Measuring the Effects of Advertising: The Digital Frontier
Online advertising offers unprecedented opportunities for measurement. A host of new metrics, clicks being the leading example, have become widespread in advertising science. New data and experimentation platforms open the door for firms and researchers to measure true causal effects of advertising on a variety of consumer behaviors, such as purchases. We dissect the new metrics and methods currently used by industry researchers, attacking the question, "How hard is it to reliably measure advertising effectiveness?" We outline the questions that we think can be answered by current data and methods, those that we believe will be in play within five years, and those that we believe could not be answered with arbitrarily large and detailed data. We pay close attention to the advances in computational advertising that are not only increasing the impact of advertising, but also usefully shifting the focus from "who to hit" to "what do I get."
|Date of creation:||Oct 2013|
|Date of revision:|
|Publication status:||published as Measuring the Effects of Advertising: The Digital Frontier , Randall Lewis, Justin M. Rao, David H. Reiley. in Economic Analysis of the Digital Economy , Goldfarb, Greenstein, and Tucker. 2015|
|Contact details of provider:|| Postal: National Bureau of Economic Research, 1050 Massachusetts Avenue Cambridge, MA 02138, U.S.A.|
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- Randall Lewis & David Reiley, 2014. "Online ads and offline sales: measuring the effect of retail advertising via a controlled experiment on Yahoo!," Quantitative Marketing and Economics (QME), Springer, vol. 12(3), pages 235-266, September.
- Avi Goldfarb & Catherine E. Tucker, 2011. "Privacy Regulation and Online Advertising," Management Science, INFORMS, vol. 57(1), pages 57-71, January.
- Tom Blake & Chris Nosko & Steven Tadelis, 2014.
"Consumer Heterogeneity and Paid Search Effectiveness: A Large Scale Field Experiment,"
NBER Working Papers
20171, National Bureau of Economic Research, Inc.
- Thomas Blake & Chris Nosko & Steven Tadelis, 2015. "Consumer Heterogeneity and Paid Search Effectiveness: A Large‐Scale Field Experiment," Econometrica, Econometric Society, vol. 83, pages 155-174, 01.
- Avi Goldfarb & Catherine Tucker, 2011. "Online Display Advertising: Targeting and Obtrusiveness," Marketing Science, INFORMS, vol. 30(3), pages 389-404, 05-06.
- James Murphy & P. Allen & Thomas Stevens & Darryl Weatherhead, 2005. "A Meta-analysis of Hypothetical Bias in Stated Preference Valuation," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 30(3), pages 313-325, 03.
- Tucker, Catherine E., 2012. "The economics of advertising and privacy," International Journal of Industrial Organization, Elsevier, vol. 30(3), pages 326-329.
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