The impact of likes on the sales of movies in video-on-demand: a randomized experiment

Peer-rating systems have become an increasingly popular way for consumers to learn about the quality of products. However, measuring the true impact of these ratings systems on consumer behavior represents a challenging empirical problem. In this paper we attempt to measure the impact of rating systems on consumer behavior by designing and implementing a randomized field experiment to determine the role that "likes" play on the sales of movies in Video-on-Demand (VoD). Specifically, we used the VoD system of a large telecommunications provider during the latter half of 2012. The VoD system of this provider suggests movies to subscribers when they log in. Suggested movies are displayed on the user's TV screen under several editorial menus. Under each menu movies are shown from left to right in decreasing order of the number of likes the movie received. During our experiment, movies were primarily placed in their true slots shown along with their true number of likes. However, sometimes some movies had their positions swapped. These movies, randomly chosen, were displayed out of order and with a fake number of likes. We found that promoting a movie by one slot increased weekly sales by 4% on average. We also found that a movie promoted (demoted) to a fake slot sold 15.9% less (27.7% more) than a true movie placed at that slot, on average across all manipulations we introduced. Likewise, we found that a movie promoted (demoted) to a fake slot received 33.1% fewer (30.1% more) likes than a true movie at that slot. Therefore, manipulated movies tend to move back to their true slot over time. Hence, we find that the self-fulfilling prophecies widely discussed in the literature on the effect of ratings on sales are hard to sustain in a market in which goods are costly and sufficiently well-known. This process is likely to converge quickly, which might lead the telecommunications provider to promote different movies over time.