In the field of User Experience (UX) Research, we apply a lot of rigor and methodology to designing and executing research projects, but often not as much on how to analyze our results. On paper, the “synthesis” phase can sound very simple. You just review your findings and come up with major takeaways to incorporate into your work.
But in reality, this stage is very complex, arduous, and time consuming. And it’s far too easy to introduce our own biases. When we introduce our own assumptions and predictions to our research synthesis, we put the validity of our findings at risk.
I think of research synthesis as a series of waves, with relatively predictable highs and lows. This helps me prepare for the natural low points in the process and to carve a path out to minimize error or bias. The synthesis wave is based on the startup lifecycle, a model developed by Paul Graham of Y Combinator that shows the natural highs and lows of working in a startup.
The four stages in the synthesis wave are:
- Externalization. This is the tough but necessary phase of listening to session recordings and identifying key takeaways from each. At this stage, I know I’ll be tempted to let my mind wander, so I schedule breaks to keep my perspective fresh.
- Affinitizing. At this stage, my goal is to find super high level, early stage patterns. I often have to remind myself to slow down, and not jump to conclusions.
- Insight identification. This is one of the most critical points of the process, where I start to tease out more nuanced findings. I come up with as many different ways as possible to visualize and reorganize the data to see what deeper patterns emerge.
- Insight refinement. Finally, I bring a critical eye to my findings and put my potential insights to the test. At this point, I make sure I consider business impact as well as user impact and bring in quantitative data to assess which insights are most meaningful to our organization.
It’s the third stage, insight identification, that’s most challenging for many UXers. So that’s the stage I’m going to explore in this post.
It’s far too easy—and common—to speed things up at this stage and just go with the surface level patterns you’ve identified in the Affinitizing phase. But I’ve found that you can push those surface level findings into much deeper insights with just a few simple tricks.
Imagine we’ve just finished a hypothetical research project where we observed and spoke with people who drink coffee.
After we finished affinitizing our notes, we found the following high level themes surfaced throughout our research:
- Commuting with coffee
- My everyday routine
- Health concerns
Looking at these themes, it’s hard to know just what to do. This is where I’ve learned to spend a little more time and start to dig deep.
One of the first things I do is come up with different spectrums that relate to my initial themes and common topics. Then, I map the different findings onto these spectrums. Since I take all of my notes on color-coded sticky notes during the Externalization phase, this makes my process very easy to visualize as I start identifying insights.
Looking at our different themes and findings, we might come up with a few different spectrums for our coffee project.
- Coffee as convenience ← → Coffee as indulgence
- Consistency ← → Variety
- Ritual ← → Routine
- Individual ← → Family
- Budget-focused ← → treat yourself!
I’ll typically draw the spectrums on a whiteboard and start moving stickies to see where they fall onto the spectrum. Often in this type of research, I’ll have done research with a couple different segments or cohorts of people. It’s helpful to have the sticky notes color-coded by each segment, so that I can see holistic patterns when I look at multiple spectrums. But if I were only working with one group, I’d try to give each participant their own color sticky.