Implicit implications
How do you know what you know? Much of what we do and the decisions that we make are based on knowledge or attitudes that are accessed without conscious effort. Hence, driving a car would be impossible if we continuously needed to think about each step of the process. Experienced doctors are able to make snap decisions by ‘reading’ a patient and their health without going through an explicit mental checklist. It is all part of the process of the automation of perception and reaction that is characteristics of expertise.
Expertise comes in a variety of forms. In one sense, we are all experts regarding the products we use or consume. Food psychologist EP Koster has often made the point that we instantly know when a food company has tampered with our favourite marmalade, even if we are not sure exactly what has changed. Experimentally, too, this was shown in a study in which very small amounts of tastants (sweet, sour, bitter) were added to foods (cream cheese, orange juice, yoghurt) that had been sampled earlier in the day. Asked to compare the new versions with those they had consumed earlier, the participants were especially sensitive to any negative change produced by minimal increases in bitterness, even though it is unlikely that would have been able to articulate what exactly the change was [1]. In other words, they were retrieving implicit rather than explicit information.
In some cases, information is encoded implicitly in the first place, and our behavior and preferences can be shaped by experiences with stimuli that never entered conscious awareness. Thus, the ingenious study of the German recipients of formula milk to which vanilla had been added showed that these experiences were influential in determining a food choice (ketchup with or without a tiny amount of added vanilla) even 30 years later [2].
Consumer research of any kind is aimed at retrieving knowledge that is assumed to be at the consumer’s fingertips. But what if it isn’t? Social psychologists sometimes study phenomena in which an ‘honest’ answer can not be assumed. Thus, if asked questions about our own attitudes to other races, there is enormous internal pressure to conform to cultural norms, even if we know that the information won’t get further than the researcher’s computer. We do not like to admit even to ourselves that we have attitudes that would meet universal disapproval if voiced.
Consumer researchers sometimes have the same concerns, although this is more motivated by the fact that ratings of liking for, say, a new product is a poor predictor of how well that product will actually do in the marketplace. The rather illogical response is sometimes to blame the consumer: they are obviously stubbornly not revealing their true attitudes towards the product. One consequence is the search for “objective” measures of liking such as brain scanning - as though there was a blind alley between “the brain” and the mouth down which honest opinions get sent.
One approach to the problem of retrieving attitudes taken by social psychologists has been the development of the Implicit Association Test (IAT). This is based on the assumption, not that people’s responses are inherently dishonest, but that there may be attitudes that are not explicitly or consciously available or that are difficult to put into words. The technique works by exploiting the fact that responses to things that belong together (words; objects) are faster than when there is a disconnect between them. So, if I flashed up pairs of words on a screen and asked you to instantly press a key, your response to “mother + father” would be quicker than to “mother + sheep”. Now, as the social psychologists do, imagine if I flashed up the name of another race (you decide which!) plus either of the words ‘dumb’ or ‘smart’. Any difference in reaction times between these two words paired with the race would reveal attitudes without ever having to ask a question about racial beliefs.
As one example, I previously (Le topic du jour: Gout qui importe; December, 2012) reported the distinction between French and American consumers in their attitudes towards food tastiness and health, the results of an IAT study that compared responses to the terms “tasty” with “healthy” and “unhealthy”.
The pairings in the IAT do not need to be words but can also be visual images such as labels, people, places or events. For instance, the IAT was recently applied to examining the fit between marketing slogans and their associated products. Pairings of the words “gentle” and “powerful” with images of the bottles of different brands of mouthwash showed that consumers had internalized the marketing messages of each company. Responses to the mouthwash that marketed itself as gentle were fastest when the bottle image was paired with this label than when paired with “powerful”; conversely, the word “powerful” produced the faster reactions times when paired with the bottle of the other brand, again consistent with its marketing [3].
There are indications that measuring implicit responses is being increasingly recognized in sensory consumer science. At the recent Pangborn Symposium in Rio de Janeiro (see: http://www.pangborn2013.com) several presentations focused on measures of implicit reactions to products, including the measurement of emotions – currently one of the current hot topics in sensory/consumers research – using the IAT. Other reported implicit measures included the measurement of facial responses, although the extent to which these might be consciously controlled is an important methodological issue.
One potential next step is to include product tasting with the IAT and assess the extent to which the product’s sensory and functional properties is congruent with the product image and concept. The final plenary talk at the 2013 Pangborn discussed the issue of fit between a product’s conceptual profile (essentially the set of associations and emotions that it evokes) and its sensory properties, noting that the degree of alignment of the two equates to whether or not a product ‘fit-to-brand’. The conclusion was that significant mismatch between a product’s conceptual profile and what it actually delivers to the consumer presents a serious risk that the product will fail [4].
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1. Koster, M.A., J. Prescott, and E.P. Koster, Incidental learning and memory for three basic tastes in food. Chem. Senses, 2004. 29(5): p. 441-453.
2. Haller, R., et al., The influence of early experience with vanillin on food preference later in life Chem. Senses, 1999. 24(4): p. 465-467.
3. Parise, C. and C. Spence, Assessing the associations between brand packaging and brand attributes using an indirect performance measure. Food Qual Pref, 2012. 24: p. 17-23.
4. Thomson, D. The application of conceptual profiling in brand, product and packaging development. 10th Pangborn Sensory Science Symposium, Rio de Janeiro, Brasil, 11-15th August, 2013.
