Methodology: Sales Forecast Calculator

1. Scope

Projects MRR and cumulative revenue over a fixed horizon using deterministic growth, conversion, and pipeline assumptions. It is not a probabilistic forecast and does not quantify forecast error.

2. Inputs and outputs

Inputs

startingMrr number (currency)
leadsPerMonth number
conversionRate percent
arpuPerCustomer number (currency)
monthlyChurn percent
horizonMonths number default: 12

Outputs

trajectory

Array of monthly MRR, new, churned, and net new MRR.
endingMrr

MRR at the final month.
cumulativeRevenue

Sum of MRR across the horizon.

Engine source: src/lib/sales-forecast-calculator/engine.ts

3. Formula / scoring logic

for m = 1..horizon:
  new_customers = leads_per_month * conversion_rate
  new_mrr       = new_customers * arpu
  churned_mrr   = mrr_{m-1} * monthly_churn
  mrr_m         = mrr_{m-1} + new_mrr - churned_mrr

4. Assumptions

Lead volume and conversion are constant. Ramp periods (new channel launching) require running the tool in segments.
Churn is applied to the prior-month MRR in aggregate; cohort-level retention curves would produce different results.
ARPU is flat — no price changes, no tier upgrades.

5. Data sources

This tool relies on user inputs and standard arithmetic; no external benchmark data is bundled. When a question depends on an industry reference (for example, typical churn rates or hourly-wage medians), the linked adjacent tools cite their primary sources on their own methodology pages.

6. Known limitations

Deterministic, not probabilistic. A ±20% range on any input cascades across the horizon; the tool does not surface that uncertainty.
No seasonality layer. E-commerce and consumer products with Q4 spikes will be off by a meaningful margin.

7. Reproducibility

Input
startingMrr = $500, leads = 200, conv = 2%, arpu = $25, churn = 4%, horizon = 12.

Expected output
endingMrr ≈ $1,700, cumulative ≈ $13,500 over 12 months at baseline inputs.

8. Change log

2026-04-24 methodology page first published.