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In Walker Brown’s 2026 scan, 2.8% of buyable styles met the stricter definition of a size run with stranded sizes beside a gap; 63.8% of analyzed stores had at least one such run. Under a broader definition that counts any sold-out size between available sizes, the rates were 10.3% of styles and 78.5% of stores. These figures describe Brown’s sample, not every Shopify apparel store—and a size gap does not by itself prove a lost sale.
What counts as a size run with a hole?
A size run is a sequence of variants ordered along a single size axis, such as XS through XL. Brown defines a broken run as one in which a size is sold out while sizes on both sides remain in stock. A sold-out size at the end of the sequence does not count as an interior gap.
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The stricter, conservative definition requires two or more sizes to remain stranded beside the gap. It is intended to filter out cases that could simply reflect a style nearing sell-through. Neither definition directly measures a shopper who wanted an unavailable size, a sale that was lost, or the cause of a stockout.
What did Brown find?
Brown reports two rates because a single missing interior size can mean something different from several sizes left stranded around a gap.
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| Measure | Broad definition | Stricter definition |
|---|---|---|
| Share of buyable styles with a qualifying gap | 10.3% | 2.8% |
| Analyzed stores with at least one qualifying run | 78.5% (234 of 298) | 63.8% (190 of 298) |
All figures in the table are results reported by Walker Brown for the 2026 study. The style-level denominator is buyable styles; the store-level denominator is the 298 stores with readable size runs.
Among styles counted as broken under the broad definition, 72.6% were missing exactly one size. Brown’s explanation for why the store-level rates converge in larger catalogues is that small stores may have a single run close to selling through, while larger catalogues accumulate more gaps. That is the author’s interpretation, not a demonstrated causal finding.
The largest catalogues
Among the 101 largest catalogues in Brown’s sample, all had at least one broad-definition gap, and 94.1% had at least one conservative-definition gap. These are subgroup results, not a rate for all large Shopify stores; the article does not establish that catalogue size causes gaps.
How the catalogue scan was conducted
Brown says the scan fetched public catalogue data from each store’s /products.json endpoint, requesting pages of up to 250 products. The article describes this approach as requiring no API key or app installation.
The study attempted 438 stores. Of those, 354 responded, representing 122,425 products. The size-run analysis included 298 stores whose variants could be read as size runs: those stores held 111,774 products and yielded 64,268 runs. The 354 responding stores and the 298-store analysis set are different groups.
Why reading variant labels matters
Product options are free text: size labels may vary in capitalization or language, appear as a later option, or use abbreviations, numeric sizing, or waist-and-inseam formats. Brown counted a product as a size run only when normalized variants differed along exactly one ordered axis. One-size products were excluded. Where a product combined colour and size, runs were split by colour rather than treating every colour-size combination as one long sequence.
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As Brown put it, “The whole insight is that ordering the variants correctly is the analysis.” The reported percentages therefore depend in part on how labels were parsed and how the author classified a sequence as ordered.
What the figures can—and cannot—tell a store owner
The rates are useful as a reason to inspect your own catalogue, not as a prediction that your store has a particular number of gaps. The sample consists of stores Brown could reach and catalogues the author could parse; it is not presented as a representative estimate of all apparel ecommerce or all Shopify merchants.
- A broad-definition gap can be an ordinary sign of sell-through when only one size remains around a missing size.
- A conservative-definition run indicates a more substantial pattern under Brown’s rule, but still does not establish customer demand, lost revenue, or why inventory became unavailable.
- The study’s results apply to its parsing and classification choices, not to an independently validated universal standard for size runs.
How to check whether your own catalogue has a gap
Use the same logic at the product-variant level: order sizes, separate colourways, and look for sold-out sizes bracketed by in-stock sizes. Then distinguish an isolated gap from multiple stranded sizes rather than treating every sold-out variant as the same problem.
- Choose a product with a genuine sequence of sizes. Exclude one-size listings and options that do not form an ordered size axis.
- Separate variants by colour where colour and size are combined, so each colour has its own size sequence.
- Order the available size labels consistently, accounting for the sizing system used by the product.
- Mark which sizes are currently in stock and which are sold out. Flag a broad-definition gap only when a sold-out size lies between in-stock sizes.
- For the stricter check, look for two or more sizes left in stock beside the gap. Review those cases separately from a run with just one size remaining.
This is a manual check based on the study’s definitions, not a claim that Brown’s public checker or any app is currently available. Availability and terms for the checker and the associated Sizecurve app are time-sensitive and are not established here.
Corrections and limits of the published analysis
Brown disclosed that the initial size grammar missed spelled-out size names. The author corrected it and reran the analysis against the same cached catalogues; the reported figures rose by a few tenths. Brown also noted an earlier, smaller pass with a slightly lower conservative result. The primary article’s search result says a linked page contains both passes and per-catalogue rows, but the page itself could not be independently opened for this coverage. The underlying data, code, and exact corrected historical values therefore have not been independently checked.
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Source: Walker Brown, “I read 298 Shopify catalogues to find out how often a size run has a hole in it,” DEV Community, stated publication date September 30, 2026. Read Brown’s article.
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