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An Application Study of Data Mining on Customer Relationship Management in Shanghai X Telecommunications Bureau

Author: XiaChangMing
Tutor: LiYing；WangXiaoGuang
School: East China University of Science and Technology
Course: Project Management
Keywords: Customer Relationship Management Data Mining Telecom Clustering Association Rules
CLC: F626
Type: Master's thesis
Year: 2011
Downloads: 120
Quote: 1
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Abstract


After several reforms and reorganizations, the marketing environment of China telecom industry has changed greatly, the competition between operators has become more and more fierce. As a customer-centric and advanced management concept, customer relationship management (CRM) achieves the growth of corporate profits and upgrade of operating level through satisfying the greatest interest of customers. If applying the advanced data analysis method--data mining to customer relationship management, the efficiency and level of customer relationship management can be greatly improved to support business operating decision. Most telecom companies have established the customer relationship management system, operational CRM and collaborative CRM have been widely used. Although analytical CRM is on the initial stage, the extensive data resources in established CRM systems provide adequate and space for the application of data mining in analytical CRM.This paper introduces some concepts, application status, and related theories of customer relationship management and data mining, and then specifies the value and application of data mining technique in customer relationship management. On that basis, it analyzes status of customer relationship management in Shanghai x telecommunications bureau, and introduces an example of customer relationship management based on association rules in the bureau, specifies the actual application procedure and process of data mining in telecommunication companies.The essay puts forward the method of using clustering model to direct data discretization in the data preparation stage. And by the use of association rules, analyzes telecom services with low rate of utilization through setting different minimum support and minimum confidence. Finally, the results are Analyzed and Enumerate the applications in active marketing, package bundle, improvement package, customer retention and so on. Systematically and roundly describes the practical application of data mining in customer relationship management of telecom enterprise. In conclusion, the paper has high theoretical and practical significance.

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