analyzing-user-feedback
Analyze user/customer feedback and produce a User Feedback Analysis Pack (source inventory, normalized feedback table, taxonomy/codebook, themes + evidence, recommendations, and feedback loop). Use for voice of customer, feature request analysis, support ticket synthesis, churn reason synthesis, and survey open-ends.
npx skills add majiayu000/claude-skill-registry --skill analyzing-user-feedback --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Analyzing User Feedback ## Scope **Covers** - Aggregating and normalizing feedback from multiple channels (support, sales, research, reviews, surveys, usage signals) - Turning raw feedback into **themes with evidence** and **actionable recommendations** - Identifying **friction / reasons users won’t use the product** (not just validation) - Producing a repeatable **feedback loop** (cadence, owners, and handoffs) **When to use** - “Synthesize our user feedback into themes and actions.” - “Analyze support tickets / feature requests for the top issues.” - “Create a voice-of-customer report for <area> in the last <time window>.” - “Summarize churn reasons / cancellation feedback.” - “Cluster survey open-ends into insights and recommendations.” **When NOT to use** - You need to collect new feedback first (use `conducting-user-interviews` / `designing-surveys`) - You need backlog prioritization as the primary output (use `prioritizing-roadmap`) - You need a PRD/spec for a chosen solution (use `writing-prds` / `writing-specs-designs`) - You only need to respond to individual tickets (support workflow, not synthesis) ## Inputs **Minimum required** - Product area / workflow to analyze (or
- Scope
- Inputs
- Outputs (deliverables)
- Workflow (8 steps)
- 1) Intake + decision framing
- 2) Inventory sources + define the sampling plan
- 3) First-pass read-through (open coding)
- 4) Build the taxonomy + codebook
- 5) Normalize and tag the feedback table
- 6) Synthesize themes + quantify carefully
- 7) Translate into actions + learning plan
- 8) Share out + establish the feedback loop + quality gate
- Quality gate (required)
- Examples
What does the analyzing-user-feedback skill do?
Analyze user/customer feedback and produce a User Feedback Analysis Pack (source inventory, normalized feedback table, taxonomy/codebook, themes + evidence, recommendations, and feedback loop). Use for voice of customer, feature request analysis, support ticket synthesis, churn reason synthesis, and survey open-ends.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill analyzing-user-feedback --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.