Abstract
For some time marketers have embraced the idea of market segmentation, i.e., defining homogeneous subsets of the total market. From these market segments one can then select the most profitable; these become the organization's target markets. The assumption is that different marketing mixes can better serve the needs of these homogeneous market segments. The technique most often used for creating data-based, homogeneous market segments is cluster analysis. One problem researchers have discovered with this technique is that the inclusion of irrelevant or noisy variables in a cluster analysis can obscure or distort “true” market structures. This problem has prompted the search for methods that identify noisy variables and either down weight or remove them.
Recently, Donoghue (1995) has proposed two univariate screening measures that his research suggests results in more homogeneous, and thus more efficacious, market segments. Our research focuses on the behavior of Donoghue's measures with data from actual marketing research studies. We investigate whether or not the Donoghue procedure leads to a more efficacious market structure. Our results with actual data are less encouraging than those reported by Donoghue, who used simulated data.