Predicting behavior from intention-to-buy measures: The par

A probabilistic model is developed that converts stated purchase intents into purchase probabilities. The model allows heterogeneity between nonintenders and intenders with respect to their probability to switch to a new "true" purchase intent after the survey, thereby capturing the typical discrepancy between overall mean purchase intent and subsequent proportion of buyers (bias). When the probability to switch of intenders is larger (smaller) than that of nonintenders, the overall mean purchase intent overestimates (underestimates) the proportion of buyers. As special cases, the upper and lower bounds on proportions of buyers are derived from purchase intents data and the consistency of those bounds with observed behavior is shown, except in predictable cases such as new products and business markets. However, a straightforward modification of the model deals with new product purchase forecasts.