Using customer sentiment analysis to predict churn before traditional metrics show it

Been looking at support ticket sentiment and app review emotions to catch users who might churn.

Seems like negative sentiment spikes about 2-3 weeks before engagement actually drops. Traditional retention metrics miss this window completely.

Anyone else tracking sentiment as an early warning system?

Timing’s everything here. Sentiment usually tanks before people actually bail. Focus on user value - if a high-value user starts complaining, drop everything and fix it. Low-value users? Maybe not worth the hassle. Set up triggers that look at both sentiment and what they’re paying you. Someone dropping $50/month who’s pissed off needs way different treatment than someone who hasn’t paid in forever. Most teams burn resources trying to save every single user at risk. Don’t do that. Go after the ones who actually move the needle on your revenue.

Push notifications beat support tickets for early warning signs. Users dismissing notifications or disabling them? That’s trouble brewing.

I watch notification engagement drops alongside app review sentiment. Together they’re way more effective - each catches different types of unhappy users.

The real challenge is making automated responses feel human when sentiment tanks.

Support tickets often lag behind. Tracking social media mentions helped us catch issues faster.

Ran something similar for a food delivery app tracking chat sentiment from customer service. You’re spot on about timing - sentiment tanked way before people stopped ordering.

Setting up alerts without constant noise was the real challenge. We focused on users hitting negative sentiment AND recent order problems. That combo gave us 10 days to jump in before they went dormant.

Best results came from catching delivery time complaints in chat. We’d comp them before they rage quit - saved about 8% of churners who would’ve been toast otherwise.

App reviews were too slow to act on, but chat sentiment was perfect for real-time fixes.

The make-or-break factor? Having someone actually respond to alerts fast. Data’s worthless if you can’t act within 24-48 hours.

Track in-app behavior too. It gives faster insights.