What Is Churn Prediction?
Churn prediction uses data to identify customers likely to leave before they do. Catching at-risk customers early dramatically reduces actual churn.
Key Takeaways
- Churn prediction uses historical behaviour patterns to identify customers at risk of leaving.
- Early warning signals include declining purchase frequency, lower spend, and reduced engagement.
- Proactive intervention on at-risk customers is significantly more effective than reacquisition.
What churn prediction does
Churn prediction is the use of data and analytical models to identify customers who are showing early signs of disengagement and are likely to stop buying. Rather than discovering a customer has churned after they've left (a lagging signal), churn prediction surfaces at-risk customers while there's still time to intervene.
Churn signals
Decreasing purchase frequency compared to the customer's own historical baseline. Declining average order value. Reduced engagement with emails or app (lower open rates, fewer logins). Increased customer service contacts (especially complaints). Absence of a repeat purchase after the customer's typical inter-purchase interval. Each of these signals is a data point; the combination creates a churn risk score.
How prediction models work
Churn prediction models are trained on historical data: they learn which combination of signals preceded churn in past customers, then apply those patterns to current customers to produce a risk score. More sophisticated models use machine learning to identify non-obvious signal combinations. Simpler models based on recency alone (e.g., customers who haven't purchased in X days) are often surprisingly effective and easy to implement.
What to do with predictions
Segment your customer base by churn risk score. High-risk customers receive immediate personalised outreach — a relevant offer, a proactive customer service call, a 'we miss you' campaign. Medium-risk customers enter a re-engagement sequence. Low-risk customers continue with normal retention communications. The ROI on retaining a high-value customer is almost always better than any acquisition equivalent.