August 4, 2026
By 
Mike Le

The Sell-Through Rate Formula for eCommerce

The Sell-Through Rate Formula for eCommerce

The sell-through rate formula is units sold divided by units received, times 100. See a worked example, per-period calculations, and the mistakes that throw the number off.

The formula is one line of arithmetic. The part that trips people up is which "units received" you plug in when the stock arrived in three separate shipments. Get the inputs right and the calculation is trivial; get them wrong and a healthy product looks like a failure.

The sell-through rate formula is units sold divided by units received, times 100, measured over a set period. That single line handles most cases. The nuance is in defining the period cleanly and counting received units without double-counting staggered deliveries, which is where most sell-through mistakes actually come from.

Key takeaways

  • The arithmetic is the easy part: the errors live in the inputs, not the division, especially how you count units received.
  • Units received drives everything: count what arrived in the period, and handle staggered shipments without adding the same stock twice.
  • Pick your numerator on purpose: all units sold gives raw sell-through; full-price units only gives the sharper margin read.
  • Per-period sell-through shows pace: weekly and cumulative views tell you how fast a buy is clearing, not just where it ended.

What is the sell-through rate formula?

Sell-through rate equals units sold divided by units received, times 100, calculated over a defined period. Units received is everything you brought in for that period; units sold is what left, before or after markdown depending on which version you want. Written as a line: sell-through % = (units sold / units received) × 100. That is the whole formula, and it works for a single SKU, a category, or a whole buy, as long as the period and the received count are defined consistently on both sides.

The reason the formula still causes trouble is that "units received" is deceptively simple. In a clean case it is one shipment; in the real world it is three partial deliveries across a quarter, and how you count them decides whether your number means anything.

The formula, written out plainly

Take a SKU, pick a window, and gather two numbers: the units you received into stock during (or before) that window, and the units you sold within it. Divide the second by the first and multiply by 100. If you received 400 units and sold 260 in the month, sell-through is (260 / 400) × 100, or 65 percent. The output is always a percentage, which is what makes it comparable across products of very different sizes. A ten-unit artisan run and a ten-thousand-unit basics buy can both be judged on the same 0-to-100 scale, which is the whole point of expressing it as a rate rather than a raw count.

Units received: handling staggered deliveries without double-counting

The most common error is mishandling stock that arrives in waves. If a 500-unit order lands as 200, then 200, then 100 across a quarter, "units received" for a full-quarter sell-through is 500, not 900 and not 200. Count each unit of received stock once, in the period it became available to sell. For a shorter window, only count what had actually arrived by then: measuring week-two sell-through against the full 500 understates the rate badly if only 200 units were on hand. Match the received count to the stock that was genuinely sellable in the window, and the number stays honest. Get this wrong and every downstream comparison inherits the error.

How do you calculate sell-through rate? (worked example)

If you received 500 units and sold 300 in a month, sell-through is 300 divided by 500, times 100, which is 60 percent. The same SKU at 300 sold against 400 received reads 75 percent: same demand, different buy, different verdict. That contrast is the lesson of the metric in one line. The units sold did not change, but the buy did, and sell-through rewards the tighter one because less cash was left sitting in unsold stock.

Walking it step by step makes the mechanics stick, and shows where the full-price version changes the answer.

Four steps, no spreadsheet required:

  • Fix the period: say one month, from receipt.
  • Count units received in the period: 500 units, arrived and sellable.
  • Count units sold in the period: 300 units, net of returns.
  • Divide and scale: (300 / 500) × 100 = 60 percent sell-through.

A 60 percent monthly sell-through on a seasonal buy is usually a healthy pace with room to clear the rest before markdown season. Read against the healthy bands in what is sell-through rate, it says the buy was close to right: not so deep that cash is stuck, not so shallow that you stocked out.

Full-price vs. all-units in the numerator. The formula does not change, but what you count as "sold" does, and it changes the meaning. Put all units sold on top and you get raw sell-through: total velocity, discounts included. Put only units sold at full price on top and you get full-price sell-through, the share that moved at the price you intended. On the same 500-unit buy, 300 total units sold is 60 percent raw, but if 90 of those sold on a markdown, full-price sell-through is 210 / 500, or 42 percent. The gap between the two is the demand you bought with discounts, and why full-price sell-through matters as the margin-honest read.

How do you calculate sell-through per period?

Per-period sell-through restarts the clock each window, weekly or monthly, so a product can show 24 percent in week one and a cumulative 60 percent by week four. That tells you pace, not just the end result. A single season-end number hides whether the buy cleared steadily or sat for a month and then dumped on a promotion. Per-period views make the shape of the sell visible while you can still act on it.

Here is the same 500-unit buy tracked across four weeks, showing both the weekly rate and the running cumulative rate:

  • 1. units received: 500; units sold (week): 120; weekly sell-through: 24%; cumulative sell-through: 24%
  • 2. units received: 500; units sold (week): 90; weekly sell-through: 18%; cumulative sell-through: 42%
  • 3. units received: 500; units sold (week): 55; weekly sell-through: 11%; cumulative sell-through: 53%
  • 4. units received: 500; units sold (week): 35; weekly sell-through: 7%; cumulative sell-through: 60%

The weekly column shows demand cooling as the launch energy fades; the cumulative column shows the buy on track to 60 percent by week four. Both readings come from the same formula, just applied to a different slice of time.

Weekly sell-through divides each week's units sold by units received, so it shows the pace in that window alone. Cumulative sell-through divides total units sold to date by units received, so it shows how much of the buy has cleared overall. Report both, because they answer different questions. Weekly tells you whether demand is accelerating or fading right now, which drives in-season decisions on price and marketing. Cumulative tells you whether the whole buy is on track to clear before markdown, which drives the reorder call. Reporting only the cumulative number hides a stall; reporting only the weekly number hides the finish line.

The formula is trivial to write and tedious to maintain across a live catalog, and a stale sell-through number is worse than none because you will trust it. Conative AI computes sell-through per SKU automatically from your connected sales and receiving data, and goes a step further: it forecasts sell-through forward so you can set a buy against a target rather than discover the result after the season. It scores forecast accuracy per SKU against actual sales, so you watch the forward number sharpen on your own catalog instead of trusting it blind. Because that score is kept per SKU, you can see how reliable that projection is and watch it sharpen as the model learns your catalog. See it work on your own numbers in the platform, or start a free trial.

Frequently asked questions

How do you calculate weekly sell-through rate?

Divide the units sold in that week by the units received, then multiply by 100. If 500 units were received and 90 sold in week two, weekly sell-through is (90 / 500) × 100, or 18 percent. Keep the received figure constant across weeks for one buy, so the weekly rates add up to the cumulative rate as the period progresses.

What units count as 'received' in the formula?

Units received is the stock that arrived and became sellable within the period you are measuring, counted once. For staggered deliveries, add each shipment as it lands, but never double-count. For a short window, only include stock that had actually arrived by then, otherwise you measure sales against inventory that was not yet available and understate the rate.

Can sell-through rate be over 100 percent?

Only if you count units sold from stock received in an earlier period against a smaller current receipt, which usually signals a counting error. Within a clean single-period calculation, sold units cannot exceed received units, so the rate caps at 100 percent. If you see a figure above 100, check whether opening stock or a prior shipment slipped into the sold count but not the received count.

How do you calculate sell-through across multiple SKUs at once?

Sum the units sold across the SKUs, sum the units received across the same SKUs, then divide the totals and multiply by 100. Do not average the individual percentages, because that hides the effect of different buy sizes. A blended rate built from summed units weights each SKU by its actual volume, which is the honest way to read a category or a whole buy.

Should the formula use units sold or revenue?

Use units for sell-through, because the metric measures how much of your physical buy has cleared. Revenue-based versions exist, but mixing prices and discounts into the numerator turns a clean inventory read into a muddier financial one. Keep sell-through in units, and use margin-based metrics separately when you want the money view. Units in, units out, is what keeps the number comparable.

How do markdowns change the sell-through calculation?

Markdowns do not change the formula, but they change which number you should read. Raw sell-through counts discounted units, so a markdown lifts it. Full-price sell-through excludes them, so it stays flat when you clear stock on sale. Track both: a strong raw rate with a weak full-price rate means the product only moves at a discount, which should temper the next buy.

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