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Predicting Customer Loyalty Labels in a Large Retail Database: A Case Study in Chile

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Book cover Data Mining

Part of the book series: Annals of Information Systems ((AOIS,volume 8))

Abstract

Although loyalty information is a key part in customer relationship management, it is hardly available in industrial databases. In this chapter, a data mining approach for predicting customer loyalty labels in a large Chilean retail database is presented. First, unsupervised learning techniques are used for segmenting a representative sample of the database. Second, the multilayer perceptron neural network is used for classifying the remaining population. Results show that 19% of the customers can be considered loyal. Finally, a set of validation tasks using data about in-store minutes charges for prepaid cell phones and distribution of products is presented.

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Acknowledgments

Clementine was used under permission of SPPS Chile. Specifically, the author would like to thank Stephen Cressall who is with SPSS Chile for his valuable help and support on the Clementine’s platform during the implementation of some models.

Furthermore, the author appreciates enormously the comments and suggestions about this business application given by Jacek M. Zurada during his visit made to Chile in January 2007. Jacek M. Zurada is a professor who belongs to the Department of Computer and Electrical Engineering, University of Louisville, USA.

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Authors and Affiliations

  1. Department of Electrical Engineering, University of Chile, Santiago, Chile

    Cristián J. Figueroa

Authors
  1. Cristián J. Figueroa
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Correspondence to Cristián J. Figueroa .

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Editors and Affiliations

  1. Inst. Wirtschaftsinformatik, Universität Hamburg, Von-Melle-Park 5, Hamburg, 20146, Germany

    Robert Stahlbock

  2. Management School, Dept. Management Science, Lancaster University, Lancaster, LA1 4YX, United Kingdom

    Sven F. Crone

  3. Inst. Wirtschaftsinformatik, Universität Hamburg, Von-Melle-Park 5, Hamburg, 20146, Germany

    Stefan Lessmann

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Figueroa, C.J. (2010). Predicting Customer Loyalty Labels in a Large Retail Database: A Case Study in Chile. In: Stahlbock, R., Crone, S., Lessmann, S. (eds) Data Mining. Annals of Information Systems, vol 8. Springer, Boston, MA. https://doi.org/10.1007/978-1-4419-1280-0_10

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  • DOI: https://doi.org/10.1007/978-1-4419-1280-0_10

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  • Print ISBN: 978-1-4419-1279-4

  • Online ISBN: 978-1-4419-1280-0

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