Modeling and Optimizing the Performance of Experiential Events

Although experiential events (e.g., product demos, product sampling) have been shown to have a positive impact on both short-term sales and the overall consumer experience, little is known about the factors that drive their success or how the effect of these events evolves over time. In this paper, we deepen our understanding of the impact of experiential events on product performance using store-level scanner data. We propose a model that captures a variety of salient features of these types of promotions (e.g., short and long-term effects, the discrete nature of the event, spatial dependence). We apply our model to data from an in-store sampling event and find evidence of a significant long-term effect of sampling on product sales. We also find that the success of the event is moderated by the size of the store conducting the event and the type and number of proximal competitors. These results are used to provide guidance to manufacturers and retailers that can help them better design and implement these types of promotions, including the task of optimally selecting the set of stores in which to conduct an event.