For insights, innovation & NPD teams

Consumer insights

Short answer

Consumer insights are explanations of consumer behaviour that are specific enough to change a decision. Not a number and not a report: an insight says why people did what they did, and what to do differently as a result. In food and drink the useful ones come from watching people use a product, not from asking them about it afterwards.

Updated 2 September 2026 · 8 min read · Eatpol, Wageningen

A report tells you what happened. An insight changes what you do next.

What consumer insights are

A consumer insight is an explanation of behaviour that is specific enough to change a decision. It has three parts: something people did, the reason they did it, and a consequence you can act on. Drop any one of the three and you are left with a fact, an opinion, or a slide.

The word gets used loosely enough that it has almost stopped meaning anything — every supplier of every kind of data now sells “insight”. So it is worth being strict about it, because the strict version is the one that earns a seat at a stage gate. If nobody does anything differently on Monday, it was not an insight.

That test is unforgiving on purpose. It rules out most dashboards, most tracking studies and a good share of what arrives in a debrief deck. It also explains why the job title exists: somebody has to be accountable for the difference between knowing something about consumers and doing something about it.

Data, research, insight — three different things

These get used interchangeably, and the confusion is expensive, because each one answers a different question and only one of them settles an argument.

01 · Data What happened Repeat purchase fell in the second month. True, precise, timestamped — and completely silent on the cause. Data tells you that something moved.
02 · Research What you asked Nine in ten said the texture was fine. An answer to a question you chose in advance, from people who were paying attention on purpose. Research tells you what people report.
03 · Insight What changes the decision Half the households cooked it for less than half the stated time, disliked the result, and never bought it again. Now there is something to fix, and a reason to fix it before the next run.

Illustrative. The point is the level of the statement, not the figures.

Data is what happened. Research is what you asked. An insight is the thing that changes a decision. Data and research are inputs; the insight is the output, and it only exists once somebody can act on it. This is also why volume does not help: a hundred more rows of the first kind never turn into the third.

The gap between the second and the third is the hard one, and it is not a matter of effort. People frequently cannot report the reason for a food choice, because most eating is habitual and largely automatic — so they supply a plausible reason instead of the real one[1]. Ask harder and you get a better-worded guess. The reason has to be observed.

The one-line test

Read the finding out loud and finish this sentence: “so we will…”. If the sentence completes itself, it is an insight. If it stalls, or if it completes with “…keep monitoring”, you have data that has been formatted to look like a conclusion.

The three jobs a consumer insights function does

Strip away the deliverables and there are three, and only three. Each one is a different moment in a launch, and each one needs different evidence. They also map onto why Eatpol has three products rather than one: Nova to shape, Studio to clarify, Vox and Domus to protect.

01 — Shape
Eatpol Nova

Shape the decision while it is still open

Evidence belongs in the room before the brief is written and the tooling is ordered. After that point, everything you learn is either a confirmation or a delay.

This is the part most often skipped, and the part that separates the teams whose work lands from the teams whose work gets filed. In Insights2020 — an industry study of over 350 CEOs, CMOs and insights leaders across 60 markets — 79% of insights functions at over-performing companies took part in strategic decision-making at all levels, against 47% at under-performers[2]. The same study found the function reporting directly to the CEO at 33% of over-performers versus 13% of under-performers. Read it as a description rather than a cause: the functions that are in the room early are the ones attached to the companies that are winning.

Being early also means challenging the assumption in the brief while challenging it is still free. The most useful thing you can do at that stage is widen the option set: not “is this idea good?” but “what else should have been on this list?”

Eatpol Nova exists for exactly that moment. It starts you from 821 products indexed across 10 award and innovation programmes, plus market-trend signals from 86 countries, instead of a blank page and a hunch. Its Observatory puts the 529 with label imagery in front of you at once, so you can see what a category has actually been rewarding — formats, claims, positionings — before anyone commits to a direction.

02 — Clarify
Eatpol Studio

Make the trade-offs explicit

Not every idea deserves a launch slot. Most of the value here is in making the choice between two options a finding rather than an argument.

Prioritisation is where insight work either earns its place or turns into diplomacy. Two concepts, one slot, and a room in which the most senior opinion tends to win. The only thing that reliably breaks that tie is evidence about behaviour: which one people actually used, kept in the cupboard and went back to.

Asking them to rate the options will not settle it, and this is the single worst case for stated intent. Purchase intentions predict sales better for existing products than new ones, better for durables than non-durables, and better over short horizons than long[3]. A new food product is on the wrong side of all three. Intentions in general translate into action roughly half the time[4] — fine for a directional read, far too soft to kill somebody's project with.

Eatpol Studio is where the comparison lives. Every study lands in one place: the footage, the transcripts, the coded behaviour and the recommendations, side by side across concepts, so a trade-off can be shown rather than asserted. Then the conversation moves from whose judgement to trust to which cost you would rather carry — which is the conversation you wanted in the first place.

03 — Protect
Vox + Domus

Protect the growth you already have

Short-term pressure is exactly when brands ship the untested thing. One week of real behaviour costs less than a delisting.

The third job is defensive, unglamorous, and the one that quietly pays for the function. When a quarter is under pressure, the reformulation goes out without a home test, the pack change ships to hit a cost target, and the line extension is approved because the slot was already booked. Each of those is a bet against a product that currently works.

The downside is not confined to the new item. Peer-reviewed work on brand dilution found that an extension carrying attribute information inconsistent with what people already believe about the parent brand can weaken those beliefs — and that dilution was less likely when consumers saw the extension as atypical of the brand[5]. In other words the risky launch is not the odd one out on the shelf. It is the one that sits closest to your core.

Nor is an established product a fixed quantity. When 105 people ate the same meat sauce once a week for ten weeks at home, boredom rose and acceptance fell over the run, least of all where there was variety and choice[6]. What you sell is being re-judged every week by people who will not tell you when they stop.

Against that, the cost of checking is small. Vox interviews your target consumers on video and comes back in about two days; Domus puts the product in their kitchen and shows you what happens over a week of real use. Set that against 50–75% of new food products failing within two years (peer-reviewed estimates; industry panels put it as high as 85%)[7] — a figure that is itself contested, with a later empirical study of food launches putting category success between 58% and 88%[8]. Either way, enough launches miss to make one week of evidence the cheap side of the trade.

Why insights fail to land

Good work gets ignored for boringly consistent reasons. Almost always one of these three, and none of them is about the quality of the analysis.

It arrives too late After the gate, the same finding stops being a decision and becomes a delay. Nobody reopens a committed launch to accommodate a slide, so the work gets acknowledged and shelved. Timing beats depth: a rough answer before the decision is worth more than a definitive one after it.
It answers a question nobody asked The study was scoped to what was easy to field, not to what the decision actually hinges on. It comes back rigorous, thorough and beside the point — and the person who has to make the call reads it, agrees with it, and still does not know what to do.
It confirms what the team decided The most dangerous one, because it feels like success. Ask people to react to a concept somebody in the room is already committed to and you will get agreement — and agreement is what gets quoted upward.

That third one has a name. The distance between what consumers say in a survey and what they do with the product at home is the say-do gap, and it is what makes reassuring research so easy to produce and so expensive to believe. A concept test can hand you a top-box score and a launch that fails anyway, without either result being a mistake — they simply measured different things.

The fix for all three is the same, and it is structural rather than methodological: move the work earlier, scope it to the decision rather than the questionnaire, and make the primary evidence behaviour rather than agreement. That is harder to schedule and much harder to argue with.

A number we are not going to give you

There is no credible peer-reviewed figure for how much of corporate research goes unused, or for how far a food concept test overstates real trial. Both numbers circulate widely; every version we could trace led back to vendor marketing with no method attached. So they are not on this page. Ask anyone who quotes one for the paper.

What this looks like as work

Concretely, on a food or drink launch: consumers recruited to match your target audience use your product in their own kitchen and record it on their own phone. You get the footage and the analysis, typically one week from kickoff — fast enough to sit inside a stage-gate cycle rather than pushing it.

What comes back is not a score. It is a ranked list of specific, fixable things: the step where four of ten people got the preparation wrong, the moment the texture changed someone's face, the point in the pack where they gave up and reached for scissors. You still ask questions — you just stop treating the answer as the primary evidence, because now you can check it against what the same person did thirty seconds earlier.

That is the whole discipline, really. Be early, be specific, and bring something a sceptic can watch. See how a study runs, or book a call and we will walk through what it would look like in your category.

The part that actually matters
Being right is not the job. Being right in time is the job.

Most products that fail are not bad products. They fail on one small, specific thing — the texture after two days in the fridge, a pack that will not reseal, a cook time nobody follows. The consumer notices. They do not complain, they do not fill anything in, and they are not angry about it. They simply stop buying, and they never say why.

So the brand watches a number fall with no cause attached to it, and the innovator never learns the reason. That lost reason is the real waste: it was observable, it was cheap to fix, and it was gone before anyone thought to look.

Which is why we think about this as a timing problem rather than a knowledge problem. The evidence that changes a launch is almost never the evidence nobody could have gathered. It is the evidence somebody gathered three weeks after the decision was made.

References

Sources

  1. Köster, E. P. (2009). Diversity in the determinants of food choice: A psychological perspective. Food Quality and Preference, 20(2), 70–82. doi.org/10.1016/j.foodqual.2007.11.002
  2. Insights2020, led by Millward Brown Vermeer / Kantar Vermeer with ESOMAR, LinkedIn, Korn Ferry and the Advertising Research Foundation — 350+ in-depth interviews with CEOs, CMOs and insights leaders and 10,000+ practitioner responses across 60 markets. Reported in Insights2020: Connecting the dots, Bizcommunity, 5 December 2016: bizcommunity.com/Article/196/19/154805.html; and ‘Over-performing’ companies use insights and analytics to drive consistency, Research Live, 30 September 2015: research-live.com/article/news/…/id/4013946. Industry research commissioned by a research supplier, not a peer-reviewed study — it is cross-sectional, so it shows association, not cause.
  3. Morwitz, V. G., Steckel, J. H. & Gupta, A. (2007). When do purchase intentions predict sales? International Journal of Forecasting, 23(3), 347–364. doi.org/10.1016/j.ijforecast.2007.05.015
  4. Sheeran, P. & Webb, T. L. (2016). The Intention–Behavior Gap. Social and Personality Psychology Compass, 10(9), 503–518. doi.org/10.1111/spc3.12265
  5. Loken, B. & John, D. R. (1993). Diluting Brand Beliefs: When Do Brand Extensions Have a Negative Impact? Journal of Marketing, 57(3), 71–84. doi.org/10.1177/002224299305700305
  6. Zandstra, E. H., de Graaf, C. & van Trijp, H. C. M. (2000). Effects of variety and repeated in-home consumption on product acceptance. Appetite, 35(2), 113–119. doi.org/10.1006/appe.2000.0342
  7. Dijksterhuis, G. (2016). New product failure: Five potential sources discussed. Trends in Food Science & Technology, 50, 243–248. doi.org/10.1016/j.tifs.2016.01.016
  8. Salnikova, E., Baglione, S. L. & Stanton, J. L. (2019). To Launch or Not to Launch: An Empirical Estimate of New Food Product Success Rate. Journal of Food Products Marketing, 25(7), 771–784. doi.org/10.1080/10454446.2019.1661930
Good to know

Frequently asked.

What are consumer insights?

Consumer insights are explanations of consumer behaviour that are specific enough to change a decision. An insight has three parts: something people did, the reason they did it, and a consequence somebody can act on. A finding that leaves everyone doing exactly what they were already going to do is data, however well presented.

What is the difference between data, market research and an insight?

Data is what happened: repeat purchase fell in month two. Research is what you asked: nine in ten said the texture was fine. An insight is the thing that changes a decision: half the households cooked it for less than the stated time, disliked the result and did not buy it again. Data and research are inputs; the insight is the output, and it only exists once somebody can act on it.

What does a consumer insights manager do?

Three jobs. Shape decisions while they are still open, by bringing evidence in before the brief is written rather than after. Make trade-offs explicit, so choosing between two concepts is a finding rather than an argument. And protect the growth the business already has, by checking changes to products that currently work before short-term pressure ships them untested.

Are consumer insights the same as market research?

No. Market research is a set of methods for collecting evidence about people. An insight is a conclusion drawn from that evidence that is specific enough to act on. You can run a great deal of research and produce no insight, and a single hour of watching someone use your product badly can produce one. Research is the input; the insight is what you owe the business in return for it.

What makes a consumer insight actionable?

A useful test: read the finding out loud and try to finish the sentence "so we will…". If it completes itself, it is actionable. If it stalls, or completes with "keep monitoring", it is a fact that has been formatted to look like a conclusion. Actionable findings name a specific behaviour, a plausible cause, and something a person can change this quarter.

Why do consumer insights fail to change decisions?

Usually one of three reasons, none about the quality of the analysis. The work arrives after the gate, when the same finding is a delay rather than a decision. It answers a question nobody was actually asking, because the study was scoped to what was easy to field. Or it confirms what the team had already decided, which feels like success and is the most expensive of the three.

Where do consumer insights come from in food and drink?

From behaviour more than from answers. Most eating is habitual and largely automatic, so people often cannot report the real reason for a choice and supply a plausible one instead. That is why watching a product being prepared, stored, served and abandoned in a real kitchen tends to produce more usable explanations than a questionnaire about the same product does.

How large a sample do you need for a consumer insight?

Smaller than people expect, because the two questions need different evidence. Estimating how many people will buy something needs scale. Explaining why they stopped needs depth: ten to twenty households observed properly will surface the specific friction that a thousand-person survey averages away. Use scale to size an effect, and observation to find its cause.

How quickly can Eatpol deliver consumer insights before a gate review?

Vox video interviews come back in about two days. A Domus in-home test, where consumers use your product in their own kitchen on video across a week, delivers about one week from kickoff, with the analysis in Eatpol Studio. That is fast enough to sit inside a stage-gate cycle rather than pushing it, which is the point: the evidence has to arrive while changing the product is still cheap.

Kickoff to results in one week

Bring evidence
they can watch.

We put your product in your target consumers’ kitchens, record what they actually do with it, and hand you the reasons behind the number — before the decision, not after it.