Research On Data Mining In CRM Of Telecom

This article analyzes the stinging competition position of telecom industry inside and outside China at present in detail. By knowing the current research on data mining in CRM telecom, it puts forward that keeping CRM well is one of the most important factors to improve the competitive capacity of telecom in the face of increasingly incandesce competition. In the face of customer data increasing explosively, data mining is the key to advance the decision-making efficiency in telecom CRM. It is very necessary to take researches on data mining in telecom CRM. Although the research on this project becomes more and more mature, the data mining methods and algorithms are still deficient and the project should be researched on deeply. The contents of this article include three main aspects. Firstly, this article introduces the basic theories and knowledge about data mining in telecom CRM and the concepts of data mining and CRM. And through building a model about customer losing prediction, it explains the mining process of data mining in telecom CRM. Then, the data mining methods and algorithms are researched on deeply, especially the association rules. It analyzes the Apriori algorithm which is one of the most common association rules algorithms in detail and find out the shortcomings of Apriori algorithm. The shortcomings mainly include two aspects which are spending many computer resources and energies in the update of association rule and data base. In order to overcome these shortcomings, this article put forward a new algorithm named NEWIUA algorithm, which is based on the IUA algorithm. IUA is one of the algorithms on association rule update. And the NEWIUA is proved more correct and efficient. At last, this article solves an example. The data is about customer operation data of a telecom industry in Chongqing city zone. The example mines the relationship between several main operations of the industry and the influences between each other, which can help the industry to make more efficient decision on operations providing and products cross-selling.