Lift-Based Bidding in Ad Selection

Authors

  • Jian Xu TouchPal Inc.
  • Xuhui Shao Yahoo Inc.
  • Jianjie Ma Yahoo Inc.
  • Kuang-chih Lee Yahoo Inc.
  • Hang Qi Yahoo Inc.
  • Quan Lu Yahoo Inc.

DOI:

https://doi.org/10.1609/aaai.v30i1.10025

Keywords:

Lift-Based Bidding, Real-Time Bidding, Demand-Side Platform, Attribution, Online Advertising

Abstract

Real-time bidding has become one of the largest online advertising markets in the world. Today the bid price per ad impression is typically decided by the expected value of how it can lead to a desired action event to the advertiser. However, this industry standard approach to decide the bid price does not consider the actual effect of the ad shown to the user, which should be measured based on the performance lift among users who have been or have not been exposed to a certain treatment of ads. In this paper, we propose a new bidding strategy and prove that if the bid price is decided based on the performance lift rather than absolute performance value, advertisers can actually gain more action events. We describe the modeling methodology to predict the performance lift and demonstrate the actual performance gain through blind A/B test with real ad campaigns. We also show that to move the demand-side platforms to bid based on performance lift, they should be rewarded based on the relative performance lift they contribute.

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Published

2016-02-21

How to Cite

Xu, J., Shao, X., Ma, J., Lee, K.- chih, Qi, H., & Lu, Q. (2016). Lift-Based Bidding in Ad Selection. Proceedings of the AAAI Conference on Artificial Intelligence, 30(1). https://doi.org/10.1609/aaai.v30i1.10025

Issue

Section

Technical Papers: Game Theory and Economic Paradigms