“Can you just get us some quick insights?”
It’s the modern researcher’s equivalent of “Can you make it quick?” at a fine-dining restaurant. You can — but you’re not getting the tasting menu.

Over the past few years, client appetite for speed has exploded. Dashboards, automation, DIY survey platforms, AI-generated summaries — everyone’s chasing faster, cheaper, easier. But there’s a growing tension: the quicker the data, the thinner the insight.

At Zing, we call it the “fast-food fallacy.” You get instant satisfaction, but the nutritional value is questionable.

What’s driving the need for speed?
Business cycles are shorter. Marketing teams are under pressure to pivot campaigns weekly, sometimes daily. Event organisers want post-show readouts within 48 hours so they can brief sponsors while everyone’s still buzzing.

Technology has also normalised immediacy — if you can get analytics in seconds from Google Ads, why shouldn’t research do the same?
But here’s the problem: good insight isn’t just about data capture, it’s about context, interpretation, and meaning. That takes thinking time.
The trade-off: speed vs. depth
When you cut timelines, you’re not just compressing fieldwork — you’re cutting space for curiosity.

Quick-turn surveys are brilliant for pulse checks, but they can’t explain the why.

AI can summarise verbatims, but it can’t feel emotion, feel the buzz of a show floor, or notice the subtle change in tone when an exhibitor says, “It was… fine.”
And that’s where the danger lies. The more we automate, the less we listen.

The quality paradox
Ironically, the rush for real-time insight can lead to poorer business decisions. Fast data can be clean but meaningless; the metrics look tidy, but they don’t answer the question you should have asked.

Quality comes from human curiosity, not just processing power.

Our role as insight professionals isn’t to be faster — it’s to be faster at finding meaning without losing rigour.
So what’s the sweet spot?
• Hybrid designs – combine agile pulse data with deeper qualitative follow-up. Fast doesn’t have to mean shallow.
• Design thinking – spend time up front defining the right question; it saves wasted speed later.
• AI as a co-pilot, not a driver – let technology streamline logistics, but keep humans for interpretation.
• Expectation management – be honest with clients about what “quick” can and can’t deliver.

The takeaway
Fast insights are here to stay — and that’s fine. But let’s not confuse tempo with truth.

We don’t need to slow down — we need to slow think.

Because when insight starts tasting like fast food, it’s time to get back in the kitchen and cook something that actually nourishes decisions.

Posted by Lisa Holt, Founder & CEO