GTLGFeb 12, 2023

Optimizing Floors in First Price Auctions: an Empirical Study of Yahoo Advertising

arXiv:2302.06018v21 citationsh-index: 5
AI Analysis

This addresses revenue optimization for online publishers like Yahoo, but it is incremental as it applies an existing concept (floors) to first price auctions with specific industry constraints.

The paper tackles the problem of setting floors (reserve prices) in first price auctions to increase ad revenue for publishers, with results showing an estimated annualized incremental revenue of +1.3% on Yahoo display inventory and +2.5% on video ad inventory.

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.

Foundations

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