Most SaaS companies track customer health using a simple score — green, yellow, red.
It feels neat and manageable. But here’s the reality:
- A customer can be “green” today and churn tomorrow.
- Scores often lag behind reality.
- They rarely capture the complexity of relationships, adoption, and business context.
Health isn’t static. It’s dynamic, evolving every day. And health scores have limits.
That’s why we need to move beyond a health score into a health system.
What’s Wrong with Health Scores?
I've seen health scores being used in all three SaaS companies I've worked at for the past 10+ years. They are a good start, but they are also:
- Static: They capture a snapshot, not a journey.
- Lagging: By the time a score drops, risk is already real.
- Shallow: They often reflect surface-level usage data, ignoring deeper context (like exec sponsor changes or roadmap alignment).
I covered these pitfalls in more depth in my previous post on why customer health is broken.
What a Health System Looks Like
A health system is more than a number. A true customer health system goes beyond scoring and instead acts as a dynamic framework for managing risk and opportunity. It continuously monitors signals, triggers alerts, and guides teams with clear next steps, making it proactive rather than reactive.
A well-defined health system is a living framework that:
1. Tracks signals dynamically
- Daily usage patterns, not just monthly averages
- Sentiment from surveys, calls, or ticket notes
- Changes in sponsorship or key stakeholders
2. Triggers alerts automatically
- Milestone alerts → Notify teams of journey checkpoints (onboarding, QBRs, renewal readiness)
- Risk alerts → Flag sudden changes (drop in usage, missed QBR, NPS detractor, executive silence)
3. Connects to action playbooks
- Each alert links directly to a pre-defined playbook (e.g. escalation, adoption workshop, sponsor reconnect)
- Responsibility is clear: who acts, when, and how
4. Feeds back into strategy
- Alerts and outcomes should loop back into your health model
- AI/analytics can surface patterns over time (e.g. which signals were early churn predictors, which interventions saved renewals)
When you shift from score to system, you catch risks before they snowball; you create consistent customer journeys across accounts; you build trust with leadership by linking actions to outcomes, and ultimately, you can enable AI to learn from signals and strengthen prediction.
In other words:
✅ Fewer surprises
✅ Faster intervention
✅ More consistent value delivery
How to Build a Health System (Step by Step)
Building a health system isn’t about starting from scratch — it’s about layering structure, signals, and action onto the journey you already manage. By following a series of deliberate steps, you can turn scattered data points into a connected system that drives consistent outcomes.
1. Map the Customer Journey
- Define the critical milestones: onboarding, first value, adoption, renewal prep, expansion.
- Document what “healthy” looks like at each stage.
2. Define Key Signals
- Separate leading indicators (daily adoption, exec engagement, QBR attendance) from lagging indicators (NPS, renewal outcome).
- Decide which signals should always trigger an alert.
3. Set Up Milestone Alerts
- Pre-scheduled check-ins based on the journey timeline (e.g. Go-Live date, Month 3 QBR, Month 12 roadmap review).
- Example: “Customer reached Month 18 post-purchase: validate ROI, discuss expansion.”
4. Set Up Risk Alerts
- Event-driven notifications based on negative signals (drop in DAUs, multiple support escalations, financial red flags).
- Example: “Customer has missed 2 consecutive QBRs. Escalate to exec sponsor.”
5. Build Action Playbooks
- For each alert, outline the exact next steps and who needs to take them by when.
- Example: Risk Alert → “Exec sponsor silent 6+ months” → Trigger sponsor reconnect playbook: align AE, send C-level outreach, schedule exec check-in.
6. Integrate Into Daily Workflow
- Deliver alerts where teams already work (CRM, Slack/Teams, email).
- Make it impossible to ignore.
- Ensure first-level management has visibility and responsibility for their team members to take the actions required in a timely manner.
7. Measure & Refine
- Track: Which alerts triggered? Which actions were taken? Did outcomes improve?
- Adjust thresholds and signals as patterns emerge.
Example: Score vs System
To see the difference clearly, let’s compare a traditional score-based model with a system-based approach. The contrast shows how one leaves you guessing, while the other ensures timely, meaningful action.
Score-based approach:
- Health = 85/100
- Color = Green
- Action = Nothing, until the number changes
System-based approach:
- Health signals: Exec sponsor not engaged, adoption stalled after feature rollout
- Alert: Triggered to CSM + AE
- Action: Sponsor reconnect playbook initiated, adoption workshop scheduled
The main difference? One is passive. The other drives action.
Scores might make dashboards look good. But customers don’t succeed because of numbers — they succeed because of the actions you take when signals change. That's why build the system, not just the scores.
If you haven’t yet, read the first post in this series: Why Customer Health Is Broken (and How to Fix It).
And stay tuned for the next post, where I’ll dive into what should actually trigger a health alert and how to build them into your customer success workflows.