Examples for Feedback Sentiment Analyzer

Analyzes 200 customer feedback items about checkout flow issues to prioritize fixes. Identifies crash (28%) and payment (28%) issues as top problems, reveals mobile checkout is significantly worse than desktop (46% vs 35% negative), and provides prioritized fix recommendations with estimated revenue impact ($75K-$150K monthly improvement potential).

Analyzes 500 feedback items from Twitter and support channels about a mobile app update over 6 days to determine if it's a crisis. Identifies severe crisis with 53% negative sentiment (vs 20-30% baseline), shows deteriorating day-by-day trend (38% to 58% negative), and provides immediate action plan including rollback/hotfix recommendations.

Analyzes 350 NPS survey comments segmented by customer tier (enterprise, pro, free) to identify satisfaction gaps. Reveals a critical 117-point satisfaction gap between Pro tier (+66 net score) and Free tier (-51 net score), identifies mobile crashes and pricing as key pain points for free users, and provides a prioritized 30-60-90 day action plan.