Research Recaps
✓ surface the insights buried across past studies
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Surfacing the value of existing research in your organization
Picture this: A stakeholder comes to you with an urgent research request for a high-priority project. As you dig into it, you realise: we've already researched this…extensively. How could they not know? Is no one listening to us? (cue existential spiral)
The uncomfortable truth is: the more research you conduct, the easier it becomes for findings to get buried. It's easy to assume stakeholders are ignoring your work, but more often, they simply can't find it.
The go-to solution is often to create a research repository: an online home for all your research that's searchable for stakeholders. And while I love a well-organised repository, they're a lot of work to set up and maintain. Even when implemented to perfection, product teams can still feel overwhelmed trying to sift through an endless archive of studies, recordings, transcripts, and reports.
The key to helping your team cut through the noise and stay current with research findings and insights? Regular research recaps.
What's a research recap?
It's a structured activity where a researcher reviews and synthesises all the research to date on a specific topic. Think of it like researching your own research. The outcome is a crisp, accessible summary of key themes, complete with links to the supporting evidence. A "Here's everything we know about X" kind of artefact.
Yes, it takes time (especially if there's a lot of research to dig through), but the value is enormous. Not only does it signpost people to all relevant previous work, but more importantly, it surfaces key insights in a way that's easy to digest and hard to ignore.
This is the kind of document that becomes part of the onboarding checklist and gets referenced for years to come. Like the research canon for your organization.
How to run a research recap
Step 1: Gather your data
Start compiling all relevant past research reports into a hyperlinked list. If you've got more than 10 to 15, narrow it down to the most recent or most relevant. Pull in both qual and quant and consider including reports from market insights or customer support too.
Step 2: Pick your workspace
Choose your analysis tool. A spreadsheet works great. Or use a collaborative whiteboard like Miro or FigJam.
Step 3: Pull out insights
Go through each report and extract key insights (a great place to start is executive summaries). Paste them into your workspace and link each one back to the original source.
Step 4: Theme your data
Group similar insights together into themes, just like you would in a typical qualitative analysis. Don't be afraid to regroup a few times until the clusters feel right.
Step 5: Filter for impact
Identify the strongest themes, the ones that recur time and time again across multiple studies or hold the most weight for the business or user experience.
Step 6: Write insight statements
Turn your top themes into insight statements. Keep them crisp and focused. Expect a few rounds of editing here, it's worth the effort to make them sing.
Step 7: Craft a narrative
Now connect your insights into a compelling story. What's the arc? What do we know now that we didn't before? Aim for clarity over detail; the aim of this exercise isn't to reveal everything we've ever learned, it's to surface the most important things we've learned.
Step 8: Share your findings
Now it's time to start working on your deliverable. Whether it's a deck, doc, or Miro board, keep it tight and actionable. Include links to source material, and optionally, add "How Might We..." questions or recommendations to prompt next steps.
Optional step 9: Run a workshop
Bring your findings to life by leading an ideation workshop with designers. Or, if time's tight, run an independent heuristic evaluation of your product to highlight gaps and opportunities.
Top tips
✨ This makes a great exercise to run collaboratively as a research team.
✨ Run it as a recurring quarterly and/or annual ritual to ensure your recap is always updated with the latest findings.
✨ I'd recommend using a slide format to make it presentation-friendly. Keep it to 10 slides maximum.
✨ Always include a single TL;DR slide, bonus points for making it pretty and shareable!
✨ Remember to weave in supporting evidence to your insights through statistics, charts, video clips or quotes.
What about AI?
As you might've noticed, I've excluded any talk of AI to this point. Here's why:
Yes, AI tools can help with research recaps, but they shouldn't serve as a replacement for digging into the data yourself. Many AI-generated takeaways are vague, repetitive, and lack broader organisational context. If you're new to research recaps or the body of work you're recapping (as a new hire, for instance), I strongly recommend doing your first several recaps without any AI. This will allow you to:
- Establish a deep, firsthand understanding of your organization's research. To be the expert on the subject, leave no stone unturned.
- Define what a successful research recap requires. Whether you're an IC or managing a team, develop a process so your recaps remain consistent and efficient over time.
This will allow you to present your recap with accuracy, credibility, and confidence. Putting AI first robs you and your team of that, ultimately hurting your users.
Once you're comfortable with your research recap process, advanced tools like Great Question AI can help you synthesize large amounts of raw research data. For example:
- Query entire studies with up to 50 hours of interview data in seconds
- Ask for specific quotes, insights, answers to questions, summaries, or reports
Each answer links to its original transcript, so you can verify accuracy. Plus, PII is masked from AI, so data will never be used by 3rd parties for training future models.
If and when you're ready, treat AI as your assistant, not a replacement. In my experience with AI so far, the best insights still come from doing the work yourself.
Why it's worth it
A research recap helps you surface the value of existing research without running a single new interview or helps stakeholders cut through the noise of your research repository. It reduces overwhelm for stakeholders, maximises the impact of your team's past work, and ensures the things that matter most to users aren't forgotten.
Yes, it takes effort, but it will save time in the long run and position you as a strategic partner, not just a research executor.
