The authors describe a methodology and a personal-computer-based decision model for selecting optimal market testing strategies. A Bayesian decision theoretic framework is used that (1) considers continuously distributed payoffs, (2) allows for updating of information on market response to strategies that are not being tested directly (relaxing the assumption of independence among test outcomes), and (3) incorporates managers’ attitude toward risk. The goals of the methodology are to bring managers a practical, usable tool that will help support their design of market tests and to obtain some insights into the market testing problem. An application of the methodology is reported to illustrate the potential of the model as a practical and easily implementable marketing decision aid. Using the analytical insights obtained from the model, the authors summarize the influence of the various characteristics of the alternative strategies on the value of a market test and the choice of the test strategy.
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