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Genetic modelling of customer retention

  • A. E. Eiben
  • A. E. Koudijs
  • F. Slisser
Conference paper
Part of the Lecture Notes in Computer Science book series (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.

Keywords

Cash Flow Direct Marketing Customer Retention Genetic Programming System Customer Defection 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 1998

Authors and Affiliations

  • A. E. Eiben
    • 1
  • A. E. Koudijs
    • 2
  • F. Slisser
    • 3
  1. 1.Dept. of Comp. Sci.Leiden UniversityThe Netherlands
  2. 2.Cap Gemini, Adaptive Systems bvThe Netherlands
  3. 3.Strategic Management & MarketingUniversity of AmsterdamThe Netherlands

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