Gligorijevic, Dj., Zhou, T., Shetty, B., Kitts, B., Pan, S., Pan, J., Flores, A., (2020) ” Bid Shading in The Brave New World of First-Price Auctions“, 29th ACM International Conference on Information and Knowledge Management (CIKM 2020), October 19-23, 2020, Virtual Event, Ireland
Online auctions play a central role in online advertising, and are one of the main reasons for the industry’s scalability and growth. With great changes in how auctions are being organized, such as changing the second- to first-price auction type, advertisers and demand platforms are compelled to adapt to a new volatile environment. Bid shading is a known technique for preventing overpaying in auction systems that can help maintain the strategy equilibrium in first-price auctions, tackling one of its greatest drawbacks. In this study, we propose a machine learning approach of modeling optimal bid shading for non-censored online first-price ad auctions. We clearly motivate the approach and extensively evaluate it in both offline and online settings on a major demand side platform. The results demonstrate the superiority and robustness of the new approach as compared to the existing approaches across a range of performance metrics.