Retail buyers' forecasts, decisions, and subsequent purchases result in billions of dollars of merchandise being purchased and offered for sale by retailers around the world. However, academic research examining this decision process has been limited, and recommendations for improvement almost nonexistent. In the present study, we begin to address this issue by introducing a new approach that compares retail buyers' consensus forecasts with those from a sample of “ordinary” consumers. The potential for incorporating forecasts from ordinary consumers suggests an opportunity to create what are termed retail prediction markets, which offer significant potential to improve the accuracy of buyers’ forecasts. We conclude with limitations and areas for future research.