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Mining Telecommunication Networks to Enhance Customer Lifetime Predictions

  • Conference paper
Artificial Intelligence and Soft Computing (ICAISC 2014)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 8468))

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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.

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Author information

Authors and Affiliations

  1. Faculty of Economics and Business, KU Leuven, Belgium

    Aimée Backiel, Bart Baesens & Gerda Claeskens

  2. School of Management, University of Southampton, UK

    Bart Baesens

Authors
  1. Aimée Backiel
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  2. Bart Baesens
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  3. Gerda Claeskens
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Editor information

Editors and Affiliations

  1. Częstochowa University of Technology, Armii Krajowej 36, 42-200, Częstochowa, Poland

    Leszek Rutkowski  & Rafał Scherer  & 

  2. Częstochowa University of Technology, 42-200, Częstochowa, Poland

    Marcin Korytkowski

  3. AGH University of Science and Technology, Mickiewicza 30, 30-059, Kraków, Poland

    Ryszard Tadeusiewicz

  4. Computer Science Division, Department of Electrical Engineering and Computer Sciences, University of California Berkeley, 94720-1776, Berkeley, CA, USA

    Lotfi A. Zadeh

  5. Computational Intelligence Laboratory, Electrical and Computer Engineering, University of Louisville, 405 Lutz Hall, 40292, Louisville, KY, USA

    Jacek M. Zurada

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© 2014 Springer International Publishing Switzerland

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Backiel, A., Baesens, B., Claeskens, G. (2014). Mining Telecommunication Networks to Enhance Customer Lifetime Predictions. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds) Artificial Intelligence and Soft Computing. ICAISC 2014. Lecture Notes in Computer Science(), vol 8468. Springer, Cham. https://doi.org/10.1007/978-3-319-07176-3_2

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  • DOI: https://doi.org/10.1007/978-3-319-07176-3_2

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-07175-6

  • Online ISBN: 978-3-319-07176-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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