Do you know what consumers associate with your brand?
Is it associated with innovation? Is it trusted? Is it perceived as a premium brand? Is it old-fashioned or trendy?
Implicit reaction time tests (IRTs) are one of the fastest growing approaches in market research and other fields to measure brand associations. Online, objective and cost-effective, they capture immediate, intuitive, gut reactions or subconscious responses to brands, campaigns, new product concepts, packaging designs and a vast array of other marketing related outputs. Free from the biases of conscious rationalization and distracting ploys inherent in quantitative and qualitative research, IRTs offer marketers a chance to study consumers at a deep, emotional level and predict their behaviour more accurately than has previously been possible.
Implicit reaction time tests, whether based on the implicit association test (the IAT) or on affective priming are on the rise in the world of market research.
Implicit market research holds the promise to unlock deep seated consumer attitudes. Using the analogy of an archaeological dig, implicit tests, like Split Second’s Impress Test, can help uncover the hidden drivers in the consumer’s mind. This is something that market researchers and brand managers have always been searching for, but now becomes ever more possible.
The way implicit reaction time tests can tap into deep seated feelings has been likened to an archaeological dig.
Yet, market researchers and brand managers can’t work on a promise alone. There is too much to lose – not just the research budget, but the financial consequences of bad research. So an important question is what can implicit reaction time tests tell us about consumer attitudes and intentions that traditional, explicit, methods cannot?
One way to test whether implicit reaction time tests, such as Split Second’s Impress Test, can measure anything useful about consumer attitudes and intentions might be to look for the predictive ability of implicit and explicit tests – are there circumstances in which either or both of these measures are strongly related to the purchasing behaviours of consumers.
There are numerous examples in the peer-reviewed literature demonstrating that in many circumstances implicit attitudes are better predictors of subsequent behaviour than explicit responses provided at the same time. For example, Steinman and Karpinski (2009) found that implicit but not explicit attitudes towards the brand GAP predicted GAP patronage and buying intentions. Brunel, Tietje and Greenwald (2004) showed that implicit methods can detect attitudes about brands that explicit measures cannot (e.g., how different races advocated different patterns of brand preferences implicitly but not explicitly).
Other research includes Priluck and Till (2009) who found that explicit and implicit measures were both good at detecting attitudinal differences between brands when the difference was large or obvious, but only implicit methods could detect differences when they are less obvious. Other research shows that implicit methods in a consumer context are difficult to fake. For example, Chan and Sengupta (2010) found that while the claims of an advertisement were dismissed, implicit responses revealed that the ad had induced favourable attitudes to the brand.
An interesting study published in 2010 by a team of researchers in Italy headed by from Michelangelo Vianello, shows how important it is to assess true feelings as opposed to those that people like to state in order to present themselves in a favourable light. College students were given two different measures of conscientiousness, one was a traditional explicit personality self-report questionnaire and the other was an implicit reaction time test whose attributes focussed on conscientiousness. Half of the students were further told to imagine that they were being tested for their ideal job (one with a good income, low effort, and so on) and the half were not told this. Those with the job-story scored higher on conscientiousness but only on the self-report test. This shows that they could give biased answers and present themselves in a very favourable light. Yet, both groups scored about the same on the implicit measure – this is remarkable because it shows that the implicit measure was not so easy to fake.
Academic studies like this provide very strong evidence of the usefulness of implicit reaction time tests. In addition to such studies, Split Second Research has a wealth of evidence from its own R&D and project work with clients to show how powerful the technique is. To read case studies relevant to your field, please contact us here.
Dr Eamon Fulcher
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