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European Conference on Genetic Programming

EuroGP 1998: Genetic Programming pp 178–186Cite as

Genetic modelling of customer retention

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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1391))

Abstract

This paper contains results of a research project aiming at the application and evaluation of modern data analysis techniques in the field of marketing. The investigated techniques are: genetic programming, rough data analysis, CHAID and logistic regression analysis. All four techniques are applied independently to the problem of customer retention modelling, using a database of a financial company. Models created by these techniques are used to gain insights into factors influencing customer behaviour and to make predictions on ending the relationship with the company in question. Comparing the predictive power of the obtained models shows that the genetic technology offers the highest performance.

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References

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Author information

Authors and Affiliations

  1. Dept. of Comp. Sci., Leiden University, The Netherlands

    A. E. Eiben

  2. Cap Gemini, Adaptive Systems bv, The Netherlands

    A. E. Koudijs

  3. Strategic Management & Marketing, University of Amsterdam, The Netherlands

    F. Slisser

Authors
  1. A. E. Eiben
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  2. A. E. Koudijs
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  3. F. Slisser
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Editor information

Wolfgang Banzhaf Riccardo Poli Marc Schoenauer Terence C. Fogarty

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© 1998 Springer-Verlag Berlin Heidelberg

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Eiben, A.E., Koudijs, A.E., Slisser, F. (1998). Genetic modelling of customer retention. In: Banzhaf, W., Poli, R., Schoenauer, M., Fogarty, T.C. (eds) Genetic Programming. EuroGP 1998. Lecture Notes in Computer Science, vol 1391. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0055937

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  • DOI: https://doi.org/10.1007/BFb0055937

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-64360-9

  • Online ISBN: 978-3-540-69758-9

  • eBook Packages: Springer Book Archive

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