What it is
Organizing, coding, and analyzing raw research (interview notes, recordings, survey responses, analytics findings) into themes, insights, and opportunities.
Why use it
Raw data is not actionable. Synthesis turns observations into shared understanding that guides design; without it, teams revert to assumptions.
Use this when
- You have finished interviews, surveys, or analytics reviews
- The team needs shared understanding of the findings
- You are moving from discovery into concept exploration
You may not need this when
- Data is minimal and findings are clear
- A prior synthesis covers the same questions
Dependencies — what you need
- Consolidated inputs: notes, recordings, survey data
- Time for collaborative sense-making
- Agreement on how insights will inform decisions
People involved
- Design
- Research
- Product
Typical outputs
- Affinity maps or thematic clusters
- Insight statements, each with its evidence
- How Might We (HMW) statements, as ideas
- Prioritized problem areas and themes
Template
Research Synthesis template
A fill-in structure for running this method: what to prepare, what to do, what to record, and how to read the result.
How AI can help
AI as augmentation — not replacement
- Cluster quotes or sticky notes into themes
- Draft HMW statements from insights
- Find contradictions or gaps across sources
- Draft an insights summary for review
- Suggest patterns manual review may have missed
AI prompt
A prompt for any AI assistant. It works only from material you paste in, keeps assumptions apart from findings, and leaves the decisions to you.