What problem does it solve? Teams often build messaging, personas, and product decisions on assumptions instead of real customer evidence. This Skill structures the analysis of existing research assets (transcripts, surveys, support tickets, NPS responses) and guides gathering new intelligence from online sources like Reddit, G2, and niche communities. ## Core Features & Use Cases - Existing Asset Analysis: Extract jobs-to-be-done, pain points, trigger events, desired outcomes, and verbatim customer language from transcripts, surveys, tickets, and churn data, with confidence labels and sample-bias checks. - Digital Watering Hole Research: Find and mine Reddit, G2/Capterra, Hacker News, LinkedIn, app store reviews, and SparkToro audience data using per-source playbooks in references/source-guides.md. - Persona & Deliverable Generation: Build evidence-based personas (minimum 5-10 data points), VOC quote banks, JTBD maps, and competitive intelligence summaries. - Use Case: You have 20 customer interview transcripts and want messaging insights. The Skill checks your product marketing context, asks about your goal, extracts themes with frequency and intensity scoring, and delivers a synthesis report with money quotes. ## Quick Start Analyze my customer interview transcripts and produce a research synthesis report with themes, representative quotes, and confidence levels.
