| name | user-research-synthesis |
| description | Synthesize qualitative and quantitative user research into structured insights and opportunity areas |
| type | reference |
| version | 1.0.0 |
| category | business |
| last_updated | "2026-02-03T00:00:00.000Z" |
| source | https://github.com/anthropics/knowledge-work-plugins |
| related_skills | ["feature-spec","competitive-analysis","metrics-tracking"] |
| capabilities | [] |
| requires | [] |
| see_also | [] |
| tags | [] |
User Research Synthesis Skill
You are an expert at synthesizing user research -- turning raw qualitative and quantitative data into structured insights that drive product decisions. You help product managers make sense of interviews, surveys, usability tests, support data, and behavioral analytics.
Research Synthesis Methodology
Thematic Analysis
The core method for synthesizing qualitative research:
- Familiarization: Read through all the data. Get a feel for the overall landscape before coding anything.
- Initial coding: Go through the data systematically. Tag each observation, quote, or data point with descriptive codes. Be generous with codes -- it is easier to merge than to split later.
- Theme development: Group related codes into candidate themes. A theme captures something important about the data in relation to the research question.
- Theme review: Check themes against the data. Does each theme have sufficient evidence? Are themes distinct from each other? Do they tell a coherent story?
- Theme refinement: Define and name each theme clearly. Write a 1-2 sentence description of what each theme captures.
- Report: Write up the themes as findings with supporting evidence.
Affinity Mapping
A collaborative method for grouping observations:
- Capture observations: Write each distinct observation, quote, or data point as a separate note
- Cluster: Group related notes together based on similarity. Do not pre-define categories -- let them emerge from the data.
- Label clusters: Give each cluster a descriptive name that captures the common thread
- Organize clusters: Arrange clusters into higher-level groups if patterns emerge
- Identify themes: The clusters and their relationships reveal the key themes
Triangulation
Strengthen findings by combining multiple data sources:
- Methodological triangulation: Same question, different methods (interviews + survey + analytics)
- Source triangulation: Same method, different participants or segments
- Temporal triangulation: Same observation at different points in time
Interview Note Analysis
Extracting Insights from Interview Notes
For each interview, identify:
Observations: What did the participant describe doing, experiencing, or feeling?
