User ResearchInterviewsInsightsAI Agent Skill
customer-research
Evidence-grounded user interview synthesis, verbatim quotation tagging, and friction point discovery.
Install Options
Install into Claude Code, Cursor, Codex, or Antigravity with:
$ npx skills add coreyhaines31/marketingskills@customer-research
Real Work Situation Solved
Turn scattered interviews into insight without making things up
“You have 8 user interviews that all say something different - how do you synthesize without guessing?”
5-Step Action Framework
- 1Pull direct user quotes out of your notes separately - keep "what the user said" clearly apart from "what I think it means".
- 2Count how many interviews raised the same issue - one person saying it isn't an insight, 5 out of 8 saying the same thing is.
- 3Attach direct evidence to every conclusion (a quote or a repeat count) - if you can't attach evidence, it's a hypothesis, not a conclusion.
- 4Note contradictions between interviews instead of smoothing them over - a contradiction is information too.
- 5Before sending the report, reread it and ask: where in my notes does this line come from? If you can't point to it, cut it.
Before
"Users generally don't like this feature, we should redo the whole thing."
After
"5 of 8 users struggled at the confirmation step (quote: 'I couldn't tell if it went through' - P3, P5, P6). 2 of 8 mentioned load speed. 1 of 8 had no issues. → The problem is concentrated in the confirmation step, not enough evidence to redo the whole flow."
Related Course Lesson
AI Agents for PM • Lesson 1
SKILL.md Source Instructions
SKILL.md • Read-only preview# Customer Research Skill Synthesize qualitative interview transcripts by separating direct user quotes from internal interpretations.