Churn risk
Spotting customers at risk of churning before they leave gives you the power to act early and keep your most valuable relationships intact. Churn Risk helps you move from reactive to proactive retention by identifying potential churners early, giving you time to step in and make a difference. Think of it as your early warning system for customer retention - helping you focus your efforts where they’ll have the biggest impact.
What makes this feature different
While traditional churn metrics tell you who’s already left, Churn Risk helps you see who might leave next. Our deep learning model analyzes patterns in customer behavior to predict potential churn before it happens, helping you move from reactive to proactive retention.
The customer card indicator
Right on each customer’s card, you’ll see their current risk level and predicted timeframe, making it easy to:
Spot high-risk customers at a glance
Prioritize outreach based on risk level
Track how risk levels change over time
How it works
Churn Risk uses a deep learning model to predict the likelihood of customer churn before it happens. Like all predictive models, it provides signals rather than certainties - use these insights as one of many tools in your retention strategy.
The model:
Updates predictions weekly
Analyzes financial data and app events
Automatically collects data through the Shopify integration
Provides time-based risk categories for targeted intervention
Understanding risk scores
Risk categories
Predictions are grouped into four time-based categories:
Low risk: Stable customers with healthy engagement patterns
0-2 weeks: Immediate attention needed
2-6 weeks: Medium-term risk
6-12 weeks: Long-term monitoring
Where to find Churn Risk insights
You can track churn risk in two key places:
Customer Profiles: Find risk assessments under Customers → select any subscribed customer → look for the risk indicator at the top of their profile
Churn Risk Report: Get a bird’s-eye view of risk levels across your entire customer base. Use this to:
Spot trends in customer risk levels
Identify clusters of at-risk customers
Plan proactive retention campaigns
Track how risk levels change over time
Data sources
The risk score draws from multiple data points to build a complete picture:
Financial metrics from your subscription data
App usage patterns showing engagement levels
Shopify store activity and status
Platform events indicating customer health
Taking action
Use Churn Risk scores to guide your retention efforts:
Immediate risks (0-2 weeks)
Reach out directly to high-value customers
Offer targeted promotions or discounts
Address any recent support issues
Medium-term risks (2-6 weeks)
Schedule check-in calls
Send engagement campaigns
Review usage patterns for optimization opportunities
Long-term risks (6-12 weeks)
Monitor for changes in usage patterns
Plan proactive engagement strategies
Identify common risk factors
Making the most of this feature
Best practices
Regularly review risk predictions
Prioritize interventions based on customer value
Track the success of retention efforts
Use alongside other churn metrics for complete context
Remember predictions are signals, not certainties
Pro tips
Cross-reference with other metrics
Compare with actual churn rates
Review customer health scores
Check recent support interactions
Segment your approach
Focus on high-value customers first
Create segment-specific retention strategies
Track effectiveness by customer type
Monitor trends
Watch for patterns in risk scores
Identify common pre-churn indicators
Use insights to improve product experience
Remember: Churn Risk predictions are early warning signals. The earlier you act on these signals, the better your chances of retaining valuable customers.
Need help developing your retention strategy? Our team is here to help you make the most of these predictions!