Paper Info
Title
Mining churning behaviors and developing retention strategies based on a partial least squares (PLS) model
Abstract
In a very competitive mobile telecommunication business environment, marketing managers need a business intelligence model that allows them to maintain an optimal (at least a near optimal) level of churners very effectively and efficiently while minimizing the costs throughout their marketing programs. As a first step toward optimal churn management program for marketing managers, this paper focuses on building an accurate and concise predictive model for the purpose of churn prediction utilizing a partial least squares (PLS)-based methodology on highly correlated data sets among variables. A preliminary experiment demonstrates that the presented model provides more accurate performance than traditional prediction models and identifies key variables to better understand churning behaviors. Further, a set of simple churn marketing programs-device management, overage management, and complaint management strategies-is presented and discussed.
Year
DOI
Venue
2011
10.1016/j.dss.2011.07.005
Decision Support Systems
Keywords
Field
DocType
near optimal,overage management,retention strategy,marketing manager,business intelligence model,complaint management,churn prediction,simple churn marketing programs-device,optimal churn management program,marketing program,concise predictive model,mobile telecommunication,prediction model,partial least squares,customer relationship management,business intelligence
Customer relationship management,Data mining,Data set,Churning,Computer science,Partial least squares regression,Complaint,Predictive modelling,Business intelligence,Mobile telephony
Journal
Volume
Issue
ISSN
52
1
0167-9236
Citations 
PageRank 
References 
14
0.72
21
Authors
5
Name
Order
Citations
PageRank
Hyeseon Lee1283.75
Yeonhee Lee215111.36
Hyunbo Cho325823.62
Kwanyoung Im4251.33
Yong Seog Kim511211.11