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Ad Industry Releases 'Final' Neuromarketing Report, Plans To Model Effectiveness Vs. 'Traditional' Research

January 19, 2012

By Joe Mandese, MediaPost

In a push to accelerate the promising field of neuromarketing, Madison Avenue’s top research authority today will release the findings of a report concluding that when used properly, neuroscience can be more insightful and effective than the “traditional” forms of survey, observational and behavioral research methods the ad industry has relied on for the past century or so to create, place and measure the effects of advertising. The authority, the ARF, also is preparing to field a new study that would utilize sophisticated marketing mix modeling techniques to compare and empirically measure the effectiveness of neuromarketing vs. conventional forms of marketing research.

The new study, which the ARF is seeking sponsors for now, would go into the field this spring, and would likely include at least two methods of neuromarketing research, and at least one traditional form of marketing research to measure the effectiveness of actual TV ad campaigns that have run and already impacted sales. By utilizing sophisticated modeling techniques, the organizers believe the industry can learn the strengths and weaknesses of the new and traditional methods of research, and to what extent they can or should be used in combination with each other.

“It is very interesting and very promising,” says Robert Woodard, who joined the ARF last year from consumer marketer Campbell Soup, where he was a big proponent of neuromarketing research methods. Woodard -- who was a key player in the first wave of benchmark studies, which included an unprecedented collaboration of some of the neuromarketing industry’s biggest competitors -- and the ARF’s Horst Stipp are leading the push, including this spring’s modeling test, which likely will be released next year during the ARF’s annual Re:Think conference in New York.

Woodard and Stipp say the ARF likely was too cautious and conservative in its initial assessment of its findings about the efficacy and application of neuromarketing methods when it released preliminary findings of the first year’s research at its annual conference last Fall, and said it is trying to correct that perception now with the release of the final report and its next round of research and testing.

Woodard acknowledges that neuromarketing methods, which utilize a variety of biometric techniques -– brain waves, facial expressions, eye-tracking, sweating and heart rate monitoring tied to scientific principles about the way the brain works –- generate “complicated signals” that are sometimes difficult to read and apply, but he says they sometimes can be better than traditional marketing research methods, because unconscious emotions account for as much as 95% of the way consumers’ brains process advertising, media and marketing communications.

He says the goal of the ARF initiatives is to understand where neuromarketing research can “do better” than traditional methods, adding that, “traditional methods are not as good as we thought.”

The ARF’s Stipp added that there is a great deal of noise and confusion within the neuromarketing research industry because “the scientists themselves don’t think alike about this.”

Moreover, the ad industry has experienced a high degree of drama surrounding some of the neuromarketing industry’s leading players, especially Nielsen-owned NeuroFocus and venture-backed EmSense, both of which boycotted the ARF’s initial study. EmSense has since gone into liquidation, and Nielsen’s NeuroFocus has created animosity on Madison Avenue -- going so far as to ambush the ARF’s release of its findings during its annual conference, but releasing its own set of “standards.”

Woodard and Stipp said the marketing mix modeling initiative would focus on TV advertising, because that is where most of the big advertising budgets still are allocated, but they said the research and findings would somehow be tied to “digital,” and ultimately, “in-store” media and marketing experiences.

 

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