My client had multiple entities and currencies, with years of monthly recurring revenue sitting in spreadsheets. The data was there — what was missing was structure. No one had ever classified the revenue by movement type. There was no way to answer basic investor questions like "what's your GRR?" or "what's your logo retention rate?"
The business had been growing, but nobody could say with confidence whether existing customers were expanding, contracting, or churning — or by how much. This is common for SaaS businesses between £0.5M and £5M ARR: the bookkeeping is done, the revenue is tracked, but the subscription-specific metrics that investors and board members expect simply don't exist yet.
We went through every customer, month by month, and classified each revenue movement into its correct category.
First-time revenue from a brand new customer entering the base.
Existing customers spending more — upgrades, additional seats, new modules.
Contractual or renewal-driven increases, separated from organic expansion.
Existing customers spending less — downgrades or reduced usage.
Customers who stopped paying entirely and left the base.
Previously churned customers returning to the product.
From that classification, we built the full MRR waterfall: beginning balance, movements by category, ending balance — all reconciled back to the general ledger so the numbers were defensible and auditable.
Every figure ties back to the source data. No black boxes, no unexplained variances — just a clean, auditable trail from raw revenue to investor-ready metrics.
With the waterfall in place, we layered on the four core SaaS metrics that come up in every investor and board conversation.
How much revenue is retained from existing customers before any expansion. The floor of your retention story.
Revenue retained including expansion. Above 100% means your existing customer base is growing on its own — the holy grail for SaaS.
The percentage of customers (not revenue) retained period over period. Tells a different story from revenue retention alone.
Average Revenue Per Account tracked over time — shows whether deal sizes are growing and whether the business is moving upmarket.
Each metric was calculated with trailing 3-month, 6-month, and 12-month windows so you could see the trend, not just a snapshot.
A single data point tells you where you are. A trend tells you where you're going. Each metric was calculated across three rolling windows to surface the full picture.
Short-term signal. Catches recent shifts in expansion or churn before they compound.
Medium-term view. Smooths out seasonal noise and one-off movements.
The investor benchmark. The standard window used in fundraising conversations and board packs.
The client went from not being able to answer "what's your net revenue retention?" to having investor-ready metrics updated monthly with a full audit trail. When they next speak to investors or board members, the numbers are there, they're accurate, and they tell a clear story about the health of the recurring revenue base.
The first build takes time — this was months of historical data across multiple entities and currencies. But the real value is what happens next.
Monthly MRR data is added to the model as it arrives.
Every movement is classified consistently using the same logic as the historical build.
GRR, NRR, logo retention, and ARPA all refresh automatically across all trailing windows.
Numbers tie back to the general ledger. No manual rework, no one-off spreadsheets.
This engagement is relevant for SaaS businesses that have recurring revenue data but haven't yet structured it for investor or board reporting.
Particularly valuable before a fundraise, when investors will ask detailed questions about retention, expansion, and churn that you need to answer with confidence.
When onboarding a new board member who expects structured SaaS metrics as a baseline for governance and strategic discussion.
When the business reaches a stage where understanding retention and expansion at a granular level becomes critical to growth decisions.
If you have the revenue data but not the metrics, book an intro call and let's talk about building the analysis for your business.
How do you calculate net revenue retention when your data has never been structured?