Simultaneous Advertiser Profit and Ad Platform Revenue Maximization in Programmatic Advertising via Feedback Control

The majority of online advertising is served through real-time bidding, and advertising campaigns are often defined as optimization problems. This paper deals with simultaneous advertiser profit and ad platform revenue maximization subject to multiple advertiser performance constraints and is an extension to the work published in [1]. The optimal bidding mechanism is derived for a large family of advertising problems; and it is shown how the solution can be implemented as three separate subsystems dealing with impression valuation, campaign control, and bid shading optimization, respectively. Feedback control is a critical aspect of the solution and makes the optimization scalable and adaptive. A proof of concept control system is proposed and simulated to demonstrate the impact of trading advertiser profit for ad platform revenue.