4 Methods to To Generate Better User Research Insights
Want your primary research to generate better insights?
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We do all this diverging/converging, plan research sessions, and then we forget to synthesize deliberately.
But synthesis is what gets the job done!
Check out these 4 great ways to put together research data for insights:
1/ ASYMMETRIC CLUSTERING MATRIX
Simple method, great for inexperienced teams.
Compares values of 2 different things and maps them on a grid.
The matrix lets you do systematic analyses, compare things, show connections and dependencies.
2/ RAINBOW SPREADSHEET
Named for the different colours used to represent the study’s participants, it’s a spreadsheet in which a team gathers all of the data collected during a UX study.
It summarises study findings and becomes the final report.
3/ JOB CLUSTER ANALYSIS
If you’d like to play with Jobs-to-be-done, this post outline the process of analysing the jobs post-interviews.
This is missing from most other resources out there!
You’ll see the theme of clustering come up here too.
Learn here + and we’re still hopeful that the JTBD clustering app from Bob Moesta and Ryan Singer is coming!
4/ OPPORTUNITY SOLUTION TREE (+DRAWING STORIES)
There are 1000’s of articles about “how to use opportunity solution trees”.
None of them show just how to pull out opportunities.
You might have to take the course to learn more details, but the method of making rudimentary drawings of stories is a surprisingly helpful way to analyse a story. But either way, trees are a great structuring mechanism.
BONUS For general note-taking advice, this is the best article I could find out there: https://www.producttalk.org/2016/02/how-to-take-notes-during-customer-research-interviews/
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TL;DR — 4 effective methods for compiling research data for analysis:
• Asymmetric Clustering Matrix
• Rainbow Spreadsheet
• Job Cluster Analysis
• Product Talk Opportunity Solution Tree + Drawing Method
+ BONUS: How To Take Notes During Customer Research Interviews