What is Seasonal forecasting?

For a small Shopify store, ignoring seasonality leads to the same mistakes every year: running out of stock right before your busiest month, or sitting on excess inventory after demand drops. Seasonal forecasting helps you plan purchase quantities and order timing around patterns you already know exist, like a spike in candle sales before winter holidays or a drop in apparel sales in summer.

To use it well, look at what happened in the same period last year or the year before, not just last month. If your store is new and has no history, start with a reasonable guess based on the category and adjust as real sales come in.

Formula

Example

A candle shop sold 100 units per month on average last year, but sold 300 units in November. The seasonal index for November is 300 / 100 = 3. If the store expects to sell 150 units per month on average this year, it should plan for roughly 150 x 3 = 450 units in November.

Common mistakes

• Using only last month's sales to predict a seasonal spike, instead of looking at the same period in prior years.
• Treating a one-time promotion or viral moment as a seasonal pattern.
• Forgetting to adjust supplier order timing earlier, since lead times mean you must order weeks or months before the seasonal spike hits.

Seasonal forecasting and SteadyShelf

SteadyShelf's demand forecasts factor in each variant's sales history so order-by dates and quantities reflect seasonal patterns rather than a flat average.

SteadyShelf is launching on the Shopify App Store. Join early access to get the install link first.

Related terms

Demand forecasting · Seasonality · Seasonal index · Moving average forecast · Lead time demand

Full inventory glossary

FAQ