The Refined Marketing Of Telecommunication Operator Based On Data Mining

With the reforming of Chinese telecommunication industry's and the splitting of the telecommunication market, customers have more and more choices of the telecommunication products and operators, this status make the competitions in the telecommunication operators become more and more intense. The previous method, which extensively developing the market, extensively developing the client resources, extensively using the advertisements, has no effect now. On the other hand, operations in all business will bring more intense market competition, the value-added services in 3G will occupy a more important position, and the user's individual requirements will become more apparent. So the core of the front-end telecommunication services must be changed from the past "Extensive marketing" into "Refined Marketing". At the same time, the telecommunication industry is a typical data-intensive industry, which's business data containing a large number of valuable information to enterprises. After years of developments, the focus of research in the Data Mining technology is being applied to various fields. The "Refined Marketing" based on the Data Mining technology can help us to find the needs of customers, analysis of customer's behavior, evaluate customer's value, and then can help us to develop marketing strategies to meet the needs of individual customers.In this paper, after analyzing of the developments of China's telecommunication industry and the status of the telecommunication marketing, based on the relevant knowledge of "data mining" and " Refined Marketing", we research Data Mining technology's applications in Customer's segmentation, Cross-selling and Customer loss warning, and then we know that the "Refined Marketing" based on the Data Mining technology is an extremely important tool for the telecom industry to enhance it's competitiveness and it will play an important role in the telecom marketing. The marketing theory analysis, data mining analysis and the marketing applications in this paper may have some suggests to the marketing staff.