customer to a real customer;
the distributing the data of the N target clients to the M agents according to the prediction characteristics of the target clients and the sales capability characteristics of the agents and preset rules comprises the following steps:
and distributing the data of the target customer with the converted power higher than the first preset value to an agent with the customer conversion rate higher than the second preset value.
In one embodiment, the method further comprises:
receiving dialing feedback information input after an operator dials a contact phone of a target customer; the dialing feedback information is used for indicating whether the target customer is converted into a real customer;
and updating the customer characteristic prediction model according to the dialing feedback information.
In one embodiment, the method further comprises:
acquiring historical information data of the target client from a data warehouse;
and performing information supplementation on the basic information data according to the historical information data.
In one embodiment, the method further comprises:
collecting a plurality of historical target customer conversions into power and sales results;
and performing predictive effect analysis on the customer characteristic prediction model according to the converted power and sales results of a plurality of historical target customers.
In one embodiment, the method further comprises:
updating the corresponding sales capability characteristics of the seat staff according to the basic information data of the target customer and the dialing feedback information;
and sending the updated sales capability characteristics of the seat staff to the electricity marketing system.
The present invention also provides an electrical pinning system, comprising:
the client data management system is used for storing basic information data of a target client; the basic information data includes at least one of: gender, occupation, age, income, consumption level, purchase of related products, contact phone call;
the electric sales system is used for storing the sales capability characteristics of the seat staff; the sales capability features of the agent include: customer conversion rate;
the data warehouse is used for storing historical information data of the clients;
an electric sales list management system for performing the method as described above.
The invention also provides an electric sales list management device, which comprises:
the acquisition module is used for acquiring basic information data of N target clients; the basic information data includes at least one of: gender, occupation, age, related product purchase;
the characteristic prediction module is used for predicting the characteristics of each target client by utilizing a trained client characteristic prediction model according to the basic information data of the N target clients to obtain the predicted characteristics of the target clients;
the acquisition module is also used for acquiring the sales capability characteristics of the M agents;
and the distribution module is used for distributing the N target customers to the M agents according to the prediction characteristics of the target customers and the sales capability characteristics of the agents and preset rules.
The present invention also provides an electric sales list management apparatus, including: a memory, a processor, and an electrical blacklist management program stored on the memory and executable on the processor, the electrical blacklist management program, when executed by the processor, implementing the steps of the electrical blacklist management method as described above.
The present invention also provides a computer readable storage medium having stored thereon an electric blacklist management program, which when executed by a processor, implements the steps of the electric blacklist management method as described above.
The invention provides an electric sales system, an electric sales list management method, an electric sales list management device, electric sales list management equipment and a storage medium. The method comprises the following steps: acquiring basic information data of N target clients; the basic information data includes at least one of: gender, occupation, age, related product purchase; predicting the characteristics of each target client by using a trained client characteristic prediction model according to the basic information data of the N target clients to obtain the predicted characteristics of the target clients; acquiring sales capability characteristics of M agents; and distributing the N target customers to the M agents according to the prediction characteristics of the target customers and the sales capability characteristics of the agents and preset rules. According to the scheme, the characteristics of the target customers are predicted and matched with the sales capability characteristics of the seat staff, and each target customer is distributed to the corresponding seat staff according to the matching degree. Thus, the client material can be objectively distributed. Compared with the manual distribution mode in the prior art, the method can analyze the characteristics of each client, so that the distribution process efficiency is higher, the matching degree with the seat staff is higher, and the probability of converting the target client into the real client is also improved.
Drawings
Fig. 1 is a schematic view of an application scenario provided by the present invention;
fig. 2 is a flowchart of a method for managing an electricity sale list according to an embodiment of the present invention;
fig. 3 is a flowchart of another method for managing an electric sales list according to an embodiment of the present invention;
FIG. 4 is a schematic structural diagram of an electrical pinning system according to an embodiment of the present invention;
fig. 5 is a schematic structural diagram of an electric sales list management apparatus according to an embodiment of the present invention;
fig. 6 is a schematic structural diagram of an electric sales list management apparatus according to an embodiment of the present invention.
The implementation, functional features and advantages of the objects of the present invention will be further explained with reference to the accompanying drawings.
Detailed Description
Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.
Telephone sales, called e-selling for short, are generally recommended to target customers by agents through telephone. The active selling mode can cover a large number of client groups and is not limited by space and time, so that the access efficiency to the clients is relatively high. Through the introduction and recommendation of the agent, the target customer is successfully converted into a real customer if the target customer purchases the product.
Whether a customer will purchase a product may be influenced by his or her needs, knowledge and evaluation of the product, and even marketing strategies. The nature of the agents is sales force, each agent has different sales styles and sales capabilities, and the conversion rate of each agent for different types of customers may be different.
In the prior art, the supervisor of the electricity pin agent generally performs rough classification on the collected information of the target customer based on own experience, and then issues the information to the agent.
Because the classification is based on the experience of the supervisor, the classification is subjective and the classification result may not be ideal. In addition, the way of sending tasks is managed, which needs to spend a certain time to analyze and classify, resulting in a certain time delay for sending client data, and it is difficult to reach the client at the first time. The classification mode refers to a single customer characteristic dimension, the classification effect is poor, and the list is difficult to issue to achieve the fine granularity of a single customer.
Based on the above, the invention provides an electric marketing system, an electric marketing list management method, an electric marketing list management device and a storage medium, which are used for analyzing customer characteristics based on customer information and issuing the customer characteristics to a seat person matched with the characteristics through constructing and training a model. The method aims to realize objective distribution of sales tasks and improve the distribution efficiency of customer data.
Fig. 1 is a schematic diagram of an application scenario provided in the present invention. The method of the invention can be applied to the electricity marketing process of various products, such as: the sale of deposit or loan transactions by financial institutions, the renting or sale of houses in the real estate industry, the sale of training courses in the educational training industry, and the like. As shown in fig. 1, the telemarketing of the deposit transaction of the financial institution is taken as an example for explanation. The customer data management system stores basic information of a large number of target customers, and the electric sales list management system is provided with a characteristic prediction model which can predict customer characteristics according to the customer basic information. The sales capability characteristics of the seat staff are stored in the electric sales system. The electric sales list management system can specifically allocate each target client to the corresponding seat member according to the prediction characteristics of the target client and the sales capability characteristics of the seat members. Each system may be mounted in a terminal having computing and storage capabilities, such as a computer and a server. Reference may be made to the following examples for specific implementations of the invention.
Fig. 2 is a flowchart of a method for managing an electric sales list according to an embodiment of the present invention. As shown in fig. 2, the method for managing an electricity affiliation list according to this embodiment may include:
s201, acquiring basic information data of N target clients.
Wherein N is a non-zero natural number.
Specifically, the basic information data of the target client can be acquired from the client material management system.
Basic information data for a target customer may include, but is not limited to, gender, occupation, age, income, consumption level, related product purchases, contact phone calls, customer channels, and the like.
In some embodiments, the basic information data of the target customer may not be complete, and some data may be missing. In this case, information such as the name of the client may be used as a key to associate other data to complement the missing information.
For example, if the customer channel of the third customer shows that the third customer is a historical customer of the company, but the data of the purchase condition of the related product is missing, the third customer can be associated with the data warehouse of the company to complete the historical purchase condition of the third customer.
The data warehouse is a tool for data management, wherein the stored data generally comprises detailed data of a company.
S202, predicting the characteristics of each target client by using the trained client characteristic prediction model according to the basic information data of the N target clients to obtain the predicted characteristics of the target clients.
The client characteristic prediction model can adopt a neural network model or a deep learning model and the like. The present invention is not limited in its type or structure.
The data for training the customer feature prediction model can comprise basic information data and conversion results of historical customers of the same product or similar products. The historical client refers to a target client for which product telemarketing is performed, and the conversion result refers to whether the historical client is converted into a real client. After training with the training data, the model may have the ability to predict target customer characteristics.
S203, obtaining the sales capability characteristics of the M agents.
Wherein M is a non-zero natural number.
Sales capability features refer to features that may embody sales capabilities of an agent. Specifically, the sales capability characteristics of the seat staff can be obtained from the electric marketing system.
In one embodiment, historical sales data of products by each agent, for example, basic information data of dialed target customers, call duration with each target customer, conversion results for each target customer, overall conversion rate and the like when the agent a sells the product B, are stored in the electricity marketing system. Meanwhile, the electricity marketing system is provided with a member characteristic prediction model, so that the sales capability characteristics of each member can be analyzed and updated.
In another embodiment, sales capability features of the individual agents are stored directly in the telemarketing system. The sales capability features of the seat staff can be obtained by analyzing a seat staff feature prediction model in the electricity sales system, can also be obtained by analyzing a seat staff feature prediction model in the electricity sales list management system, or can be obtained by analyzing a seat staff feature prediction model in other special systems.
And S204, distributing the N target customers to the M agents according to the prediction characteristics of the target customers and the sales capability characteristics of the agents and preset rules.
After the prediction characteristics of the target customer and the sales capability characteristics of the seat staff are determined, the target customer can be distributed according to the matching of the characteristics.
The method for managing the electric sales list provided by the embodiment comprises the following steps: acquiring basic information data of N target clients; the basic information data includes at least one of: gender, occupation, age, related product purchase; predicting the characteristics of each target client by using a trained client characteristic prediction model according to the basic information data of the N target clients to obtain the predicted characteristics of the target clients; acquiring sales capability characteristics of M agents; and distributing the N target clients to the M agents according to the prediction characteristics of the target clients and the sales capability characteristics of the agents and preset rules. And each target client is distributed to the corresponding agent according to the matching degree by predicting the characteristics of the target client and matching the characteristics with the sales capability characteristics of the agent. Thus, the client material can be objectively distributed. Compared with the manual distribution mode in the prior art, the method can analyze the characteristics of each client, so that the distribution process efficiency is higher, the matching degree with the seat staff is higher, and the probability of converting the target client into the real client is also improved.
In one embodiment, the target customer's predictive features include: the conversion success rate is used for indicating the prediction probability of successfully converting the target customer into the real customer; sales capability features of the agent include: a customer conversion rate for indicating a prediction probability that an agent successfully converts a target customer to a real customer; distributing the data of N target clients to M agents according to the prediction characteristics of the target clients and the sales capability characteristics of the agents and preset rules, wherein the method comprises the following steps: and distributing the data of the target customer with the converted power higher than the first preset value to an agent with the customer conversion rate higher than the second preset value.
This is just one possible implementation, and how to match the target customer and the agent may be implemented in other ways. For example, the target customer in area a is assigned to an agent with a higher conversion rate for the target customer in area a.
It should be noted that, the present invention aims to improve objectivity and efficiency of target customer allocation by using a technical means of "automation of matching between target customer and agent", where what dimension the target customer and agent implement matching may be affected by factors such as product sales and customer groups, and specific analysis may be performed according to actual data analysis results, which is not limited in the present application.
In one embodiment, the method further includes: receiving dialing feedback information input after an operator dials a contact phone of a target customer; dialing feedback information for indicating whether the target client is converted into a real client or not; and updating the customer characteristic prediction model according to the dialing feedback information.
After the target client is allocated to the seat, the dialing state of the seat can be detected, and after the call is detected to be disconnected, a form filled in by feedback information can be popped up on a display interface for the seat to input the dialing feedback information. Specifically, the dialing feedback information may include intention information of the customer, conversion results, other valid information, and the like.
In addition, the data of the next target client can be displayed for the agent to dial after the agent fills in the feedback information, so that the effective feedback information can be collected.
In another implementation, the call process between the seat and the target customer can be recorded. And processing the recording data, extracting effective information in the recording data, and finishing automatic recording of dialing feedback information in real time.
The above-described process may be performed by the electric sales list management system, by the electric sales system, or by another dedicated system.
The updating the customer characteristic prediction model according to the dialing feedback information may specifically include: updating training sample data according to basic information data and dialing feedback information of the target client; and training the client characteristic prediction model according to the updated training sample data.
The dialed basic information data and the dialed feedback information of the target client are used as training sample data, and the prediction accuracy of the model is further improved.
It will be appreciated that the target customer that has been dialed is the historical target customer. According to the real sales results of the historical target customers, the prediction effect of the model can be analyzed.
Specifically, the conversion into power and sales results of a plurality of historical target customers may be collected; and performing prediction effect analysis on the customer characteristic prediction model according to the converted power and sales results of the plurality of historical target customers.
The conversion success rate is the prediction probability of the model for successfully converting the target customer into the real customer, and the sales result represents the real probability of successfully converting the target customer into the real customer. By comparing the two, the prediction effect of the model can be roughly judged.
Further, the prediction effects of the new and old models are analyzed before and after the model update, and the update effect can be estimated approximately.
In a specific embodiment, the method further includes the following steps of analyzing, by using an agent feature prediction model in the electricity sales list management system, to obtain the sales capability features of the agent: updating the sales capability characteristics of corresponding seat staff according to the basic information data of the target customer and the dialing feedback information; and sending the updated sales capability characteristics of the seat staff to the electricity marketing system.
The sales capability feature of the seat person is obtained based on analysis of a seat person feature prediction model in the electricity marketing system, and in a specific embodiment, the method may further include: and sending the basic information data and the dialing feedback information of the target customer to the electric sales system so that the electric sales system updates the sales capability characteristics of the corresponding seat staff.
After the sales capability characteristics of the seat staff are updated, subsequent distribution to the target customers can be guided, the distribution efficiency is further improved, and the conversion rate of the target customers is improved to a certain extent.
Fig. 3 is a flowchart of another method for managing an electric sale list according to an embodiment of the present invention. As shown in fig. 3, a specific implementation is shown.
And obtaining training data of the customer characteristic prediction model by pulling the latest modeling data, carrying out model training, and then putting the trained model on line. And realizing management operation of version updating of the model through AI business control and management. Thus completing one training and online period of the model.
When the target client needs to be distributed, the client management system pushes the list of the target client to the electric sales list management system. Meanwhile, the electric sales system synchronizes the information of the seat staff to the electric sales list management system. And then, through AI service control and management, pulling the model on the line, processing and generating a result list. The result list already contains the predicted characteristics of the target customer obtained by the analysis of the customer characteristic prediction model. And then allocating an agent to each target client in the list, and pushing the list to the electric pin system according to an allocation result so as to enable the agent to dial. After the dialing is finished, the seat personnel carry out the feedback of the dialing performance. The feedback data is used for performance analysis and display on one hand, and is added to a training sample set on the other hand, and is used for a new round of model training and updating.
This embodiment is one implementation of the present invention shown for explaining the implementation process in detail, and the scheme is not limited thereto.
Fig. 4 is a schematic structural diagram of an electrical pinning system according to an embodiment of the present invention. As shown in fig. 4, the electric pinning system 400 provided by the present embodiment may include: customer data management system 401, electricity sales system 402, data warehouse 403, and electricity sales list management system 404.
A client data management system 401 for storing basic information data of a target client; the basic information data includes at least one of: gender, occupation, age, income, consumption level, purchase of related products, contact phone call;
an e-selling system 402 for storing sales capability features of the agent; sales capability features of the agent include: customer conversion rate;
a data warehouse 403 for storing historical information data of the client;
an electrical pin list management system 404 for performing the method as in the above embodiments.
However, the present invention is not limited thereto, and each system may be mounted on a separate server or mounted on the same server.
In a specific embodiment, the electric pin list management system 404 may be further divided into three sub-modules, including: the intelligent list interaction sub-module, the data modeling sub-module and the list management sub-module.
The intelligent list interaction submodule is responsible for interacting with the customer data management system and the electric sales system and receiving data of the customer data management system and the electric sales system.
And the data modeling submodule is responsible for acquiring a data warehouse to complement the list characteristics, training a model and generating the model. And receiving a characteristic prediction request from the intelligent list interaction module, and performing characteristic prediction on the target client.
And the list management submodule is responsible for modeling state management, model effect analysis and dialing feedback information display.
The functions of the above sub-modules can be realized by a server. Specifically, data interaction with a client data management system can be realized by using one server a, data interaction with a power distribution system can be realized by using another server B, management of a modeling turntable and display of dialing feedback information can be realized by using another server C, AI data modeling can be realized by using another server D, and a feature prediction function of an AI model can be realized by using another server E. The implementation manner herein is merely an example, and the number of servers and the specific functions implemented by the servers may be adjusted according to actual requirements.
Each system in this embodiment may cooperate with the method for managing an electricity sales list in the foregoing embodiments, and specific implementation manners and technical effects thereof may refer to the foregoing embodiments, which are not described herein again.
Fig. 5 is a schematic structural diagram of an electric sales list management apparatus according to an embodiment of the present invention. As shown in the figure, the electric outlets list management apparatus 500 provided in this embodiment may include: an acquisition module 501, a feature prediction module 502, and an assignment module 503.
An obtaining module 501, configured to obtain basic information data of N target clients; the basic information data includes at least one of: gender, occupation, age, and related product purchase.
The feature prediction module 502 is configured to predict features of each target customer according to the basic information data of the N target customers by using a trained customer feature prediction model, so as to obtain predicted features of the target customers.
The obtaining module 501 is further configured to obtain sales capability features of the M agents.
And the allocating module 503 is configured to allocate the N target clients to the M agents according to the predicted characteristics of the target clients and the sales capability characteristics of the agents and according to a preset rule.
In one embodiment, the target customer's predictive features include: the conversion success rate is used for indicating the prediction probability of successfully converting the target customer into the real customer;
sales capability features of the agent include: a customer conversion rate for indicating a prediction probability that an agent successfully converts a target customer to a real customer;
the allocating module 503 is specifically configured to, when allocating the data of the N target clients to the M agents according to the predicted characteristics of the target clients and the sales capability characteristics of the agents and according to the preset rules: and distributing the data of the target customer with the converted power higher than the first preset value to an agent with the customer conversion rate higher than the second preset value.
In one embodiment, the apparatus further comprises: a receiving module 504, configured to receive dialing feedback information input after the operator dials a contact phone of the target customer; dialing feedback information is used to indicate whether the target customer is transformed into a real customer. And an updating module 505, configured to update the customer characteristic prediction model according to the dialing feedback information.
In a specific embodiment, the obtaining module 501 is further configured to: historical information data of the target client is obtained from the data warehouse. The apparatus further comprises: and a supplementing module 506, configured to perform information supplementing on the basic information data according to the historical information data.
In one embodiment, the apparatus further comprises: a collecting module 507 for collecting the converted power and sales results of the plurality of historical target customers. And the analysis module 508 is used for performing prediction effect analysis on the customer characteristic prediction model according to the converted power and sales results of the plurality of historical target customers.
In one embodiment, the update module 505 is further configured to: and updating the sales capability characteristics of the corresponding seat staff according to the basic information data and the dialing feedback information of the target client. The device still includes: a sending module 509, configured to send the updated sales capability characteristics of the seat staff to the telemarketing system.
The apparatus of this embodiment may implement the method for managing an electricity sale list in the foregoing embodiment, and specific implementation manners and technical effects thereof may refer to the foregoing embodiment, which is not described herein again.
Fig. 6 is a schematic structural diagram of an electric sales list management apparatus according to an embodiment of the present invention. As shown in the figure, the electric outlets list management apparatus 600 provided in this embodiment may include: a memory 601, a processor 602, and an electrical pin list management program stored on the memory and executable on the processor, the electrical pin list management program implementing the steps of the electrical pin list management method as described above when executed by the processor 602.
Optionally, the electric pin list management apparatus 600 may further include a display 603.
The above-described respective devices of the electrical pin list management apparatus 600 may be connected by a bus.
The memory 601 may be a separate memory unit or a memory unit integrated into the processor 602. The number of processors 602 is one or more.
In the above-mentioned implementation of the electrical pin list management apparatus 600, the memory and the processor are directly or indirectly electrically connected to each other to realize data transmission or interaction, that is, the memory and the processor may be connected through an interface or may be integrated together. For example, the components may be electrically connected to each other via one or more communication buses or signal lines, such as a bus. The Memory may be, but is not limited to, a Random Access Memory (RAM), a Read Only Memory (ROM), a Programmable Read-Only Memory (PROM), an Erasable Read-Only Memory (EPROM), an electrically Erasable Read-Only Memory (EEPROM), and the like. The memory is used for storing programs, and the processor executes the programs after receiving the execution instructions.
Further, the software programs and modules within the aforementioned memories may also include an operating system, which may include various software components and/or drivers for managing system tasks (e.g., memory management, storage device control, power management, etc.), and may communicate with various hardware or software components to provide an operating environment for other software components.
The processor may be an integrated circuit chip having signal processing capabilities. The processor may be a general-purpose processor, and may include a Central Processing Unit (CPU), an image processor, and the like, and may implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of the present invention.
The present invention also provides a computer-readable storage medium, on which an electric revocation list management program is stored, which, when executed by a processor, implements the steps of the electric revocation list management method as above.
It should be noted that, in this document, 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. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
The above-mentioned serial numbers of the embodiments of the present invention are merely for description and do not represent the merits of the embodiments.
Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but in many cases, the former is a better implementation manner. Based on such understanding, the technical solutions of the present invention may be embodied in the form of a software product, which is stored in a storage medium (such as ROM/RAM, magnetic disk, optical disk) and includes instructions for enabling a terminal device (such as a mobile phone, a computer, a server, an air conditioner, or a network device) to execute the method according to the embodiments of the present invention.
The above description is only a preferred embodiment of the present invention, and not intended to limit the scope of the present invention, and all modifications of equivalent structures and equivalent processes, which are made by using the contents of the present specification and the accompanying drawings, or directly or indirectly applied to other related technical fields, are included in the scope of the present invention.
Claims (10)
1. An electric sales list management method, comprising:
acquiring basic information data of N target clients; the basic information data includes at least one of: gender, occupation, age, related product purchase;
predicting the characteristics of each target client by using a trained client characteristic prediction model according to the basic information data of the N target clients to obtain the predicted characteristics of the target clients;
acquiring sales capability characteristics of M agents;
and distributing the N target customers to the M agents according to the prediction characteristics of the target customers and the sales capability characteristics of the agents and preset rules.
2. The method of claim 1,
the predicted characteristics of the target customer include: a conversion success rate for indicating a prediction probability of successful conversion of the target customer to a real customer;
the sales capability features of the agent include: a customer conversion rate indicating a prediction probability that the agent successfully converts the target customer to a real customer;
the distributing the data of the N target clients to the M agents according to the prediction characteristics of the target clients and the sales capability characteristics of the agents and preset rules comprises the following steps:
and distributing the data of the target customer with the converted power higher than the first preset value to an agent with the customer conversion rate higher than the second preset value.
3. The method of claim 1 or 2, further comprising:
receiving dialing feedback information input after an operator dials a contact phone of a target customer; the dialing feedback information is used for indicating whether the target customer is converted into a real customer;
and updating the customer characteristic prediction model according to the dialing feedback information.
4. The method of claim 1 or 2, further comprising:
acquiring historical information data of the target client from a data warehouse;
and performing information supplementation on the basic information data according to the historical information data.
5. The method of claim 2, further comprising:
collecting a plurality of historical target customer conversions into power and sales results;
and performing predictive effect analysis on the customer characteristic prediction model according to the converted power and sales results of a plurality of historical target customers.
6. The method of claim 3, further comprising:
updating the corresponding sales capability characteristics of the seat staff according to the basic information data of the target customer and the dialing feedback information;
and sending the updated sales capability characteristics of the seat staff to the electricity marketing system.
7. An electrical pinning system, comprising:
the client data management system is used for storing basic information data of a target client; the basic information data includes at least one of: gender, occupation, age, income, consumption level, purchase of related products, contact phone call;
the electric sales system is used for storing the sales capability characteristics of the seat staff; the sales capability features of the agent include: customer conversion rate;
the data warehouse is used for storing historical information data of the clients;
an electrical sales listing management system for performing the method of any of claims 1-6.
8. An electric outlets list management apparatus, comprising:
the acquisition module is used for acquiring basic information data of N target clients; the basic information data includes at least one of: gender, occupation, age, related product purchase;
the characteristic prediction module is used for predicting the characteristics of each target client by utilizing a trained client characteristic prediction model according to the basic information data of the N target clients to obtain the predicted characteristics of the target clients;
the acquisition module is also used for acquiring the sales capability characteristics of the M agents;
and the distribution module is used for distributing the N target customers to the M agents according to the prediction characteristics of the target customers and the sales capability characteristics of the agents and preset rules.
9. An electric sales list management apparatus, characterized in that the electric sales list management apparatus comprises: memory, a processor and an electrical pin list management program stored on the memory and executable on the processor, the electrical pin list management program when executed by the processor implementing the steps of the electrical pin list management method according to any one of claims 1 to 7.
10. A computer-readable storage medium, having stored thereon an electrical blacklist management program, which when executed by a processor, implements the steps of the electrical blacklist management method of any one of claims 1 to 7.
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