Auto-bidding in Online Advertising: Campaign Management and Fairness

Explore the complexities of auto-bidding in online advertising through this Google TechTalk presented by Jason Liang. Delve into two key aspects of digital advertising: multi-channel conversion maximization and improving individual fairness in auction outcomes. Learn about the challenges advertisers face when procuring ad impressions across multiple platforms and the limitations of controlling individual ad auctions. Discover an efficient learning algorithm for optimizing per-channel levers to approximate global optimal conversion. Examine a novel fairness metric that measures individual bidder welfare loss and uncovers the impact of advertiser strategies on fairness. Investigate how machine learning advice can be utilized to improve welfare guarantees and fairness at the individual bidder level in classic auction formats. Gain insights into the intersection of operations research, mechanism design, and revenue management in online marketplaces.