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Using cluster analysis and DEA-discriminant analysis to predict group membership of new customers

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  • Reza Farzipoor Saen

Abstract

To understand the value of customers and target the most profitable customers, this paper uses cluster analysis to classify customers into four groups as platinum, gold, iron, and lead. Then, to predict group membership of new customers, data envelopment analysis-discriminant analysis (DEA-DA) model is applied. This paper operationalises the concept proposed by Zeithaml et al. (2001), ('The customer pyramid: creating and serving profitable customers', California Management Review, Vol. 43, No. 4, pp.118-142) on forming the customer pyramid. A case study demonstrates the application of the proposed approach.

Suggested Citation

  • Reza Farzipoor Saen, 2013. "Using cluster analysis and DEA-discriminant analysis to predict group membership of new customers," International Journal of Business Excellence, Inderscience Enterprises Ltd, vol. 6(3), pages 348-360.
    • Handle: RePEc:ids:ijbexc:v:6:y:2013:i:3:p:348-360
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    Cited by:

    1. Tavassoli, Mohammad & Badizadeh, Taliva & Farzipoor Saen, Reza, 2016. "Performance assessment of airlines using range-adjusted measure, strong complementary slackness condition, and discriminant analysis," Journal of Air Transport Management, Elsevier, vol. 54(C), pages 42-46.

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