Customer-Churn Research Based on Customer Segmentation

Author

Zhang Xiao-bin ; Feng, Gao ; Hui, Huang

Author_Institution

Sch. of Comput. Sci., Xi´´an Polytech. Univ., Xi´´an, China

fYear

2009

fDate

6-7 June 2009

Firstpage

443

Lastpage

446

Abstract

This article explores the unique features of the customer relationship management (CRM) system in Telecom industry and presents a customer-churn model based on customer segmentation. First, the improved Fuzzy C-means clustering algorithm is used to segment customer and conclude high value customer group characteristics. Second, using the history data and SAS Enterprise Miner builds a prediction model of customer-churn based on SAS data mining technology. Last but not least, the result of customer segmentation is applied to customer-churn model and gotten accuracy list of lost customer. Experiment proves that this method can obtain a satisfactory result of customer-churn.

Keywords

customer relationship management; data mining; fuzzy set theory; pattern clustering; telecommunication industry; customer relationship management; customer segmentation; customer-churn research; data mining; fuzzy C-means clustering algorithm; telecom industry; Clustering algorithms; Companies; Computer science; Customer relationship management; Data mining; Delta modulation; Electronic commerce; History; Kernel; Synthetic aperture sonar; Customer Segmentation; Customer-churn; Fuzzy C-Means Clustering; Kernel method; SAS Data Ming;

fLanguage

English

Publisher

ieee

Conference_Titel

Electronic Commerce and Business Intelligence, 2009. ECBI 2009. International Conference on

Conference_Location

Beijing

Print_ISBN

978-0-7695-3661-3

Type

conf

DOI

10.1109/ECBI.2009.86

Filename

5190494