Essay · Product Design

From insight to feature: closing the gap between research and decisions.

Apr 2025 6 min read

A framework for moving from qualitative research to product decisions that actually ship — and why the gap is a translation problem, not a research problem.


There’s a failure mode in product work that nobody talks about enough: collecting great qualitative research, sharing it in a slide deck, and then watching nothing happen. The data was real. The interviews were insightful. But the findings never made it into a roadmap. They lived and died in a shared folder.

The gap isn’t a research problem. It’s a translation problem.

The insight trap

User interviews are seductive. People tell you interesting things. You find patterns. You write them up as themes. And then product decisions get made based on whatever was loudest in the last meeting.

The problem is that insights are observations, not decisions. “Users find the onboarding confusing” is an insight. It doesn’t tell you what to build. It doesn’t tell you whether to simplify step three, redesign the whole flow, or add contextual tooltips. Without a translation layer, insights are just expensive quotes.

The translation layer

The framework I’ve landed on: Insight → Assumption → Hypothesis → Test.

An insight is something you observed: “Three out of five users skipped the profile setup step.” An assumption is the mechanism you think explains it: “Users don’t understand why their profile matters before they’ve experienced value.” A hypothesis is testable: “If we move profile setup to after the first value moment, completion rate will increase.” A test is how you prove or disprove it.

Most teams jump from insight to solution. The assumption and hypothesis steps are where you earn the right to build — and where you avoid building the wrong thing with confidence.

What this changes in practice

Research meetings get more useful. Instead of “here are themes from the interviews,” you can say “here are the assumptions these themes challenge or confirm.” That’s a conversation decision-makers can engage with.

Roadmap prioritisation gets less political. When features are tied to specific hypotheses with clear success metrics, you have a shared basis for prioritisation beyond whoever argued loudest.

Findings stay alive longer. An insight translated into an assumption doesn’t go stale — it either gets confirmed, disproved, or waits for the right moment. All three are valid states. All three are better than a folder nobody opens.

Léa Thuy Vu is a product and growth professional based in Vietnam. Currently at ChargePoint Vietnam, previously at the Clinton Health Access Initiative. Writes about incentives, product, and behavior change.
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