Telecom Customer Relationship Management Based On Data Mining Research

As an advanced "customer-oriented" management conception, customer relationship management can realize the target of maximum profit increase via the maximum customer benefit satisfaction. While data mining, as an advanced data analysis methodology, is an effective tool for the in-depth analysis of customer data. Customer relationship management system based on data mining is the ultimate application of customer relationship management of data mining, and the best approach to facilitate the enterprise to achieve the established target.In the customer relationship management field, which problems should be solved for the customer analysis? How to apply data mining technology to customer data model pertinently based on the data mining methodology? So far the systematic research on the aforementioned questions is still rare.The thesis firstly introduces the research background, the research status, concept of the customer relationship management and relevant theory; analyze the basic theory and characteristics of customer relationship management, and customer relationship analysis model, and expatiates customer relationship management from the perspective of economics and marketing theory. Subsequently, the thesis introduces the basic elements of data mining and the application model; apply the data mining technology to customer relationship management, based on the analysis of data mining technology and application model. Finally, detailed illustration with examples is made to the application of deepening customer relationship management via data mining. Based on the nature and consumption behavior of both lost customer and retained customer, data mining analysis is made to sketch the forecast model of lost customer, and analyze of which customer the probability of losing is relatively higher and the consumption behavior of the lost customer, and other elements leading to the losing of customer, to divide the customer of the telecom via data mining technology for accurate one-to-one marketing, and to prevent telecom fraud via data mining technology. At last, the thesis analyzes the CRBT users based on the data mining technology to promote mobile add-on product sales.