review-analyzer-skill transforms raw e-commerce customer reviews into actionable strategic intelligence using a robust 22-dimension AI tagging framework. It automatically profiles user personas, usage scenarios, product pain points, and key selling drivers across 15 structured insight chapters, featuring deterministic anomaly detection for quality spikes and churn risks. Supporting multi-source input from local CSV files and SellerSprite ASIN scraping, seamless Feishu/Lark document synchronization, and six glassmorphic HTML visualization dashboards, it gives product managers and cross-border sellers the deep Voice of Customer (VOC) data needed to optimize listings, fix product defects, and identify market opportunities.
주요 기능
016 polished HTML dashboard themes including Premium Gold, Dark Tech, and Stripe Executive
0215-chapter deep insight VOC reports with zero-cost deterministic anomaly signal detection
03122 GitHub stars
04Multi-source data ingestion supporting local CSV datasets and SellerSprite ASIN integration
0522-dimension AI tagging covering user personas, usage scenarios, quality, features, and sentiment
06One-click synchronization of markdown reports and chart visualizations directly to Feishu/Lark
사용 사례
01Building executive VOC presentations and interactive dashboards for stakeholder and R&D reviews
02Conducting competitor review audits on Amazon to discover product differentiators and market gaps
03Diagnosing negative review clusters and defect trends to guide manufacturing and quality improvements