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."
If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
|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.|
Web page: http://www.nber.org
More information through EDIRC
References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Avi Goldfarb & Catherine E. Tucker, 2011. "Privacy Regulation and Online Advertising," Management Science, INFORMS, vol. 57(1), pages 57-71, January.
- Tucker, Catherine E., 2012. "The economics of advertising and privacy," International Journal of Industrial Organization, Elsevier, vol. 30(3), pages 326-329.
- Thomas Blake & Chris Nosko & Steven Tadelis, 2015.
"Consumer Heterogeneity and Paid Search Effectiveness: A Large‐Scale Field Experiment,"
Econometric Society, vol. 83, pages 155-174, 01.
- 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.
- 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 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.
When requesting a correction, please mention this item's handle: RePEc:nbr:nberwo:19520. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: ()
If references are entirely missing, you can add them using this form.