Using Quasi-Experimental Data To Develop Empirical Generalizations For Persuasive Advertising

Abstract

<h3>ABSTRACT</h3> “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. We describe our EGs as normative statements, i.e., “evidence-based principles.” Using data from 240 pairs of print advertisements from five editions of the <i>Which Ad Pulled Best</i> series, we analyzed 56 of the advertising principles from <i>Persuasive Advertising</i> 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. Aspects of the advertisements differed, however, as in illustrations, headlines, and text. The findings from 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, quasi-experimental findings always agreed with experimental findings. This is impressive given that the quasi-experimental analyses—and some of the experimental analyses—involved small samples, and often used different criteria.