Abstract
IValtlm, MA Summary.-Conioint and Preference Analyses were used in an attempt to identify a potential new product's optimal configuration. From each analysis. the same co~clusions were drawn, that is, there was no analytic advantage of one analysis over the other. Since the Preference Analysis was more simple and less costly to use, this procedure seems more desirable to use in optimizing a new product's design. When a new producc is under development, it is common to test a few alternative configurations among consumers. Because only a few alternatives are tested, consumers have little input into the ultimate design of the new product. This limited inpur from consumers is probably one of the reasons why so many new products fail. Having identified the need for a new product, we brought consumers into the design process quickly. In focus groups, farmers who currently own and operate farms with 180+ acres evaluated festures which might be incorporated into the new product. From this initial efforr, it was clear that the producc should consist of a cluster of four product features which for proprietary reasons, we will refer to as Features A, B, C, and D. Features A and B each could assume two levels and Features C and D three levels each. The new prcduct under consideration could be configured in 36 ways. The problem, then, was to identify that configuration which would exhibit the most appeal to the target market. Because this effort was important, we decided to evaluate the appeal of the various product configurations using Conjoint Analysis, a procedure much touted for its utility in optimizing a new product's design (Green & Rao, 1971; Green & Srinivisan, 1975), and Preference Analysis. In this report the relative efficacy of Conjoint Analysis and Preference Analysis in optimizing a new product's design is compared. Prior to discussing this study, a comment on the conceptual background is needed for both Conjoint and Preference Analysis. Co~zjoint Analysis
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