In innovation testing, one question comes up consistently: Should we test with our target segment, or with a broader audience?
On the surface, the answer feels obvious. After all, innovations are designed with someone in mind. Surely, testing with the “right” consumer target sharpens insights and reduces noise.
Yet, decades of innovation evidence suggest the opposite. When testing focuses on a narrow target, it does not refine results; it often distorts them.
The Hidden Risk of Testing Among ‘Targets’
Target audiences are, by definition, familiar. They already buy your category; most have your brand in their repertoire; they understand and respond well to your marketing language. That familiarity can inflate appeal, overstate potential, and mask real barriers to adoption.
Successful innovation, however, does not generate growth by playing within a finite pool of target consumers. The evidence-based tenets of marketing science show that innovations often derive significant portions of volume outside their target by reaching lighter buyers, occasional users, considering future entrants, and unexpected usage occasions. When testing is confined to a predefined target, that expansion potential disappears from both the analysis and innovation planning – leaving money on the table.
Why Broad Samples Are More Predictive of In Market Potential
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Testing innovations with a total representative universe of consumers allows innovators to witness what actually happens when a new idea hits the market.
Broad samples always capture those who involved in the purchase decision including:
- Consumers who are not yet category buyers, but could enter the category due to changing habits ( a portioned premium chocolate praline – could appeal to premium chocolate buyers of course, but it could also appeal to non-buyers, if they’re current GLP-1 users or considerers, conscious about their wellness, mindful of portion control, attempting to spend less on certain high inflation categories… in a nutshell, anyone with purchasing power)
- Occasional and situational purchasers who drive incremental volume (if we focus on portioned premium chocolate praline buyers today, we ignore those who manage to stave off cravings unless it is a particularly stressful period, they’re on vacation, or it’s the holidays)
This matters because innovation success is rarely driven by targets alone. In many categories, half of sales volume comes from consumers who were never part of the original “core” audience. Ignoring them at the testing stage means underestimating both opportunity and risk.
That risk is further exacerbated by the leaky bucket concept – innovation research demonstrates brands must continuously generate substantial new buyer trial—often up to 80% as much in year two as in year one—to offset natural buyer attrition and sustain franchise growth.
Innovation Isn’t Static. Testing Shouldn’t Be Either
Categories and markets evolve faster than target definitions. A “core consumer” today may not exist in the same form tomorrow. Broad-based testing future-proofs innovation decisions by anchoring them in behaviour, not assumptions.
It also enables comparability. When all initiatives are tested on the same broad foundation that reflects market specific purchasing power, innovation teams can reliably prioritise across countries, brands, portfolios, categories. The question shifts from “Who liked this most?” to “What role can this play in driving growth?”
That distinction is subtle, but critical.
Targets Still Matter – Just Not Where You Think
None of this suggests that target audiences are irrelevant. Quite the opposite.
Targets are essential as an analytical lens, not as a sampling shortcut. Once an innovation is tested broadly, target group analysis helps answer sharper questions:
- Which groups drive early adoption versus sustained volume?
- How to move from targeted to broad messaging ?
In other words, targets help optimise how an innovation is brought to market—not determine whether it deserves to be there.
The Real Risk in Innovation Testing Isn’t Failure. It’s False Confidence
Innovation testing isn’t about proving that an idea works in a carefully curated and static vacuum. It’s about understanding how it will survive and scale in the real world, where consumers are dynamic, diverse, and distracted.
It would be inadvisable to go to a single retailer, isolate the full-time working millennials living in proximity, those whose current attitudinal and behavioural characteristics slot them into Segment 5 of your Typing Tool and expose only them to your NPD, ignoring all other potential purchasers today and tomorrow. Yet too often, that’s exactly how many test.
Testing that truly reflects the market’s full and evolving complexity leads to innovation decisions that are more predictive, more robust, and built to endure.
