Customer health has always been at the heart of Customer Success. But in most SaaS organisations, the way we measure it hasn’t kept up with how customers actually evolve.
We started with health scores — simple, single-number snapshots that promised clarity but often delivered false confidence. Then we learned that what really matters isn’t the score itself but the system behind it — a structure of signals, alerts, and playbooks that help teams act in real time.
That evolution took us from monitoring customers to actually managing them. Still, even the best health systems face a new challenge: scale.
When you’re tracking thousands of customers across dozens of products, regions, and behaviours, no human can realistically spot every trend or risk early enough. That’s where AI health scoring comes in — not as a replacement for human judgment, but as an accelerator of it.
AI gives us the ability to move from static, manual interpretation to predictive, data-driven action. Instead of waiting for a red score or a missed milestone, we can now see subtle behavioural shifts — declining engagement, tone changes in communication, or anomalies in product usage — that reveal what’s coming next.