Estimating new product demand from biased survey data

Market researchers often conduct surveys asking respondents to estimate their future demand for new products. However, projected demand may exhibit systematic bias. For example, the more respondents like a product, the more they may exaggerate their demand. We found evidence of such exaggeration in a recent survey of demand for a potential new video product. In this paper, we develop a computationally tractable procedure that corrects for a general form of systematic bias in demand projections. This general form is characterized by a monotonictransformation of projected demand, and covers exaggeration bias as a special case.