Name
Title | ||
|---|---|---|
Churn management optimization with controllable marketing variables and associated management costs |
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 successful churn management program. A PLS prediction model is first calibrated to estimate the churn probabilities 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 controllable 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 prediction 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. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1016/j.eswa.2012.10.043 | Expert Syst. Appl. |
Keywords | Field | DocType |
churn probability,pls prediction model,management cost,marketing model,pls optimization model,churn management model,highest management,optimization model,associated management cost,control model,controllable marketing variable,churn management optimization,triangulation,sequential quadratic programming | Least squares,Data mining,Management model,Computer science,Triangulation (social science),Test data,Local search (optimization),Sequential quadratic programming,Optimization problem,Marketing | Journal |
Volume | Issue | ISSN |
40 | 6 | 0957-4174 |
Citations | PageRank | References |
2 | 0.39 | 21 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yong Seog Kim | 1 | 112 | 11.11 |
| Hyeseon Lee | 2 | 28 | 3.75 |
| John D. Johnson | 3 | 267 | 21.49 |