AI means market research studies can now be turned around in days, leaving brands with more insights than ever. But these insights are often gathered and analysed separately. One team might be tracking the brand while another tests pricing or new concepts, each with a different agency and approach.

These results aren’t always shared, and silos are costing clients. Forrester estimates that up to 73% of enterprise data is never used for analytics, while Warc reports that, more broadly, marketers expect to waste 26% of their budgets.

This is also a problem for insight leaders, who are often judged on the growth they deliver on top of how fast they do so. Research needs to help them connect the dots while giving them enough evidence to influence business decisions.

A way forward is to build research on established marketing science, such as mental availability and the category entry points (CEPs) that underpin it.

Breaking down silos

Avery Fine, research and commercial strategy expert lead at market research company Appinio, has seen firsthand the impact of a disjointed insights strategy.

Fine says brands may turn to the company for mental availability research while using separate vendors for pricing or ad research. “When that research is shared across marketing, product, and brand teams, they lose a lot of the synthesis of how to make the data actionable,” she explains.

If data isn’t democratised properly, there’s “no single source of truth,” says Fine. “So much gets lost in translation working between these internal teams.”

The cost isn’t just wasted budgets, but sometimes also innovations that miss the mark, adding to the more than 85% of new consumer products Nielsen has long said fail.

To tackle this, Appinio recommends starting with two foundational studies: mental availability research, which examines how and when a brand comes to mind compared with competitors, and psychographic segmentation which identifies the audiences most worth targeting and the best way to talk to them. Together, they show brands what they need to be known for, who they need to reach and how to bring this to life.

The aim is to give every new study the same starting point. Pricing, ad testing and concept development can then build on the same understanding of the audience and the brand associations it needs to own, rather than being treated as separate exercises. Fine describes it as a “connected growth engine.”

In an industry focused on speed, AI is one way of delivering the quick turnarounds clients now expect. A 2025 Market Research Institute International (MRII) study found AI use is growing, with 62% of respondents saying “most” or “some” of their team was using it.

Fine believes there’s a lot of “sensationalism” around AI’s role in research, predicting it will eventually become just another tool. Researchers can use AI to analyse data and make recommendations, she says, but it can’t replace the marketing science needed to interpret those findings and apply them to business decisions.

Brand insight teams are being asked to do more with less too, so choosing the right research is essential.

Fine says she’s heard from some clients who’ve seen their budgets shrink or had up to half of their teams let go, while pressure from senior leadership keeps growing. “It’s not the economy to be trial and erroring your way through,” she says.

That means carefully picking what research to run. Lito Giourouki, associate director of insights at Japanese beauty and personal care company Kao, says speed and quality needn’t be “opposing forces.” The key is being “choiceful” about whether something calls for a quick poll or a more in-depth study.

From brand tracking to better decisions

When Kao relaunched a haircare brand earlier this year, it combined mental availability research with willingness-to-pay analysis to inform pricing and future innovation.

“It really felt like the missing piece in terms of us understanding not just how our brand is thought of or perceived, but how we could turn that into a commercial opportunity,” Giourouki says.

The data found the needs customers commonly associate with a product weren’t always the ones they’re willing to pay more to address. It also showed some brand associations were less distinctive than Kao previously assumed.

“It helped us sharpen our communication strategy, because it reinforced the importance of building those stronger and more consistent mental connections in certain spaces where we had the right to win,” says Giourouki.

The results also led to more collaboration with Kao’s marketing and innovation teams about which product benefits, such as repair or moisturising, to back.

“For the first time we went into all those conversations really aligned. It wasn’t marketing fighting sales and insights trying to be the referee,” Giourouki says.

A fast-food win

Appinio has applied similar thinking beyond haircare, building a system for one of Germany’s largest fast-food chains.

The business came to Appinio with too many silos and a brief to “build research that really builds upon itself,” says Fine.

Her team started with mental availability and psychographic segmentation. It then took its top three or four CEPs into ad testing and campaigns. These same CEPs were used to test pricing – asking customers what they’d pay for a burger at specific moments, like late at night or while running family errands.

These findings don’t “just stay in one body of research,” says Fine. They now feed into the chain’s product, marketing and pricing decisions.

Rigour at speed

Speed is what Appinio is best known for, but Fine says it’s set up to offer rigour too.

Its platform allows clients to track live data as it comes through, while behind the scenes its operations team is monitoring the data, cleaning it and running quality assurance checks before a study launches.

Fine’s role adds another layer of integrity, she says. She joins pitch calls to get an oversight of what’s being sold and works with clients to match their questions to the right method.

The latter is crucial since clients don’t always have time to design research to get the answers they need. Fine gives questions around price as an example. Consumers are likely to say price is important when buying something but running conjoint analysis that asks them to choose between products at different prices can reveal more.

Making data an easier sell

Even robust research isn’t always easy for insights teams to sell further up the chain.

Fine often hears concerns from brand insights leaders that research-heavy, jargon-filled findings aren’t going to land with the c-suite. “I’m going to get this in front of my CMO, and [they’re] going to roll [their] eyes,” they tell her.

Appinio’s job is to let its clients present insights to their CMOs confidently, without worrying about “the calculus” behind them. “We handle that and make sure it’s packaged in a really digestible way,” she continues.

For Kao’s Giourouki, this self-assurance was invaluable. “There is such an overload of data and insights these days,” she says. “But what it did give us was that clear framework for action… and that really is super key when you’re trying to prioritise confidently.”

And with UK marketers reporting cuts to research budgets until recently, Fine says insights should act as a kind of insurance for insight leaders, giving them confidence before a decision and a clear rationale to point to if it’s challenged.

Data won't replace the gut feeling that often guides creative and marketing decisions, Fine says, but it can provide some “guardrails.”

From research producers to validators

Fine herself has worked in-house and says the first step towards more connected research is getting everything in one place. “There’s infrequently a single reference point for all of the research that’s being done across the different teams,” she says.

Giourouki has worked in insights for 20 years and says the project hasn’t changed how she sees her job, but it has changed how other departments in Kao see it.

“It’s really helped us move from just viewing consumer insight as something that we report on, like a brand health tracker, into a tool that allows us to identify future growth opportunities,” she says.

• Find out more about how Appinio are helping their clients to build connected research growth engines.