Comparing predicted prices in auctions for online advertising

Eric Bax; Anand Kuratti; Preston McAfee; Julian Romero

doi:10.1016/j.ijindorg.2011.06.001

Comparing predicted prices in auctions for online advertising

Eric Bax, Anand Kuratti, Preston McAfee, Julian Romero

Research output: Contribution to journal › Article › peer-review

5 Scopus citations

Abstract

Online publishers sell opportunities to show ads. Some advertisers pay only if their ad elicits a user response. Publishers estimate response rates for ads in order to estimate expected revenues from showing the ads. Then publishers select ads that maximize estimated expected revenue. By taking a maximum among estimates, publishers inadvertently select ads based on a combination of actual expected revenue and inaccurate estimation of expected revenue. Publishers can increase actual expected revenue by selecting ads to maximize a combination of estimated expected revenue and estimation accuracy.

Original language	English (US)
Pages (from-to)	80-88
Number of pages	9
Journal	International Journal of Industrial Organization
Volume	30
Issue number	1
DOIs	https://doi.org/10.1016/j.ijindorg.2011.06.001
State	Published - Jan 2012
Externally published	Yes

Keywords

Auction
Bias
Prediction
Reversion
Validation

ASJC Scopus subject areas

Industrial relations
Aerospace Engineering
Economics and Econometrics
Economics, Econometrics and Finance (miscellaneous)
Strategy and Management
Industrial and Manufacturing Engineering

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10.1016/j.ijindorg.2011.06.001

Cite this

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title = "Comparing predicted prices in auctions for online advertising",

abstract = "Online publishers sell opportunities to show ads. Some advertisers pay only if their ad elicits a user response. Publishers estimate response rates for ads in order to estimate expected revenues from showing the ads. Then publishers select ads that maximize estimated expected revenue. By taking a maximum among estimates, publishers inadvertently select ads based on a combination of actual expected revenue and inaccurate estimation of expected revenue. Publishers can increase actual expected revenue by selecting ads to maximize a combination of estimated expected revenue and estimation accuracy.",

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AB - Online publishers sell opportunities to show ads. Some advertisers pay only if their ad elicits a user response. Publishers estimate response rates for ads in order to estimate expected revenues from showing the ads. Then publishers select ads that maximize estimated expected revenue. By taking a maximum among estimates, publishers inadvertently select ads based on a combination of actual expected revenue and inaccurate estimation of expected revenue. Publishers can increase actual expected revenue by selecting ads to maximize a combination of estimated expected revenue and estimation accuracy.

KW - Auction

KW - Bias

KW - Prediction

KW - Reversion

KW - Validation

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Comparing predicted prices in auctions for online advertising

Abstract

Keywords

ASJC Scopus subject areas

Access to Document

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