Sell-through rate answers one question: of everything we made available, how much has actually sold? It sounds trivial until two people in the same meeting quote different numbers — usually because one divides by units received and the other by units received plus opening stock.
Sell-Through Rate Definition Used in Retail Reporting
Pick one definition per brand, write it down, and put it in the report description. The version below divides net sales units by total units made available in the period.
DAX Measures for Sell-Through Rate in Power BI
Three measures: net units, available units, and the ratio. Keeping them separate makes the number auditable — and lets you show both denominators side by side while the definition is being agreed.
Net Units :=
SUM ( Sales[Units] ) - SUM ( Sales[ReturnUnits] )
Available Units :=
CALCULATE (
SUM ( Stock[OpeningUnits] ) + SUM ( Receipts[Units] ),
REMOVEFILTERS ( 'Date'[Week] )
)
Sell-Through % :=
DIVIDE ( [Net Units], [Available Units] )Weekly Sell-Through Curve in a Retail Dashboard
A single percentage tells you little. The curve — cumulative sell-through by week, against last season — is what makes people act: too flat and the buy was too deep, too steep and you will be out of size before the season ends.
| Category | Units received | Sell-through, wk 8 | Gross margin |
|---|---|---|---|
| Dresses | 1,240 | 68% | 42% |
| Knitwear | 980 | 54% | 38% |
| Denim | 1,510 | 74% | 47% |
| Outerwear | 640 | 39% | 31% |
| Accessories | 720 | 61% | 55% |
| Footwear | 560 | 33% | 29% |
Common Sell-Through Calculation Mistakes in Power BI
- Filtering the denominator by week, so availability resets every week and the curve looks flat.
- Leaving returns in sales units, which inflates sell-through in categories with high return rates.
- Mixing markets with different season start weeks in one cumulative view.