In this workshop, Eric Bradlow will demonstrate a conjoint methodology that allows researchers to learn about a focal category (yogurt) by leveraging results from a conjoint study on a related category (ice cream). He will also present a data collection task that uses choice pairs between overlapping product categories such as hiking jackets and sleeping bags and a Bayesian model that uses out-of-category information to improve out-of-sample prediction accuracy. Since this approach uses standard conjoint software with no modifications, it can be used immediately as a practical marketing research tool for managerially relevant decisions such as market share predictions.

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