CN110910163A - Automobile distribution customer demand analysis method and system based on customer relationship management system - Google Patents
Automobile distribution customer demand analysis method and system based on customer relationship management system Download PDFInfo
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Abstract
The invention provides a method and a system for analyzing automobile distribution customer requirements based on a customer relationship management system. The automobile distribution customer demand analysis method based on the customer relationship management system comprises the following steps: executing system customer information intelligent aggregation processing, integrating the information of customers on each platform system including a self-built system and a third-party system to form comprehensive personal information of each customer, and storing the comprehensive personal information into a customer relationship management system; performing automatic extraction and arrangement processing of client data, arranging the comprehensive personal information, and extracting client identity related information and client behavior information from the comprehensive personal information; performing customer behavior analysis processing, and dynamically maintaining state information and operation information of customers in a customer relationship management system by analyzing the extracted customer identity related information and customer behavior information; and executing the client interaction suggestion processing, and giving client interaction suggestions based on the user portrait.
Description
Technical Field
The invention relates to the field of automobile accessories, in particular to an automobile accessory customer demand analysis method and system based on a customer relationship management system.
Background
Customer Relationship Management (CRM) refers to an information system that uses software, hardware, and networking technologies to build a customer information collection, management, analysis, and utilization system for an enterprise. The customer relationship management system takes the management of customer data as a core, records various interactive behaviors of an enterprise and customers in the marketing and sales process and states of various related activities, provides various data models and provides support for later analysis and decision.
A traditional general CRM system needs to carry out a large amount of configuration and information input in the implementation process of the system, and the work can only be finished and processed in a manual mode. Moreover, the CRM system has a large number of people and a complicated role, a great deal of effort is needed to maintain the data of the CRM system, and the data analysis can only simply provide some ranking and reporting data.
Particularly, for the customers in the automobile and distribution industry, the number of the customers is as large as that of group chain customers and that of individual users, the types of the customers are multiple, the span of the operation range is large, the frequency of the customer transaction is very different, and the customers of various types need multi-dimensional aggregation and analysis. Meanwhile, in the process of using products, customers generate a large amount of user data every moment, and the user data analysis mode of each type of customer is different. How to predict the transaction requirements of customers and guide business promotion and product transaction by using the existing user data and combining with the user operation types under the condition of not needing a large amount of manual input and empirical analysis becomes a problem which is difficult to solve in customer management of the automobile distribution industry.
Disclosure of Invention
The technical problem to be solved by the invention is to provide a method and a system for analyzing the requirement of a vehicle distribution customer based on a customer relationship management system, aiming at the defects in the prior art, wherein the method and the system automatically capture the customer data of each platform, identify the belonged customers, intelligently analyze the types of the customers, form a user image and guide the business, can meet the requirements of daily sales visit and product transaction, and improve the production efficiency.
The invention provides a steam distribution customer demand analysis method based on a customer relationship management system, which comprises the following steps:
the first step is as follows: executing system customer information intelligent aggregation processing, integrating the information of customers on each platform system including a self-built system and a third-party system to form comprehensive personal information of each customer, and storing the comprehensive personal information into a customer relationship management system;
the second step is as follows: performing automatic extraction and arrangement processing of client data, arranging the comprehensive personal information, and extracting client identity related information and client behavior information from the comprehensive personal information;
the third step: performing customer behavior analysis processing, and dynamically maintaining state information and operation information of customers in a customer relationship management system by analyzing the extracted customer identity related information and customer behavior information;
the fourth step: and executing the client interaction suggestion processing, and giving client interaction suggestions based on the user portrait.
Preferably, in the first step, the user characteristic information of each platform system is extracted, the account numbers belonging to the same customer on each platform system are associated to one customer entity through cross comparison of the user characteristic information, and the user information of the account numbers belonging to the same customer on each platform system is integrated into the comprehensive personal information of the customer entity, so that the intelligent aggregation of the customer information is realized.
Preferably, the self-built system comprises an enterprise internal ERP system, a vehicle type part price inquiry and quotation platform, a vulnerable part mall and an electronic catalog EPC inquiry system, and the third-party system comprises a WeChat public number, a WeChat applet, a WeChat contact platform and a nailing external contact platform.
Preferably, the customer identity related information comprises store names, customer states, customer grades, customer sources, operation types, contact calls, store addresses, customer properties, operation subjects, importance degrees, WeChat contacts, QQ numbers and mailboxes; the customer behavior information comprises the details of the historical transaction data of the customer, the real-time transaction data of the customer, price inquiring information of the customer and the inquiry preference of the customer.
Preferably, the customer interaction advice comprises: customer visit suggestions, customer visit route planning suggestions and warehouse logistics planning suggestions.
According to the invention, the invention also provides a steam distribution customer demand analysis system based on the customer relationship management system, which comprises the following steps: the system comprises a system client information intelligent aggregation module, a client data automatic extraction and arrangement processing module, a client behavior analysis and portrait processing module and a client interaction suggestion processing module;
the system customer information intelligent aggregation module is used for integrating information of customers on each platform system including a self-built system and a third-party system to form comprehensive personal information of each customer and storing the comprehensive personal information into a customer relationship management system;
the client data automatic extraction and arrangement module is used for arranging the comprehensive personal information, extracting client identity related information and extracting client behavior information from the comprehensive personal information;
the client behavior analysis processing module is used for dynamically maintaining the state information and the operation information of the client in the client relationship management system by analyzing the extracted client identity related information and the client behavior information;
the client interaction suggestion processing module is used for giving client interaction suggestions based on the user representation.
Preferably, the system customer information intelligent aggregation module extracts the user characteristic information of each platform system, cross-compares the user characteristic information, associates the account numbers belonging to the same customer on each platform system to a customer entity, and integrates the user information of the account numbers belonging to the same customer on each platform system into the comprehensive personal information of the customer entity, so as to realize the intelligent aggregation of the customer information.
Preferably, the self-built system comprises an enterprise internal ERP system, a vehicle type part price inquiry and quotation platform, a vulnerable part mall and an electronic catalog EPC inquiry system, and the third-party system comprises a WeChat public number, a WeChat applet, a WeChat contact platform and a nailing external contact platform.
Preferably, the customer identity related information comprises store names, customer states, customer grades, customer sources, operation types, contact calls, store addresses, customer properties, operation subjects, importance degrees, WeChat contacts, QQ numbers and mailboxes; the customer behavior information comprises the details of the historical transaction data of the customer, the real-time transaction data of the customer, price inquiring information of the customer and the inquiry preference of the customer.
Preferably, the customer interaction advice comprises: customer visit suggestions, customer visit route planning suggestions and warehouse logistics planning suggestions.
Based on the invention, the salesperson does not need to input complicated information any more, and only needs to reflect the whole transaction data faithfully, so that the whole CRM system is not a simple information input and query tool any more, but can provide a sales scheme through big data and intelligent analysis. The invention can supplement the big data knowledge base by tracking the whole sales link, solves the problem that the customers need to be maintained depending on the professional degree and experience of the sales staff in the past, meets the requirements of the customers, changes the mode of the sales visit, improves the efficiency of the sales visit and reduces the threshold of the sales visit.
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A more complete understanding of the present invention, and the attendant advantages and features thereof, will be more readily understood by reference to the following detailed description when considered in conjunction with the accompanying drawings wherein:
fig. 1 schematically shows a flowchart of a customer demand analysis method for a steam distribution based on a customer relationship management system according to a preferred embodiment of the present invention.
Fig. 2 schematically shows a block diagram of a customer demand analysis system for a steam distribution based on a customer relationship management system according to a preferred embodiment of the present invention.
It is to be noted, however, that the appended drawings illustrate rather than limit the invention. It is noted that the drawings representing structures may not be drawn to scale. Also, in the drawings, the same or similar elements are denoted by the same or similar reference numerals.
Detailed Description
In order that the present disclosure may be more clearly and readily understood, reference will now be made in detail to the present disclosure as illustrated in the accompanying drawings.
< first embodiment >
Fig. 1 schematically shows a flowchart of a customer demand analysis method for a steam distribution based on a customer relationship management system according to a preferred embodiment of the present invention.
As shown in fig. 1, the method for analyzing the demand of the steam distribution customer based on the customer relationship management system according to the preferred embodiment of the present invention includes:
first step S1: executing system customer information intelligent aggregation processing, integrating the information of customers on each platform system including a self-built system and a third-party system to form integrated personal information of each customer, and storing the integrated personal information into a customer relationship management system;
for example, the self-built system comprises an enterprise internal ERP system, a vehicle type part inquiry and quotation platform, a vulnerable part mall, an electronic catalog EPC inquiry system and the like, and the third-party system comprises a WeChat public number, a WeChat applet, a WeChat contact platform, a nailing external contact platform and the like.
The client has unique user characteristic information (characteristic value) on each platform, such as head portrait, nickname, mobile phone number, micro-signal, registration information, authentication information and the like of the user. The user characteristic values of all the platform systems are extracted, account numbers belonging to the same customer on all the platform systems are related to a customer entity through cross comparison of user characteristic information, and the user information of the account numbers belonging to the same customer on all the platform systems is integrated into comprehensive personal information of the customer entity, so that intelligent aggregation of customer information is achieved.
Through the integration of the module, each system is not an isolated island of information, but the information of each system interacts with each other to form a user behavior network.
Second step S2: performing automatic extraction and arrangement processing of client data, arranging the comprehensive personal information, and extracting client identity related information and client behavior information from the comprehensive personal information;
specifically, for example, the customer identity-related information includes data such as store names, customer statuses, customer ratings, customer sources, business types, contact calls, store addresses, customer properties, business subjects, importance levels, WeChat contacts, QQ numbers, mailboxes, and the like; the customer behavior information comprises customer historical transaction data details, customer real-time transaction data, customer inquiry quotation information, customer inquiry preference and the like.
Third step S3: performing customer behavior analysis and portrait processing, and dynamically maintaining state information and operation information of customers in a customer relationship management system by analyzing the extracted customer identity related information and customer behavior information to form customer portraits which accord with customer characteristics;
specifically, the extracted and sorted customer behavior and information data are analyzed. For example, the main operation range, monthly transaction amount and client state of a client can be analyzed through the historical transaction data of the user, dynamic commodity recommendation can be performed through the real-time transaction data of the user, and the special vehicle repair system, operation type and quality preference of the client can be analyzed through inquiring quotation information of the client. By analyzing the customer behavior data, the data such as the status, classification, business type, business scope, etc. of the customer are dynamically maintained, and finally, a user portrait (customer portrait) conforming to the customer characteristics is formed.
Fourth step S4: and executing the client interaction suggestion processing, and giving client interaction suggestions based on the user portrait.
The user portrait is formed through the analysis of the customer behavior, and after the user portrait is relatively accurate, the user can be known as a large maintenance chain or a small individual maintenance shop; whether to engage in the project of fast maintenance or accident car maintenance; what is the brand quality of the commonly used accessories; what the transaction period of the customer is, etc. Based on the data, the intelligent inference about when the customer needs to trade and the type and quantity of the traded goods provides reference for the salesperson.
The geographic position of the customer is determined in the customer data extraction, and intelligent visiting route planning and intelligent warehouse logistics planning can be carried out.
Therefore, based on the invention, the salesperson does not need to input complicated information any more, and only needs to reflect the whole transaction data faithfully, so that the whole CRM system is not a simple information input and query tool any more, but can provide a sales scheme through big data and intelligent analysis. The invention can also supplement the big data knowledge base by tracking the whole selling link, solves the problem that the customers need to be maintained depending on the professional degree and experience of the salesman in the past, meets the requirements of the customers, changes the mode of the selling visit, improves the efficiency of the selling visit and reduces the threshold of the selling visit.
< second embodiment >
Fig. 2 schematically shows a block diagram of a customer demand analysis system for a steam distribution based on a customer relationship management system according to a preferred embodiment of the present invention.
As shown in fig. 2, the system for analyzing the demand of the steam distribution customer based on the customer relationship management system according to the preferred embodiment of the present invention includes: the system comprises a system customer information intelligent aggregation module 100, a customer data automatic extraction and sorting processing module 200, a customer behavior analysis and representation processing module 300 and a customer interaction suggestion processing module 400.
The system customer information intelligent aggregation module 100 is configured to integrate information of customers on each platform system including a self-built system and a third-party system to form integrated personal information of each customer, and store the integrated personal information into a customer relationship management system.
For example, the self-built system comprises an enterprise internal ERP system, a vehicle type part inquiry and quotation platform, a vulnerable part mall, an electronic catalog EPC inquiry system and the like, and the third-party system comprises a WeChat public number, a WeChat applet, a WeChat contact platform, a nailing external contact platform and the like.
The client has unique user characteristic information (characteristic value) on each platform, such as head portrait, nickname, mobile phone number, micro-signal, registration information, authentication information and the like of the user. The user characteristic values of all the platform systems are extracted, account numbers belonging to the same customer on all the platform systems are related to a customer entity through cross comparison of user characteristic information, and the user information of the account numbers belonging to the same customer on all the platform systems is integrated into comprehensive personal information of the customer entity, so that intelligent aggregation of customer information is achieved.
Through the integration of the module, each system is not an isolated island of information, but the information of each system interacts with each other to form a user behavior network.
The client data automatic extraction and arrangement processing module 200 is used for arranging the integrated personal information and extracting the client identity related information and the client behavior information from the integrated personal information.
Specifically, for example, the customer identity-related information includes data such as store names, customer statuses, customer ratings, customer sources, business types, contact calls, store addresses, customer properties, business subjects, importance levels, WeChat contacts, QQ numbers, mailboxes, and the like; the customer behavior information comprises customer historical transaction data details, customer real-time transaction data, customer inquiry quotation information, customer inquiry preference and the like.
The customer behavior analysis and representation processing module 300 is used for dynamically maintaining the state information and the business information of the customer in the customer relationship management system by analyzing the extracted customer identity related information and the customer behavior information, and forming the customer representation according with the customer characteristics.
Specifically, the extracted and sorted customer behavior and information data are analyzed. For example, the main operation range, monthly transaction amount and client state of a client can be analyzed through the historical transaction data of the user, dynamic commodity recommendation can be performed through the real-time transaction data of the user, and the special vehicle repair system, operation type and quality preference of the client can be analyzed through inquiring quotation information of the client. By analyzing the customer behavior data, the data such as the status, classification, business type, business scope, etc. of the customer are dynamically maintained, and finally, a user portrait (customer portrait) conforming to the customer characteristics is formed.
The customer interaction suggestion processing module 400 is configured to present customer interaction suggestions based on the user representation.
The user portrait is formed through the analysis of the customer behavior, and after the user portrait is relatively accurate, the user can be known as a large maintenance chain or a small individual maintenance shop; whether to engage in the project of fast maintenance or accident car maintenance; what is the brand quality of the commonly used accessories; what the transaction period of the customer is, etc. Based on the data, the intelligent inference about when the customer needs to trade and the type and quantity of the traded goods provides reference for the salesperson.
The geographic position of the customer is determined in the customer data extraction, and intelligent visiting route planning and intelligent warehouse logistics planning can be carried out.
Likewise, based on the invention, the salesperson does not need to input complicated information, and only needs to reflect the whole transaction data really, so that the whole CRM system is not a simple information input and query tool any more, but can give out a sales scheme through big data and intelligent analysis. The invention can supplement the big data knowledge base by tracking the whole sales link, solves the problem that the customers need to be maintained depending on the professional degree and experience of the sales staff in the past, meets the requirements of the customers, changes the mode of the sales visit, improves the efficiency of the sales visit and reduces the threshold of the sales visit.
< specific examples >
System customer intelligent aggregation
The salesperson adds the client A as a WeChat friend, establishes a WeChat group and can acquire the head portrait and the nickname of the client A.
The client A pays attention to the WeChat public number, and can acquire the head portrait, the nickname and the ID of the WeChat opening platform of the client A.
The client A registers an account number in the WeChat applet, and can obtain the head portrait, the nickname, the WeChat open platform ID and the client mobile phone number of the client A.
Through the cross comparison of the client information of the three channels, the client can be associated through the head portrait, the nickname and the WeChat open platform ID of the client, and the head portrait, the nickname, the WeChat open platform ID and the client mobile phone number of the client A can be obtained.
Through the mobile phone number of the customer, the information of the customer A in a vulnerable part mall and the information of an ERP system in an enterprise can be obtained. Therefore, users of all the systems can be aggregated, the chat records of the client A and the salespersons on the WeChat, the operations carried out on the public numbers and the small programs and the transaction conditions of the mall and the ERP system can be aggregated, the purpose of client aggregation is achieved, and the client A can be known more comprehensively.
Automatic extraction and arrangement of customer data
When the sales are in daily visit, store names, customer states, customer grades, customer sources, operation types, contact calls, store addresses, customer properties, operation subjects, importance degrees, WeChat contacts, QQ numbers, mailboxes and other data need to be maintained.
The client states include: potential customers, initial contact, follow-up on hold, bargained customers, loyal customers, invalid customers.
The customer classification comprises: first class repair plants, second class repair plants, and third class repair plants.
The customer sources include: introduction of acquaintances, online and offline pushing, network popularization, channel agency and active contact.
The operation types comprise: quick repair, comprehensive, tyre, special repair, 4S.
The client properties include: enterprise customers, individual customers.
In this example, for example, customer status of customer A is a business customer, customer rating is a type of service shop, customer source is acquaintance introduction, business type is specialization, and customer nature is an enterprise customer.
Through customer aggregation, the behavior and transaction of customer A on other platforms and systems can be obtained.
In this example, customer a made 5 orders, 5 accumulators, 10 oil filters, and 100 liters of oil, respectively, by a salesperson's visit in the last month, for example. Meanwhile, the price inquiry of the parts of the galloping car is carried out for 8 times in the last month. The inquiry of the running car fitting is often made in an electronic catalog system.
Customer behavior analysis and portrayal
Through the arrangement of the basic information and the analysis of the transaction data, the transaction preference and the behavior preference of the customer can be obtained, and the transaction amount of the customer can be predicted.
In this example, the transaction data for customer a is, for example, 5 watts of battery purchased in a month, 10 muller oil filters, and 100 liters of jaboticaba oil. And has 8 inquiries for the car running. The query of the galloping car fitting is queried in an electronic catalog query system for a plurality of times.
Through data analysis, the basic situation of considering the client a is that the client state is a transaction client, the client classification is a maintenance factory, the client source is introduced by an acquaintance, the operation type is a special repair, and the client property is an enterprise client, so that a conclusion can be drawn:
through inquiry and inquiry adaptation, the client A can be known to be a special repair shop for the galloping cars, and most of the entering cars are galloping cars.
Through historical transaction analysis, it can be known that the monthly purchase amount of the client A is about 5 ten thousand.
From the purchasing brand perspective, customer A's purchasing preference is an international brand consumable part.
Through price inquiry data analysis, the main business of the client A is the quick maintenance of the galloping vehicle, and the client A also has the capability of maintaining the accident vehicle.
Customer interaction advice
A relatively accurate customer representation can be obtained from customer behavior analysis, and the characteristics of the customers are combined with sales experience and big data analysis, so that the sales can be helped to better grasp the requirements of the customers.
In this example, it can be known that the purchase frequency of the client a is about 5 units/month, and the sales can make a visit once per week, so the visit reminder to the sales client a appears once per week. And preferably recommending the vulnerable parts of the international large brand adapted to the type of the galloping vehicle in consideration of the purchasing preference of the client A. According to the purchase amount of the client A, the client can be considered to lay goods in storage batteries, oil filters and engine oil products, and high-end brand recommendation can be carried out in products such as spark plugs, brake pads and shock absorbers.
On the one hand, the customer representation may provide recommendations to the sales person when visiting online. On the other hand, the customer representation is also used in the customer online system.
In this example, it is determined that the exclusive brand of customer A is a running brand, the category is primarily vulnerable parts, the brand of accessories is a large international brand, and the system automatically predicts the query result that customer A would like based on the big data and sales experience based on these preferences when the customer next uses the query system or places an order online, for example.
It should be noted that the terms "first", "second", "third", and the like in the description are used for distinguishing various components, elements, steps, and the like in the description, and are not used for indicating a logical relationship or a sequential relationship between the various components, elements, steps, and the like, unless otherwise specified.
It is to be understood that while the present invention has been described in conjunction with the preferred embodiments thereof, it is not intended to limit the invention to those embodiments. It will be apparent to those skilled in the art from this disclosure that many changes and modifications can be made, or equivalents modified, in the embodiments of the invention without departing from the scope of the invention. Therefore, any simple modification, equivalent change and modification made to the above embodiments according to the technical essence of the present invention are still within the scope of the protection of the technical solution of the present invention, unless the contents of the technical solution of the present invention are departed.
Claims (10)
1. A steam distribution customer demand analysis method based on a customer relationship management system is characterized by comprising the following steps:
the first step is as follows: executing system customer information intelligent aggregation processing, integrating the information of customers on each platform system including a self-built system and a third-party system to form comprehensive personal information of each customer, and storing the comprehensive personal information into a customer relationship management system;
the second step is as follows: performing automatic extraction and arrangement processing of client data, arranging the comprehensive personal information, and extracting client identity related information and client behavior information from the comprehensive personal information;
the third step: performing customer behavior analysis processing, and dynamically maintaining state information and operation information of customers in a customer relationship management system by analyzing the extracted customer identity related information and customer behavior information;
the fourth step: and executing the client interaction suggestion processing, and giving client interaction suggestions based on the user portrait.
2. The method for analyzing the requirements of the automobile parts customers based on the customer relationship management system as claimed in claim 1, wherein in the first step, the user characteristic information of each platform system is extracted, the account numbers belonging to the same customer on each platform system are associated to a customer entity through cross comparison of the user characteristic information, and the user information of the account numbers belonging to the same customer on each platform system is integrated into the comprehensive personal information of the customer entity, so as to realize intelligent aggregation of the customer information.
3. The customer relationship management system-based automobile distribution customer demand analysis method according to claim 1 or 2, wherein the self-built system comprises an enterprise internal ERP system, a vehicle type part price inquiry and quotation platform, a vulnerable part mall and an electronic catalog EPC inquiry system, and the third party system comprises a WeChat public number, a WeChat applet, a WeChat contact platform and a nailed external contact platform.
4. The automobile distribution customer demand analysis method based on the customer relationship management system according to claim 1 or 2, characterized in that the customer identity related information comprises store names, customer states, customer grades, customer sources, operation types, contact calls, store addresses, customer properties, operation subjects, importance degrees, WeChat contacts, QQ numbers, mailboxes; the customer behavior information comprises the details of the historical transaction data of the customer, the real-time transaction data of the customer, price inquiring information of the customer and the inquiry preference of the customer.
5. The analysis method for the demand of the steam distribution customer based on the customer relationship management system as claimed in claim 1 or 2, wherein the customer interaction suggestion comprises: customer visit suggestions, customer visit route planning suggestions and warehouse logistics planning suggestions.
6. A steam distribution customer demand analysis system based on a customer relationship management system is characterized by comprising: the system comprises a system client information intelligent aggregation module, a client data automatic extraction and arrangement processing module, a client behavior analysis and portrait processing module and a client interaction suggestion processing module;
the system customer information intelligent aggregation module is used for integrating information of customers on each platform system including a self-built system and a third-party system to form comprehensive personal information of each customer and storing the comprehensive personal information into a customer relationship management system;
the client data automatic extraction and arrangement module is used for arranging the comprehensive personal information, extracting client identity related information and extracting client behavior information from the comprehensive personal information;
the client behavior analysis processing module is used for dynamically maintaining the state information and the operation information of the client in the client relationship management system by analyzing the extracted client identity related information and the client behavior information;
the client interaction suggestion processing module is used for giving client interaction suggestions based on the user representation.
7. The system of claim 6, wherein the intelligent aggregation module extracts the user characteristic information of each platform system, cross-compares the user characteristic information, associates the accounts of the same customer on each platform system with a customer entity, and integrates the user information of the accounts of the same customer on each platform system into the comprehensive personal information of the customer entity, so as to achieve intelligent aggregation of the customer information.
8. The customer relationship management system-based automobile distribution customer demand analysis system according to claim 6 or 7, wherein the self-built system comprises an enterprise-internal ERP system, a vehicle type part price inquiry and quotation platform, a vulnerable part mall, an electronic catalog EPC inquiry system, and the third-party system comprises a WeChat public number, a WeChat applet, a WeChat contact platform and a nailed external contact platform.
9. The automobile distribution customer demand analysis system based on the customer relationship management system according to claim 6 or 7, wherein the customer identity related information comprises store names, customer statuses, customer grades, customer sources, operation types, contact calls, store addresses, customer properties, operation subjects, importance levels, WeChat contacts, QQ numbers, mailboxes; the customer behavior information comprises the details of the historical transaction data of the customer, the real-time transaction data of the customer, price inquiring information of the customer and the inquiry preference of the customer.
10. The customer relationship management system-based steam distribution customer demand analysis system according to claim 6 or 7, wherein the customer interaction suggestions comprise: customer visit suggestions, customer visit route planning suggestions and warehouse logistics planning suggestions.
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Cited By (2)
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| CN111708811A (en) * | 2020-05-27 | 2020-09-25 | 北京嗨学网教育科技股份有限公司 | Visitor data management method and device, electronic equipment and storage medium |
| CN113327138A (en) * | 2021-06-30 | 2021-08-31 | 北京百易数字技术有限公司 | Marketing customer data management method and system |
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