Dynamic Revenue Management for Online Display Advertising

In this paper, we propose an dynamic optimization model to maximize a web publisher’s online display advertising revenues. Specifically, our model dynamically selects which advertising requests to accept and dynamically delivers the promised advertising impressions to viewers so as to maximize revenue, accounting for uncertainty in advertising requests and website traffic. After characterizing the structural properties of our model, we propose a Certainty Equivalent Control heuristic and then show with a real case study that our optimization-based method typically outperforms common practices. Our analysis thus highlights the importance of integrating the sales function with the advertisement delivery function in web publishing companies for globally maximizing revenues.