CN115860315A - Enterprise customer relationship management system and data processing method - Google Patents
Enterprise customer relationship management system and data processing method Download PDFInfo
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Abstract
The invention discloses an enterprise customer relationship management system and a data processing method, relates to the field of enterprise management, and solves the technical problems that in the prior art, the correlation of customer services is difficult to mine, the final service execution is performed by sales personnel, the workload of the sales personnel is increased, and the customer requirements cannot be met in time; analyzing basic customer information, and then estimating the service scale by combining an empirical formula; the sales information is reasonably set according to the service type and the service scale and is sent to the corresponding client, so that the labor cost can be effectively reduced, and the client is prevented from being disturbed frequently; according to the method, the original data are extracted from the business data according to the customer requirements, and the target data meeting the customer requirements are obtained after screening, so that the customer requirements can be timely and accurately met; meanwhile, matching the associated clients according to the client requirements, extracting the target data corresponding to the associated clients and feeding back the target data to the associated clients; customer requirements can be accurately mined, and customer satisfaction is improved.
Description
Technical Field
The invention belongs to the field of enterprise management, relates to an enterprise customer relationship intelligent management technology, and particularly relates to an enterprise customer relationship management system and a data processing method.
Background
An enterprise Customer Relationship Management (CRM) system refers to the process of managing the interaction between an enterprise and customers. The enterprise customer management system can accurately master customer requirements based on technologies such as data warehouse and data mining, and further assists enterprises to complete maintenance and expansion of customer groups.
The prior art (chinese patent application publication No. CN 114663105A) discloses an enterprise customer relationship management system and method, which performs overall analysis and correlation analysis on collected customer information, and can complete information distribution according to the analysis result and remind the sales staff to perform follow-up processing. In the prior art, when a customer relationship is processed, the final service execution after the customer is analyzed is still performed by a salesperson, the advantages of an enterprise customer relationship management system cannot be exerted, and the customer relationship is not timely because a response cannot be automatically given to the simple customer requirements; therefore, it is desirable to provide an enterprise customer relationship management system and a data processing method.
Disclosure of Invention
The present invention is directed to solving at least one of the problems of the prior art; therefore, the invention provides an enterprise customer relationship management system and a data processing method, which are used for solving the technical problems that in the prior art, the correlation of customer services is difficult to mine, the final service execution is performed by sales personnel, the workload of the sales personnel is increased, and the customer requirements cannot be met in time.
In order to achieve the above object, a first aspect of the present invention provides an enterprise customer relationship management system, which includes a central control module, and a data acquisition module and a customer interaction module, which are in communication and/or electrical connection with the central control module;
the data acquisition module acquires and improves basic customer information through enterprise personnel or the Internet; the basic customer information comprises a customer name, a customer address, a contact way, a customer type and a customer scale;
the central control module extracts the service data from the internal data and associates the service data with the corresponding customer name; extracting the service type required by the customer based on the basic customer information, and finishing automatic sale by combining a customer interaction module;
the customer interaction module collects customer requirements, and the central control module extracts and feeds back service data according to the customer requirements; and simultaneously, performing associated client matching and performing service data feedback on the associated clients.
Preferably, the data acquisition module acquires perfect basic customer information through enterprise personnel or the internet, and the perfect basic customer information includes:
enterprise personnel fill in and perfect basic customer information one by one according to the customer information template, and upload and store the basic customer information; or the enterprise personnel at least fills in the client name, then links the Internet, perfects the basic client information according to the client information template, and uploads and stores the basic client information.
Preferably, the central control module extracts the service data from the internal data and associates the service data with the corresponding customer name, and the method includes:
extracting internal data and input basic customer information;
extracting service data from the internal data according to the client name in the basic client information, and associating the service data with the client name; the business data comprises business types, business progress and associated sales personnel;
setting a reading authority according to the service type of the service data; when the internal data is updated, correspondingly updating the business data corresponding to the client name; the reading authority is used for carrying out classified secrecy on the service data.
Preferably, the hub control module extracts the service type of the customer requirement based on the basic customer information, and completes the automatic sales by combining the customer interaction module, including:
judging whether the corresponding client is a new client or not according to the basic client information; if yes, the client tag KB is set to 1; if not, judging whether the last service cycle of the corresponding client is finished according to the service data, if so, setting the client tag KB to be 1, otherwise, setting the client tag KB to be 0;
matching the business type of the enterprise according to the client type in the basic client information; simultaneously, calculating the service scale YGM of the corresponding service type according to a formula YGM = alpha x KB x KG x DYG; wherein, alpha is a proportional coefficient set according to experience, KG is a customer scale, and DYG is a service scale corresponding to a unit customer scale;
and automatically generating sales information according to the extracted service type and the service scale, sending the sales information to corresponding customers through a customer interaction module, and timely receiving customer feedback.
Part of data in the formula is obtained by removing dimensions and calculating the numerical value of the data, and the formula is a formula which is closest to the real condition and obtained by simulating a large amount of collected data through software; the preset parameters and the preset threshold values in the formula are set by those skilled in the art according to actual conditions or obtained through simulation of a large amount of data.
Preferably, after the basic customer information is entered, the hub control module generates a customer account for the corresponding customer, and sends the customer account to the customer interaction module for backup, including:
taking the customer name in the basic customer information as an account name, and generating an account password after carrying out encryption processing according to the customer type, the contact way and the customer scale; the number of times of using the account password is fixed;
the account name and the account password are associated to generate a customer account, and the customer account is sent to a customer interaction module; when the customer needs data interaction, the customer interaction module verifies the customer account.
Preferably, the central control module extracts and feeds back the service data according to the customer requirement, and the method includes:
receiving, by a customer interaction module, a verification customer requirement;
extracting initial data from corresponding service data according to customer requirements, and integrating data meeting customer account reading permission in the initial data into target data; and feeding the target data back to the client through the client interaction module.
Preferably, the central control module performs associated customer matching based on customer requirements, and performs service data feedback on the associated customers, including:
extracting basic customer information of a customer corresponding to customer requirements and business data of the corresponding customer; generating a customer matching sequence based on the extracted basic customer information and the service data;
matching the client matching sequence with basic client information stored in the internal data of the enterprise, and extracting clients with matching degrees meeting requirements as associated clients; and performing data feedback for the associated client according to the client requirement.
The second aspect of the present invention provides a data processing method for an enterprise customer relationship management system, including:
acquiring and improving basic customer information through enterprise personnel or the Internet; extracting business data related to the client from the internal data of the enterprise, and establishing an association relationship between the business data and the corresponding client;
mining the service type required by the customer according to the basic customer information, predicting the corresponding service scale according to the empirical data, and further generating sales information and sending the sales information to the corresponding customer;
collecting customer requirements, and extracting and feeding back service data according to the customer requirements; and simultaneously, carrying out associated customer matching, matching service data for the associated customers according to customer requirements, and feeding back the service data to the associated customers.
A third aspect of the present invention provides an enterprise customer relationship management apparatus, comprising a storage medium and a processor; the storage medium is used for storing operation instructions, and the processor executes the operation instructions to control the operation of the enterprise customer relationship management system.
Compared with the prior art, the invention has the beneficial effects that:
1. the method analyzes the client type based on the basic client information, reasonably sets the client label, matches the appropriate service type in the enterprise according to the client type, and estimates the service scale by combining an empirical formula; the sales information is reasonably set according to the service type and the service scale and is sent to the corresponding client, so that the labor cost can be effectively reduced, and the client is prevented from being disturbed frequently.
2. According to the method, the original data are extracted from the business data according to the customer requirements, the target data meeting the customer requirements are obtained after screening and fed back to the customer, and the customer requirements can be timely and accurately met; meanwhile, matching the associated clients according to the client requirements, extracting the target data corresponding to the associated clients and feeding back the target data to the associated clients; customer requirements can be accurately mined, and customer satisfaction is improved.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a schematic diagram of the system of the present invention;
FIG. 2 is a schematic diagram of an automated marketing process of the present invention;
FIG. 3 is a schematic diagram illustrating a service data feedback procedure according to the present invention;
FIG. 4 is a schematic diagram of the working steps of the present invention.
Detailed Description
The technical solutions of the present invention will be described clearly and completely with reference to the following embodiments, and it should be understood that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
In the prior art, when enterprise customer relationship management is performed, customer information is generally collected as much as possible, the customer information is classified and managed, and sales personnel is reminded to execute sales service at regular time, so that the workload of the sales personnel is increased, and the customers are possibly disturbed; in addition, when the customer needs are met, a salesperson generally answers the customer needs one to one, and associated customer needs are not considered in time, so that the customer maintenance efficiency is low, and the customer experience is influenced.
Referring to fig. 1, a first embodiment of the present invention provides an enterprise customer relationship management system, which includes a central control module, and a data acquisition module and a customer interaction module, which are in communication and/or electrical connection with the central control module; the data acquisition module acquires and improves basic customer information through enterprise personnel or the Internet; the central control module extracts the service data from the internal data and associates the service data with the corresponding customer name; extracting the service type required by the customer based on the basic customer information, and finishing automatic sale by combining a customer interaction module; the customer interaction module collects customer requirements, and the central control module extracts and feeds back service data according to the customer requirements; and simultaneously, performing associated client matching and performing service data feedback on the associated clients.
In the enterprise customer relationship management system provided by the invention, the central control module is mainly responsible for data processing and data mining, so that the central control module needs to perform data interaction with the data acquisition module and the customer interaction module. The data acquisition module is mainly used for acquiring supplementary basic client information from the inside of an enterprise and the Internet, for example, the data acquisition module is connected with a server in the enterprise or an intelligent terminal of a salesman, or is connected with a related third-party Internet platform. The client interaction module is mainly used for completing data interaction between the enterprise and the client, mainly receiving the client requirement and feeding back the business data corresponding to the client requirement to the client.
The basic customer information comprises customer names, customer addresses, contact ways, customer types, customer scales and the like which do not belong to enterprise public data, and a customer portrait can be constructed through the central control module according to the basic customer information. The customer address refers to the registered address of the enterprise and also includes the standing address of the individual customer. The contact information mainly comprises a telephone number and a mailbox. The customer type mainly refers to the industry (preferably, the segment industry) to which the customer belongs. The customer scale mainly comprises staff scale and performance scale, and the customer scale is very important for evaluating and acquiring sales information.
The data acquisition module of the invention obtains and perfects the basic customer information through enterprise personnel or internet, and comprises: enterprise personnel fill and perfect basic customer information one by one according to the customer information template, and upload and store the basic customer information; or the enterprise personnel at least fills in the client name, then links the Internet, perfects the basic client information according to the client information template, and uploads and stores the basic client information.
When the enterprise personnel determines the client, the information is preferably provided according to the client information module, when partial information is not complete, at least the corresponding client name needs to be provided, and then other information can be supplemented through the third-party Internet platform. After the backbone control module receives the underlying customer information, it is stored after necessary processing (including building customer figures and performing customer classifications).
The invention relates to a central control module which extracts service data from internal data and associates the service data with a corresponding customer name, and the method comprises the following steps: extracting internal data and input basic customer information; extracting service data from the internal data according to the client name in the basic client information, and associating the service data with the client name; setting a reading authority according to the service type of the service data; and when the internal data is updated, correspondingly updating the business data corresponding to the client name.
Internal data here includes data collected across the enterprise as well as data generated by processes internal to the enterprise. After basic customer information is input, whether data related to customers exist in internal data of an enterprise is preferentially searched, and if yes, an association relationship between the internal data and the data is established. Here, the data related to the client includes not only business transactions with the client, but also policy data and supply chain data related to the client.
The business data includes business type, business progress and associated sales personnel. If the client is a new client, the service type and the service progress do not exist. The associated sales person may be understood as the sales person assigned by the business to the customer.
It should be noted that as each activity of the enterprise progresses, more and more internal data is generated. The business data of the client should be updated periodically based on the updated internal data. The business data needs to set certain read authority, for example, the business data of a certain client is open to the client and the related sales personnel, and is confidential for other people. In order to ensure that the business data does not disclose the business secrets of the enterprise, the business data needs to be filtered according to relevant rules before being extracted, for example, the business data may include business progress, but should not include corresponding business executors.
Referring to fig. 2, in a preferred embodiment, the hub control module extracts the service type of the customer requirement based on the basic customer information, and completes the automatic sales by combining with the customer interaction module, including: judging whether the corresponding client is a new client or not according to the basic client information; if yes, the client tag KB is set to 1; if not, judging whether the last service cycle of the corresponding client is finished according to the service data, if so, setting the client tag KB to be 1, otherwise, setting the client tag KB to be 0; matching the business type of the enterprise according to the client type in the basic client information; simultaneously, calculating the service scale YGM of the corresponding service type according to an empirical formula; and automatically generating sales information according to the extracted service type and the service scale, sending the sales information to corresponding customers through a customer interaction module, and timely receiving customer feedback.
When the sales work is automatically carried out, whether a customer is a new customer or not needs to be judged, if the customer is the new customer, the automatic sales flow is directly started, and if the customer is an old customer, the service period needs to be considered. And then, judging whether the business suitable for the client exists in the enterprise according to the client type, if so, estimating the business scale corresponding to the client, and accurately finishing the sale after the business type and the business scale are determined.
The present embodiment is illustrated next: suppose there are project customers a, B and C, the customer sizes of the three are 100, 200 and 300, respectively, and the unit business sizes of the three are 0.2, 0.5 and 0.4, respectively; the client A is a new client, the client B is an old client which finishes the last service cycle, and the client C is an old client which does not finish the last service cycle; the project client and the business of the enterprise cooperate to have a business cycle, namely, the next business can not be developed when the previous business is not finished.
According to the embodiment, the client tags KB of the clients a and B are set to 1, and the client tag of the client C is set to 0, then the traffic sizes of the three clients are respectively 20, 100 and 0 (α is 1) according to the formula. Obviously, when performing automated sales, sales information (including sales contents and sales price) should be set for customer a according to the business scale 20, and sales information should be set for customer B according to the business scale 100, and there is no need to set sales information for customer C because the last business of customer C has not yet been completed. This not only enables targeted marketing to the customer, but also does not disturb the customer for an unscheduled marketing.
It should be noted that DYG is a business scale corresponding to a unit customer scale, that is, an empirical data obtained by combining the empirical data, the customer type, and the customer scale. If a client belongs to the traditional manufacturing industry and the average project amount of each research and development staff in the industry is 1 ten thousand yuan, DYG =1, and if the research and development staff of the client is 10, the corresponding project amount is 10. The reasonable selection of the customer scale elements is an effective way to obtain accurate DYG, namely, the elements most relevant to the business scale are selected, such as a research and development staff and a patent application budget hook, and a front-line worker and a yield hook.
In an alternative embodiment, after the basic customer information entry, the hub control module generates a customer account for the corresponding customer and sends the customer account to the customer interaction module for backup, including: taking the customer name in the basic customer information as an account name, and generating an account password after carrying out encryption processing according to the customer type, the contact way and the customer scale; the account name and the account password are associated to generate a customer account, and the customer account is sent to a customer interaction module; when the customer needs data interaction, the customer interaction module verifies the customer account.
After the sales information is generated, the sales information is sent to the customer through the customer interaction module, and therefore the automatic sales is completed. Given the lower likelihood that this mode of sale will disturb the customer, it can be sent to the customer mailbox without customer verification. When a customer submits a demand to an enterprise, the customer needs to log in a corresponding customer account.
Notably, the account password for the customer account is generated based on the customer type, contact details, and customer size. Randomly extracting a plurality of characters from a client type code, a contact address or a client scale to generate an account password; and the client type, the contact way and the client scale generation can be all subjected to hash processing, and a plurality of characters are extracted from the processed hash result to generate the account password. For example, each account password can be used three times, and after three times, a new account password is generated by extracting from the hash result again.
Referring to fig. 3, in a preferred embodiment, the backbone control module performs extraction feedback on the service data according to the customer requirement, including: receiving, by a customer interaction module, a verification customer requirement; extracting initial data from corresponding service data according to customer requirements, and integrating data meeting customer account reading permission in the initial data into target data; and feeding the target data back to the client through the client interaction module.
In the business advancing process, a customer can often know the business progress and query related information, and in the existing enterprise customer relationship management system, generally, a salesperson queries in the system according to the customer requirements and then feeds back the query result to the customer, which obviously has low efficiency. The invention automatically extracts the original data according to the customer requirements, and generates the target data after necessarily screening the original data, and the target data is fed back to the customer to meet the customer requirements. The purpose of screening the original data is to avoid sending the private data of the enterprise to the client, that is, if the private data is included in the client requirement, the part of the client requirement related to the private data cannot be met.
In an optional embodiment, the central control module performs associated client matching based on the client requirement, and performs service data feedback on the associated client, including: extracting basic customer information of a customer corresponding to customer requirements and business data of the corresponding customer; generating a customer matching sequence based on the extracted basic customer information and the service data; matching the client matching sequence with basic client information stored in the internal data of the enterprise, and extracting clients with matching degrees meeting requirements as associated clients; and performing data feedback for the associated client according to the client requirement.
When one client has the requirement, the client similar to the client may have the corresponding requirement, so the invention extends to acquire the associated client and actively provides data feedback for the associated client. Matching of related clients mainly comprises the steps that client types and client addresses are matched firstly, namely clients of the same types are influenced by the same policy, then client scales are matched, if the client scales are consistent, research and development periods of the clients are similar, and finally matching is carried out according to service data, namely service types, service schedules and the like; if the similarity of the matching contents is extremely high, the objective reflection on the client requirements is similar. It should be noted that the matching process may be completed by an existing deep learning model, and details are not described herein.
It should be noted that when the customer needs are many and complicated, the customer needs may be filtered and then the associated customers may be obtained, and if 30% of the customer needs relate to the business progress in a short time, the associated customers may be matched according to the customers corresponding to the customer needs.
Referring to fig. 4, a second embodiment of the present invention provides a data processing method of an enterprise customer relationship management system, including: acquiring and improving basic customer information through enterprise personnel or the Internet; extracting business data related to the client from the internal data of the enterprise, and establishing an association relationship between the business data and the corresponding client; mining the service type of the customer requirement according to the basic customer information, and predicting the corresponding service scale according to the empirical data, so as to generate sales information and send the sales information to the corresponding customer; collecting customer requirements, and extracting and feeding back service data according to the customer requirements; and simultaneously, carrying out associated customer matching, matching service data for the associated customers according to customer requirements, and feeding back the service data to the associated customers.
The embodiment of the third aspect of the invention provides an enterprise customer relationship management device, which comprises a storage medium and a processor; the storage medium is used for storing operation instructions, and the processor executes the operation instructions to control the operation of the enterprise customer relationship management system. A processor in the device executes an operation instruction in a storage medium to control a central control module, a data acquisition module and a customer interaction module to work, and further the data processing method is realized.
Although the present invention has been described in detail with reference to the preferred embodiments, it will be understood by those skilled in the art that various changes may be made and equivalents may be substituted for elements thereof without departing from the scope of the present invention.
Claims (9)
1. The enterprise customer relationship management system comprises a central control module, a data acquisition module and a customer interaction module, wherein the data acquisition module and the customer interaction module are in communication and/or electrical connection with the central control module; the method is characterized in that:
the data acquisition module acquires and improves basic customer information through enterprise personnel or the Internet; the basic customer information comprises a customer name, a customer address, a contact way, a customer type and a customer scale;
the central control module extracts service data from the internal data and associates the service data with the corresponding customer name; extracting the service type required by the customer based on the basic customer information, and finishing automatic sale by combining a customer interaction module;
the customer interaction module collects customer requirements, and the central control module extracts and feeds back service data according to the customer requirements; and simultaneously, performing associated client matching and performing service data feedback on the associated clients.
2. The system of claim 1, wherein the data collection module obtains the perfection of the underlying customer information via enterprise personnel or the internet, and comprises:
enterprise personnel fill in and perfect basic customer information one by one according to the customer information template, and upload and store the basic customer information; or the enterprise personnel at least fills in the client name, then links the Internet, perfects the basic client information according to the client information template, and uploads and stores the basic client information.
3. The enterprise customer relationship management system of claim 2, wherein the hub control module extracts business data from the internal data and associates the business data with a corresponding customer name, comprising:
extracting internal data and input basic customer information;
extracting service data from the internal data according to the client name in the basic client information, and associating the service data with the client name; the business data comprises business types, business progress and associated sales personnel;
setting a reading authority according to the service type of the service data; when the internal data is updated, correspondingly updating the business data corresponding to the client name; the reading authority is used for carrying out classified confidentiality on the service data.
4. The enterprise customer relationship management system of claim 3 wherein the hub control module extracts the business type of customer needs based on the underlying customer information and completes automated sales in conjunction with the customer interaction module, comprising:
judging whether the corresponding client is a new client or not according to the basic client information; if yes, the client tag KB is set to 1; if not, judging whether the last service cycle of the corresponding client is finished according to the service data, if so, setting the client tag KB to be 1, otherwise, setting the client tag KB to be 0;
matching the business type of the enterprise according to the client type in the basic client information; simultaneously, calculating the service scale YGM of the corresponding service type according to a formula YGM = alpha x KB x KG x DYG; wherein, alpha is a proportional coefficient set according to experience, KG is a customer scale, and DYG is a service scale corresponding to a unit customer scale;
and automatically generating sales information according to the extracted service type and the service scale, sending the sales information to corresponding customers through a customer interaction module, and timely receiving customer feedback.
5. The enterprise customer relationship management system of claim 4, wherein after entry of the base customer information, the hub control module generates customer accounts for the corresponding customers and sends the customer accounts to the customer interaction module for backup, comprising:
taking the customer name in the basic customer information as an account name, and generating an account password after carrying out encryption processing according to the customer type, the contact way and the customer scale; the number of times of using the account password is fixed;
the account name and the account password are associated to generate a customer account, and the customer account is sent to a customer interaction module; when the customer needs data interaction, the customer interaction module verifies the customer account.
6. The enterprise customer relationship management system of claim 5, wherein the hub control module abstracts feedback from business data based on customer demand, comprising:
receiving, by a customer interaction module, a verification customer requirement;
extracting initial data from corresponding business data according to customer requirements, and integrating data meeting customer account reading authority in the initial data into target data; and feeding the target data back to the client through the client interaction module.
7. The enterprise customer relationship management system of claim 6, wherein the hub control module performs associated customer matching based on customer requirements and business data feedback for associated customers, comprising:
extracting basic customer information of a customer corresponding to customer requirements and business data of the corresponding customer; generating a customer matching sequence based on the extracted basic customer information and the service data;
matching the client matching sequence with basic client information stored in the internal data of the enterprise, and extracting clients with matching degrees meeting requirements as associated clients; and performing data feedback for the associated customers according to the customer demands.
8. The data processing method of the enterprise customer relationship management system according to any one of claims 1 to 7, comprising:
acquiring and improving basic customer information through enterprise personnel or the Internet; extracting business data related to the client from the internal data of the enterprise, and establishing an association relationship between the business data and the corresponding client;
mining the service type required by the customer according to the basic customer information, predicting the corresponding service scale according to the empirical data, and further generating sales information and sending the sales information to the corresponding customer;
collecting customer requirements, and extracting and feeding back service data according to the customer requirements; and simultaneously, carrying out associated customer matching, matching service data for the associated customers according to customer requirements, and feeding back the service data to the associated customers.
9. The enterprise customer relation management device is characterized by comprising a storage medium and a processor; the storage medium is used for storing operation instructions, and the processor executes the operation instructions to control the operation of the enterprise customer relationship management system according to any one of claims 1 to 7.
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| CN117251633A (en) * | 2023-10-08 | 2023-12-19 | 国任财产保险股份有限公司 | Customer data management system |
| CN117312400A (en) * | 2023-10-18 | 2023-12-29 | 上海网萌网络科技有限公司 | Intelligent customer management system and method based on artificial intelligence |
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| CN117312400A (en) * | 2023-10-18 | 2023-12-29 | 上海网萌网络科技有限公司 | Intelligent customer management system and method based on artificial intelligence |
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Application publication date: 20230328 |