From efficient reporting to meaningful insight
Editor’s note: John Bird is an executive vice president at market research firm Infotools, an Ipsos company.
One of my favorite moments in any project is when the data surprises you.
We often use New Zealand tourism data in our demos, exploring who visits the country and what makes each traveler group distinct. Within seconds, patterns start to emerge – some expected, some surprising. U.S. visitors, for instance, are far more likely to arrive by sea and seek out native birds, while Australians are less interested in cultural attractions than nearly any other group. Visitors from Germany stand out as the least similar to anyone else, while those from Singapore behave almost exactly like Australians. Insights like these appear instantly, the kind that once took hours of manual crosstabbing to uncover – if they were uncovered at all!
Gone are the days of endless filters or static tables. Today, just a few clicks can bring data to life. And my curiosity quickly kicked in. Seeing those profiles side by side made me want to ask better questions: Why do these groups behave so differently? What experiences or expectations are shaping their choices?
That spark, the moment when you realize you’ve uncovered something worth chasing, is what discovery should feel like in marketing research. It’s often why many of us chose careers in this field in the first place.
The insight industry beyond efficiency
Over the past decade, our industry has poured enormous effort into speed and automation. We’ve built tools that clean data faster, standardize dashboards and shorten turnaround times. Those advances have real value, but they’ve also made it easy to lose sight of what made us researchers in the first place: the drive to explore, question and interpret.
I’ve sat through many debriefs where the data was perfectly visualized, beautifully automated and, somehow, flat. There were no surprises, no “what if” moments and no sense of play. It’s as if the efficiency we gained came at the cost of curiosity.
That’s why I think the next evolution of our field isn’t about more automation. It’s about better exploration. The tools we build now should make that exploration easier by giving researchers the power to see patterns faster and ask better questions. Whether it’s using advanced features that instantly surface what makes one audience different from another, or having an intelligent assistant that helps interpret and contextualize findings, the goal is the same: to spend less time preparing data and more time understanding it. These kinds of innovations expand where curiosity can take us.
From reporting to investigating
I’ve spent enough years in research to remember when analysis meant hours building tables and recutting data by hand. It was slow, but it forced you to get close to the data – to live in it long enough to notice the unexpected.
Today, technology gives us the freedom to explore without the friction. When updates happen automatically and data from multiple sources – such as tracking studies, CX programs, sales data and traditional survey data – can be viewed together, we get to spend our time asking “why,” not “what.”
That shift changes everything. Instead of treating reports as the end of the process, we can treat them as the beginning of a conversation. Instead of waiting for insights to be delivered, we can start investigating in real time.
Designing for discovery
In one project our team worked on, a public transport client in Auckland used to manage separate satisfaction trackers for bus, train and ferry services. By combining those programs into a single, connected view, the team could finally see how riders moved between modes and where gaps in satisfaction overlapped. What started as a dashboard turned into an investigation.
That’s the key to designing analysis environments that inspire curiosity. We certainly don’t need to cram more charts on a page. Instead, data needs to invite people in to make them want to click, compare and ask questions. When done well, a dashboard can serve as a prompt.
Even small design choices make a difference. I once helped build an ice cream survey dashboard where the visuals were deliberately playful bright colors and included fun hover effects and even digital “sprinkles.” It sounds trivial, but people spent more time exploring it because it felt approachable. The more time they spent, the more they discovered.
The evolving craft of research
I’ve come to think that the craft of research is shifting from analysis to sensemaking. We have no shortage of data; what we need are new ways to connect it, interpret it and turn it into meaningful stories.
That requires both technology and mind-set. On the technology side, we now have systems that handle repetitive tasks in the background like data cleaning, mapping and updating so we can focus on thinking. On the human side, it means rewarding exploration instead of perfection. Sometimes the most valuable findings come from what looks, at first, like a tangent.
When I run a training session or demo, I always tell teams: Don’t rush to the conclusion. Follow your curiosity. Look for the things that don’t fit the pattern. Those moments of tension that lie in the outliers. The inconsistencies are where insight often hides.
Rekindling curiosity in marketing research
It’s tempting to think our value as researchers lies in efficiency, but I think it lies in curiosity. The future of research will depend on our ability to move from reporting to investigating, from dashboards to dialogue, and from efficiency to engagement.
Because in the end, the goal is to make discovery possible again. The best insights rarely come from what we set out to prove. They come from the things that make us stop and say, “That’s interesting. Let’s dig into that.”