All plans · EUR · closed months through September 2026
Monthly change in recurring revenue, by source
End of month
Share of MRR, September 2026
% of starting MRR retained, by signup month
| Account | MRR | Health | Last login | Status |
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This SaaS metrics dashboard is a working concept on sample data for Planvio, a fictional B2B software company that bills in euros. It covers 24 closed months, October 2024 to September 2026, and opens on what I would want in a monthly revenue review: where MRR came from, where it went and which accounts might leave next.
Six figures sit at the top: MRR, ARR, net revenue retention, average monthly logo churn, ARPA (average revenue per account) and CAC payback in months. Switch between a 6 and a 12 month window and each one recalculates, with the change against the prior window or the month before it.
The main chart splits each month's change in MRR into its four sources. New and expansion revenue stack above zero, contraction and churn hang below it, and a line tracks net new MRR. This is the chart that explains a weaker month. In the sample data, September 2026 had the highest churn of the past year, and a 12-month high in expansion is what kept growth going.
Beside it are month-end MRR as a line and revenue by plan (Starter, Team, Business and Enterprise), with account counts and how each plan's share of MRR moved. Below, a cohort heatmap shows how much of its starting MRR each signup month still brings in, month by month, and an accounts-at-risk table lists six accounts with their MRR, a health score, last login and the reason they were flagged, such as a failed payment or falling usage.
It is a web app written in HTML, CSS and JavaScript, with SVG charts. The page holds one sample dataset of monthly new, expansion, contraction and churn MRR, new and lost accounts, and sales and marketing spend, and everything else is derived from it. Net revenue retention is starting MRR plus expansion, minus contraction and churn, divided by starting MRR. CAC payback is sales and marketing spend divided by new MRR at a 78% gross margin. The page also checks that the plan breakdown adds up to the final MRR and account count, and logs a warning if it does not.
The AI note is filled from the same numbers: net new MRR against the month before, whether churn was the highest in 12 months, whether expansion made up for it, and how many at-risk accounts have a failed payment. In the demo it is a template; for a client, a language model can write the note from the computed figures, so it never has to calculate anything itself.
For your company, I replace the sample data with your billing system and CRM, refreshed on a schedule, with access limited to the people who should see revenue by account. If your reporting runs on Power BI, the same layout can be built there.
A SaaS KPI dashboard is easy to overload. I kept this one to metrics that explain each other: the movements chart explains the MRR line, the cohorts explain net revenue retention, and the at-risk table shows which accounts could make next month's churn bar taller. Pipeline or product usage detail can sit on a page of its own.
I can build a SaaS metrics dashboard like this on your own billing and CRM data. Live dashboards · All examples