Sell-through rate is the share of the stock you had available that actually sold in a given period. The basic formula is units sold ÷ units received × 100: receive 600 sweaters, sell 333 in eight weeks, and your eight-week sell-through is 55.5%. It answers one question buyers and e-commerce managers ask every week: how much of what we bought has turned into sales?
The number is simple, but it only becomes useful once you fix three things: which denominator you use, which period you measure, and at what level you read it. A style-level rate of 55% can hide a size that sold out in week three and a color that will still be on the shelf in spring. This guide covers the formula and its variants, worked examples (illustrative numbers), how sell-through differs from inventory turnover and the stock-to-sales ratio, and how to read it per attribute and per channel so it drives reorders, markdowns and range cuts.
Sell-through rate formula and the three denominators in use
Every source agrees on the numerator: units sold in the period. They disagree on what you divide by, and that difference changes the result more than most people expect:
- Units received: units sold ÷ units received in the period × 100. The worked example in Shopify's sell-through guide uses it: order 1,000 cupcakes for the month, sell 800, and the rate is 80%. It fits product drops and seasonal buys where all stock arrives at the start.
- Beginning inventory plus receipts: units sold ÷ (beginning inventory + units received) × 100. Klipfolio uses this form. It works for items that carry stock over from one period into the next.
- Sold plus what is left: Shopify's Products by sell-through rate report divides units sold by units sold plus units still in inventory, per variant, over the most recent 30 days. If no units went missing or came back, this equals the second formula.
Pick one definition per business, write it down and use it in every report, or a buyer and a marketer will argue about two numbers that are both correct. The table shows why, using one black merino sock variant over one month: 200 pairs in stock on the first day, 100 pairs received mid-month, 180 sold and 120 left at the end.
One sock variant, four sell-through rates
| Units received | Sold ÷ received | 180 ÷ 100 | 180% |
|---|---|---|---|
| Beginning stock only | Sold ÷ beginning stock | 180 ÷ 200 | 90% |
| Beginning stock + receipts | Sold ÷ (beginning + received) | 180 ÷ 300 | 60% |
| Sold + ending stock (Shopify) | Sold ÷ (sold + ending) | 180 ÷ 300 | 60% |
The receipts-only result of 180% is not an error in arithmetic; it is the wrong formula for a replenished item. Use units received for one-off buys that start from zero, and beginning stock plus receipts for everything you carry over. A rate above 100% is a signal that the denominator is missing stock, not that you sold more than you had.
Weekly, monthly or season-to-date: choosing the measurement window
The period decides what the number can tell you. Three windows cover most needs:
- Weekly sell-through (units sold this week ÷ units available at the start of the week) shows momentum. It is the early warning for a launch or a promotion, and it drops naturally as stock runs down, so compare it with the same week of a comparable style rather than with last week.
- Monthly or rolling 30 days suits replenished core items. Shopify's report uses the most recent 30-day period, with a processing delay of about two days.
- Season-to-date (cumulative units sold ÷ total units bought for the season) is the number for seasonal buys and capsules. Read it against a plan curve: how far along you expected to be by this week.
A plan curve is the most useful thing you can add to a sell-through report. Decide before launch what cumulative sell-through you expect by each week, then compare. The chart below plots the illustrative merino sweater style from the next section against a plan of 75% by week 8.
Season-to-date sell-through: merino crew sweater vs plan
Illustrative example| Week of season | Actual | Plan |
|---|---|---|
| Wk 1 | 8% | 10% |
| Wk 2 | 16% | 20% |
| Wk 3 | 24% | 30% |
| Wk 4 | 31% | 40% |
| Wk 5 | 38% | 50% |
| Wk 6 | 44% | 60% |
| Wk 7 | 50% | 68% |
| Wk 8 | 55.5% | 75% |
Worked example: one merino sweater read by size and by color
Take an illustrative crew-neck merino sweater bought for a 14-week autumn season: 600 units in three colors and four sizes, all received before launch. After eight weeks, 333 units have sold. Season-to-date sell-through is 333 ÷ 600 = 55.5%, which looks like a mildly slow style. Split by attribute, it is two different stories.
Merino crew sweater after 8 weeks, by size and color
| Size | S | 120 | 54 | 45% |
| Size | M | 180 | 117 | 65% |
| Size | L | 180 | 126 | 70% |
| Size | XL | 120 | 36 | 30% |
| Color | Navy | 240 | 168 | 70% |
| Color | Grey | 210 | 105 | 50% |
| Color | Mustard | 150 | 60 | 40% |
| Style total | All | 600 | 333 | 55.5% |
Three readings follow from the split. Size L and navy are selling at 70%, so the navy L variant is likely to sell out well before week 14 and is worth a reorder if the supplier can deliver in time. XL is at 30%, which points to a size curve that was bought too wide at the top, a lesson for next season's buy rather than something to fix now. Mustard at 40% is the markdown candidate.
The same split works for any attribute that describes a buying decision: material (merino vs cotton blend), fit, price band, sleeve length, pack size, or for hard goods the capacity or wattage. The assortment planning guide shows how to group styles into cells by these attributes and find gaps; sell-through is the performance figure you put in each cell.
Sell-through vs inventory turnover vs stock-to-sales ratio
These three metrics get mixed up because they all describe how fast stock moves. They answer different questions:
- Sell-through rate counts units, for a chosen period and usually per style or variant: how much of the stock you had has sold. It is the buyer's metric for reorders and markdowns.
- Inventory turnover is cost of goods sold ÷ average inventory value at cost, usually over a year: how many times you sold through and replaced your stock. Days inventory outstanding is 365 ÷ turnover, so a turnover of 4.0 means about 91 days. The inventory turnover calculator works both out. It is a finance and cash metric, read at category or company level.
- Stock-to-sales ratio is stock at the start of a period ÷ sales in that period, in units or retail value, usually per month. A ratio of 4 means four months of stock at the current rate of sale.
- Weeks of supply is units on hand ÷ average weekly units sold. It is the forward-looking twin of sell-through and the number you compare with the weeks left in the season.
The metrics convert into each other when nothing is received during the period. A monthly stock-to-sales ratio of 4 means you sold a quarter of your opening stock that month, which is a monthly sell-through of 25%. A style at 90% sell-through can still sit in a category with a weak turnover if the rest of the category is overbought, which is why buyers look at both levels.
Sell-through per sales channel: shared stock vs allocated stock
Per-channel sell-through only means something when each channel has its own stock. If your webshop and a marketplace draw from one warehouse pool, there is no channel denominator: report each channel's share of units sold instead, and keep sell-through at the variant level.
Allocated stock is different. Units you send into a marketplace's fulfillment program, a retailer on consignment or a physical store are committed to that channel. Back to the sweater: 500 units stayed in your own warehouse for the webshop and 287 sold (57.4%), while 100 units went to a marketplace fulfillment warehouse and 46 sold (46%). The lower marketplace rate is a real problem, because moving units back costs money. Check the listing before blaming demand: a missing size chart, a weak title or a wrong category on the marketplace depresses sell-through as surely as a bad color choice.
Turning the read into reorders, markdowns and range cuts
Sell-through becomes a decision when you put it next to weeks of supply and the weeks left in the season. In the sweater example, six weeks remain at week 8:
- Navy: 72 units left, selling about 18 a week, so 4 weeks of supply against 6 weeks left. Reorder the fastest sizes if lead time allows, and do not discount.
- Mustard: 90 units left, selling about 6 a week over the last two weeks, so 15 weeks of supply against 6 left. Plan a markdown now, while there is still time for a second step.
- XL across colors: 84 units left at a few units a week. A markdown on XL alone rarely works, because shoppers who need XL are already buying it. Hold, then clear at season end, and cut the XL share in the next buy.
- Repeat losers: a variant that misses plan two seasons in a row is a candidate to drop. The SKU rationalization guide covers how to decide and how to retire it without breaking feeds and links.
Work out what a markdown does to margin before you set it. At an illustrative EUR 89 price and EUR 34 cost, a 30% markdown to EUR 62.30 cuts the margin per unit from EUR 55 to EUR 28.30, which still beats holding the stock into next year. The markup vs margin post explains why a 30% markdown removes far more than 30% of the margin, and the contribution margin guide adds the fees, shipping and returns that still come off each marked-down sale. In the EU, also record the lowest price of the 30 days before the reduction: it is the prior price you have to show next to the markdown.
What counts as a good sell-through rate
No cross-industry benchmark is backed by published data, and the targets that circulate differ by source. Shopify's guide gives 70% to 80% as a quick gut-check for in-period assortments, more than 80% within the launch window for seasonal drops, and 40% to 60% per month or quarter for core products, and labels its category figures illustrative. Klipfolio treats below 20% as a common point for concern and warns that above 80% may mean you are running lean and risking stockouts. Neither cites a study.
The useful part is the split Shopify makes: a seasonal buy and a replenished core item need different targets, because one cannot be reordered and the other is meant to be. Beyond that, the better benchmark is your own plan and history. Compare a style with the same week of a similar style last season, set a season-to-date target per category before you buy, and treat 100% well before the end of the season as a sign you bought too little or priced too low, not as a win.
Attribute data that makes sell-through readable
The by-size and by-color split only works if every SKU carries clean, consistent attribute values. If one supplier writes "Navy", another "navy blue" and a third leaves color in the title, your sales report has five color groups instead of three and the 70% navy signal disappears. Across the 32 catalogs that use attributes in WISEPIM's State of Product Data report, the median attribute was filled on 1.9% of products at import, so for many stores the split is not possible until the data is fixed.
WISEPIM is not an inventory system and has no sell-through report: stock counts and sales come from your shop platform or ERP. What it does is keep the attributes that sell-through is grouped by complete and consistent. Attribute management uses option sets, shared lists of allowed values for select attributes such as size, color and material, and AI enrichment can fill missing values from titles, descriptions and supplier data. Export SKU, size, color and material to CSV or Excel and join the file with your sales report by SKU, and every attribute becomes a sell-through dimension.
With that in place, a weekly sell-through read per attribute takes minutes instead of a cleanup project, and next season's buy can start from the size curve and colors that actually sold.
