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Getting insights from data – getting to the “why?”
When you ask consumers about your products, make sure you are using the correct research method.
You may have read about the now famous story of Herman Miller’s Aeron office chair. He developed the chair through the cycle of development, market research, more development, more market research, and so on. Finally, deciding on the design we see now. His research focussed on asking consumers two questions (1) please rate the chair on comfort and (2) please rate the chair on aesthetics. His plan was to use the design which received the highest ratings on both. The trouble was that any design he created got very low ratings on both, even though in his mind he thought he had designed the perfect office chair. Notwithstanding this poor consumer feedback, he went to market…and it became the top selling office chair!
The moral of the story? When you ask someone to rate something new, if it is not simple and obvious or they really can’t verbalise how they feel, they will say they don’t like it. Often consumers will choose the least sophisticated option when they are forced to say why they like it.
The psychologist Tim Wilson has carried out a lot of research showing that when people say they actually like something they often make up a story – an explanation that has no resemblance to reality (in a typical experiment it is the manipulation that determined the liking rather than the story the participant made up). Infact, Tim Wilson has shown that people actually have very poor insights into their own inner worlds – he argues that we are strangers to ourselves.
Consumer Insights – Beyond Liking
To yield more effective consumer insights, we need to go beyond what is immediately visible and dig deeper. We need to examine why the consumer is doing what they are doing in their own world. Insights that are fresh, true, targeted and actionable are those we need to develop.
Split Second’s Implicit research methods go beyond liking. They seek to ask why a consumer prefers this brand, product, or packaging rather than that brand, product or packaging. It can tell us why and how one piece of advertising creative will work on one target audience but not another demographic. Split second’s implicit conusmer testing is able to characterise the feelings the consumer has towards the products, going much deeper than simple liking and disliking. The method is very consumer focussed and bypasses those biases that can influence verbal responses. Split second’s implicit tests are very difficult to fake, hence they provide a pure read-out of consumers’ feelings.
New product development should be cyclical: design the concept, test the market, design the prototype, test the market, develop several design options and test the market. Before implicit technology, this was a slow process, but now with the aid of our IMPRESS platform this product development cycle becomes a reality. We can turn around results in 48 hours, so your development team can get on with the business of optimising the product.
Dr Eamon Fulcher
What can implicit reaction time tests tell us about consumer attitudes and intentions that traditional, explicit, methods can’t?
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 reaction time tests hold the promise to unlock deep seated consumer attitudes. Using the analogy of an archaeological dig (as a colleague of mine likes to use), implicit tests, like Split Second’s Impress Test, can help uncover the hidden treasures buried in the consumer’s mind. This is something that market researchers and brand managers have been looking to use for some time, given the weaknesses of traditional methods.
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.