Build SaaS Metrics Dashboards

Defines, calculates, and visualizes the core SaaS metrics that drive subscription business decisions: Monthly and Annual Recurring Revenue tracked by new, expansion, contraction, and churned movement, Customer Acquisition Cost, Customer Lifetime Value, an LTV:CAC ratio that should sit at 3:1 or higher for healthy unit economics, monthly churn rate, and Net Revenue Retention measuring expansion against churn within existing cohorts. A worked MRR-movement SQL query buckets subscription changes by month into new, expansion, contraction, and churned components summed into net-new MRR, and an accurate churn-rate query specifically avoids the common pitfall of a naive denominator by joining a start-of-month customer count against that same month's churned-customer count. Customer health scoring is computed as a weighted 100-point score across four factors: usage ratio worth up to 40 points, payment-delay history worth up to 20, recent support ticket volume worth up to 20 and inverted so fewer tickets scores higher, and feature adoption rate worth up to 20.

Dashboard architecture follows a five-tier hierarchy: top KPIs (MRR, ARR, customer count, churn rate), growth trends (an MRR waterfall chart, an acquisition funnel), cohort analysis (retention curves, customer lifecycle), operational metrics (CAC payback period, support ticket trends), and segmentation by plan type, customer size, and region - matched to specific chart types: waterfall charts for MRR movement, cohort heatmaps for retention, line charts for trends, funnel charts for conversion, and scatter plots for CAC-versus-LTV correlation. An alert framework defines warning and critical thresholds:

const alertThresholds = {
  monthlyChurnRate: { warning: 5, critical: 8 },
  ltvcacRatio: { warning: 2.5, critical: 2.0 },
  mrrGrowthRate: { warning: -5, critical: -10 },
  customerHealthScore: { warning: 60, critical: 40 }
};

evaluated against live metrics to generate leveled alerts. Segmentation models split customers by ARR tier (SMB under $10K, mid-market $10K-$100K, enterprise over $100K), by usage (power, regular, at-risk), and by lifecycle stage (onboarding, active, expansion-ready, churn-risk).

Use it when building or refining a SaaS metrics dashboard, defining or auditing metric calculations, or designing stakeholder-specific reporting views. Revenue recognition follows accrual-based accounting, with one-time fees separated from recurring revenue, mid-month upgrades and downgrades prorated, and deferred revenue tracked for annual subscriptions. Stakeholder-specific views are recommended over one generic dashboard: a high-level CEO view, pipeline and conversion metrics for sales leadership, health scores and churn prediction for customer success, revenue recognition and forecasting for finance, and feature adoption and usage for product. The data pipeline runs ETL from CRM, billing, and product analytics into a centralized warehouse layer, with stream processing for real-time updates and validation rules for anomaly detection.

Takes raw billing, CRM, and product-usage data; produces core SaaS KPIs, cohort and health-score analyses, stakeholder-specific dashboard views, and threshold-based alerts for churn, LTV:CAC, and MRR growth degradation.

SaaS operators, finance, and customer success teams who need accurate, well-modeled recurring-revenue metrics and dashboards rather than vanity metrics or naive calculations that hide real churn.