A Life-Cycle Model of Drama TV Series Using Google Trends Data

Increased time-shifted TV viewing practice undermines the role of traditional viewer ratings in gauging consumer interests in primetime TV drama. This paper introduces Google Trends data as a supplementary measure of popularity and proposes a lifecycle model for describing the pattern of search activity related to TV drama shows. The model is accomplished by developing three models that deal with the different phases (i.e., prerelease, on-season, and post-season period) that a TV drama series goes through. In our empirical analysis, we demonstrate that the proposed model provides an apt description of the diffusion pattern of consumer search activity related to a primetime TV drama series. We also show that the search volume that accumulated during the pre-season period has predictive power to expect the level of consumer interest in the upcoming season premiere. We also find that the release of the following seasons of a drama series accompanies the search for its previous seasons because of her reciprocal spillover effects. Our findings indicate the importance of monitoring the online search activity of consumers in the TV drama industry.