AI Churn Scoring

Introduction

Acquiring new customers can cost up to five times more than retaining existing ones. For subscription businesses, retention isn’t just cost-effective — it directly drives predictable, long-term growth.

To achieve this, retention teams need to focus their efforts where it matters most — on subscribers who are at the highest risk of churning. The challenge lies in accurately identifying these at-risk subscribers early enough and ensuring that retention efforts are both data-driven and resource-efficient.

That’s where Chargebee’s AI Churn Scores come in.

Chargebee’s AI Churn Scores anticipates customer churn in the near future. Chargebee uses machine learning models trained on your historical billing data to predict the likelihood of a customer canceling their subscription within a defined time period (for example, the next 90 days).

Using Churn scores customer retention teams can:

• Proactively identify at-risk customers across subscriber base.

• Personalize retention strategies for high risk subscribers.

• Make data-driven decisions that support long-term business growth.

Chargebee’s churn scores are available directly within the Chargebee Growth platform. This enables teams to not only identify their at-risk customers but also take immediate actions to proactively retain them through Growth Plays, targeted interventions designed to engage high-risk subscribers and convert predictive insights into measurable retention outcomes.

Understanding churn scores

Chargebee provides two out-of-the-box attributes available to assess the churn risk of a customer:

• Churn Risk Score: A numeric value ranging from 1 to 100 that indicates a customer’s likelihood of churning, i.e., ceasing to be a customer, based on historical data and predictive modelling. The higher the score, the higher the likelihood of churn for the customer. Chargebee stores the churn scores for all your active paying customers wherever applicable.

• Churn Risk Levels: A simplified interpretation of the churn score, categorised into one of three levels:

  • High Risk: Any customer with a churn score between 70 to 100 is flagged as a high risk customer.

  • Medium Risk: Any customer with a churn score between 40 to 69 is marked as a medium risk customer.

  • Low Risk: Any customer with a churn score 1 to 39 is flagged as a low risk customer.

Limitations

Chargebee’s Churn scores are currently a part of EAP and have the following limitations.

• Available only to Chargebee Billing customers.

• At least 90 days of billing data is required to generate reliable scores.

• Predictions are probabilistic; use them to guide strategy, not as absolute indicators.

• Model accuracy may vary by industry, or data volume.

FAQs

1. How does churn scoring help my business?

Churn scores identify customers most likely to stop using your service, enabling your teams to proactively retain them. Use these insights to design data-driven retention strategies, reduce cancellations, and forecast customer lifetime value more accurately.

2. What kind of insights can I get from churn scores?

You’ll see customers categorized into High, Medium, and Low churn risk segments. This helps you understand dissatisfaction trends, monitor engagement patterns, and prioritize revenue-saving actions.

3. How reliable are churn scores?

Chargebee’s churn prediction model uses real billing data — actual customer transactions, renewals, and payment events — not assumptions. Each model is retrained and validated regularly to maintain high accuracy.

4. Does a high churn score mean a customer will definitely leave?

Not necessarily. A high score indicates increased churn likelihood, allowing you to intervene early — before a customer decides to cancel.

5. Can I see what factors influenced a customer’s churn score?

Yes. Chargebee provides explainability insights that show key drivers like payment failures, downgrades, or lack of renewals.

6. Can I segment customers by churn likelihood?

Yes. Using churn attributes (Low, Medium, High) in the dashboard helps to create segments, or combine them with other customer data (e.g., MRR, plan tier, location) for personalized campaigns.

7. Can I export churn data for external tools?

Yes. You can export churn data via the dashboard link in the Audience Builder for use in email automation, CRMs, or customer success platforms.

8. What data is used to generate churn scores?

Chargebee’s model uses clean billing data — grounded in real transactions

9. How accurate is the churn prediction?

Model performance is continuously evaluated using metrics like precision, recall, and F1 score. While accuracy can vary by business, using transaction-level data provides stronger reliability than assumption-based models.

10. Will providing more data improve the model?

Yes. Supplying relevant product usage or engagement data improves model precision and reduces false positives over time.

11. What type of model does Chargebee use?

Chargebee employs supervised machine learning models optimized for classification tasks. These models are retrained regularly to adapt to your evolving business.

12. Does the model stay updated as my business changes?

Yes. Chargebee monitors data drift and retrains the model periodically to ensure continued accuracy and relevance.

13. Why don’t I see churn scores for all customers?

Only active, paying customers with sufficient billing history are scored.

14. How often are churn scores updated?

Every 7 days, using the latest validated model.

15. Can I export churn scores?

Yes. An export option is provided in the customer preview section (part of churn dashboard).