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Summary
We got into UX research to make products work better for humans. However, the pace of product iteration has gotten so fast, our research resources have gotten so thin, that we are continuously being asked to be faster, while also bringing more pithy - more relevant findings. Product teams don’t have the time to hear long readouts. “How does this impact the decision I need to make this week?” they want to know. The best way to ensure research insights are both timely and relevant is to make your research synthesis process collaborative. Using a canvas to co-synthesize with your team can be fun, speedy and incredibly impactful. In this talk, Shipra Kayan from Miro gives an inside look at Miro’s research process. We follow an example that shows how the teams run a user testing session (moderate 5 tests, synthesize, reflect and make decisions) in just one and a half days during a design sprint. See hacks and tips for importing data, tagging, clustering, facilitating and presenting all from a single space. Walk away with new ideas for how to synthesize collaboratively with your cross-functional teams to immediately impact design decisions.
Key Insights
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Collaborative involvement of stakeholders at the research brief and synthesis stages drastically improves research relevance and team buy-in.
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Using anonymous input modes helps surface honest hopes and fears from stakeholders, reducing groupthink.
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AI-driven clustering in Miro expedites sensemaking of qualitative data but still requires manual adjustment by researchers.
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Tagging stickies collaboratively during note taking prevents data duplication and ensures richer synthesis.
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Research insights resonate more when created jointly with product teams, promoting faster adoption in decision-making.
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Research needs often shift quickly in business contexts, so research processes must speed up to keep relevance.
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Workshopping with structured diverging and converging phases leads to clearer prioritization than traditional meetings.
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Design sprints exemplify compressed timelines where rapid collaborative synthesis is critical.
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AI is best suited as a supportive tool in research workflows, not as a replacement for human interpretation.
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Live embedding of documents and spreadsheets into Miro supports seamless integration of multiple data sources.
Notable Quotes
"Research is not gonna have the impact it has if we don't hear the actual fears and needs of stakeholders upfront."
"Workshops aren’t about just gathering input but about getting the group to converge on the most important things."
"Using private mode in Miro allows people to input ideas anonymously, reducing hesitation and increasing honest feedback."
"If you want research insights to be relevant, they have to feel like insights of the whole team, not just the researcher."
"The speed of business has accelerated, so we need research processes that keep up, not months-long projects."
"The first and last parts of research projects—the brief and the synthesis—should be 80 to 90% collaborative."
"Tags on stickies create human-driven categorization that AI clustering can then build on."
"In design sprints, we set the mindset upfront to be pessimistic about ideas to gain confidence through testing."
"Voting is a great way to prioritize which fears and risks to address in a research plan."
"AI is improving weekly, but it still needs researchers’ input to refine themes and clusters effectively."
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