Recovering Household Preferences for Digital Entertainment

Cable TV return path data made possible by current generation set-top boxes present a new opportunity to analyze household viewing behavior and recover household viewing preferences from it. This research develops a model of household viewing preference that supports quantifying a household's valuation for different categories of digital content within the constraints of the programs to which it subscribes. This study uses a data set of more than 1 million observations on households from a digital entertainment firm that offers basic and premium services. Our estimation is via a Bayesian hierarchical model that employs the Gibbs sampler. The results show that households have relatively homogeneous preferences for entertainment content, but they show heterogeneous preferences for content in the specific packages to which they subscribe. In addition, both HD and premium movies subscriptions have a differentiation effect on enhancing household preferences toward their most preferred content. The findings provide useful insights for understanding household preferences, and are intended to support promotion and content strategy adjustments to improve customer satisfaction.