Exploring the Value of Online Product Reviews in Forecasting Sales: the Case of Motion Pictures

he growing popularity of online product review forums invites the development of models and metrics that allow firms to harness these new sources of information for decision support. Our work contributes in this direction by proposing a novel family of diffusion models that capture some of the unique aspects of the entertainment industry and testing their performance in the context of very early postrelease motion picture revenue forecasting. We show that the addition of online product review metrics to a benchmark model that includes prerelease marketing, theater availability and professional critic reviews substantially increases its forecasting accuracy; the forecasting accuracy of our best model outperforms that of several previously published models. In addition to its contributions in diffusion theory, our study reconciles some inconsistencies among previous studies with respect to what online review metrics are statistically significant in forecasting entertainment good sales. CHRYSANTHOS DELLAROCAS, XIAOQUAN (MICHAEL) ZHANG, AND NEVEEN F. AWAD