Document Type

Article

Journal/Book Title/Conference

Expert Systems with Applications

Volume

40

Issue

6

Publisher

Elsevier

Publication Date

5-2013

First Page

2198

Last Page

2207

DOI

10.1016/j.eswa.2012.10.043

Abstract

In this paper, we propose a churn management model based on a partial least square (PLS) optimization method that explicitly considers the management costs of controllable marketing variables for a success- ful churn management program. A PLS prediction model is first calibrated to estimate the churn proba- bilities of customers. Then this PLS prediction model is transformed into a control model after relative management costs of controllable marketing variables are estimated through a triangulation method. Finally, a PLS optimization model with marketing objectives and constraints are specified and solved via a sequential quadratic programming method. In our experiments, we observe that while the training and test data sets are dramatically different in terms of churner distributions (50% vs. 1.8%), four control- lable variables in three marketing strategies significantly changed through optimization process while other variables only marginally changed. We also observe that the most significant variable in a PLS pre- diction model does not necessarily change most significantly in our PLS optimization model due to the highest management cost associated, implying differences between a prediction and an optimization model. Finally, two marketing models designed for targeting the subsets of customers based on churn probability or management costs are presented and discussed.

Comments

This is a final accepted manuscript. The published version may be accessed here http://dx.doi.org/10.1016/j.eswa.2012.10.043

The publisher retains the copyright to this work and may require a subscription to access the published version.

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