Sell-through rate tells you how much of the stock you had has been sold. This guide gives the formula, a worked example, the reason it matters and the mistakes that make the number misleading.
What sell-through rate is
Sell-through rate is the share of your available stock that sold during a period, shown as a percentage. A high rate means stock is moving. A low rate means units are sitting. Shopify's inventory reports define it as the total quantity of items sold divided by the total quantity sold plus the total quantity still in inventory.
- Units sold: Units sold in the period
- Units remaining: Units still in stock at the end of the period
- Sell-through rate: Units sold ÷ (units sold + units remaining) × 100
A concrete example
You start the month with 200 units of a scarf and do not restock. By the end of the month you have sold 120 and 80 are left.
| Step | Number |
|---|---|
| Units sold | 120 |
| Units remaining | 80 |
| Sold plus remaining | 200 |
| Sell-through rate | 120 ÷ 200 = 60% |
Now take a second scarf: 200 units at the start, 30 sold, 170 left. That is 30 ÷ 200, or 15%. Same starting stock, very different result.
Why it matters for a store
Sales alone do not tell you whether you bought the right amount. Sell-through compares what sold with what you had, which makes it useful for buying decisions.
- Reordering: A fast-moving product may run out before the next delivery
- Markdowns: A slow-moving product may need a price change or a bundle
- Buying: Comparing rates across products shows where you over-ordered
Common mistakes
The rate is easy to calculate and easy to misread. There is no single good number, because it depends on the product, the season and how long the period is.
- ❌ Comparing a 7-day rate for one product with a 30-day rate for another
- ❌ Reading a high rate as good news when the product sold out and lost sales
- ❌ Ignoring restocks that arrived partway through the period
- ❌ Judging a seasonal item on an off-season month
- ✅ Using the same period for every product you compare
Sell-through pairs well with speed of sale, so see how to calculate sales velocity. For the products at the bottom of the list, see how to find and clear dead stock.
Doing this at scale
StockSense forecasts per-SKU demand from your order history using velocity, trend, seasonality and lead-time-aware safety stock. It recommends a reorder point, quantity and date, ranks SKUs by revenue at risk, and drafts purchase orders grouped by supplier. See StockSense.