Customer Health Score Analyzer

Customer Health Score Analyzer helps you stay ahead of churn by fusing multiple customer signals — product usage, NPS, support activity, and billing data — into a single, real-time health score. Whether you're operating a high-touch enterprise SaaS or a low-touch self-serve model, this tool delivers actionable visibility into the wellbeing of your customer base.

What is it?

The app ingests structured customer data across your key systems and calculates a weighted health score using predefined rules or machine learning. It then breaks down what's driving the score, highlights leading indicators of churn or expansion, and provides tailored recommendations to improve customer outcomes.

Why use this app?

• 🛑 Early Warning System
  Spot at-risk accounts before they churn with proactive score monitoring based on behavioral, support, and revenue signals.

• 📊 Actionable Signal Breakdown
  Know exactly which inputs (NPS dip, overdue invoices, usage drops) are dragging a score down — and which are boosting it.

• ⚙️ Customizable Weighting
  Adjust weights by customer segment, product tier, or lifecycle stage. ML options available for dynamic scoring over time.

• 📈 Strategic Ops Enablement
  Power your CSM workflows, renewal risk forecasting, and automated playbooks with clean, unified health scoring.

How it works

1. Integrate data sources
   Provide metrics from product usage, support tools, surveys, and billing systems.

2. Define signal weighting
   Apply static weights or let the app learn patterns over time with optional ML scoring.

3. Get live scores and diagnostics
   See the current score, trend history, and driver breakdown for each customer or segment.

4. Take action
   Use built-in recommendations to address risks, upsell healthy accounts, or trigger interventions.

What you'll need to provide

To generate meaningful scores, prepare the following:

• Data Sources: (e.g., usage metrics, NPS scores, support ticket stats, payment info)
• Weighting Logic: % importance of each signal
• Segments/Product Lines: (if different logic applies)
• Score Frequency: (e.g., real-time, daily, weekly)
• Threshold Definitions: What constitutes good/poor health?

Who it's for

• SaaS companies managing renewals and expansions
• Customer success teams scaling with automation
• Product leaders needing a unified view of user engagement
• RevOps teams aligning support, billing, and product data