The SaaS Revenue Estimator projects monthly and annual recurring revenue from customer count, average subscription revenue, new customers, and churn. It models the next month’s ending customer base and converts that base into a recurring revenue run rate.
This view is useful for planning hiring, infrastructure, sales capacity, and cash needs. Because it uses a simplified blended customer model, it works best for directional scenarios rather than detailed cohort forecasting or revenue recognition.
1. Enter starting customers
Use the active paying-customer count at the beginning of the month.
2. Add expected new customers
Enter accounts expected to become active during the month.
3. Set monthly churn
Use the percentage of starting customers expected to cancel during the month.
4. Enter average revenue
Use blended monthly recurring revenue per active customer.
5. Review the run rate
Check ending customers, ending MRR, and annualized recurring revenue.
Where:
Assumptions: New customers are treated as fully active at the ending run rate, and expansion or contraction revenue inside existing accounts is not modeled separately.
The ARR figure annualizes ending MRR and does not model seasonality or contract timing.
Scenario estimate only; not audited revenue guidance.
Given:
Calculation:
Churned customers = 1,000 × 0.04 = 40
Ending customers = 1,000 − 40 + 90 = 1,050
Ending MRR = 1,050 × $85 = $89,250
ARR run rate = $89,250 × 12 = $1,071,000
Result: $89,250 ending MRR.
The scenario ends the month with 1,050 customers and an annual recurring revenue run rate of $1,071,000.
This simplified model applies churn only to starting customers. A detailed cohort model may apply partial-period churn or activation timing to new customers.
Not necessarily. ARR is a recurring revenue run rate based on ending MRR, while recognized revenue depends on service periods, contract terms, and accounting policy.
They are captured only if you adjust average revenue per customer. A more detailed model would separate expansion MRR, contraction MRR, and customer churn.
The input accepts whole customers, while churn may create a fractional estimate. Treat fractional output as an expected value across a customer population.
Ending customers and MRR decline. Use the result to test how much acquisition, retention improvement, or pricing change is needed to reverse the decline.