Mining churning behaviors and developing retention strategies based on a partial least squares (PLS) model

Authors:
Hyeseon Lee;Yeonhee Lee;Hyunbo Cho;Kwanyoung Im;Yong Seog Kim
Affiliations:
Division of Industrial and Management Engineering, Pohang University of Science and Technology, San 31 Hyoja, Pohang 790-784, Republic of Korea;Division of Industrial and Management Engineering, Pohang University of Science and Technology, San 31 Hyoja, Pohang 790-784, Republic of Korea;Division of Industrial and Management Engineering, Pohang University of Science and Technology, San 31 Hyoja, Pohang 790-784, Republic of Korea;Division of Industrial and Management Engineering, Pohang University of Science and Technology, San 31 Hyoja, Pohang 790-784, Republic of Korea;Management Information Systems Department, Jon M. Huntsman School of Business, 3515 Old Main Hill, Utah State University, Logan, UT 84322-3515, USA
Venue:
Decision Support Systems
Year:
2011

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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.