Where SaaS finance gets hard
Early on, a spreadsheet and a billing system export are enough. Then the invoice volume grows, pricing gets more complex, annual contracts arrive with mid-term upgrades, and an investor asks for cohort retention by segment. The spreadsheet breaks, the billing system's reports do not answer the question, and the finance lead spends the week before each board meeting reconciling three versions of MRR.
Meanwhile revenue recognition becomes a monthly risk, the forecast is a growth rate applied to last month, and the metrics in the deck cannot be traced back to the ledger. Diligence, when it comes, finds the gaps.
What we build for subscription businesses
- SaaS metrics from invoice-level data: MRR and ARR bridges, gross and net churn, net revenue retention, cohorts, lifetime value, acquisition cost and payback
- Revenue recognition automation under IFRS 15 and FRS 102, with deferred revenue schedules generated from billing data
- SaaS FP&A: driver-based forecasts built from pipeline, retention curves and pricing, with scenario planning for hiring and spend
- Board and investor reporting packs that present the SaaS metrics alongside the financials, reconciled
- Billing, CRM and accounting integration: Stripe, Chargebee or Recurly connected to Xero, QuickBooks or NetSuite and to HubSpot or Salesforce
- Cash flow forecasting that accounts for annual-in-advance billing, collections and runway
- Access to our Revenue Intelligence platform for invoice-level recognition, lifecycle classification and churn forecasting
Metrics that survive diligence
An investor's diligence team will rebuild your MRR from invoices and compare it with your deck. We build your metrics the same way, from the same data, with every definition written down and every movement traceable. When the questions come, the answers are already there.
Forecasting a business that is mostly under contract
A SaaS forecast is dominated by two things: how much of the existing base renews and expands, and how fast new business lands. We model the first from lifecycle data, applying retention curves by cohort and segment rather than one blended churn rate, and the second from pipeline and conversion history. The result is a forecast that explains itself and that the board can interrogate line by line.
This is also the problem our Revenue Intelligence platform is built to solve at scale: invoice-level revenue recognition, lifecycle classification of every customer, and multidimensional churn and retention forecasting. Subscription businesses working with us on consultancy are the first to be offered pilot access.
Who we work with
B2B and B2C SaaS, subscription and membership businesses from around £1m ARR to £30m ARR, typically between seed and Series B or under private equity ownership, and the investors and portfolio finance teams around them.
If your SaaS metrics do not reconcile to your ledger, or your forecast is a growth rate rather than a model, start a conversation with us.
Good questions, straight answers
We are pre-Series A. Is this too early?
If you have a few hundred invoices a month and a board that asks about retention, it is the right time. Getting the metrics and revenue recognition right early is far cheaper than rebuilding them during a fundraise.
Do you replace our billing system's reporting?
We build on top of it. Billing systems are good at collecting money and poor at classifying revenue movements consistently. We take the invoice-level data and build the metrics, recognition and forecasts that the billing reports cannot provide.
How do we get access to the Revenue Intelligence platform?
The platform is patent pending and running as a pilot programme. Subscription businesses working with us are offered pilot access first. Ask about it through the enquiry form or on the platform page.
The services behind this work
- SaaS and subscription analytics
MRR, ARR, churn, cohorts, retention forecasting and revenue recognition, built from invoice-level data. Investor-ready subscription metrics that reconcile to the ledger, and the foundation for our Revenue Intelligence platform.
- FP&A and XP&A
Budgeting, rolling forecasts, driver-based models and board reporting, delivered as a fractional FP&A function. Extended into XP&A so sales, operations and people plans tie back to one set of numbers.
- Finance automation and data engineering
ETL and system integration for finance, automated reconciliations and a month-end that runs on pipelines rather than people. The data foundation that makes reporting, planning and AI possible.
- Business intelligence
Power BI and custom dashboards for finance: management reporting, semantic models and the data engineering beneath them. Reporting that reconciles to the ledger and refreshes without anyone re-keying a number.