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Here, There, and Everywhere: Correlated Online Behaviors Can Lead to Overestimates of the Effects of Advertising

Proceedings of the 20th ACM International World Wide Web Conference (WWW20) 2011, pp.157-166.

10 Pages Posted: 9 Jun 2012  

David Reiley Jr.

Google, Inc.

Justin M. Rao

Microsoft Research; Microsoft Corporation - Microsoft Research - Redmond

Randall A. Lewis

Netflix

Date Written: 2011

Abstract

Measuring the causal effects of online advertising (adfx) on user behavior is important to the health of the WWW publishing industry. In this paper, using three controlled experiments, we show that observational data frequently lead to incorrect estimates of adfx. The reason, which we label “activity bias,” comes from the surprising amount of time-based correlation between the myriad activities that users under- take online. In Experiment 1, users who are exposed to an ad on a given day are much more likely to engage in brand- relevant search queries as compared to their recent history for reasons that had nothing do with the advertisement. In Experiment 2, we show that activity bias occurs for page views across diverse websites. In Experiment 3, we track account sign-ups at a competitor’s (of the advertiser) website and find that many more people sign-up on the day they saw an advertisement than on other days, but that the true “competitive effect” was minimal. In all three experiments, exposure to a campaign signals doing “more of everything” in given period of time, making it difficult to find a suitable “matched control” using prior behavior. In such cases, the “match” is fundamentally different from the exposed group, and we show how and why observational methods lead to a massive overestimate of adfx in such circumstances.

Keywords: advertising effectiveness, field experiments, browsing behavior, causal inference, selection bias

JEL Classification: J4, J1

Suggested Citation

Reiley, David and Rao, Justin M. and Lewis, Randall A., Here, There, and Everywhere: Correlated Online Behaviors Can Lead to Overestimates of the Effects of Advertising (2011). Proceedings of the 20th ACM International World Wide Web Conference (WWW20) 2011, pp.157-166.. Available at SSRN: https://ssrn.com/abstract=2080235

David H. Reiley Jr. (Contact Author)

Google, Inc. ( email )

1600 Amphitheatre Parkway
Second Floor
Mountain View, CA 94043
United States

Justin M. Rao

Microsoft Research ( email )

641 Avenue of Americas
7th Floor
New York, NY 11249
United States

Microsoft Corporation - Microsoft Research - Redmond ( email )

Building 99
Redmond, WA
United States

Randall A. Lewis

Netflix ( email )

Los Gatos, CA
United States
312-RA-LEWIS (Phone)

HOME PAGE: http://www.econinformatics.com/

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