A monthly revenue report, without a BI team

What changed and why

Recurring revenue rose €2,336 to €342,458, below the average rise of €2,677 a month over the previous 12 months. Growth slowed on two lines: 141 trials converted to paid, the fewest in 12 months (average 157), and upgrades added €5,720 (average €5,942). Churn was low: 153 customers left, 3.4% of those paying at the start of the month (average 3.6%), and only 2 of them were on Scale. Existing customers paid 0.8% less than in August, so without new and returning customers, revenue would have fallen.

Revenue bridge, August to September

Each line is customers times the change in their monthly price: a Starter customer moving up to Growth adds €70, and a Growth customer who leaves takes €99.

Customers by plan

Every new or returning customer joins Starter, and customers move one plan at a time.

The next 6 months

From the end of September, the model runs 1,000 times. By March 2027, recurring revenue reaches a median €346,600; in 8 runs of 10 it lands between €326,600 and €363,000.

The forecast runs on the company’s rates as the revenue forecast demo sets them, with its churn level uncertain. It has no seasonality and no price changes.

Checks and sign-off

Sign-off. This report is a routine refresh: the same report as every month, on the month’s data. A routine refresh of a signed-off report carries the checks in its method note and no new signature. What the analytics director signs is what you act on, such as a decision memo drawn from the report.

What it reads. Billing or invoicing history per customer, with plan changes and cancellations, from exported files or your warehouse. Where the data goes is set out on data handling.

How it is built. In the first sprint, agents write the report’s queries and its checks. Scripts, not AI, check its numbers and claims, and a review agent checks the work before it reaches you. Each month after that, the report runs again on the month’s data, with the same checks and its method note.

How it arrives. As a document, a notebook or a simple web page like this one. How the forecast inside it is built is on revenue forecasting. The checks to run on any AI-made report are in how to check the numbers in an AI-generated report.

Not covered. Building a data warehouse, or dashboards in Looker or Power BI. The report reads the data where it already is.

Try the forecast. Change the sign-ups, the churn and how sure the company is of it, and watch this report’s forecast move, in the revenue forecast demo.