The future of consumer research trends
Editor’s note: Kimberly Bastoni is the chief revenue officer at Alida, a Toronto-based customer experience and software firm.
I have been reading through all the latest 2026 trend articles and think pieces for the year ahead. And while I do think many of my peers are on the right track – embracing of thoughtful AI, focusing on trust and transparency and keeping the human touch alive throughout research strategy – I don’t think 2026 will be defined by neat, predictable trends. Instead, it will be a year defined by one overarching reality: Unpredictability.
We can read every report, attend every conference, and debate every prediction, but the reality is that consumer behavior is more volatile than it's ever been, and many organizations are not prepared for it. Confidence remains shaky, expectations keep rising, the legal implications of AI are facing growing scrutiny, and the competitive landscape is getting tougher every single day. Leaders are being asked to move faster with fewer resources and make smarter decisions, all while the ground keeps shifting beneath them both in terms of consumer trends and the economy.
The end of predictable consumer behavior
As McKinsey & Company notes in its report, State of the Consumer 2025: When Disruption Becomes Permanent, today’s consumers aren’t irrational, it’s the traditional frameworks we’ve relied on to understand them that no longer fully apply. The firm points out that the shocks of the pandemic in 2020 have left lasting effects on global sentiment, producing purchasing behavior that often defies easy explanation.
And this reality has serious implications for the research landscape. If broad, generalized samples are no longer enough to make sense of increasingly unpredictable consumer behavior, what does it mean that organizations are relying on them to predict what comes next? Researchers are constantly being asked to forecast the future, but how accurate can those predictions be if they are not grounded in direct, ongoing input from real customers? Anything else leaves too much to assume and introduces unnecessary risk at a time when the stakes are only getting higher.
While it might be tempting to opt for what looks like the most cost-effective option in a one-time sample, the hidden trade-offs are significant. Research predictions are only as strong as the data behind them, and large third-party sample pools can include bots, biased respondents, or people who are not actually your customers, even when additional effort is spent cleaning the data. The result is insights that feel cheaper upfront but become expensive when decisions are built on unstable foundations.
At the same time, many organizations are accelerating AI adoption in ways that amplify these weaknesses rather than solve them. There is no question that AI will continue shaping the future of research and can be a powerful amplifier when paired with strong customer data. It can process enormous volumes of information, scan conversations at scale, surface patterns quickly, and highlight signals humans might miss. But layering AI on top of weak sample quality only magnifies the gaps and AI-generated samples are not a replacement for real people. AI cannot empathize, read cultural nuance, sense shifting emotions, or truly understand the trade-offs consumers navigate in their daily lives.
When strategy is built on weak data, it scales blind spots
So, when organizations rely on AI layered over weak data, they aren’t becoming more forward-looking – they’re automating their blind spots. This is why I’m skeptical of firmly leaning in on any consumer trends for 2026 because any prediction made today could look completely different by the end of Q1.
A smarter approach is to stop obsessing over prediction and start rethinking how your organization learns about its customers. The critical question for leaders who want to do well in 2026 should be: “Do we have a research strategy in place that keeps pace with our audiences that matter most?” Do you have continuous access to your real, verified customers? Or are you still leaning on third-party samples and sporadic studies that capture only a snapshot in time?
Companies that win are those that listen to real customers
If your connection to customers is occasional, your understanding will be too. So how do you predict the unpredictable? You don’t. You prepare for it. You build a flexible, always-on research program that keeps real people at the center of every decision. That means moving away from strategies built on broad, generalized samples you can’t be sure reflect your true customers, or from checking in once or twice a year. It means creating a system that lets you engage customers as new questions arise, test ideas quickly and adjust in real time based on what you learn. When AI’s analytical power is paired with continuous access to real, verified customers, research moves beyond guesswork and into insights that solve your business issues as they arise.
In an unpredictable world, the companies that succeed in 2026 won’t be those with the best crystal ball. They’ll be the ones that stay closest to their customers.