User research synthesis: the process of going from “Oh my god, I’m drowning in data,” to “here are the top 5 things we learnt about our users”. If it sounds hard… that’s about right—it is.
Luckily, there are ways to bring order to the chaos! I’ve spoken to Designers & Researchers from teams big and small, ranging from Etsy, Spotify and Wrike to freelancers—below are the distilled learnings from those conversations. 👇
There are many different ways to approach synthesis—so which route should you go down? To choose the right approach, answer 2 questions first:
Sometimes in a round of usability testing, every person makes the same mistake and it’s painfully clear what the takeaway is (seriously, the users are in so much pain). In other cases, you’re swimming in pools of generative research data trying to figure out—what was the point of it all?
If the patterns are clear, synthesis becomes much lighter—focused on extracting evidence that’ll communicate the point clearly to your stakeholders (like that clip of a user pulling their hair out in frustration).
When conclusions are not-so-obvious or you want to be extra sure of your findings for an important project, it’s time to dive deeeeep into the sea of data!
“When you have a deadline and you have all this data—there’s a lack of clarity, uncertainty, and overwhelming possibilities. How do I put this into a form that can be understood?” — Samantha Reis, UX Researcher
After speaking to teams around the world, we’ve found clear patterns in how people process data. There are really 3 key ways our brains convert huge masses of information into insights, and depending on the person, one of these methods just clicks:
“Miro helps me analyze data… I put Post-Its on the canvas and start seeing if we can make clusters on how these themes are connected.”—Běla Beránková, Wrike
The process here involves 3 steps:
This method also works really well for collaborative synthesis—so if you need to bring in a team member or two and review data together, this may be the way to go!
Some folks have the uncanny ability to bookmark key moments from conversations in their heads, identifying patterns and constructing storylines without putting pen to paper.
“The storyline is in my head… I may highlight data so I can pick it up easily, but I don’t need to analyze as such.” — Sanjana Purker, Spotify
The third category is of folks who need to see data in rows and columns, everything categorized neatly to be able to detect patterns across conversations (this is me!).
“I have a spreadsheet with raw data on every person. Within the participant tab I have columns for questions, notes, and insights… I then can see that for 3 out of 5 participants, I got the same insight.”—Alex Loh, Etsy
Not sure which method will suit you? This can evolve a bit based on the complexity of the project and your experience in the field — but the best way to know is to give each a try!
By the way, Looppanel can auto-generate editable transcripts, create AI notes to analyze, and auto-generate affinity maps! Try it out now.
Looppanel automatically records your calls, transcribes them, and centralizes all your research data in one place