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Implicit Testing in Consumer Product Research

By layering implicit associations onto explicit data collection we have the opportunity to learn key information that can drive product development.


Editor’s Note: Daniel will be presenting “Not Just What We See, But Also What We Smell” at the IIeX Forum on Nonconscious Consumers. Join Daniel and other industry experts November 14-15 in Chicago to learn how the world’s biggest, most successful brands are turning to the behavioral sciences and nonconscious measurement tools to better understand, measure, and predict consumer behavior. Find out more here

By Daniel Blatt

Product research is too often neglected by consumer product companies, who tend to invest disproportionate time and money on marketing and communication research.  At Q Research Solutions (Q) we believe that consumer product research is critically important to win market share. Great product research, allows you to understand consumer preferences and drivers and to develop superior products that consumers love and buy again and again.

Traditional product research is excellent for understanding what consumers can verbalize, namely what they like and don’t like, and to a lesser extent why.  However, we know that purchase and repurchase behaviour is not always directly predicted by what consumers tell you. This disconnect between what consumers tell you and what they do has sparked a lot of discussion and research.

In Thinking, Fast and Slow, Kahneman wrestles with flawed ideas about decision making and the impact of System 1 & System 2. System 1 “is the brain’s fast, automatic, intuitive approach”, System 2 is “the mind’s slower, analytical mode, where reason dominates.” Kahneman says “System 1 is…more influential…guiding…[and]…steering System 2 to a very large extent.”

Traditional product testing has focused on system 2, or what the consumer can or choose to explicitly verbalize not to mention that consumers are often unaware of why they bought something. This makes understanding the implicit or System 1 critical.  Market researchers understand this and are starting to develop and include implicit association measurement techniques into their toolboxes.

At Q we understand that although System 1 has been well studied and to some extent applied in communication and marketing research it has been largely ignored in consumer product testing, or even worse misapplied through the study of reaction time.  Studying a consumer’s reaction time to an explicit idea, is not an implicit test but rather a “fast explicit” test.

With this paradigm in mind, we partnered with Emotive Analytics who has adapted a real implicit technique, not based on reaction time, called the Affect Misattribution Procedure (AMP).  It was developed by Dr. Keith Payne, PhD at the University of North Carolina and has over 10 years of use and has amassed impressive credentials.

Next month at the IIEX forum in Chicago we will be presenting some brand new findings in this very area. In particular, we’ll be demonstrating how real implicit testing can be applied to the sensory and consumer product research field.  In a first of its kind experiment, we demonstrate how combining traditional System 2 testing with System 1 implicit testing (Affect Misattribution Procedure) can aid product development.

We show how emotions and feelings are activated and can be measured by, activating the sense of smell. And we answer two important questions:

  1. Are different fragrances implicitly associated with different emotions and feelings?
  2. If so, how do these implicit associations compare to explicit associations with the same emotions and feelings?

What we discovered is that implicit will never completely replace traditional methods. In traditional testing there can be occasions where the respondent will provide overly positive opinions, however through the use of implicit we can really look at the real underlying and subconscious reactions to the stimuli. This doesn’t mean that implicit will replace traditional testing, but by layering implicit associations onto explicit data collection we have the opportunity to learn key information that can drive product development.

For the full details of our experiments in the subconscious come visit us at IIEX in Chicago next month.

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One response to “Implicit Testing in Consumer Product Research

  1. Too much is written about the unreliability of explicit questions in capturing consumer attitudes. The reference is always to the inability of market research to capture real motivations for consumer behaviour. The argument is tied up with the very topical Systems theory of Kahneman and Behavioral Economics that suggests high degrees of irrationality around consumer decision making. Neuroscience has been trying to prove this decision theory with brain imaging without any great success. Current research suggests that Type 1 and Type 2 responses occur at the same time and are not clearly localized. A number of research firms have got on the Implicit data capture band wagon claiming great things for the technology. However when you dig into the methodologies most of them look like Explicit data capture “done fast”.

    The most thorough attempt to identify implicit attitudes has come from the research into the AMP model mentioned here. One of the most surprising findings from research using AMP is that there is not always such a big difference between Explicit and Implicit measures as this article suggests quite correctly. In fact a lot of the supposed difference was in study design. It is clearly very “trendy” now to fall for this “you cannot ask consumers a question directly” nonsense. Market research has recognized this problem does exist in some areas and it is why qualitative solutions, ethnography and discrete choice models were developed.

    Its great to see one market research company challenging this smug and sometimes self serving view.

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