Approaches to Customer Segmentation

Journal of Relationship Marketing, 2007

41 Pages Posted: 2 Aug 2006

See all articles by Bruce Cooil

Bruce Cooil

Vanderbilt University - Statistics

Lerzan Aksoy

Koc University

Timothy L. Keiningham

Ipsos Loyalty - North America


Customer segmentation has virtually unlimited potential as a tool that can guide firms toward more effective ways to market products and develop new ones. As a conceptual introduction to this topic, we study how an innovative multi-national firm (Migros Turk) has developed an effective set of segmentation strategies. This illustrates how firms can construct novel and inventive approaches that provide great value. A-priori, and custom designed post-hoc methods are among the most important approaches that a firm should consider.

We then review general approaches to customer segmentation, with an emphasis on the most powerful and flexible analytical approaches and statistical models. This begins with a discussion of logistic regression for supervised classification, and general types of cluster analysis, both descriptive and predictive. Predictive clustering methods include cluster regression and CHAID (Chi-squared automatic interaction detection, which is also viewed as a tree classifier). Finally, we consider general latent class models that can handle multiple dependent measures of mixed type. These models can also accommodate samples that are drawn from a pre-defined group structure (e.g., multiple observations per household). To illustrate an application of these models, we study a large data set provided by an international specialty-goods retail chain.

Keywords: Latent class model, clustering, cluster regression, logistic regression, classification, conjoint analysis, random effect, multilevel model, inactive covariate, satisfaction

JEL Classification: C30, M21, M30, M31, M37

Suggested Citation

Cooil, Bruce and Aksoy, Lerzan and Keiningham, Timothy L., Approaches to Customer Segmentation. Journal of Relationship Marketing, 2007, Available at SSRN:

Bruce Cooil (Contact Author)

Vanderbilt University - Statistics ( email )

Nashville, TN 37203
United States

Lerzan Aksoy

Koc University ( email )

Cayir Cad. No: 5 Istinye
Sariyer 80910, Istanbul, 34450

Timothy L. Keiningham

Ipsos Loyalty - North America ( email )

Parsippany, NJ
United States

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