Inventory glossary

What is Seasonal index?

Seasonal index is a number that shows how much a product's demand in a given period is above or below its yearly average, used to adjust forecasts for predictable ups and downs across the year.

If a Shopify store sells more candles in November and December and less in summer, a flat average will underorder before the holidays and overorder after. A seasonal index lets you adjust each month's forecast up or down based on past patterns, instead of treating every month the same.

To use it, you take past sales for a period, divide by the average sales across all periods, and get a multiplier. A value above 1 means demand is higher than average that period, below 1 means lower. You multiply your baseline forecast by this index to get an adjusted forecast for that month.

Formula

Seasonal index = Average demand in period / Average demand across all periods

Example

A candle store sells 1,200 units a year, averaging 100 units a month. In December they sold 250 units last year. Seasonal index for December = 250 / 100 = 2.5. If the baseline forecast for next December is 100 units, the adjusted forecast is 100 x 2.5 = 250 units.

Common mistakes

  • Using only one year of data, which can mistake a one-off spike for a seasonal pattern.
  • Applying the same seasonal index to every product, when different SKUs peak at different times.
  • Forgetting to update the index as sales patterns shift over time, especially for newer products with short histories.

Seasonal index and SteadyShelf

SteadyShelf's forecasting looks at each variant's own sales history, including seasonal swings, to set order-by dates and quantities rather than relying on 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 · Moving average forecast · Forecast accuracy · Demand variability

Full inventory glossary

FAQ

Why does a seasonal index matter for reordering?

Because it stops you from using a flat yearly average that underorders before peak months and overorders right after them, which leads to either stockouts or excess stock.

How many years of data do you need to calculate a reliable seasonal index?

There is no fixed rule, but more than one year is better since a single year can mix in one-off events with the true seasonal pattern.

Let SteadyShelf do this math for every SKU

Order-by dates per supplier, seasonal forecasts and draft POs for your Shopify store. $29/month after a 30-day free trial.

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