Big data customer obtaining processing method and system

Abstract

The invention relates to the technical field of customer source data acquisition, analysis and processing, in particular to a big data customer acquisition processing method which specifically comprises the following steps: inputting a feature site to retrieve enterprises around the feature site and obtain a retrieval data set; the retrieval data set is matched with a main database composed of cooperative clients, and a to-be-developed data set composed of non-cooperative clients and a to-be-confirmed data set composed of clients located in the main database but not located in the retrieval data set are obtained; business development activities are carried out on non-cooperative clients in the to-be-developed data set; and performing subsequent cooperation possibility confirmation on the clients in the to-be-confirmed data set, and deleting client data with low subsequent cooperation possibility from the main database so as to reduce the possibility that the performance of the main database is greatly influenced.

Description

Technical Field

[0001] The present application relates to the field of customer source data acquisition, analysis and processing technology, and in particular to a big data customer acquisition processing method and system. Background Art

[0002] Customer resources are important data for enterprises. In the past, there were two methods of acquiring customers: passive methods, such as advertising, and active methods, such as door-to-door sales and proactive communication at relevant exhibitions. However, this method required a lot of manpower. With the rapid development of big data technology, there is no need to spend a lot of manpower to acquire customer data.

[0003] For example, the information processing method, device, system and medium for acquiring customers with announcement number CN113139000B searches for companies registered in the vicinity of a designated location, and compares them with the data set of existing customers to obtain a data set composed of non-customer companies. Then, corresponding promotion and other business activities can be carried out in the non-customer data set.

[0004] Regarding the above-mentioned related technologies, the designated location is generally the location of the user from whom the customer source is to be acquired. In addition to newly registered companies, there may also be some deregistered or relocated companies around the user's location. At this time, this group of customers may not necessarily have the possibility of cooperation. If the customer data set with no possibility of cooperation continues to be retained in the database, it will increase the database's storage requirements and reduce the corresponding data query and operation speed in the database, which will have a significant impact on the database's performance. Summary of the Invention

[0005] In order to reduce the impact on database performance, the present application provides a big data customer acquisition processing method and system.

[0006] On the one hand, the present application provides a big data customer acquisition processing method that adopts the following technical solution.

[0007] A big data customer acquisition processing method specifically includes the following steps.

[0008] S1. Input a characteristic location to search for businesses around the characteristic location and obtain a search data set; S2. Match the search dataset with the master database consisting of cooperated customers to obtain a dataset to be developed consisting of uncooperative customers and a dataset to be confirmed consisting of customers in the master database but not in the search dataset; S3. Conduct business development activities for non-cooperative customers in the development dataset; S4. Confirm the possibility of subsequent cooperation for the customers in the confirmed data set, and delete the customer data with low possibility of subsequent cooperation from the main database.

[0009] By adopting the above technical solution, some customers with whom we have cooperated cannot be retrieved during the search process, that is, when the corresponding customer company may relocate or go bankrupt, the subsequent cooperation with the corresponding customer will be affected. After contacting the customer, once it is confirmed that there is no possibility of cooperation, the corresponding customer data can be deleted from the main database to reduce the accumulation of invalid data in the main database and reduce the impact on the performance of the main database.

[0010] Optionally, in step 1, a characteristic location is preset, and a search is performed for businesses around the preset characteristic location after a predetermined time interval.

[0011] By adopting the above technical solution, a location can be preset to conduct regular searches of surrounding businesses, so as to timely obtain potential customers around the preset location.

[0012] Optionally, the retrieval data set is classified according to the retrieval time to form a data table to be processed, and the data table to be processed is stored in the retrieval database.

[0013] By adopting the above technical solution, the search results at different times can be stored for reference, so as to analyze the situation and quantity of surrounding enterprises.

[0014] Optionally, the business development activity in S3 specifically includes the following steps: S31. Obtaining email addresses of enterprises and managers to form a target email address collection; S32. Sending customer development emails related to the business to the target mailbox collection; S33. When the customer acquisition email is opened and the browsing time is greater than or equal to the browsing time threshold, the customer data corresponding to the corresponding email address is stored in the high-interest customer database and direct marketing is carried out; S34. If the corresponding customer accepts cooperation, the corresponding customer data will be migrated to the main database; if the corresponding customer refuses to cooperate, the corresponding customer data will be deleted from the high-interest customer database; if the corresponding customer needs to be considered, the corresponding customer data will be retained in the high-interest customer database.

[0015] By adopting the above technical solution, non-cooperative customers are screened by sending emails first, and marketing activities are prioritized for customers who read the customer acquisition emails and browse for a certain period of time, so as to reduce waste of manpower.

[0016] Optionally, in S33, when the customer acquisition email is opened and the browsing time is less than the browsing time threshold, the customer data corresponding to the corresponding email address ID is stored in the low-interest customer database. After direct marketing is completed for each customer in the high-interest customer database, direct marketing is carried out for the customers in the low-interest customer database.

[0017] By adopting the above technical solutions, we can reduce the loss of some potential customers, make better use of manpower where it is needed, and make a more reasonable allocation of human resources.

[0018] Optionally, if the customer in the low-interest customer database accepts cooperation, the corresponding customer data will be migrated to the main database; if the corresponding customer refuses to cooperate, the corresponding customer data will be deleted from the low-interest customer database; if the corresponding customer needs to be considered, the corresponding customer data will be migrated to the high-interest customer database.

[0019] By adopting the above technical solution, the customer data in the low-interest customer database can be managed more reasonably.

[0020] Optionally, care emails are sent regularly to each customer in the high-interest customer database, and direct marketing is carried out to the corresponding customer after the care emails are opened.

[0021] By adopting the above technical solutions, the possibility of customer cooperation is increased.

[0022] Optionally, in S33, when the time length of sending the customer acquisition email is greater than or equal to the opening time length threshold and the customer acquisition email has not been opened, the customer data corresponding to the corresponding mailbox ID is stored in the low-interest customer database.

[0023] By adopting the above technical solution, when the customer acquisition email has not been opened for a long time, the customer may have the habit of changing the email address or not reading the email. In order to reduce the possibility of missing customer cooperation, it is also necessary to market to customers who have not read the customer acquisition email when there are sufficient human resources.

[0024] Optionally, when a customer acquisition email in at least one mailbox corresponding to a customer in the low-interest customer database is opened and the browsing time is greater than or equal to a browsing time threshold, the corresponding customer data is migrated from the low-interest customer database to the high-interest customer database.

[0025] By adopting the above technical solutions, we can conduct marketing activities to customers who are interested in the business in a timely manner and improve the success rate of customer cooperation.

[0026] Secondly, the big data customer acquisition processing system provided in this application adopts the following technical solution.

[0027] A big data customer acquisition processing system operates according to the above-mentioned big data customer acquisition processing method, including at least one terminal device and a server; the terminal device inputs and presets characteristic locations and transmits them to the server for retrieval, and the server distributes each customer data in the high-interest customer data or low-interest customer database to the terminal device for direct marketing.

[0028] By adopting the above technical solutions, customer data can be distributed, marketing activities can be carried out quickly and timely to customers who are interested in the business, and the success rate of cooperation can be improved.

[0029] In summary, this application has at least the following beneficial effects: Reduce the accumulation of invalid data in the primary database and reduce the impact on the primary database performance. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] Figure 1 It is a step-by-step diagram of a big data customer acquisition processing method; Figure 2 It is a logical block diagram of business development activities in S3 of a big data customer acquisition processing method. DETAILED DESCRIPTION

[0031] The present application is further described in detail below with reference to the accompanying drawings.

[0032] This application embodiment discloses a method for processing big data customer acquisition, referring to Figure 1 , specifically including the following steps.

[0033] S1. Input a feature location to search for businesses around the feature location and obtain a search dataset.

[0034] Among them, the characteristic location can be directly input or preset on the terminal device of the management personnel or business personnel. After the characteristic location is preset, the server can search for enterprises based on the preset location and the corresponding range value, such as enterprises within 100 kilometers around the company or the corresponding county or city, to collect enterprise data whose registered places meet the preset location conditions in the public industrial and commercial information of the Industrial and Commercial Bureau, etc., and classify them according to the search time to form several data tables to be processed, such as a search once a month or half a month. Each data table to be processed is stored in the search database, so as to analyze the growth number and type of enterprises around the characteristic location regularly, such as half a year or a year, to make fine adjustments to its own business.

[0035] S2. Match the search dataset with the main database consisting of cooperated customers to obtain a dataset to be developed consisting of uncooperative customers and a dataset to be confirmed consisting of customers in the main database but not in the search dataset.

[0036] The company name, corresponding personnel name, mobile phone number, email address, company revenue, etc. in the business information disclosed by each customer are integrated into a data record and classified into the corresponding data set to be developed or to be confirmed, so that when the terminal user opens the corresponding customer data, the terminal can display the detailed information of the corresponding customer to the corresponding management personnel or business personnel.

[0037] S3. Conduct business development activities for non-cooperative customers in the development dataset.

[0038] Among them, the business development activities in S3 specifically include the following steps.

[0039] S31. Obtain the mailboxes of enterprises and managers from the customer data to form a target mailbox collection.

[0040] S32. Send customer development emails related to the business to the target mailbox collection.

[0041] Among them, in order to classify customers later, it is necessary to know whether the customer opens the customer development email and how long they stay on the email content page. To this end, the email tracking function is used within a reasonable range to obtain real-time information on the status of the customer development email.

[0042] S33. When the customer acquisition email is opened and the browsing time is greater than or equal to the browsing time threshold, which may be 5-10 seconds, the customer data corresponding to the corresponding email ID is stored in the high-interest customer database and direct marketing is carried out.

[0043] Among them, direct marketing is to randomly distribute customer data in the high-interest customer database and send it to the business personnel's terminal. The corresponding business personnel will check the details of the corresponding customers and make immediate telephone contact to communicate the specific business situation and answer corresponding questions, so as to promote the achievement of cooperation in a timely manner.

[0044] S34. If the corresponding customer accepts cooperation, the corresponding customer data will be migrated to the main database; if the corresponding customer refuses to cooperate, the corresponding customer data will be deleted from the high-interest customer database; if the corresponding customer needs to be considered, the corresponding customer data will be retained in the high-interest customer database.

[0045] In addition, during S33, when the customer acquisition email is opened and the browsing time is less than the browsing time threshold, the customer data corresponding to the corresponding mailbox ID is stored in the low-interest customer database. After completing direct marketing for each customer in the high-interest customer database, direct marketing is carried out on the customers in the low-interest customer database. If the customer in the low-interest customer database accepts cooperation, the corresponding customer data is migrated to the main database; if the corresponding customer refuses cooperation, the corresponding customer data is deleted from the low-interest customer database; if the corresponding customer needs to be considered, the corresponding customer data is migrated to the high-interest customer database.

[0046] At the same time, in S33, when the time it takes to send a customer acquisition email is greater than or equal to the opening time threshold, which can be one week or two weeks, and the customer acquisition email has not been opened, that is, the corresponding customer is not interested or the customer is indeed busy or the customer has disabled email tracking, the customer data corresponding to the corresponding email address ID will be stored in the low-interest customer database, and when a business person is free, it will be assigned to the corresponding business person to understand the customer's details.

[0047] Since some customers in the high-interest customer database have certain cooperation intentions but have not yet reached a cooperation, it is necessary to follow up in real time to understand the customers' willingness and send care emails to each customer in the high-interest customer database on a regular basis. After the care emails are opened, direct marketing is carried out to the corresponding customers. For example, care emails are automatically sent every two weeks or one month, as well as on corresponding holidays.

[0048] At the same time, in order to further reduce the possibility of missing customers who are willing to cooperate, when the customer acquisition email or care email in at least one mailbox corresponding to the customer in the low-interest customer database is opened and the browsing time is greater than or equal to the browsing time threshold, the corresponding customer data will be migrated from the low-interest customer database to the high-interest customer database, and the customer will be promptly assigned to the business personnel's terminal for immediate direct marketing.

[0049] In addition, after the business personnel complete the direct marketing activities, they can set labels and make notes for the corresponding customers on the terminal so that management personnel can understand the corresponding customers' intentions when contacting the corresponding customers next time.

[0050] S4. Confirm the likelihood of subsequent cooperation for the customers in the pending confirmation dataset. This means assigning each customer in the pending confirmation dataset to the terminal of a corresponding business or management personnel. The corresponding personnel will immediately contact and communicate with the customer to understand the specific circumstances and reasons for the change in the customer's registered address and the customer's willingness for subsequent cooperation. The corresponding personnel will then mark the corresponding customer as "continued cooperation," "high likelihood of subsequent cooperation," "medium likelihood of subsequent cooperation," or "low likelihood of subsequent cooperation." Customers marked as "continued cooperation" will be retained in the master database. Customers marked as "high likelihood of subsequent cooperation" will be migrated to the high-interest customer database. Customers marked as "medium likelihood of subsequent cooperation" will be migrated to the low-interest customer database. Customers marked as "low likelihood of subsequent cooperation" will be deleted from the master database.

[0051] The implementation principle of a big data customer acquisition processing method in an embodiment of the present application is: timely confirming customers whose industrial and commercial addresses have changed in the main database. On the one hand, it can timely understand the customer's situation in order to judge subsequent cooperation, and on the other hand, it can timely delete customer data with low cooperation possibility from the main database to ensure that the performance of the main database during use is not greatly affected.

[0052] An embodiment of the present application also discloses a big data customer acquisition processing system, including at least one terminal device and a server; the terminal device inputs and presets characteristic locations and transmits them to the server for retrieval, and the server distributes each customer data in the high-interest customer database or the low-interest customer database to each terminal device in turn, and gives priority to allocating customer data in the high-interest customer database so that the business personnel of the corresponding terminal device can conduct direct marketing.

[0053] The implementation principle of a big data customer acquisition processing system in an embodiment of the present application is: first contact and communicate with customers with high cooperation willingness, and then take inventory of customers with low cooperation willingness, so as to reduce the tediousness of business personnel in analyzing and classifying customers, so that business personnel can carry out marketing activities more efficiently.

[0054] The above are all preferred embodiments of the present application, and are not intended to limit the scope of protection of the present application. Therefore, any equivalent changes made based on the structure, shape, and principle of the present application should be included in the scope of protection of the present application.

Claims

1. A big data customer acquisition processing method, characterized by: The specific steps include: S1. Input a characteristic location to search for businesses around the characteristic location and obtain a search data set; S2. Match the search dataset with the master database consisting of cooperated customers to obtain a dataset to be developed consisting of uncooperative customers and a dataset to be confirmed consisting of customers in the master database but not in the search dataset; S3. Conduct business development activities for non-cooperative customers in the development dataset; S4. Confirm the possibility of subsequent cooperation for the customers in the confirmed data set, and delete the customer data with low possibility of subsequent cooperation from the main database.

2. The big data customer acquisition processing method according to claim 1, characterized in that: In the step 1, a characteristic location is preset, and a search is performed on the surrounding enterprises of the preset characteristic location after a predetermined time interval.

3. The big data customer acquisition processing method according to claim 2, characterized in that: The retrieval data set is classified according to the retrieval time to form a data table to be processed, and the data table to be processed is stored in the retrieval database.

4. The big data customer acquisition processing method according to claim 1, characterized in that: The business development activities in S3 specifically include the following steps: S31. Obtaining email addresses of enterprises and managers to form a target email address collection; S32. Sending customer development emails related to the business to the target mailbox collection; S33. When the customer acquisition email is opened and the browsing time is greater than or equal to the browsing time threshold, the customer data corresponding to the corresponding email address is stored in the high-interest customer database and direct marketing is carried out; S34. If the corresponding customer accepts cooperation, the corresponding customer data will be migrated to the main database; if the corresponding customer refuses to cooperate, the corresponding customer data will be deleted from the high-interest customer database; if the corresponding customer needs to be considered, the corresponding customer data will be retained in the high-interest customer database.

5. The method for processing big data customer acquisition according to claim 4, characterized in that: In S33, when the customer acquisition email is opened and the browsing time is less than the browsing time threshold, the customer data corresponding to the corresponding email address ID is stored in the low-interest customer database. After direct marketing is completed for each customer in the high-interest customer database, direct marketing is carried out for the customers in the low-interest customer database.

6. The method for processing big data customer acquisition according to claim 5, characterized in that: If the customer in the low-interest customer database accepts cooperation, the corresponding customer data will be migrated to the main database; if the corresponding customer refuses to cooperate, the corresponding customer data will be deleted from the low-interest customer database; if the corresponding customer needs to be considered, the corresponding customer data will be migrated to the high-interest customer database.

7. A big data customer acquisition processing method according to claim 4 or 6, characterized in that: Caring emails are regularly sent to each customer in the high-interest customer database, and after the caring emails are opened, direct marketing is carried out to the corresponding customers.

8. The big data customer acquisition processing method according to claim 4, characterized in that: In the S33, when the time length of sending the customer acquisition email is greater than or equal to the opening time length threshold and the customer acquisition email has not been opened, the customer data corresponding to the corresponding mailbox ID is stored in the low-interest customer database.

9. The big data customer acquisition processing method according to claim 8, characterized in that: When a customer acquisition email in at least one mailbox corresponding to a customer in the low-interest customer database is opened and the browsing time is greater than or equal to the browsing time threshold, the corresponding customer data is migrated from the low-interest customer database to the high-interest customer database.

10. A big data customer acquisition processing system, operating according to a big data customer acquisition processing method according to any one of claims 1 to 9, characterized in that: The invention comprises at least one terminal device and a server; the terminal device inputs and presets characteristic locations and transmits the information to the server for retrieval; the server distributes each customer data in the high-interest customer data or low-interest customer database to the terminal device for direct marketing.

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