An Empirical Analysis of the Value of Information Sharing in the Market for Online Content | Beales, Eisenach

J. Howard Beales, Jeffrey A. Eisenach; An Empirical Analysis of the Value of Information Sharing in the Market for Online Content; Navigant Economics, commissioned by the Digital Advertising Alliance (DAA); 2014-01; 19 pages.

Abstract

(from the Introduction)

This paper studies the importance of consumer-related information to the market for display advertising and, in turn, to the publishers who produce and distribute online content. Our study is based on two primary data sets. The first is a large, impression-level database of advertising placements during a one-week period in August 2013, provided by two anonymous companies that operate advertising exchanges with automated bidding. These data form the basis for an econometric analysis that allows us to measure the premium paid by advertisers for ads served to customers with cookies, and ultimately to assess the added economic value generated by information sharing in the online content market. The second data set, provided by Adomic, measures the relative prevalence of ads generated by different advertising models based on observations of display ad placements for the top 4000 publishers. This data set allows us to assess the relative significance of third party advertising technology models to the industry in general, and to smaller, “long-tail” web sites in particular.

The results of our econometric analysis corroborate and extend an emerging body of empirical work documenting the value of information sharing in online advertising. Our estimates indicate that advertisers place significantly greater value on users for whom more information is available, and our results are highly significant both in a statistical and economic sense: after controlling for other factors, the availability of cookies to capture user-specific information is found to increase the observed exchange transaction price by at least 60 percent relative to the average price (for users with “new” cookies), and by as much as 200 percent (for users with longer-lived cookies). In addition, the Adomic data reveal that even the largest publishers rely on third-party technology models to serve approximately half of their advertising impressions, while “long-tail” publishers rely upon third-party technology models for up to two thirds of their advertising volumes.

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