Most SaaS metrics dashboards are built for board meetings, not daily decisions.
When your data lives in Stripe (billing), Postgres (product), HubSpot (CRM), and BigQuery (warehouse), you can build a metrics dashboard that answers the questions your team asks every week: Are we growing? Are we retaining customers? Are we profitable? Where should we invest next?
The 4 metrics that matter (and how to calculate them)
1. MRR Growth
MRR growth comes from multiple sources tracked in Stripe. New MRR comes from new subscriptions, while expansion MRR includes upgrades and add-ons that increase customer value. Contraction MRR captures downgrades that reduce revenue, and churn MRR reflects cancellations. Your net MRR is simply New plus Expansion minus Contraction minus Churn, giving you the true growth rate.
2. Customer Health
Customer health combines signals from multiple systems. Track active users from Postgres by counting users active in the last 30 days. Monitor feature adoption by seeing which key features your customers actually use. Watch support ticket volume and resolution times from HubSpot to identify product issues early. Finally, monitor billing health from Stripe by tracking payment failures that indicate customer satisfaction problems.
3. Unit Economics
Unit economics tell you if your business model works. Calculate CAC from HubSpot by dividing marketing spend by new customers acquired. Calculate LTV from Stripe by multiplying average revenue per customer by retention rate. Your payback period is CAC divided by MRR per customer, showing how long until you recover acquisition costs. Aim for an LTV to CAC ratio greater than 3 to 1, ensuring healthy unit economics.
4. Pipeline Health
Pipeline health metrics from HubSpot show your sales engine’s performance. Track pipeline created by counting new deals entered into your system. Monitor pipeline velocity by measuring time to close, identifying bottlenecks in your sales process. Calculate win rate by dividing won deals by won plus lost deals. Finally, track revenue per deal to understand average deal size and identify opportunities to increase value.
What to build first (week 1)
Start with a simple weekly metrics dashboard that tracks MRR trends including new, expansion, contraction, and churn. Add customer count metrics showing new customers, churned customers, and total customers over time. Include pipeline metrics that show deals created, deals won, and pipeline velocity. Finally, display unit economics including CAC, LTV, and payback period so you can see if your business model is working.
Once you have these core metrics, add cohort retention analysis broken down by signup month to see how retention improves over time. Add revenue by plan to understand which plan tiers drive the most value. Finally, add churn analysis by segment, breaking down churn by plan tier, usage patterns, and support interactions to identify at-risk customers early.
Why most metrics dashboards fail
Most metrics dashboards fail because data is stale, updated monthly instead of daily, making it too slow for real-time decision making. Definitions drift over time as MRR means different things in different tools, leading to inconsistent calculations. Context is missing when dashboards show current numbers without comparison to last week, last month, or last quarter, making it impossible to understand trends. Actionability is low when dashboards show what happened but don’t indicate what to do about it.
With our managed data platform, metrics update automatically as new data arrives, so your team can make decisions based on current numbers rather than last month’s spreadsheet.
The hidden cost of manual metrics
When metrics are calculated manually, they’re updated monthly which is too slow for making timely decisions. They’re inconsistent because different definitions exist in different tools, leading to confusion about which numbers to trust. They’re error-prone as formulas break when data structures change, requiring constant maintenance. Most importantly, they’re not actionable because they show what happened without indicating what to do about it.
Automated metrics mean you can see trends as they happen rather than waiting until month-end. You can make decisions based on current data instead of outdated information. You can trust the numbers because definitions are consistent across all calculations. Most importantly, you can act faster without waiting for monthly reports to understand what’s happening in your business.