The consumer's rent vs. buy decision in the rentailer

In this paper, we focus on the perspective and business model of the rentailer — a retail outlet that rents and sells new and used home video titles. This requires predicting the consumer's decision to rent or buy a particular title, segmenting its customer base, and pricing new and used titles. We develop a new model based on a simple heuristic found in the behavioral marketing literature of how people predict their own usage of a service. We estimate the model using a unique panel dataset obtained from a large rentailer, and find it provides a good fit to the data. Using the model estimates we obtain a metric indicating a latent customer tendency to buy at full price (compared to buying at a lower price or renting). Other diagnostic information from the model may help convert renters into buyers. First, expected viewing may be pitched to the consumer in order to persuade consumers that the movie will be well utilized. Secondly, we use the model to generate customized new and used title prices.