Customer health score

A customer health score is a metric that helps businesses understand, on a scale from strong to at risk, their relationship with a particular customer. Think of it as a quick health check on customer engagement, satisfaction, loyalty, and likelihood to stay or churn. The score is usually calculated by combining multiple signals into a single number, often represented on a scale (for example, 0–100 or red/yellow/green).

A customer health score can take many factors into account, including product usage frequency, support ticket volume, response to surveys, and payment history. The goal is to create a snapshot of how “healthy” the customer is so teams can act early if something seems off.

How does a customer health score work?

Businesses first define which indicators best reflect customer success for their specific product or service. For a software company, this might include login frequency, feature adoption, renewal rate, and customer support activity. A services firm, on the other hand, might be more interested in communication cadence, satisfaction scores, and project outcomes.

Once data points are selected, they’re weighted based on importance. A customer who logs in daily but gives low satisfaction scores may still be considered at risk. A strong health score generally combines:

• Engagement data: How often the customer uses your product or interacts with your team
• Support data: The number, severity, resolution time, and recurrence rate of tickets or issues
• Financial data: Renewals, upsells, payment timeliness, and expansion revenue
• Sentiment data: Survey results, NPS scores, written feedback, and social media mentions

The result is a single metric that can be tracked over time to spot trends.

Why customer health scores matter

Healthy customers renew. Unhealthy customers churn. A well-designed score allows account managers and customer success teams to prioritize outreach and resources where they’re most needed.

Proactive companies use health scores as both an early warning signal and a growth tool. They are able to easily identify customers who are thriving and might be ready for an upsell or referral request. Over time, a company can even benchmark what “healthy” looks like across its customer base and refine its approach as the business scales.

The role of AI in customer health scoring

AI makes health scores more powerful by finding patterns humans might miss. For instance, machine learning models can weigh dozens of variables—everything from login times, feature usage patterns, sentiment in support tickets, renewal history, and engagement with product updates or announcements—and predict churn risk with greater accuracy. When it comes to customer service, AI agents can automatically adjust their approach based on a customer’s health score, offering extra support or flagging the case for human follow-up.

When used correctly, a customer health score turns scattered customer data into a clear signal and helps businesses act before problems become cancellations.

Customer health score is a decision-making tool that helps teams know where to spend their time, which accounts need attention, where growth opportunities lie, and how to prioritize resources effectively. While they require thought and regular monitoring, customer health scores are one of the most reliable predictors of churn and one of the best levers for retention.