A Survey on Bid Optimization in Real-Time Bidding Display Advertising

Abstract

Real-Time Bidding (RTB) is one of the most important forms of online advertising, where an auction is hosted in real time to sell the individual ad impression. How to design an automated bidding strategy in response to the dynamic auction environment is crucial for improving user experience, protecting the interests of advertisers, and promoting the long-term development of the advertising platform. As an exciting topic in the real-world industry, it has attracted great research interest from several disciplines, most notably data science. There have been abundant studies on bidding strategy design which are based on the large volume of historical ad requests. Despite its popularity and significance, few works provide a summary for bid optimization. In this survey, we present the latest overview of the recent works to shed light on the optimization techniques where most of them are validated in practice. We first explore the optimization problem in different works, explaining how these different settings affect the bidding strategy designs. Then, some forms of bidding functions and specific optimization techniques are illustrated. Further, we specifically discuss a new trend about bidding in first-price auctions, which have gradually become popular in recent years. From this survey, both practitioners and researchers can gain insights of the challenges and future prospects of bid optimization in RTB.