Computer Science ›› 2011, Vol. 38 ›› Issue (5): 154-158.

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Customer Segmentation Modeling on Factor Analysis and K-MEANS Clustering

PENG Kai,QING Yong-bin,XU Dao-yun   

  • Online:2018-11-16 Published:2018-11-16

Abstract: To develop customers' potential demands for data services, the research for customer segmentation has become a primitive work of telecommunications operators in order to run a differentiated users' marketing. Through the use of clustering algorithm, this paper presented a segmentation modeling for differentiating customers using short messaging services in telecommunications operators. Firstly, based on factor analysis, redundant properties were simplified in the complex data mining under variable parameters in order to improve the quality and efficiency of the modeling, and then the customer segmentation model was constructed through unsupervised clustering K-MEANS algorithm. It was verified that the SMS users have the obvious differentiation of characteristics by using the cluster model. In 2009,a western communications enterprise achieved significant benefits with application of the model in the differentiated data service marketing.

Key words: Value-added service,Factor analysis, Perm eability of short message service,Data exploration, Data training , Time interval

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