Customer information management system

Abstract

The invention discloses a client information management system. The system comprises a client information integration module, a data updating and maintaining module, a data encryption and storage module and a data analysis and mining module, the customer information integration module is used for integrating the customer information and the business information and screening out interested data in the customer information; the data updating and maintaining module is used for updating customer information regularly and tracking service information; the data encryption storage module is used for establishing storage spaces for different clients and storing the storage spaces into an information base in a unified encryption mode; and the data analysis and mining module is used for carrying out business mining on the interested data and the business information, generating sales suggestions and pushing the sales suggestions. Through the technical scheme of the invention, the communication efficiency between the enterprise and the customer can be improved, and the customer satisfaction and the performance can be improved.

Description

Technical Field

[0001] The present invention relates to the technical field of information management, and in particular to a customer information management system. Background Art

[0002] As market competition intensifies, companies need to better understand customer needs and provide personalized services and market strategies to maintain competitiveness and improve performance. However, traditional customer management methods have many problems, such as scattered customer data, incomplete information, and cumbersome sales processes. There is a lot of room for improvement in current customer management methods.

[0003] In order to solve these problems and improve the communication efficiency and management level between the company and its customers, it is urgently necessary to develop a new customer management platform that can centrally manage and analyze customer information, provide comprehensive customer data integration and analysis functions, assist companies in understanding customer needs, formulate personalized marketing strategies, and optimize marketing processes, thereby improving customer satisfaction and performance. Summary of the invention

[0004] In view of this, the purpose of the present invention is to provide a customer information management system to achieve the maintenance and development of customer information and enhance the comprehensive analysis capability of customer needs.

[0005] In a first aspect, an embodiment of the present invention provides a customer information management system, including:

[0006] The customer information integration module is used to integrate customer information and business information, discard invalid data and delete duplicate data, and filter out the data of interest in customer information;

[0007] The data update and maintenance module is used to regularly update customer information and track business information, and feed back the updated customer information and business information to the data analysis and mining module;

[0008] The data encryption storage module is used to establish storage space for different customers and store the data in the information base in a unified encryption method;

[0009] The data analysis and mining module is used to conduct business mining on the data of interest and business information, generate sales suggestions and push them;

[0010] Among them, customer information includes: customer's text data, behavior data, image data, and video data.

[0011] Furthermore, the customer information integration module includes: an identity verification unit, an information processing unit and a label unit;

[0012] The identity verification unit is used to query the source of customer information and business information, determine the registration information of the information source, determine whether the registration information of different information sources is consistent, and bind the customer information and business information with consistent registration information;

[0013] The information processing unit is used to filter out the data of interest from the customer information;

[0014] The label unit is used to label the customer accordingly according to the data of interest.

[0015] Furthermore, the information processing unit includes: an information classification subunit; the information classification subunit is used to classify different customers into different priorities according to the data of interest, and is also used to convert customer information and business information into different data transmission formats.

[0016] Furthermore, the data update and maintenance module includes: a feedback unit and an update unit;

[0017] The feedback unit is used to provide feedback to the update unit when the customer information or business information changes;

[0018] The updating unit is used to instruct the customer information integration module to update the data according to the changed data information.

[0019] Furthermore, the data encryption storage module includes: a data encryption and decryption unit, a data grouping unit;

[0020] The data encryption and decryption unit is used to encrypt the integrated customer information and business information into an unreadable form, and decrypt it when querying the customer information and business information;

[0021] The data grouping unit is used to group and store the integrated customer information and business information.

[0022] Furthermore, the data analysis and mining module includes: a data matching unit and a project pushing unit;

[0023] The data matching unit is used to generate a business recommendation report for the customer based on the data of interest and the business information using a recommendation algorithm;

[0024] The project push unit is used to push customers to business personnel and push services to customers after the data matching unit generates a service recommendation report.

[0025] Furthermore, the recommendation algorithm includes at least one of collaborative filtering recommendation, content-based recommendation, knowledge-based recommendation, and hybrid recommendation.

[0026] Furthermore, the data matching unit is also used to extract implicit information from the data of interest and business information using machine learning to generate a business recommendation report for the customer.

[0027] Compared with the prior art, the present invention has the following beneficial effects:

[0028] The technical solution of the embodiment of the present invention integrates customer information and business information through a customer information integration module, discards invalid data and deletes duplicate data, and filters out data of interest in the customer information; the data update and maintenance module regularly updates customer information, tracks business information, and feeds back to the data analysis and mining module; the data encryption storage module establishes storage space for different customers, and stores it in the information database in a unified encryption method; the data analysis and mining module performs business mining on data of interest and business information, generates sales suggestions and pushes them, thereby realizing the maintenance of customer information and improving the comprehensive analysis capability of customer needs.

[0029] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present invention, nor are they intended to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0031] Figure 1 It is a structural diagram of a customer information management system provided according to the first embodiment of the present invention. DETAILED DESCRIPTION

[0032] The present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It is to be understood that the specific embodiments described herein are only used to explain the present invention, rather than to limit the present invention. It should also be noted that, for ease of description, only parts related to the present invention, rather than all structures, are shown in the accompanying drawings.

[0033] Embodiment 1

[0034] Figure 1 This is a structural diagram of a customer information management system provided in Embodiment 1 of the present invention. This embodiment is applicable to situations where customer information is managed. Figure 1As shown, the system includes: a customer information integration module 10, a data update and maintenance module 20, a data encryption storage module 30 and a data analysis and mining module 40.

[0035] In the embodiment of the present invention, the customer information management system can be developed with actual application as the background, Java language as the development language, JSP design page, Tomcat server as the Web server, and MySQL database as the data storage, so as to ensure the stability of the system.

[0036] In summary, modules are connected by communication, and the system has the ability to select and integrate technologies. During project development, it selects appropriate development frameworks, technical tools, and databases. The system has the ability to understand and evaluate various technologies, and can select appropriate technologies for development based on project requirements. It can also be deeply integrated with the company's existing systems to provide comprehensive enterprise management solutions.

[0037] The customer information integration module 10 is used to integrate customer information and business information, discard invalid data and delete duplicate data, and filter out data of interest.

[0038] Among them, customer information includes: customer text data, behavior data, image data, and video data. Business information includes orders, contracts, invoices, and other information generated by services, products, or projects.

[0039] In the embodiments of the present invention, in addition to the information already entered by the system, customer information may also include third-party information obtained through a third party, and in addition to the information already entered by the system, business information may also include third-party information obtained through a third party. Customer information may be information obtained through any formal channels, including: social networking sites or software, public accounts, phone records, third-party open platforms, etc. This information exists in the form of text, behavior, images or videos on various public web pages or platforms, and can be legally obtained through crawler technology.

[0040] It should be noted that the customer's text data includes: chat records, information registration, personal sharing, etc., and the customer's behavior data includes: attention, likes, comments, browsing history, rewards, etc. on social platforms. Through the customer's behavior data, we can preliminarily screen out the information that the customer is interested in. The customer's image data and video data include: chat records, personal sharing, etc.

[0041] The customer information integration module 10 specifically includes: an identity confirmation unit 101 , an information processing unit 102 and a label unit 103 .

[0042] The identity verification unit 101 is used to query the sources of customer information and business information, determine the registration information of the information source, judge whether the registration information of different information sources is consistent, and bind the customer information and business information with consistent registration information.

[0043] In an embodiment of the present invention, customer information and business information come from a variety of different channels, including customer information manually entered by marketing personnel, information crawled from third-party websites, and personal information left by customers during the loan or other business processing. The sources of customer information and business information are required to be highly reliable. According to the reliability of different information sources during registration or registration, it is necessary to eliminate invalid information for information acquisition sources with low reliability. Subsequently, the customer information and business information are bound, and a unique number is assigned to the customer after the information is bound. After all reliable data from different sources are collected, duplicate data is removed. The identity verification unit 101 completes the elimination of invalid information and the deletion of duplicate information while performing the binding process of customer information and business information.

[0044] The information processing unit 102 is used to filter out interesting data from the customer information and business information.

[0045] In an embodiment of the present invention, the data of interest in the customer information includes: querying business keywords from text data, identifying business products of interest to customers from image and video data, and determining the business fields of interest to customers from customer behavior data. For text data, a business keyword vocabulary is established. When business keywords appear in text data, the content in the text data is marked and the number of times each business keyword appears is recorded. For image and video data, image recognition technology is used to identify target objects in images or video frames, and the features of the target objects are matched with the product features in the product library. For behavioral data, the information of interest to customers is preliminarily screened out based on the business fields of interest to customers.

[0046] The information processing unit 102 specifically includes: an information classification subunit 1021 .

[0047] The information classification subunit 1021 is used to classify different customers into different priorities according to the data of interest, and is also used to convert customer information and business information into different data transmission formats.

[0048] In an embodiment of the present invention, different customers may have different interests in different products or services, which will be reflected in their personal business records or personal social information. Through preliminary data screening, the products or services that customers are interested in can be preliminarily obtained. The information classification subunit 1021 marks customers with high adaptability as high priority and customers with low adaptability as low priority according to the adaptability of the product or service to the customer. In addition, the information classification subunit 1021 can also classify customer information and business information, and convert the text, behavior, image, and video in the customer information into different data formats, for example: converting text into data tables, data sets, etc., to facilitate subsequent matching and push. Convert the information in the business information into formats such as XML and JSON to facilitate subsequent processing and analysis.

[0049] The label unit 103 is used to label the customer accordingly according to the data of interest.

[0050] The identity verification unit 101 assigns a unique number to the customer after the information is bound. The label unit 103 labels the customer with one or more labels based on the business keywords in the text data of different customers, the business products in the image and video data, and the business fields in the behavior data. In this embodiment, the data analysis and mining module 40 quickly classifies or clusters the customers through the customer's labels. The label unit 103 can not only label the customers, but also label special customers and special reasons.

[0051] In an embodiment of the present invention, the customer information integration module 10 first checks the customer information from different sources, discards invalid data and deletes duplicate data after confirming the identity of the customer, and filters out the data of interest. It then unifies different data transmission formats for different types of data, and finally labels the customer according to the data of interest to achieve integration of multi-source information.

[0052] In summary, the customer information management system has the ability to integrate and manage data. The customer management platform needs to integrate a large amount of customer data, including basic information, transaction records, etc., requiring the system to design and implement efficient data storage and management mechanisms to ensure data security, integrity and accessibility.

[0053] The data update and maintenance module 20 is used to regularly update customer information and track business information, and feed back the updated customer information and business information to the data analysis and mining module 40.

[0054] In the embodiment of the present invention, customer information and business information may change at any time, and the data update and maintenance module 20 sets a fixed period to query customer information and business information. When customer information changes, first determine whether the changed information is invalid or duplicate information based on the source of the customer information change, and then update the data of interest based on the changed customer information. When business information changes, track the signing or cancellation of the business.

[0055] The data updating and maintaining module 20 includes: a feedback unit 201 and an updating unit 202 .

[0056] The feedback unit 201 is used to provide feedback to the updating unit 202 when the customer information or the service information changes.

[0057] Specifically, changes in customer information include changes in registration information, updates in social information, etc. For changes in registration information, the changed customer information is treated as a new customer and a new customer number is assigned. For updates in social information, data of interest is filtered out based on the updated customer information.

[0058] In the embodiment of the present invention, the feedback unit 201 establishes a connection relationship with the data source of each third-party information, reads the data update in each data source in real time, and then feeds back to the update unit 202. After the update unit 202 confirms that the updated data is valid data, it instructs the customer information integration module 10 to integrate the data information again to ensure the consistency of the third-party information data and the integrated data in the customer information integration module 10, such as data comparison, update, conflict, and resolution to prevent data duplication, omission, error, inconsistency, etc. The feedback unit 201 is also used to collect customer feedback for the corresponding business when the business information is updated. The customer feedback includes: satisfaction feedback, cancellation reasons, rejection reasons, complaint information, etc.

[0059] In summary, the function of the feedback unit 201 is to monitor the changes of the third-party data in real time, and when the data changes are detected, the feedback update unit 202 confirms whether the updated data is valid data. Valid data means that the third-party information source is reliable and does not belong to the data that already exists in the integrated data.

[0060] The updating unit 202 is used to instruct the customer information integration module 10 to update the data according to the changed data information.

[0061] When the feedback unit 201 detects data changes, the update unit 202 first checks the changed data with the integrated data to determine whether the updated data is reliable and whether it already exists in the integrated data, and then instructs the customer information integration module 10 to integrate the data again and feed back to the data analysis and mining module 40.

[0062] In the embodiment of the present invention, the update unit 202 needs to rely on the feedback unit 201 for feedback on external data, and for the inherent internal information retained by the customer in the information management system, the internal staff can modify the customer reserved information according to their own modification authority, and the update unit 202 records the modification history. The modified information enters the integrated data to complete the replacement and establishes a mapping with the information before the modification. When the information before the modification expires, it is discarded. The customer reserved information may include: reserved phone number, work information, address information, etc.

[0063] The data encryption storage module 30 is used to create storage spaces for different customers and store the data in the information base in a unified encryption manner.

[0064] The data encryption storage module 30 specifically includes: a data encryption and decryption unit 301 and a data grouping unit 302 .

[0065] In an embodiment of the present invention, the system also includes a customer query module for facilitating internal employees to query customer information and business information, and the information accessed by the customer query module exists in the data encryption storage module 30, specifically in the storage space allocated by the data grouping unit 302.

[0066] The data encryption and decryption unit 301 is used to encrypt the integrated customer information and business information into an unreadable form, and decrypt it when querying the customer information and business information.

[0067] In an embodiment of the present invention, the data encryption and decryption unit 301 adopts data serialization, data compression, data encryption and other technologies to ensure the security of the data transmission process, and prevents data leakage, tampering, forgery, illegal access, etc. by encoding, compressing, encrypting, decrypting, verifying and authorizing the data.

[0068] The data grouping unit 302 is used to group and store the integrated customer information and business information.

[0069] In the embodiment of the present invention, grouping and aggregation help to easily implement data analysis using various functions. Different customers can be divided into different categories according to their importance. The customer information and business information of the same customer are stored in the same group. In the group, the compressed packages of text data, behavior data, image data, and video data are stored in different units according to the data type. Business information is stored separately in a new unit to ensure that when customer information or business information is updated, the system can quickly locate the updated customer information. In particular, when internal employees modify customer information, the customer information needs to be replaced and mapped with the information before the modification, and rapid positioning and replacement are required.

[0070] In the embodiment of the present invention, the function of the data integration storage module 30 is to integrate a large amount of customer data for the customer management platform, including basic information, transaction records, etc. This requires the system to design and implement an efficient data storage and management mechanism to ensure the security, integrity and accessibility of the data.

[0071] The data analysis and mining module 40 is used to perform business mining on the data of interest and business information, generate sales suggestions and push them.

[0072] The data matching unit 401 is used to generate a business recommendation report for a customer based on the data of interest and the business information by using a recommendation algorithm.

[0073] The recommendation algorithm includes at least one of collaborative filtering recommendation, content-based recommendation, knowledge-based recommendation, and hybrid recommendation.

[0074] Collaborative filtering recommendation uses the past behavior of existing customer groups to predict which services, products or projects the current user is most likely to like, including: customer-based collaborative filtering and product-based collaborative filtering. Customer-based collaborative filtering recommends services that other customers with similar interests like to customers, and product-based collaborative filtering recommends products similar to the products he liked before. The core of collaborative filtering recommendation is: assuming that people are like birds of a feather, customers have similar behaviors, and their needs and preferences are also similar. The required input data includes customer records, context parameters, and group data.

[0075] Content-based recommendation is to evaluate the similarity between products that the customer has not seen and the items that the current customer liked in the past. First, some features are extracted for each product to represent the product, and then the feature data of the products that a customer liked (and disliked) in the past are used to learn the customer's preferences. Finally, based on the candidate product representation and customer preferences, the n items that the user is most likely to be interested in are generated for the user. The core of content-based recommendation is to follow the principle of "constant in the face of change" and recommend similar products based on the products that the user liked in the past. The required input data includes customer records, context parameters, and product features.

[0076] Knowledge-based recommendation refers to recommendations that rely on information sources that are not used by collaborative filtering and content-based recommendation. It relies on detailed knowledge of product features. Customer needs may be expressed as demand values ​​or threshold ranges for product features. Product features include information such as product prices and functions. The core of knowledge-based recommendation is that it is assumed that there will be additional information sources, that is, explicit personalized knowledge. The required input data includes user records and context parameters, product features, and knowledge models.

[0077] Hybrid recommendation combines collaborative filtering recommendation, content-based recommendation, and knowledge-based recommendation.

[0078] The data matching unit 401 is also used to extract implicit information from the data of interest and the business information by using machine learning to generate a business recommendation report for the customer.

[0079] Machine learning includes three categories: regression, classification, and clustering. Regression methods include: least squares method, polynomial regression and other regression learning methods, simulate the customer's business processing regression curve, determine the customer's business demand model, and explore the periodicity and seasonal characteristics of the curve. Classification methods include: perceptron, deep learning, decision tree, random forest and other classification methods to classify the business needs of different customers. Clustering methods include: K-means, density clustering, principal component analysis and other clustering methods, clustering customers in space according to customer information and business information, analyzing the main factors affecting customer business processing and predicting the business processing needs of customers of the same type. On the basis of labeling the customer by the label unit 103, the efficiency of regression, classification and clustering is significantly improved.

[0080] In an embodiment of the present invention, the data matching unit 401 has a built-in recommendation algorithm. The recommendation algorithm matches customers with businesses based on the data of interest and business information screened by the data integration module 10, and screens out products with high matching degrees from the product library. The data matching unit 401 also has a machine learning algorithm for extracting implicit information and generating a recommendation report for reference by internal business personnel.

[0081] The business push unit 402 is used to push customers to business personnel and push services to customers after the data matching unit 401 generates a business recommendation report.

[0082] In an embodiment of the present invention, the business push unit 402 pushes customers who are qualified to handle business to marketing personnel, and through the data matching unit 401, the in-depth mining of customers allows the marketing personnel to accurately provide project services to customers. At the same time, customers can also register and log in to the system as visitors after providing reliable identity information. The business push unit 402 pushes product information, service information or project information to the customer's homepage based on the customer's business recommendation report.

[0083] In summary, the function of the data analysis and mining module 40 is to provide in-depth analysis and mining of customer data. The customer information management system in the embodiment of the present invention has powerful data analysis and mining capabilities, can apply machine learning and data mining algorithms, extract useful information and business opportunities from massive data, and generate visual reports and insights.

[0084] Furthermore, the customer information management system in the embodiment of the present invention may also include: a user authority allocation module.

[0085] In the embodiment of the present invention, the user logs in to the customer information management system by registering an account and receiving a verification code. In addition to internal employees, external customers can enjoy the rights of registering an account as a visitor. The user rights allocation module allocates different rights to internal employees and external customers according to the identity of the user to ensure the safe operation of the system. Internal employees can perform operations such as customer information query, order query, and information modification in the system. Different levels of internal employees are assigned different levels and ranges of modification rights. External customers can perform information registration, service query, product query, business order, business tracking, and other operations in the system.

[0086] Furthermore, the customer information management system in the embodiment of the present invention may also include: a UI design module.

[0087] In the embodiment of the present invention, the UI design module designs different interfaces for different users, and can also adjust different rendering colors according to the user's personal preferences. The operation interface of internal employees and the operation interface of external customers are designed independently and connected through the communication module. The transaction information of external customers enters the operating system of internal employees through the communication module. The UI interface can be implemented by any one of JSP, jQuery, and BootStrap.

[0088] In summary, the system needs to improve the user interface design and user experience. In order to improve the user experience, the customer management platform needs to have a friendly user interface design and operation process, requiring the system to have good user experience design capabilities and be able to continuously optimize the interface and process based on user feedback.

[0089] Furthermore, the customer information management system in the embodiment of the present invention may also include: a push module.

[0090] In the embodiment of the present invention, the push module is used to push customer information of potential customers to internal employees, and at the same time, provide leisure and entertainment, advertising news, product projects and other services to external customers, and establish customer tags according to the customer's interest level.

[0091] Security and privacy protection: The customer management platform involves a large amount of sensitive customer data, which places high demands on security and privacy protection. The system development team needs to have professional knowledge and technical capabilities in information security to ensure the secure storage and transmission of data and prevent data leakage and abuse.

[0092] The embodiment of the present invention first realizes standardized data management by integrating customer information and business information and filtering out data of interest in customer information; then updates and maintains customer information and business information to ensure that the system can adapt to data updates in a timely manner; finally, business mining is performed on data of interest and business information to push highly adapted services to customers. The technical solution in the embodiment of the present invention not only improves management efficiency, optimizes marketing processes and personalized marketing; at the same time, it improves competitiveness, promotes enterprise development, and improves user experience and data-driven decision-making. These benefits help enterprises improve operational efficiency, reduce costs, enhance market competitiveness, and achieve sustainable development and innovation.

[0093] It will be appreciated by those skilled in the art that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, although the present invention has been described in detail with reference to the aforementioned embodiments. It will be appreciated by those skilled in the art that the present invention is not limited to the specific embodiments described herein, and that various obvious changes, readjustments and substitutions can be made by those skilled in the art without departing from the scope of protection of the present invention. Therefore, although the present invention has been described in more detail through the above embodiments, the present invention is not limited to the above embodiments, and may include more other equivalent embodiments without departing from the concept of the present invention, and the scope of the present invention is determined by the scope of the appended claims.

Claims

1. A customer information management system, characterized in that: include: Customer information integration module, data update and maintenance module, data encryption storage module and data analysis and mining module; The customer information integration module is used to integrate customer information and business information, discard invalid data and delete duplicate data, and filter out interesting data in customer information; The data update and maintenance module is used to regularly update customer information and track business information, and feed back the updated customer information and business information to the data analysis and mining module; The data encryption storage module is used to establish storage space for different customers and store the data in the information base in a unified encryption method; The data analysis and mining module is used to conduct business mining on the data of interest and business information, generate sales suggestions and push them; Among them, customer information includes: customer's text data, behavior data, image data, and video data.

2. The system according to claim 1, characterized in that The customer information integration module includes: an identity verification unit, an information processing unit and a label unit; The identity verification unit is used to query the source of customer information and business information, determine the registration information of the information source, determine whether the registration information of different information sources is consistent, and bind the customer information and business information with consistent registration information; The information processing unit is used to filter out the data of interest from the customer information; The label unit is used to label the customer accordingly according to the data of interest.

3. The system according to claim 2, characterized in that The information processing unit includes: an information classification subunit; the information classification subunit is used to classify different customers into different priorities according to the data of interest, and is also used to convert customer information and business information into different data transmission formats.

4. The method according to claim 1, characterized in that: The data update and maintenance module includes: a feedback unit and an update unit; The feedback unit is used to provide feedback to the update unit when the customer information or business information changes; The updating unit is used to instruct the customer information integration module to update the data according to the changed data information.

5. The system according to claim 4, characterized in that The data encryption storage module includes: a data encryption and decryption unit and a data grouping unit; The data encryption and decryption unit is used to encrypt the integrated customer information and business information into an unreadable form, and decrypt it when querying the customer information and business information; The data grouping unit is used to group and store the integrated customer information and business information.

6. The system according to claim 1, characterized in that The data analysis and mining module includes: a data matching unit and a project pushing unit; The data matching unit is used to generate a business recommendation report for the customer based on the data of interest and the business information using a recommendation algorithm; The project push unit is used to push customers to business personnel and push services to customers after the data matching unit generates a service recommendation report.

7. The system according to claim 6, characterized in that The recommendation algorithm includes: at least one of collaborative filtering recommendation, content-based recommendation, knowledge-based recommendation, and hybrid recommendation.

8. The system according to claim 6, characterized in that The data matching unit is also used to extract implicit information from the data of interest and business information using machine learning to generate a business recommendation report for the customer.

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