CASE 2 - How We Saved a Fintech Startup 6 Weeks of Runway by Predicting Churn Before It Happened
The Client Seed-stage fintech startup, $500K ARR, 6 months runway remaining. Building expense management software for SMBs. Fresh out of YC, growing fast but bleeding customers they couldn't afford to lose.
The Nightmare The CEO was lying awake at 3 AM refreshing their customer dashboard, watching their best customers cancel with zero warning. They'd upgraded features, increased usage, seemed happy - then boom, cancelled. Each lost customer burned weeks of precious runway.
Customer churn: 8% monthly (unsustainable)
Average time to detect churn risk: After cancellation
Revenue loss: $40K monthly from "happy" customers
Runway impact: Losing 6 weeks every quarter
With 6 months left, every board update was getting more tense. Investors were asking tough questions about unit economics they couldn't answer.
The killer detail? Their best customer - a $2K monthly account - had cancelled the day after their weekly check-in call where the founder said "everything's going great, we love the product." 48 hours later: cancellation email. No explanation.
What We Found in 2 Weeks We analyzed 6 months of user behavior data. The patterns were hidden but consistent:
89% of churned customers showed specific warning signs 3-4 weeks before cancellation
"Healthy" usage metrics were meaningless - engagement dropped in subtle ways
Support ticket sentiment predicted churn better than feature usage
High-value customers had different churn patterns than SMB accounts
The Churn Prediction System Built a machine learning model that scored every customer's churn risk weekly:
Tracked 23 behavioral signals across product usage, support interactions, and billing patterns
Flagged at-risk customers 30 days before typical churn
Created automated alerts for customer success intervention
Accuracy rate: 87% prediction accuracy
The 60-Day Results
Monthly churn dropped from 8% to 5.2% (-35%)
Revenue recovery: $28K monthly from prevented churn
Customer success team intervened on 94% of high-risk accounts
Runway extension: 6 additional weeks of operation
The Moment Everything Changed Week 3 after implementation, the system flagged their second-largest customer ($3.5K monthly) as high churn risk. The customer success team reached out proactively. Turns out they were frustrated with a specific workflow but hadn't complained. Fixed in 48 hours. Customer renewed for 2 years.
Why This Matters Seed-stage companies can't afford to lose customers they could have saved. Every churn event burns runway that could have funded growth.
The CEO's Reaction "I went from losing sleep over surprise cancellations to getting early warnings we could actually act on. Godwin didn't just reduce churn - he gave us back control of our destiny."
Ready to see which customers are about to leave? I'll analyze your churn patterns for free. If I can't predict which customers will cancel in the next 30 days, dinner's on me.