Blog
Research, repositories, and doing research well
Practical guides on UX research repositories, research operations, and turning evidence into decisions.
Testing Figma prototypes with people who don't use Figma
You can put a Figma prototype in front of anyone: paste the share link and it runs inside the test, no account and no plugin. What that setup measures well, the sharing mistake that quietly ruins studies, and when to test a real build instead.
Unmoderated usability testing: send a link, get answers
Moderated research doesn't scale to every question. Unmoderated testing does: share one link, participants complete tasks on their own time, and results land in your repository. What it is, when to use it, the block types, and how to write tasks that don't bias the answer.
Testing vibe-coded prototypes: Figma Make, Lovable & v0
AI builders make a working prototype in an afternoon — so why still test with static mockups? Drop a one-line snippet into a live Figma Make, Lovable, or v0 app and capture real clicks and journeys, no rebuild required.
First-click testing: the earliest signal of task success
Where someone taps first predicts whether they'll finish the task — decades of research say so. A practical guide to first-click testing: what it measures, how to read a click heatmap, and the mistakes that invalidate results.
Insight triage: from validated finding to product roadmap
Most research findings die in reports, not in disagreement. A triage workflow — raw finding to review, validation, opportunity, and backlog — and why the board tracking it should be a view of your insights, never a copy.
Affinity mapping: turning interview noise into themes
Affinity mapping is how a wall of interview notes becomes a handful of themes you can defend. The method, practical rules for doing it remotely, where AI clustering helps, and how to turn clusters into insights.
From highlight to insight: tagging and coding interview notes
Highlighting and tagging are how raw interview notes become reusable, evidence-backed insights. A practical workflow for coding qualitative research — without losing the quote behind each finding.
How Lens uses AI in UX research (and how it handles your data)
AI in research tools is often hype or a black box. Here's exactly what Lens's AI does, what data it sends, and how it stays grounded in your own research — assisting judgment, never replacing it.
What is a UX research repository? (and why teams need one)
A plain-English guide to UX research repositories: what they are, what problems they solve, the features that matter, and how to choose one.
GDPR-compliant user research: a practical guide
Research is personal data. A practical, non-legalese guide to running user research under GDPR — lawful basis, consent, minimization, retention, data-subject rights, and where AI fits.
Research repository vs. spreadsheets: when to switch
Spreadsheets are where most research starts — and where it quietly breaks. Where they fail, what a repository adds, when a sheet is still fine, and how to migrate.
How to run a research repository your team actually uses
A repository only pays off if people use it. Practical principles and an operating model for adoption — effortless capture, a consistent taxonomy, linked evidence, and clear ownership.
Insight management: making research findings reusable
Most research findings are used once and forgotten. What insight management is, what makes an insight reusable, and the practices that keep findings working long after a study ends.
ResearchOps: a starter guide for small teams
ResearchOps is the plumbing that lets research scale. What it is, the pillars that matter, and a pragmatic first-90-days plan for teams without a dedicated ops function.
Consent management for user research
Consent is both a legal requirement and a trust signal. What good consent looks like, what to track per participant, and how to handle expiry, withdrawal, and retention.