“People don’t always do what they say, and they don’t always say what they do.”
While consumers might think they know exactly what they think or prefer, they really only have limited access to their own implicit preferences. This is one of the major obstacles that marketers face when doing market research.
In order to understand these implicit preferences more accurately, market researchers need to tap into the subconscious mind of the customer.
So, how can we tap into the consumer’s subconscious and gather deeper insights?
Essentially, most questions in marketing can be simplified to how strong two thoughts are connected in the mind (e.g., ‘How strongly is brand X associated with quality Y?’).
Today, cognitive and social psychology have developed several thorough research methods that help us in measuring the associative strength between two concepts in the mind. These methods are usually reaction-time methods, stemming from the cognitive psychological principle that our brains respond faster to thought concepts that are more strongly connected compared to concepts that are not similar to each other (e.g., apple and banana will most likely be close and it will take shorter reaction time to identify the next piece of fruit, while a book will take longer to react to after the presentation of the apple).
The reaction times are measured using a simple computer task, and thus do not require intricate (and expensive!) brain imaging equipment.
In this blog, we discuss the three most prominent scientific methods to measure implicit associations, while briefly going over its strengths and weaknesses. Let’s take a closer look.
1. Implicit Association Test (IAT)
The Implicit Association Test (IAT) is the most researched and recognized implicit research method, and therefore the tool of choice for most market researchers.
How is this test executed?
During the IAT, participants are tasked to press two keys on the keyboard in order to sort words and/or images in categories. Each key corresponds to a brand and a word relating to an association. In one block, the target brand will be coupled to a positive association by being represented under the same key. An example is shown below: positive words and the target brand are assigned to the left key and negative words and another brand that serves as a baseline for comparison are assigned to the right key.
Left key | Right key |
Positive words (e.g. 'joy') | Negative words |
Experimental brand | Baseline brand |
In the following block of trials, the sorting rules are switched such that the right key still represents the negative association but now is coupled to the target brand:
Left key | Right key |
Positive words | Negative words |
Baseline brand | Experimental brand |
As the brain needs more time to process incongruent presentations, the associative strength between the brand and the word can be calculated as the difference in reaction time between the countered two blocks. When the target brand is identified more quickly when presented with positive words compared to the identification when it presented next to negative words, we conclude that the brand is experienced positively.
The IAT has several pros when it comes to market research. The pros include, other than being the most validated implicit association measure for market research, it also has the highest predictive power on behavior, as well as the best internal consistency. The main downside of the IAT is the need for a comparison or baseline brand.
In short, the IAT has proven itself to be a reliable and useful tool for market researchers. Want to know more about IAT?
2. Affective Priming Task (APT)
Another test that measures the strength of implicit association is the Affective Priming Task which adopts a sorting method comparable to the IAT. The APT differs from related tests as it uses a priming procedure: the stimulus in question is preceded by a word or image that is flashed for a brief moment, typically between 100 and 300 ms. The preceding brief flash is known as subliminal priming: the duration of the flash is sufficient for people to perceive the prime, but not long enough for people to be aware of its influence on them.
After this subliminal prime of the brand logo, the respondent is presented with an emotionally loaded word and categorizes that as being either positive or negative.
An APT trial look like this:
Prime with brand logo → positive word (e.g. ‘joy’) → press key to sort
Prime with neutral image → positive word (e.g. ’joy’) → press key to sort
When the link between the prime and the target already exists (e.g. both the target word and the primed brand are positive in the mind of the consumer), people are likely to react faster than during trials in which there is no link between prime and the target.
To make it a bit more concrete, let’s say you are a huge fan of Nike. If you are primed with a logo of Nike, and a positive word shows up afterwards (e.g. quality), you are probably pressing the key faster than when a negative word shows up afterwards (e.g. ugly).
The associative strength between the prime and the target word is then determined by the reaction time differences between positive and negative trials.
A big plus of using the APT is that it doesn’t require baseline or comparison brands. However, the test requires a relatively high number of trials to reach reliability, while it also needs greater experimental control, since it is essential the prime remains undetected.
3. Go/No-Go Association Test (GNAT)
Contrary to the previous two methods, the Go/no-go association test does not use the concept of pressing keys in order to sort stimuli. Instead, people either have to press a key (go) or disregard it (no-go), depending on whether the stimulus fits a specific sorting rule.
Sounds vague? Here is an example.
In the first block, participants press a certain key when either a positive word or the target brand shows. If they see a negative word, or another brand, they’re told not to press the key. For the next block, this process changes: Participants now press the key for negative words and the target brand, and not for positive words or the other brand.
Does the GNAT also calculate associative strength through reaction time differences?
Unlike the methods mentioned previously, the GNAT calculates associative strength through the number of errors made versus the number of correct responses. Therefore, a better performance on the brand + positive block compared to the brand + negative block suggests a positive association.
The GNAT is advantageous as it doesn’t require baseline or comparison brands, similar to the APT. Furthermore, the GNAT appears to be a more natural measure for products that are bought out of impulse. The downside of the GNAT is that the internal consistency is somewhat lower than the staple of implicit research methods, the IAT.
The Best Method for Implicit Association Measurement?
Generally, the IAT is the optimal method to measure implicit associations. Even though you do need to include another brand to serve as a baseline comparison, the IAT is arguably the highest validated test with the most predictive power. This does not mean that the APT and the GNAT should be overlooked! If the research question somehow does not allow for an extra brand to be taken into consideration, the two methods are very adequate alternatives.
At Unravel we regularly conduct market research for national and international brands. We regularly use the IAT method for this, for example in branding research or packaging research. Furthermore EEG, Eye Tracking, Biometrics and Behavioral Experiments fall into our neuro toolbox. Based on a research issue, we decide which methods are the best fit.
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