Say what you mean…mean what you say?
As adults, we want most situations and conversations to end pleasantly. If I am put in a difficult situation, I will try my best to find a way to be politically correct and come out unscathed, socially accepted.
Consider an industry where two brands dominate the market. Brand A sells at a slightly higher price point than Brand B and is seen as more aspirational than Brand B. In a consumer research which asks respondents to assess both brands and identify the brand that they would most likely buy, Brand A gets more mentions. However, in the market, brand B’s sales are higher. Traditional consumer research, in this example, fails to predict buyer behaviour.
Why did this happen?
Often, when conducting consumer research around sensitive topics like political preferences, or in industries where it is important to be seen as socially correct, we humans tend to hide our true responses and say what the other person wants to hear. In some cases, we aren’t even aware of our true emotions.
In situations where people are reluctant to report what they truly feel, some may not even know what drives their decision-making, implicit methods can help1. Psychologists believe that in our subconscious, we are constantly sorting and bucketing concepts —- good vs. bad; pretty vs. ugly; male vs. female; young vs. old. We do this very quickly in our brains. Eg. Female=pink; man=strong.
There are a whole host of implicit research methods that use biometrics, heart-rate monitoring and other neuro-science methods that are best implemented in a lab. For the purpose of consumer research, facial coding, eye-tracking and the Implicit Association Test are easiest to apply.
Consider a research problem which requires evaluating a gaming app before launch. Traditional market research would ask respondents to describe their likes and dislikes, salient features, associations around “for me”, “relevance”, “uniqueness” and finally purchase intent. Most respondents are likely to give you rational responses — nothing wrong with that, but is it the whole truth?
Instead, consider first putting a camera installed with eye-tracking and facial coding software in front of the respondent when he/she is examining the app. Where do the eyes focus first? Where do they gaze longer? How do the facial expressions change — what indicates pleasure, what creates discontent?
Now combine these implicit methods with traditional explicit questions as discussed above and you have holistic respondent feedback.
Facial coding and eye tracking techniques can be implemented in a variety of areas — advertising copy testing, packaging testing, retail space testing using AR/VR, web design and social media among others.
If you Google “IAT”, the top link on the page will take you to the Harvard Implicit Association Test2. Psychologists from Harvard, University of Virginia, and the University of Washington founded Project Implicit in 1998. They developed the Implicit Association Test (IAT) to measure attitudes and beliefs that people may be unwilling or unable to share.
Complete your own IAT here. You may be surprised to discover biases you never knew you had.
Consider the example about brands A and B mentioned earlier. Traditional research using only explicit methods in this instance failed to predict buyer intentions. This is because explicit research methods are very good at understanding “what happened?” rather than “what is going to happen?”3. And while it is important to understand consumer attitudes, these are not good predictors of behaviour.
IAT can help uncover brand-category associations, brand-attribute associations and help to identify how a brand’s image differs from that of its closest competitor4.
Political researchers have often used IAT to understand voting behaviour of undecided voters5. This tool is especially powerful in countries where candidates/ political parties have polarised ideologies and a substantial group of voters are hesitant to express their true opinions at the polls.
When used in conjunction with traditional methods, implicit research techniques provide insights that may be difficult to capture otherwise. Their applicability has been proven across a variety of industries and address a range of areas — from brand & marketing to anthropology.
We will be featuring more articles in the near term focusing on specific tools in implicit testing and how these can enhance the insights from traditional market research.
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