Customer Sentiment Analysis Platform

SaaS company was losing customers before realizing they were unhappy. We built a sentiment analysis platform that identifies at-risk customers early, reducing churn by 32%.

SaaS company struggled to identify at-risk customers from 100K+ monthly support tickets and emails.

• •100K+ monthly support interactions
• •No early warning system for churn risk
• •Manual ticket review not scalable

• Identify at-risk customers 30+ days before churn
• Reduce churn by 25%+
• Automate sentiment tracking

Fine-tuned BERT model for sentiment classification + topic modeling. Real-time dashboard showing customer health scores and churn risk.

Approach

• →Fine-tuned BERT on support conversations
• →Topic modeling to identify pain points
• →Real-time customer health scoring
• →Integrated with CRM for automated workflows