Date of this Version
This paper argues that “quasi-experimental data” provide a valid and relatively low-cost approach toward developing empirical generalizations (EGs). These data are obtained from studies in which some key variables have been controlled in the design. These EGs are described as normative statements, i.e., “evidence-based principles.” Using data from 240 pairs of print advertisements from five editions of the Which Ad Pulled Best series, the authors analyzed 56 of the advertising principles (listed) from Persuasive Advertising by J. Scott Armstrong (New York: Palgrave Macmillan, forthcoming). These data controlled for target market, product, size of the advertisement, media, and in half the cases, for the brand. The advertisements differed, however, e.g. in illustrations, headlines, and text. The findings from the quasi-experimental analyses were consistent with field experiments for all seven principles where such comparisons were possible. Furthermore, for 26 principles they unanimously corroborated the available laboratory experiments as well as the meta-analyses for seven principles. In short, the quasi-experimental findings always agreed with experimental findings, even though the quasi-experimental analyses, and some of the experimental analyses, involved small samples, and often used different criteria. From an issue of JAR devoted to `empirical generalisations’: the papers were first presented at a conference at the Wharton School, University of Pennsylvania in December 2008.
Armstrong, J. S., & Patnaik, S. (2009). Using Quasi-Experimental Data to Develop Empirical Generalizations for Persuasive Advertising. Retrieved from https://repository.upenn.edu/marketing_papers/167
Date Posted: 31 May 2011
This document has been peer reviewed.