What is MAPE?

For a small Shopify store, MAPE tells you whether you should trust your forecast numbers or treat them as rough guesses. If a product's MAPE is low, your forecast for that SKU has been reliable and you can order closer to the predicted amount. If it's high, you should add more safety stock or review the forecast method, because past forecasts for that item have been unreliable.

Use MAPE by checking it per product or product group, not just as one store-wide number. A candle scent that sells steadily will usually have a lower MAPE than a new apparel print that nobody has sales history for. Track it over a few months so one bad month does not skew your view of a SKU's predictability.

Formula

Example

A candle store forecasted 100 units of a vanilla candle in January but sold 120. The error is |120-100|/120 = 0.1667, or 16.67%. In February it forecasted 90 and sold 95, an error of |95-90|/95 = 5.26%. The MAPE across the two months is (16.67% + 5.26%) / 2 = about 10.97%.

Common mistakes

• Calculating MAPE on a SKU with very low or zero actual sales, which produces a misleadingly huge or undefined percentage.
• Looking at one month's MAPE and assuming it applies to every product, when accuracy varies a lot between fast sellers and slow sellers.
• Using MAPE alone without checking whether errors are consistently too high or too low, which hides a pattern a simple average would miss.

MAPE and SteadyShelf

SteadyShelf's forecasts per variant become more useful to you when you track MAPE over time, since it shows which SKUs you can trust for tighter ordering and which ones need extra buffer stock.

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

Related terms

Demand forecasting · Forecast accuracy · Forecast bias · Standard deviation of demand · Moving average forecast

Full inventory glossary

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