Comparing the predictive utility of demographics to alternative segmentation schemes

This paper compares the predictive power of demographic variables with those of other, more complex segmentation bases. To achieve this objective, the mean R-square of20 demographic models obtained from a representative survey was judged against mean R-square of 99 non-demographic models, in comparable product categories, drawn from existing published studies. The result indicates that demographics have significantly higher explanatory power than some well-established segmentation bases, such as psychographics and benefits. Further, a non-symmetrical U-shape relationship was found between demographics' utility and adoption rate. That is, demographics appear to better predict consumer behavior at the early or late stages of the adoption process. This key observation helps to explain the inconsistency found in the literature in relation to the predictive power of demographic variables. Overall, our findings strongly refute the proposition advanced by a number of prominent market segmentation researchers that the relationships between demographic segments and marketing variables are too weak to be of any practical value. Based on the result of this analysis, therefore, it is concluded that demographics are, at least as useful as other segmentation bases.