What problem does it solve? Product teams collect large volumes of user feedback from surveys, reviews, and CSV exports but struggle to turn it into structured insights about who is satisfied, who is not, and why. This Skill synthesizes raw feedback into segment-level profiles with sentiment scores, pain points, and prioritized recommendations. ## Core Features & Use Cases - Segment Identification: Detects at least three distinct user segments or personas directly from the feedback data. - Sentiment Scoring: Assigns each segment an overall sentiment score from -1 to +1, with satisfaction drivers, detractors, and approximate NPS estimates. - JTBD & Pain Point Extraction: Maps each segment's jobs-to-be-done, recurring complaints, unmet needs, and positive themes with supporting quotes. - Use Case: You have 2,000 app store reviews and a CSV of survey responses for your SaaS product. Run this Skill to get segment profiles showing which user groups love the product, which are at churn risk, and the top improvements per segment. ## Quick Start Analyze the attached user feedback CSV and identify user segments with sentiment scores, pain points, and actionable recommendations for each group.
