Revenue Forecast Calculator

What counts as revenue (and what doesn’t)

Revenue is your total sales for a period before any expenses — the top line, not profit. Keep sales tax out of it: the tax you collect at checkout is remitted to the state and never belongs to the business, so a $108 sale in a 8 % jurisdiction contributes $100 of revenue. If you report on an accrual basis (GAAP), count revenue when it is earned; on a cash basis, when it is received — either works here, as long as your history is consistent.

Enter the same monthly series you track in your books. Twelve months of history is ideal: enough for the regression and smoothing methods to detect a trend, and a full seasonal cycle for the seasonal method.

The six forecasting methods, in plain English

• Straight-line growth — applies a fixed monthly growth rate to your latest month. Best when growth is steady or you are projecting to a target.
• Moving average — averages your recent months and rolls that forward. Best for stable businesses with noisy month-to-month numbers.
• Linear regression — fits a trend line through all your history (the math behind Excel’s FORECAST function) and extends it. Best with 6+ months of consistent trend.
• Exponential smoothing — weights recent months more heavily, so it reacts faster when momentum shifts. Best when conditions changed recently.
• Seasonal forecast — multiplies a growth path by monthly seasonal indices (holiday-season retail peak, summer tourism peak). Best when your December looks nothing like your February.
• Run rate — holds your average month flat: average monthly revenue × months. The classic conservative baseline, and how startups quote “annualized run rate” (ARR).

Top-down vs bottom-up projections

Everything above is bottom-up: built from your own trading data. Top-down starts from total market size (“the US market is $5B; we capture 0.1 %”) — fast, but investors discount it heavily because the market-share assumption is unfalsifiable. The credible pattern is bottom-up from history (or, pre-revenue, from capacity: leads × close rate × average contract value), sanity-checked top-down. If your bottom-up projection implies you own half your local market by month 12, one of the two is wrong.

Worked example: a 12-month projection in dollars

Say last month’s revenue was $12,000, your history supports about 3 % monthly growth, and you project 12 months with the straight-line method:

1. Month 1: $12,000 × 1.03 = $12,360
2. Month 2: $12,360 × 1.03 = $12,731
3. Month 12: $12,000 × 1.03¹² ≈ $17,109
4. Total projected revenue for the year ≈ $175,400
5. With a ±15 % scenario band, month 12 lands between about $14,500 (worst case) and $19,700 (best case) — budget expenses against the worst case.

Realistic growth benchmarks for US small businesses

Established US small businesses typically grow revenue at low-to-mid single digits annually: retail 2–5 %, professional services 4–8 %, e-commerce and SaaS commonly 10–30 %+ while scaling. Compounding hides aggression: 3 % monthly is 43 % a year, and 10 % monthly triples your business annually — fine for a seed-stage startup’s upside case, reckless as a baseline. Forecast with a base case you would bet payroll on, and let the optimistic band carry the ambition.

US specifics: fiscal years, taxes and where to get your data

Most US small businesses report on the calendar year, though corporations may elect a different fiscal year — the forecaster labels rows by calendar month, which matches how QuickBooks, Stripe and Square export monthly revenue. Pull your trailing-twelve-months report from any of them and paste the numbers straight in.

Keep projections consistent with how you file: sales tax excluded, refunds netted out, and one accounting basis throughout. If you sell subscriptions, forecast MRR here the same way — the run-rate method is exactly the “current MRR × 12” convention, and the growth methods model expansion on top.