Posted price programmatic guarantee in display advertising

This paper presents a revenue maximisation model for sales channel allocation based on dynamic programming. It helps the media seller to determine how to distribute the sales volume of page views between guaranteed and nonguaranteed channels for display advertising. The model can algorithmically allocate and price the future page views via standardised guaranteed contracts in addition to real-time bidding (RTB). This is one of a few studies that investigates programmatic guarantee (PG) with posted prices. Several assumptions are made for media buyers’ behaviour, such as risk-aversion, stochastic demand arrivals, and time and price effects. We examine our model with an RTB dataset and find it increases the seller’s expected total revenue by adopting different pricing and allocation strategies depending the level of competition in RTB campaigns. The insights from this research can increase the allocative efficiency of the current media sellers’ sales mechanism and thus improve their revenue.