The Difference Between Implicit vs. Explicit Testing

The Difference Between Implicit vs. Explicit Testing

With several different research approaches, from more conventional polls, focus groups, and milk research, to more advanced immersive VR / AR research, eye-tracking techniques, and various behavioural science-based approaches, market research is a fascinating area.

But several of these words are easily recognizable-implicit vs. explicit testing is not spoken about as much. This paper discusses precisely what the distinction between implicit and explicit study is and what the future of these methodologies entails.

Implicit vs. Explicit - The Difference Defined

Explicit testing methods are those direct methods that allow consumers to take the time to think on their reactions before responding to them, such as conventional surveys and focus groups, offering more educated and logical perspectives. What distinguishes this form of research is the incitement of system 2 thought among participants.

The exact opposite is implicit testing. It includes strategies that immerse participants in the ideal scenario and rely on their intuitive, in-the-moment behaviour to generate more specific observations rather than rationalized choices. The most common implicit test is the Implicit Association Test, created by Harvard University, which analyses the behaviours and values that individuals may be unable or unable to disclose. System 1 thought is what distinguishes implicit tests.

It is important to note that while these definitions allow you to build the beginning of an understanding on implicit vs. explicit research methods, many implicit research authors mention a scale of 'implicitness' defined by how controlled the testing conditions are, which means that there is currently no fully implicit testing method, but there are techniques that encourage a stronger system.

Evolving Research Methods - The Difference Explored

It is important to note that while these concepts allow you to construct the beginning of an understanding on implicit vs. explicit research methods, many implicit research authors discuss a scale of 'implicitness' determined by how regulated the testing conditions are, which implies that there is currently no completely implicit testing process, but there are techniques that promote a stronger framework.

Yet, there are limits to these research methods, as Aaron Reid so clearly notes, no matter how much we innovate them with mobile, smart, and automation technologies: limits on motivation, truthful responses, possibilities for response choices, ability to express our responses without a lot of effort on all ends, and knowledge. Reid drew up a table of limitations based on a report by Nose et al in his article on implicit testing, describing them in a more detailed way, which can be found here.

We have not been blinded by our familiarity and dependence on these methods to the fact that these rationalized perspectives do not yet encompass the full range of human decision-making. They lack emotional connection and influence; instead of exposing their true character, thoughts and beliefs, they are focused on what users would like themselves to be.

So, it comes as no surprise that our market research approaches have developed to incorporate and be informed by external sources of research, often from fields of behavioural science such as psychology, cultural anthropology, and sociology; and that the more advanced, modern techniques that are still very unique in the industry are based on capturing a customer's behaviours.

This can currently be achieved by common methods such as: social media intelligence, which allows researchers to monitor consumers engaging in a non-research setting with each other; facial and eye monitoring technology while customers walk through a store; recording equipment as a participant faces a scenario through virtual or augmented reality; or wearable and smartwatch.

These are, however, strategies that can be accurately categorized as implicit research approaches, which also on a smaller scale provide an insight into the emotional, unconscious decision-making process of a participant directly related to action-led decisions, which is very important if we are to close the interpretation gap between reasonable motives which impulsive behaviour of consumers.

Consumer Intention vs. Action – Looking to the Future of Implicit Testing

Let's take a moment to think about this topic that we are all familiar with as insight professionals: our industry has been plagued by the discrepancy between customer purpose and consumer behaviour for years, making well-researched and well-intentioned data totally off-base. This gap is a problem that we can slowly begin to close by knowing the difference between implicit and explicit testing, but we still need to answer one major question about these two styles of testing: how do we fit implicit testing into conventional systems of research?

And it isn't one or the other when it comes to implicit and explicit testing. Fitting both research modes with each other will show more about our participants to us than taking both of them separately. Much as the two human behavioural mechanisms are interconnected and affect each other, so can the strategies that we have chosen to observe them. This is how we close the distance between purpose and action by recognizing how our actions and character work together and educating them on a regular basis.