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:

1. Customer Profiles: Find risk assessments under Customers → select any subscribed customer → look for the risk indicator at the top of their profile

2. 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:

1. Immediate risks (0-2 weeks)

   • Reach out directly to high-value customers
   • Offer targeted promotions or discounts
   • Address any recent support issues

2. Medium-term risks (2-6 weeks)

   • Schedule check-in calls
   • Send engagement campaigns
   • Review usage patterns for optimization opportunities

3. 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

1. Cross-reference with other metrics

   • Compare with actual churn rates
   • Review customer health scores
   • Check recent support interactions

2. Segment your approach

   • Focus on high-value customers first
   • Create segment-specific retention strategies
   • Track effectiveness by customer type

3. 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!