Practical insight, honest thinking, and the occasional opinion, for researchers who care about doing it properly.
Why AI can't do real research on its own, where it makes research faster, cheaper and better, and practical checklists for communities, live interviews and AI-moderated chats.
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Why AI can't do real research on its own, where it makes research faster, cheaper and better, and practical checklists for communities, live interviews and AI-moderated chats.
An honest look at AI-moderated interviews: the different kinds, where they help, and when a human moderator or a live focus group is the better choice.
Where to find research participants, how to write a screener, how much to pay them, how many to over-recruit, and how to keep them taking part.
What an in-depth interview is, how long it should be, IDIs or a focus group, how many you need, and how to run and analyse them online or in person.
A practical guide to online focus groups: group size, length, recruitment and no-shows, the discussion guide, stimulus, the client backroom, interpreters and analysis.
Long-term communities got a reputation for being slow, expensive and hard to keep alive. It was never the idea that failed: it was the tooling, and the tooling has changed.
The real cost drivers of an online research community: panel size, length, how much the vendor runs, recruitment, incentives, custom design and languages, plus how to brief a vendor for an accurate quote.
Qualitative research has never been richer. The challenge is making sense of it all. How the connected Qualzy and DoReveal workflow helps researchers move from collection to confidence.
Consumers say they want sustainability, then choose convenience at dinnertime. Why the say-do gap shows up in the kitchen, and how observational research reveals what surveys miss.
What an MROC (market research online community) is, how it differs from a panel and from a short online discussion, how long communities run and when one is the wrong choice.
Researchers were already using both platforms side by side. Here's how our partnership with DoReveal helps teams move from richer data to deeper insight.
The "compare 47 tabs before buying" era may be ending. Here's what AI-led shopping means for brand research, and why staying close to real consumer behaviour is now the key advantage.
How to design and run an online diary study: length, entry frequency, prompts and media, keeping participants going with nudges, and analysing entries with key points, themes and clip reels.
What async qual is, how it differs from live sessions, the main formats from pre-tasks to communities, and how to combine async and live in one project.
An honest look at where AI genuinely helps researchers, where it still falls short, and how to think clearly about adopting it without the hype.
Qualzy and CoLoop join forces to bring a new level of AI-powered analysis to qualitative research datasets, and what that means in practice.
Where is qual research heading? Five considered predictions on how methodology, technology, and client expectations are going to shift, and what that means for researchers today.
What it actually looks like to build generative AI into the fabric of a research business, not as a gimmick, but as a genuine operational shift.
Generative AI isn't coming for qualitative research. It's already here. This is what that actually means for how we work, think, and compete.
ISO 27001 certification isn't a box to tick. It's a rigorous ongoing commitment. Here's what it required, and why it matters for researchers handling sensitive participant data.
Transparency, consent, and what researchers owe participants when AI becomes part of how their responses are processed and interpreted.
Analysis doesn't have to mean weeks of reading and rereading transcripts. Practical approaches to make qual analysis faster, cleaner, and more defensible.
The science suggests that webcam settings systematically change how participants process stimuli, with implications for every moderator running online groups.
Neither is categorically superior, but the academic and practical evidence has a lot to say about when each approach serves researchers better.
The fundamentals: what qualitative research is, how it differs from quantitative, and the core methods that define the discipline. A clear-headed primer for newcomers and a useful refresher for everyone else.
From scoping the brief to analysing findings, a practical walkthrough of how to run qual market research that actually answers the business question.
A practical buyer's guide for research teams evaluating platforms, what separates the right tool from one that creates more work than it saves.
The question clients always ask, and the honest answer isn't a formula. What actually determines the right sample size in qual, and how to explain it clearly.
The case for async online qual: broader reach, richer data, lower cost and more considered answers, plus when face-to-face is still the right call.
