Optimizing Floors in First Price Auctions: an Empirical Study of Yahoo Advertising
Miguel Alcobendas, Jonathan Ji, Hemakumar Gokulakannan, Dawit Wami, Boris Kapchits, Emilien Pouradier Duteil, Korby Satow, Maria Rosario Levy Roman, Oriol Diaz, Amado A. Diaz, Rabi Kavoori
TL;DR
This paper develops a model to set floors in first-price online ad auctions, accounting for bidder data restrictions and two bidder types (regular DSPs and rebroadcasters), and demonstrates its deployment at Yahoo. The approach maximizes publisher revenue by optimizing a floors vector $\rho$ using estimated bid distributions and participation rates, while incorporating an outside option (waterfall) and type-based floor constraints. Empirical deployment shows positive short-term gains, with +1.3% incremental revenue on Yahoo display and +2.5% on video, driven by shifts in bidding behavior and higher clearing prices. The work highlights practical considerations for large ad platforms, including production-scale estimation, randomized experimentation, and the balance between internal exchange revenue and external options.
Abstract
Floors (also known as reserve prices) help publishers to increase the expected revenue of their ad space, which is usually sold via auctions. Floors are defined as the minimum bid that a seller (it can be a publisher or an ad exchange) is willing to accept for the inventory opportunity. In this paper, we present a model to set floors in first price auctions, and discuss the impact of its implementation on Yahoo sites. The model captures important characteristics of the online advertising industry. For instance, some bidders impose restrictions on how ad exchanges can handle data from bidders, conditioning the model choice to set reserve prices. Our solution induces bidders to change their bidding behavior as a response to the floors enclosed in the bid request, helping online publishers to increase their ad revenue. The outlined methodology has been implemented at Yahoo with remarkable results. The annualized incremental revenue is estimated at +1.3% on Yahoo display inventory, and +2.5% on video ad inventory. These are non-negligible numbers in the multi-million Yahoo ad business.