Preloaded with three years of a seasonal retail revenue curve — swap it for your own store's numbers and get a forecast that actually accounts for your yearly cycle.
Retail rarely moves in a straight line — holiday quarters, back-to-school, and category-specific peaks repeat every year. With two or more years of monthly history, Salesdamus backtests a seasonal model against a plain trend and keeps whichever one actually predicted your recent months better, instead of assuming this December will look like an average month.
Shorter history still works — you'll just get a trend-only forecast until you have enough data for the seasonal pattern to backtest reliably.
Paste from Excel (Ctrl+V), import a CSV, or load an example
| MONTH ? | SALES ? | EXPENSES ? | CONVERSION % ? | |
|---|---|---|---|---|
How many future periods to project. Confidence intervals widen further out.
Press to launch forecast
Have a target? See what growth rate it actually needs — checked against your real history.
Forecast total revenue across locations, or run it separately per store — paste whichever series you want projected. It doesn't combine multiple series into one model automatically.
Two full years is the practical minimum; three or more makes the backtest — and the model choice it produces — noticeably more stable.