Journal of Advertising Research
February 9, 2010
Advertising Research Foundation

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Current Issue

Volume 49, No. 4, December 2009


Getting Metrics Right
Geoffrey Precourt, Volume 49, No. 4, December 2009, pp.395-396
DOI: 10.2501/S0021849909091004

In his editorial, Geoffrey Precourt discusses the use of metrics to marketers and introduces the articles for this issue of the Journal of Advertising Research. ...



Viewpoint: Just Asking - Why You Should Make People Curious about Your Brand
Joel Rubinson, Volume 49, No. 4, December 2009, pp.399-400
DOI: 10.2501/S0021849909091016

In Viewpoint, Joel Rubinson discusses the effect of curiosity on humans and how marketers can engage it. He presents factors to consider for building curiosity into products, brand communications and retail activation including creating places to explore or using rich digital media. ...



Commentary: Who Owns Metrics? Building a Bill of Rights for Online Advertisers
Ben Edelman, Volume 49, No. 4, December 2009, pp.401-403
DOI: 10.2501/S0021849909091028

In his commentary, Benjamin Edelman writes on industry fair practice on the use of metrics. He presents the rights of advertisers: the right to know where its ads are shown; the right to meaningful, itemized billing; the right to use its data as it sees fit; the right to enjoy the fruits of its advertising campaigns; and the right to resolve disputes fairly and transparently. ...



It’s Personal: Extracting Lifestyle Indicators in Digital Television Advertising
George Lekakos, Volume 49, No. 4, December 2009, pp.404-418
DOI: 10.2501/S0021849909091041

Digital television technology developments provide the unprecedented opportunity to personalize television advertisements enhanced with interactive features on the basis of viewers’ preferences or interests. Existing personalization techniques applied over interactive platforms such as the Web provide the framework for the development of novel personalization approaches that ta ...



Measuring Advertising Quality on Television: Deriving Meaningful Metrics from Audience Retention Data
Dan Zigmond, Sundar Dorai-Raj, Yannet Interian and Igor Naverniouk, Volume 49, No. 4, December 2009, pp.419-428
DOI: 10.2501/S0021849909091090

In recent years, there has been an explosion of interest in collecting and analyzing television set-top box (STB) data (also called "return-path" data). As U.S. television moves from analog to digital signals, digital STBs increasingly are common in American homes. Where these are attached to some sort of return path (as is the case in many homes subscribing to cable ...



A New Branch of Advertising: Reviewing Factors That Influence Reactions to Product Placement
Eva A. van Reijmersdal, Peter C. Neijens and Edith G. Smit, Volume 49, No. 4, December 2009, pp.429-449
DOI: 10.2501/S0021849909091065

This literature review presents a quantitative synthesis of 57 studies on product placement and shows which factors are most effective. It shows that placement characteristics, such as placement commerciality, modality, and prominence, have a strong impact on audience reactions. Audience characteristics, such as attitudes and beliefs about brand placement, advertising, and medi ...



How Effective is Creativity? Emotive Content in TV Advertising Does Not Increase Attention
Robert G. Heath, Agnes C. Nairn and Paul A. Bottomley, Volume 49, No. 4, December 2009, pp.450-463
DOI: 10.2501/S0021849909091077

Emotive creativity is generally believed to facilitate communication by increasing attention. However, during relaxed TV viewing, psychology suggests we may pay less not more attention to emotive ads. An experiment conducted in a realistic viewing environment found that ads that were high in emotive content correlated with a 20 percent lower level of attention and that attentio ...



A Special Report from the Advertising Research Foundation - The Foundations of Quality Initiative: A Five-Part Immersion into the Quality of Online Research
Robert Walker, Raymond Pettit and Joel Rubinson, Volume 49, No. 4, December 2009, pp.464-485
DOI: 10.2501/S0021849909091089

This article introduces a measure of television ad quality based on audience retention using logistic regression techniques to normalize such scores against expected audience behavior. By adjusting for features such as time of day, network, recent user behavior, and household demographics, we are able to isolate ad quality from these extraneous factors. We introduce the model u ...