World Media Economics and Management Conference 2016

With the rise of big data, information on historical demand is at the consumers’ fingertips (e.g., via Google Trends). We examine how the availability of such demand curves impacts individual and aggregate consumer behavior. We argue that historical sales patterns incite consumers to draw inferences about future demand in terms of trajectory and uncertainty. This is important for companies interested in anticipating future developments or managing demand. In three experiments, we show that historical information on sales trends (a) impacts individual consumer decisions above and beyond the effect of cumulative sales, (b) increases market concentration as compared to the absence of sales information, and (c) can lead to a lower market concentration than sales information without historical trends. Specifically, information on positive global and short-term trends increases future sales much more than simply providing cumulative sales information (e.g., on the number of previous downloads). Observed prior adoption velocity and variation however decrease future sales by alerting consumers to the potential uncertainty of future developments.