Mining Telecommunication Networks to Enhance Customer Lifetime Predictions

14 Pages Posted: 12 Mar 2014

See all articles by Backiel Aimée

Backiel Aimée

KU Leuven - Faculty of Business and Economics (FEB)

Bart Baesens

KU Leuven - Faculty of Business and Economics (FEB)

Gerda Claeskens

KU Leuven - Department of Economics

Date Written: March 2014

Abstract

Customer retention has become a necessity in many markets, including mobile telecommunications. As it becomes easier for customers to switch providers, the providers seek to improve prediction models in an effort to intervene with potential churners. Many studies have evaluated different models seeking any improvement to prediction accuracy. This study proposes that the attributes, not the model, need to be reconsidered.

By representing call detail records as a social network of customers, network attributes can be extracted for use in various traditional prediction models. The use of network attributes exhibits a significant increase in the area under the receiver operating curve (AUC) when compared to using just individual customer attributes.

Suggested Citation

Aimée, Backiel and Baesens, Bart and Claeskens, Gerda, Mining Telecommunication Networks to Enhance Customer Lifetime Predictions (March 2014). Available at SSRN: https://ssrn.com/abstract=2407006 or http://dx.doi.org/10.2139/ssrn.2407006

Backiel Aimée (Contact Author)

KU Leuven - Faculty of Business and Economics (FEB) ( email )

Naamsestraat 69
Leuven, B-3000
Belgium

Bart Baesens

KU Leuven - Faculty of Business and Economics (FEB) ( email )

Naamsestraat 69
Leuven, B-3000
Belgium

Gerda Claeskens

KU Leuven - Department of Economics ( email )

Leuven, B-3000
Belgium

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