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Survey winners don’t always win on the shelf. Learn why testing claims on packaging reveals what truly drives shopper decisions.
a single sentence that makes sense to me
Most consumer insights teams have experienced some version of this story. A claims study goes into field with a dozen alternatives in text format. Respondents read each one carefully, provide a considered rating on appeal, believability and likely purchase intent, then a winner emerges. The winning claim then makes its way onto the pack design. Six months later when the pack has been updated, sales from shelf look the same as previously and nothing has changed. Nobody digs into why, because the research said the claim was strong, and the research was done the same way it’s always been done for decades.
In the past, we would all say the research was done properly and the traditional way. The main problem is that the claims were not tested in the context of the pack design. The claim that won in the previous research was a sentence on a screen, read with full attention by a consumer who had agreed to read it. The claim that ultimately found its way on the pack was a few words competing with a brand block, a flavor descriptor, a product image, and forty neighboring packs on the retail shelf for a fragment of a shopper's attention. Those are two different realities. We test the first one and launch the second.
Eye-tracking research is blunt on this point. Commercial shelf studies consistently find that shoppers look at an individual pack for roughly two seconds. In a typical claims survey, that same claim gets twenty or thirty seconds of deliberate reading and rationalizing, often preceded by an instruction to consider it carefully. The test simulates a reader; the shelf supplies a glance.
The academic evidence goes further. In the Journal of Consumer Psychology, Milosavljevic and colleagues showed that when choices are made quickly, visual salience biases what people pick more than their stated preferences do. Under time pressure, participants in their experiments sometimes chose the snack they liked less, because it stood out more.
And in a Journal of Marketing eye-tracking study, Chandon, Hutchinson, Bradlow and Young found that adding shelf facings lifted a brand’s evaluation only when those facings pulled more attention. The shelf space itself did nothing. The attention it captured did the work. Attention wasn’t the first step toward evaluation, it was the mechanism behind it. A pack element that goes unseen contributes nothing, however persuasive it would have been up close.
Apply that to claims. A claim can be the most believable, most motivating sentence in your test and still contribute nothing in market, because at the shelf it never got read. An isolated claims test has no way of telling you this.
Put a nutrition claim in front of someone on a screen and it performs. People rate the product as healthier, say they are more likely to buy, and the claim looks like a winner. A 2025 study in the International Journal of Research in Marketing tested that against real purchase data. Holtrop and colleagues found that nutrition claims changed which item shoppers picked but did not increase the quantity of what they actually bought. Shifting a shopper from a competitor to your pack is a win. The catch is that the isolated test implied a bigger effect than the shelf delivered, and it gave no signal about whether the claim would win that switch at all.
That’s the blind spot an isolated test can’t capture. On screen, the claim stands alone. It commands attention, builds belief, and drives intent to buy. On the shelf, it competes with price, ingrained shopper habits, and dozens of neighboring packs. What felt compelling in isolation gets diluted in context. A strong standalone score is a signal to keep refining the claim, not a reliable prediction of how it will perform once it’s on pack.
None of this means claims are weak at the shelf. Eye-tracking studies of front-of-pack labeling find that short claims are detected faster and more often than detailed information panels. A 2020 choice experiment in Food Quality and Preference using granola bar concepts linked the attention a claim had generated to the likelihood the product was chosen.
Claims pull eyes and shape personal choices. But notice where those effects were measured: on the pack, where the claim's size, placement, and competition with every other design element are part of the result. The same literature shows the trade-offs, since attention given to one element comes from somewhere else on the pack. A claim's effect is inseparable from its execution.
Testing claims in context is not exotic. It amounts to three changes to standard practice.
First, the stimulus becomes the pack, not the sentence. Each shortlisted claim gets executed as a true pack variant: same design, same shelf, only the claim changes. If a claim is too long to fit the pack at a readable size, that is a finding, and you want it before launch rather than after.
Second, the benchmark becomes the current pack. The commercial question is rarely which of twelve sentences people like best. It is whether adding this claim beats the pack you already have. Variants should be read on their lift against the incumbent, because a claim that wins on paper without moving anyone off the current pack is not worth its space or investment.
Third, the measures get sequenced, visibility first and buying second. A claim that is not seen within the first seconds of exposure never gets the chance to persuade, so reporting persuasion scores without attention data supports claims that will never be read. Run claims research this way and the rank order changes more often than is comfortable. A claim that finished first as a sentence can lose to the third-place claim once both sit on the pack in context, simply because the shorter one survives the glance.
We’ve spent decades in insights perfecting how we measure claims in isolation. The next step is harder and more necessary: determining whether they can drive sales in the reality where they actually compete, on pack.
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The views, opinions, data, and methodologies expressed above are those of the contributor(s) and do not necessarily reflect or represent the official policies, positions, or beliefs of Greenbook.
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