An empirical study of reserve price optimisation in real-time bidding

Yuan, Shuai and Wang, Jun and Chen, Bowei and Mason, Peter and Seljan, Sam (2014) An empirical study of reserve price optimisation in real-time bidding. In: The 20th ACM SIGKDD international conference on Knowledge discovery and data mining, 24 - 27 August 2014, New York City.

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Item Type:Conference or Workshop contribution (Paper)
Item Status:Live Archive


In this paper, we report the first empirical study and live test of the reserve price optimisation problem in the context of Real-Time Bidding (RTB) display advertising from an operational environment. A reserve price is the minimum that the auctioneer would accept from bidders in auctions, and in a second price auction it could potentially uplift the auctioneer's revenue by charging winners the reserve price instead of the second highest bids. As such it has been used for sponsored search and been well studied in that context. However, comparing with sponsored search and contextual advertising, this problem in the RTB context is less understood yet more critical for publishers because 1) bidders have to submit a bid for each individual impression, which mostly is associated with user data that is subject to change over time. This, coupled with practical constraints such as the budget, campaigns' life time, etc. makes the theoretical result from optimal auction theory not necessarily applicable and a further empirical study is required to confirm its optimality from the real-world system; 2) in RTB an advertiser is facing nearly unlimited supply and the auction is almost done in "last second", which encourages spending less on the high cost ad placements. This could imply the loss of bid volume over time if a correct reserve price is not in place. In this paper we empirically examine several commonly adopted algorithms for setting up a reserve price. We report our results of a large scale online experiment in a production platform. The results suggest the our proposed game theory based OneShot algorithm performed the best and the superiority is significant in most cases.

Keywords:Real-time bidding, Reserve price auction, Optimisation
Subjects:G Mathematical and Computer Sciences > G400 Computer Science
N Business and Administrative studies > N500 Marketing
Divisions:College of Science > School of Computer Science
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ID Code:19630
Deposited On:19 Nov 2015 19:57

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