Academic journal article Journal of Managerial Issues

Assessing the Validity of Market Segments Using Conjoint Analysis

Academic journal article Journal of Managerial Issues

Assessing the Validity of Market Segments Using Conjoint Analysis

Article excerpt

Marketing is easy to learn, yet extremely difficult to practice well. Some marketing consultants (Clancy and Shulman, 1994) believe that most marketing programs do not earn an acceptable return on investment. Even segmentation decisions, surely a cornerstone of marketing theory and practice, are subject to the same criticism. Part of the problem lies in the difficulty of rigorously applying concepts in practice.

An important question in marketing is when a decision maker may legitimately conclude that two market segments are distinct in a marketing sense, and then follow the strategic and tactical consequences of that decision. Researchers have put forward several criteria for answering such a question (Frank et al., 1972; Lehmann and Winer, 1994). However, the two key issues are the theoretical one of differential response and the practical one of accessibility of the two market segments. Then, a decision to acknowledge the two market segments as distinct and to develop and implement separate marketing strategies for them is founded on the belief that such a decision will lead to higher total profits, despite the increase in total costs this implementation will in all likelihood produce. Since segment size and measurability are relatively easy to verify in practice, such a decision rests ultimately on the presumption that the two market segments will exhibit differential response to the firm's marketing instruments and the firm can reach them with different marketing mixes. In general, it is extremely difficult for decision makers to simultaneously ascertain the validity of both such assessments, differential response and accessibility of segments.

Two recent updates of older reviews of conjoint analysis (Wittink and Cattin, 1989; Green and Srinivasan, 1990) attest to the theoretical as well as practical vigor of this versatile marketing research tool, which has been used in numerous decision-making contexts including advertising assessment (D'Souza and Rao, 1995). Conjoint analysis is first and foremost a tool to measure buyer preferences. As Green and Krieger (1991) make clear, if buyer heterogeneity exists, then conjoint measurement will help uncover this fact. Thus, it is not surprising that segmentation is a rich field for applications of conjoint analysis (Green, 1977; Kamakura, 1988; Green and Krieger, 1991). However, these studies use conjoint analysis primarily to construct market segments, and it is not always clear that the constructed segments can be meaningfully pursued in the marketplace. In fact, the focus of most segmentation research has been on segment construction rather than segment validation. The research outlined in this article uses conjoint analysis to validate(1) market segments that have been constructed by other methods. The main benefit of such an approach is that managers will not have to make intuitive assumptions about the validity of market segments, and win be in a better position to make more profitable segmentation decisions.

In the next section the background to this study is established. This is done by exposing the problem of segment validity in the context of recent research in segmentation and conjoint analysis. The method for validating market segments that we propose is then explained and tested in three product market situations. Finally, we discuss the advantages and disadvantages of our approach for validating market segments.


Since Wind's (1978) comprehensive review of segmentation research there have been several major developments. The availability of scanner panel data has resulted in simultaneous market structuring(2) and segmentation studies (Grover and Srinivasan, 1987; Kamakura and Russell, 1989; Jain et al., 1990; Wedel and Steenkamp, 1991), as web as the widespread use of choice models. These have now been applied in order to estimate category and brand level segments of consumer response to marketing-mix variables (Gensch, 1985; Bucklin and Gupta, 1992; Gupta and Chintagunta, 1994; Bucklin et al. …

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