Imagine choosing a chocolate bar at the cash register. You might glance at the display, your hand moves to pick it up, and it’s done. No time for weighing the pros and cons or an inner debate about cocoa percentages. The whole thing is over in a couple of seconds. Then, if someone stopped you and asked why you picked it, your reason would sound sensible. Yet it will also have been invented after the fact, as the chances are the whole process was driven by your subconscious brain.

If that decision happens so fast, the real question for anyone in market research is how you measure it. Simply asking consumers questions won’t get you there. You have to catch the decision closer to its source: in the brain itself, and in its patterns of quick, automatic responses that run beneath awareness. Some recent studies provide examples of why this is the case.

Researchers at Erasmus University in Rotterdam collected fMRI scans from 113 people in two countries while they watched 85 video ads, then read which mental processes were active moment by moment (1). The processes that predicted whether someone would go on to like an ad were emotion and memory, and they appeared as early as three seconds into the ad. Social reasoning and slower, more consciously deliberate processing came later. Emotion predicted almost at once and then mattered less as the ad played on, as if the brain had already filed the ad under ‘like’ or ‘don’t like’ in the first few seconds, before the viewer had consciously worked out what they were watching.

Eye movements also reveal how decisions happen quickly. In one study, people browsed virtual product designs while their gaze was tracked, and a model could recognise which item they were about to pick with 90% accuracy from their viewing patterns in the three seconds before they committed (2). This is the ‘gaze cascade’ that earlier research had found was a sales predictor in 2003 (3): in the run-up to a choice, we look more and more at the thing we’re about to choose, and the bias builds before we’re aware of having decided. A separate piece of work using a deep-learning model called RETINA predicted which laptop people would choose from just five seconds of raw eye-tracking data, well before they apparently reached their decision (4).

The decision doesn’t even have to wait for you to consciously focus on a product. In a study by neuroscientists in Berlin, people saw photos of cars for 2.4 seconds each inside an fMRI scanner (5). One group rated each car’s looks. The other had to keep their eyes fixed on a point away from the car and never rated it, so the car only crossed their field of view while they were busy with something else. Afterwards, everyone was asked which cars they would want to buy. The brain response as each car appeared predicted the later choice, and it predicted just as well for the cars people never actually looked at. I wrote about this experiment in my book Neuro Design (6), and it still surprises me.

We not only make choices automatically within seconds but can form an opinion on something new extremely rapidly. This is the power of the first impression, what psychologists call ‘thin-slicing’: a quick, accurate read taken from the thinnest sliver of experience. The psychologist Nalini Ambady showed people silent two-second clips of a teacher they had never met and asked them to rate how good the teacher was (7). Those two-second verdicts closely matched the ratings given by students who had sat with the same teacher for a whole semester, showing that our automatic first impressions can also be long lasting.

Our brains evolved to make quick decisions outside of our conscious awareness. For most of our history, survival rewarded a fast read of a situation, safe or dangerous, good or bad, approach or avoid, made in a moment and acted on. The slow, deliberate, reason-it-through machinery came later, and it runs at a different pace. Our buying decisions lean on this older, quicker system far more than we might realise.

And the pressure has only grown. Back in 2016, Facebook’s Messenger and WhatsApp alone were already carrying 60 billion messages a day, three times the world’s SMS traffic, and the number has climbed since (8). We are now encountering more novel information and messages per day than our ancestors might have in their whole lives. Meaning our attention spans have never been under so much pressure.

If the decision is largely made in the first few seconds, the standard market-research question (‘what did you think of this ad?’) is likely to be inadequate. By the time someone answers, they’ve left the fast, automatic part of the process and entered the slow, reason-giving part. They aren’t lying. They are just giving you their best guess.

I’m not saying people are bad at introspection in general. I’m saying that for a quick, emotional, visual kind of judgement, the conscious explanation arrives too late and gets reconstructed on the way out.

For example, ask a tennis player to spell out the split-second calculations behind returning a serve, where to move and the exact angle to hold the racket, and she would be lost for words. The skill sits below the level she can put into words. Fast buying decisions are no different. The doing and the explaining run on separate tracks, and a survey can only reach one of them.

When you want a considered opinion, the meaning of a brand, or what people think a campaign is saying, a well-designed question is the right tool. But to predict what someone will actually do, you need to reach the parts a survey can’t: the automatic associations, emotions and the desire for the product.

This is where response-time and eye-tracking methods are useful. They don’t claim to expose hidden thoughts people are deliberately concealing. They capture how quickly and how consistently a response forms.

Response time measures can be some of the most revealing signals we have. If you show someone a brand and an attribute and measure how fast they link the two, the speed tells you something the rating doesn’t. A quick, fluent ‘yes’ is a different mental event from a slow, effortful one, even when both end up as a 7 out of 10 on a scale. Our own Fast Choice method, which measures Intuitive Associations, is built on this: it records not just which associations people endorse but how readily they come.

Eye-tracking measures add the visual half. The gaze cascade studies show that attention and choice are bound together: the chosen option is usually the most looked-at and the last looked-at before the decision (9). For anything that competes for a first glance, which is most packaging, most ads and most shelves, knowing where the eye goes in the opening seconds is knowing where the decision is being made.

The strongest reason to take these measures seriously is that they predict behaviour at the group level, sometimes better than asking does. In research on which news stories get shared online, brain responses from a small sample predicted what a much larger population went on to share, and did so more reliably across cultures than people’s own stated intentions (10). Neural, eye-tracking, response-timed and behavioural signals of this kind seem to capture something more universal than a verbal answer, which is filtered through language, mood and the desire to look reasonable.

None of this makes surveys completely obsolete. We use scales, multiple-choice and open questions for the things people can reflect on: brand meaning, considered preference, what a campaign is trying to say. But we use response-time and eye-tracking for the things that happen too fast to report: the first emotional responses, the pull of one pack over another or the automatic association between a brand and an idea. Reading the two together allows us to see both the decision and what people will say about the product or brand.

The choice is made in about three seconds or less. The smart approaches to market research are therefore the ones that measure those three seconds, rather than only rely on post-rationalisations. The decisions that drive purchases are made in the brain, fast and mostly out of sight, and the words we give for them come later.

1. Chan, H-Y. et al. (2024). Neural Signals of Video Advertisement Liking: Insights into Psychological Processes and Their Temporal Dynamics. Journal of Marketing Research, 61(5), 891–913.

2. Palacios-Ibáñez, A. et al. (2023). Predicting Decision-Making in Virtual Environments: An Eye Movement Analysis with Household Products. Applied Sciences, 13(12), 7124.

3. Shimojo, S., Simion, C., Shimojo, E. and Scheier, C. (2003). Gaze bias both reflects and influences preference. Nature Neuroscience, 6(12), 1317–1322.

4. Unger, M., Wedel, M. and Tuzhilin, A. (2024). Predicting consumer choice from raw eye-movement data using the RETINA deep learning architecture. Data Mining and Knowledge Discovery, 38(3), 1069–1100.

5. Tusche, A., Bode, S. and Haynes, J-D. (2010). Neural Responses to Unattended Products Predict Later Consumer Choices. Journal of Neuroscience, 30(23), 8024–8031.

6. Bridger, D. (2017). Neuro Design: Neuromarketing Insights to Boost Engagement and Profitability. London: Kogan Page.

7. Ambady, N. and Rosenthal, R. (1993). Half a Minute: Predicting Teacher Evaluations from Thin Slices of Nonverbal Behavior and Physical Attractiveness. Journal of Personality and Social Psychology, 64(3), 431–441.

8. Facebook F8 Developer Conference (2016), 12 April. Figure announced by Mark Zuckerberg and reported by TechCrunch, ‘Facebook Messenger and WhatsApp process 60 billion messages a day’.

9. Agost, M-J. and Bayarri-Porcar, V. (2024). The Use of Eye-Tracking to Explore the Relationship Between Consumers’ Gaze Behaviour and Their Choice Process. Big Data and Cognitive Computing, 8(12), 184.

10. Chan, H-Y. et al. (2023). Neural signals predict information sharing across cultures. PNAS, 120(44), e2313175120.