Save Customers Before They Go
Predictive retention that works.
Build churn prediction solutions that identify at-risk customers early, trigger the right interventions, and retain valuable relationships—before it's too late.
Churn Prediction Excellence
Our prediction solutions save valuable customers.
Customers leave silently. By the time you notice, they've already decided. Reactive retention is too late—the best save rate is single digits. Meanwhile, you're wasting resources on customers who weren't at risk.
We build churn prediction systems that see departure coming. ML models identify risk signals—declining engagement, support issues, payment problems—before the customer decides to leave. Early warning gives time for effective intervention. Targeted actions address the specific risk factors. The result: higher retention, lower costs, better customer relationships.
Why Build Custom Churn Prediction?
Expert prediction development for your customer patterns.
Custom churn prediction learns your customer signals—your engagement patterns, your risk factors, your intervention windows—not generic models that miss industry-specific behaviors.
Purpose-built prediction integrates with your customer data, triggers your retention workflows, and evolves with changing patterns.
Requirements & Prerequisites
Understand what you need to get started and what we can help with
Required(2)
Customer Data
Historical customer behavior and outcomes.
Churn History
Past churn events for model training.
Recommended(1)
Intervention Data
Past retention actions and results.
Common Challenges & Solutions
Understand the obstacles you might face and how we address them
Late Detection
Customers leave before intervention.
Our Solution
Early warning with adequate lead time.
False Positives
Wasted retention resources.
Our Solution
Precision tuning for your business costs.
Generic Signals
Missing industry-specific patterns.
Our Solution
Custom features from your data.
No Actionability
Predictions without interventions.
Our Solution
Reason codes and recommended actions.
Your Dedicated Team
Meet the experts who will drive your project to success
Customer Success
Responsibility
Define retention strategies.
Experience
Customer retention
Marketing
Responsibility
Design retention campaigns.
Experience
Retention marketing
Analytics
Responsibility
Provide customer data.
Experience
Customer analytics
Product
Responsibility
Integrate predictions.
Experience
Product management
Engagement Model
Ongoing model monitoring and optimization
Success Metrics
Measurable outcomes you can expect from our engagement
Prediction Accuracy
88%
AUC-ROC score for predictions.
Typical Range
Early Warning Lead
45 days
Time before likely churn.
Typical Range
Churn Reduction
30%
Decrease in customer churn.
Typical Range
Save Rate
35%
At-risk customers retained.
Typical Range
Resource Efficiency
+60%
Better targeting of retention spend.
Typical Range
LTV Recovery
+25%
Customer lifetime value saved.
Typical Range
Return on Investment
Churn prediction delivers ROI through retention.
Revenue Saved
10-30%
Within Of at-risk revenue
Retention Cost
-40%
Within More targeted spend
Payback Period
2-4 months
Within Typical timeframe
“These are typical results based on our engagements. Actual outcomes depend on your specific context, market conditions, and organizational readiness.”
Why Choose Us?
See how our approach compares to traditional alternatives
| Aspect | Our Approach | Traditional Approach |
|---|---|---|
| Detection | Early warning Time to intervene | Reactive |
| Targeting | Precise risk scores Efficient spend | Broad segments |
| Actions | Reason codes + recommendations Actionable insights | Prediction only |
| Learning | Continuous improvement Adapts to changes | Static model |
Technologies We Use
Modern, battle-tested technologies for reliable and scalable solutions
Python
ML development
TensorFlow
Deep learning models
scikit-learn
ML algorithms
PostgreSQL
Customer data
Ready to Get Started?
Let's discuss how we can help you with predictive analytics.