Abstract
A major trend in mobile advertising is the emergence of real time bidding (RTB) based marketplaces on the supply side and the corresponding programmatic impression buying on the demand side. In order to acquire the most relevant audience impression at the lowest cost, a demand side player has to accurately estimate the win rate and winning price in the auction, and incorporate that knowledge in its bid. In this paper, we describe our battle-proven techniques of predicting win rate and winning price in RTB, and the corresponding bidding strategies built on top of those predictions. We also reveal the close relationship between the win rate and winning price estimation, and demonstrate how to solve the two problems together. All of our estimation methods are developed with distributed framework and have been applied to billion order numbers of data in real business operation.
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Li, X., Guan, D. (2014). Programmatic Buying Bidding Strategies with Win Rate and Winning Price Estimation in Real Time Mobile Advertising. In: Tseng, V.S., Ho, T.B., Zhou, ZH., Chen, A.L.P., Kao, HY. (eds) Advances in Knowledge Discovery and Data Mining. PAKDD 2014. Lecture Notes in Computer Science(), vol 8443. Springer, Cham. https://doi.org/10.1007/978-3-319-06608-0_37
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DOI: https://doi.org/10.1007/978-3-319-06608-0_37
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-06607-3
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