Genetic Modelling of Customer Retention

by

Eiben, A., E., Koudijs, A., E. and Slisser, F.

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Info: Proceedings of the First European Workshop on Genetic Programming (Conference proceedings), 1998, p. 178-186
Keywords:genetic algorithms, genetic programming
Abstract:
This paper contains results of a research project aiming at the application and evaluation of modern data analysis techniques [DA] in the field of marketing. The investigated techniques are: genetic programm ing, rough data analysis, [DA] CHAID and logistic regression analysis. [LR] 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.
Notes:
EuroGP'98
Author(s) DL:Online papers for Eiben, A., E.

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BibTex:
@InProceedings{eiben:1998:gmcr,
  author =       "A. E. Eiben and A. E. Koudijs and F. Slisser",
  title =        "Genetic Modelling of Customer Retention",
  booktitle =    "Proceedings of the First European Workshop on Genetic
                 Programming",
  year =         "1998",
  editor =       "Wolfgang Banzhaf and Riccardo Poli and Marc Schoenauer
                 and Terence C. Fogarty",
  volume =       "1391",
  series =       "LNCS",
  pages =        "178--186",
  address =      "Paris",
  publisher_address = "Berlin",
  month =        "14-15 " # apr,
  publisher =    "Springer-Verlag",
  keywords =     "genetic algorithms, genetic programming",
  ISBN =         "3-540-64360-5",
  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 programm ing,
                 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.",
  notes =        "EuroGP'98",
}