Value of Targeting
- Kshipra BhawalkarAffiliated withGoogle, Inc.
- , Patrick HummelAffiliated withGoogle, Inc.
- , Sergei VassilvitskiiAffiliated withGoogle, Inc.
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.
- Value of Targeting
- Book Title
- Algorithmic Game Theory
- Book Subtitle
- 7th International Symposium, SAGT 2014, Haifa, Israel, September 30 – October 2, 2014. Proceedings
- pp 194-205
- Print ISBN
- Online ISBN
- Series Title
- Lecture Notes in Computer Science
- Series Volume
- Series ISSN
- Springer Berlin Heidelberg
- Copyright Holder
- Springer-Verlag Berlin Heidelberg
- Additional Links
- Industry Sectors
- eBook Packages
To view the rest of this content please follow the download PDF link above.