Value of Targeting

  • Kshipra Bhawalkar
  • Patrick Hummel
  • Sergei Vassilvitskii
Conference paper

DOI: 10.1007/978-3-662-44803-8_17

Part of the Lecture Notes in Computer Science book series (LNCS, volume 8768)
Cite this paper as:
Bhawalkar K., Hummel P., Vassilvitskii S. (2014) Value of Targeting. In: Lavi R. (eds) Algorithmic Game Theory. SAGT 2014. Lecture Notes in Computer Science, vol 8768. Springer, Berlin, Heidelberg

Abstract

We undertake a formal study of the value of targeting data to an advertiser. As expected, this value is increasing in the utility difference between realizations of the targeting data and the accuracy of the data, and depends on the distribution of competing bids. However, this value may vary non-monotonically with an advertiser’s budget. Similarly, modeling the values as either private or correlated, or allowing other advertisers to also make use of the data, leads to unpredictable changes in the value of data. We address questions related to multiple data sources, show that utility of additional data may be non-monotonic, and provide tradeoffs between the quality and the price of data sources. In a game-theoretic setting, we show that advertisers may be worse off than if the data had not been available at all. We also ask whether a publisher can infer the value an advertiser would place on targeting data from the advertiser’s bidding behavior and illustrate that this is impossible.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Kshipra Bhawalkar
    • 1
  • Patrick Hummel
    • 1
  • Sergei Vassilvitskii
    • 1
  1. 1.Google, Inc.USA

Personalised recommendations