Bracketing benchmarks by category: where multi-size orders cluster

September 27, 2026

A single sitewide bracketing rate hides more than it reveals. When you break multi-size ordering down by category, the spread is dramatic: the hardest-fit categories bracket at several times the rate of the easy ones. Knowing where your categories sit against benchmarks tells you whether you have a sitewide problem or a category problem, and those demand different fixes.

The benchmarks below reflect what we see across apparel brands on Shopify. Treat them as directional, not gospel: your customer base and price point shift the numbers. But the ordering, which categories bracket most, is remarkably stable.

The high-bracketing categories

Denim sits at the top for most brands. Bracketing rates of 25 to 35 percent are common, meaning a quarter to a third of denim orders contain two or more sizes. The reasons are structural: denim fit is unforgiving, vanity sizing varies wildly between brands, and stretch content changes the fit in ways size charts cannot capture. A customer who wears a 28 in one brand genuinely does not know their size in yours.

Dresses and tailored pieces come next, typically 18 to 28 percent. Here the issue is multidimensional fit: a dress has to work at the bust, waist, and hips simultaneously, so the odds that a single size nails all three are low. Occasion dresses bracket even more, because the cost of a poor fit at an event feels catastrophic to the buyer.

Footwear deserves its own note. Bracketing looks different here, half sizes instead of full sizes, but the rate is high: 20 to 30 percent for brands that sell between sizes. Width variation compounds it. A shopper between a 8 and 8.5 will order both without a second thought.

The low-bracketing categories

At the other end, tees, knit tops, and accessories bracket at 5 to 10 percent. The fit is forgiving, the price is low, and the cost of being wrong is small, so shoppers commit to a size. Outerwear sits in the middle, 12 to 18 percent, because the layered, relaxed fit tolerates error but the high price makes shoppers cautious.

The low-rate categories matter for a different reason: they are your control group. If tees start bracketing at 15 percent, something changed that has nothing to do with fit, usually a policy change, a new customer cohort, or a UX change that made multi-size ordering easier. Watch the easy categories for early warnings.

How to use the benchmarks

First, compute your own rates per category using the same definition: orders containing two or more sizes of the same SKU, divided by total orders in the category. Compare against the ranges above. Categories running hot relative to benchmark are where fit content, fit guidance, and in-cart nudges earn their keep.

Second, weight by margin impact, not just rate. A category with a 30 percent bracketing rate but low return cost may matter less than a category at 15 percent with expensive two-way shipping. Multiply the bracket rate by the average cost per bracketed order to get the dollar ranking. That ranking, not the rate ranking, sets your priority queue.

Third, track the trend, not just the level. A category drifting upward over two quarters is telling you something changed: a new fit block, a supplier switch, or a product mix shift toward harder-fit styles. The benchmark tells you where you stand. The trend tells you where you are going.

What the benchmarks do not tell you

Category averages hide SKU-level concentration. Even in a high-bracketing category, a handful of products usually drives most of the multi-size orders. Run the SKU ranking within each hot category before spending on category-wide fixes. You will often find that fixing fit content on five products moves the category rate more than any sitewide initiative.

And benchmarks do not diagnose cause. A high rate could mean poor fit content, inconsistent grading, a bracketing-friendly returns policy, or simply a customer base that learned the habit. The benchmark tells you where to look. The investigation, fit-guide analytics, review mining, customer cohorts, tells you what to fix. Measure against the benchmark quarterly, and let the outliers set your agenda.