📊 Sell-Through Rate Calculator

Sell-through rate is units sold divided by units received. Receive 800 units and sell 620, and the sell-through rate is 77.5 percent, with 180 units (22.5 percent) remaining. It is retail’s purest demand signal: what share of what you bought did customers actually want?

Buyers live and die by this number. High sell-through means the buy was right and reorders are safe; low means markdowns loom and open-to-buy is trapped. It is the report card on every assortment decision.

How to Use This Calculator

Enter units received into inventory and units sold in the period. Use the same SKU, category, or store for both, and the same date range.

The Sell-Through Formula

The period matters enormously: 77.5 percent in two weeks is a hit; 77.5 percent in six months is a slow burn. Always pair the rate with the timeframe, and compare like seasons: this December against last December, not against July. Sell-through differs from sell-in (what you bought from vendors); it measures the customer, not the warehouse.

Online and store rates differ structurally: endless-aisle assortments sell through slower per SKU than curated store sets. Benchmark within channel before judging.

Worked Example

800 units received, 620 sold. Sell-through = 620 / 800 = 77.5 percent. Remaining = 180 units, 22.5 percent of the buy. At the current pace of 155 units a week, cover is just over one week: reorder now or face a stockout.

Markdown version: 800 received, 320 sold in 8 weeks = 40 percent. The buy was wrong for the price or the season. Options: mark down 25 percent to accelerate, bundle with a winner, or return to vendor if terms allow. Every week of delay converts potential markdown into deeper markdown; our discount calculator prices the promotion. The lesson for next buy: cut the order 40 percent or fix the product.

Reading the Rate

Context adjusts every band: basics should sell through higher than fashion, and new launches deserve a ramp before judgment. Track sell-through weekly for fashion, monthly for basics, and always against plan, not only against last year. Pair it with safety stock math so winners do not become stockouts: high sell-through without buffer is a different failure.

Open-to-Buy: Planning the Next Purchase

Sell-through tells you what happened; open-to-buy tells you what to do. The OTB formula converts the sales plan into purchase dollars: forecast sales plus markdowns plus desired ending inventory, minus what you already hold. High sell-through on winners argues for bigger OTB next cycle; low sell-through argues for smaller buys and earlier markdowns. The two metrics form the buying loop: sell-through grades the past, OTB budgets the future. Run both monthly and the assortment starts managing itself.

Sell-Through and Cash Flow

Slow sell-through traps cash: every unsold unit is money that cannot fund the next buy. A category at 40 percent sell-through with $200,000 tied up in remainder stock is a $120,000 interest-free loan to the warehouse. Markdowns feel like losses, but they convert dead stock to cash that funds winners. The fastest-growing retailers mark down aggressively and reinvest instantly; the slowest nurse losers at full price.

Measure inventory productivity alongside sell-through: GMROI, gross margin return on inventory investment, combines margin and turn into one dollars-out-per-dollar-in number. High sell-through at deep markdowns can still produce poor GMROI; moderate sell-through at full price can produce excellent GMROI. The trio, sell-through, markdown rate, GMROI, tells the complete trading story. Cash released is opportunity created.

Sell-Through in E-commerce

Online sell-through runs lower per SKU because assortments are wider: a thousand SKUs at 40 percent can outsell a hundred at 80 percent. Judge e-commerce sell-through against the channel’s own history and against traffic: low sell-through with high traffic is a conversion problem, low sell-through with low traffic is a demand problem. Different diagnoses, different cures.

The e-commerce advantage is speed of read: daily sell-through data lets buyers react in days, not seasons. Set automated alerts at thresholds: below 20 percent in week two flags a dog, above 60 percent flags a reorder. The winners in online retail are not better guessers; they are faster reactors. Data velocity is the edge.

Estimates for planning only, not financial advice.