Turn scattered feature requests into a prioritized list based on actual demand.
/feature-request-analyzer4-6 hrs → 10 min
Compared to doing it manually
/feature-request-analyzerType this in Claude to run the skill
Requests are everywhere. Some ideas appear 50 times, others once from a loud customer.
/welcome/feature-request-analyzer in Claude to run the skill/jtbd-extractorExtract Jobs-to-be-Done statements from research data to uncover innovation opportunities.
/user-interview-analyzerTransform interview transcripts into structured insights with quotes, patterns, and recommendations.
/feedback-categorizerAnalyze and categorize customer feedback into actionable themes using affinity mapping.
/app-review-analyzerExtract themes, complaints, and feature requests from app reviews at scale.
Don't just count requests — understand the underlying problems. Group by job-to-be-done, identify patterns, consider requester segments, and estimate impact. One enterprise request might outweigh 100 free user requests.
Not always. Users describe solutions, not problems. Dig into WHY they want it. Often the underlying need can be solved better than the requested feature. "If I had asked people what they wanted, they would have said faster horses."
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