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Fashion Ecommerce Benchmarks: Conversion, AOV, Returns

The core fashion ecommerce benchmarks in one place, each tied to its publisher and year: conversion, order value, cart abandonment, and returns.

Jason

Written by

Jason

Published on

July 11, 2026

Fashion Ecommerce Benchmarks: Conversion, AOV, Returns

The key numbers

  • Fashion and apparel ecommerce converts in the low single digits: Littledata put the average for style and fashion stores at 1.9% (2023 benchmark), and IRP Commerce measured 1.53% in the fashion clothing and accessories market in May 2026.
  • The top tenth of fashion stores convert more than 6.1% of their visitors, according to Littledata (2023).
  • Average order value in fashion clothing and accessories was £91.53 in May 2026, per IRP Commerce, down from £95.84 a year earlier.
  • About seven in ten online carts never reach checkout: Baymard Institute puts the documented average cart abandonment rate at 70.22%, drawn from 50 studies (updated September 2025).
  • US online purchases come back at 19.3%, part of $849.9 billion in total US retail returns in 2025, according to the National Retail Federation and Happy Returns.
  • Online apparel is the most returned major category at 24.4%, and size and fit is the leading reason, named by 53% of sellers, both from Coresight Research (2023).

Benchmarks are useful right up until someone quotes one without a source. A single "fashion converts at 3 percent" line gets copied across a hundred blogs until nobody can say where it came from. This page does the opposite. Every number below is tied to the group that published it, with the year and a link, so you can check the primary source instead of the summary of a summary.

Conversion rate benchmarks for fashion#

There is no single true conversion rate for fashion ecommerce, and any page that hands you one is hiding the methodology. What the credible sources agree on is the neighborhood: low single digits, usually between 1.5 and 2 percent for a typical store.

Littledata, which benchmarks Shopify stores through its analytics, put the average conversion rate for style and fashion stores at 1.9 percent in its 2023 data. The spread underneath that average matters more than the average itself. To reach the top fifth you need to convert more than 4.3 percent of visitors, and the top tenth convert above 6.1 percent. The gap between a median store and a very good one is roughly threefold, so the ceiling sits far higher than the average suggests.

IRP Commerce, which reports live data from its retail network, measured the fashion clothing and accessories conversion rate at 1.53 percent in May 2026, up from 1.33 percent a year earlier. That figure lands a little below Littledata's because it is a different set of stores measured a different way, which is exactly the point. Treat 1.5 to 1.9 percent as the honest middle, not a target.

Average order value in fashion#

IRP Commerce reported an average order value of £91.53 in the fashion clothing and accessories market for May 2026, down 4.5 percent from £95.84 the year before. The number is in pounds because IRP's network skews to UK and European stores, worth remembering before you set it next to a dollar figure from a US-heavy source.

Average order value is highly methodology-sensitive. It swings with product mix, discounting, currency, and whether returned orders are counted, so a clean cross-source fashion figure is hard to pin down. We show the one we could verify on the publisher's own page and leave the rest out rather than quote a number we cannot stand behind.

Cart abandonment#

Roughly seven in ten online carts are abandoned before the buyer pays. Baymard Institute puts the documented average cart abandonment rate at 70.22 percent, calculated from 50 separate studies and last updated in September 2025. That is not a fashion-only number, it is ecommerce wide, but clothing carts carry an extra stall point of their own, because so much of a clothing purchase is a guess about fit.

Baymard's research repeatedly finds that unexpected extra costs at checkout, meaning shipping, taxes, and fees, are the most common reason shoppers give for walking away. For a clothing store a second reason hides in plain sight. A shopper who cannot tell whether a garment will fit is far more likely to stall at the cart than one who already knows their size.

Returns benchmarks#

Returns are where fashion pays for the fit guessing, and this is the best documented corner of the picture. The headline comes from the National Retail Federation and its partner Happy Returns, whose 2025 Retail Returns Landscape put total US retail returns at $849.9 billion, or 15.8 percent of everything sold. Buy online and the rate climbs to 19.3 percent.

Apparel is the worst major category online. Coresight Research, in a 2023 study of US apparel brands and retailers, measured the online apparel return rate at 24.4 percent, which worked out to roughly $38 billion of clothing shipped back that year. Coresight also asked sellers why the clothes came back, and size and fit was the top answer, named by 53 percent of them, far ahead of any other cause.

Two more figures round out the story. McKinsey and Company, in a 2021 returns-management survey of North American apparel retailers, attributed about 70 percent of apparel returns to poor fit or style, and the honest version of the stat keeps both halves. Narvar, in its 2021 State of Returns report, found that 58 percent of shoppers bracket, ordering the same item in several sizes meaning to keep one and send the rest back. The one figure from peer-reviewed research rather than a vendor page comes from Zalando's SizeFlags study at the KDD 2021 conference, which cut size-related returns by 3.8 percent in a controlled test of 720,000 shoppers per group. The fuller picture is in our guide to ecommerce return statistics.

How to read a benchmark without fooling yourself#

A benchmark is a mirror held up to the whole industry, and the industry is not your store. The most useful number is the one you already own: last quarter's conversion rate, your own return rate, your own average order value. Beat your own baseline and you are winning, wherever the industry average sits.

When you reach for an outside number, check three things: who measured it, when, and how they defined "fashion", since fast fashion, luxury, and accessories each convert differently. Those three questions explain almost every gap between two sources quoting the same metric.

One throughline connects the numbers on this page. Fit uncertainty shows up twice, once as carts that never convert and again as clothes that come back, so anything that gives a shopper a confident answer on their size tends to move both lines at once. That is the case for a real size chart and a size recommender on the product page, and the tactics that put it to work are in our guide to reducing clothing returns.

Sources#

Frequently asked questions#

What is a good conversion rate for fashion ecommerce?#

A typical fashion store converts in the low single digits. Littledata's 2023 benchmark put the average for style and fashion at 1.9 percent, and IRP Commerce measured 1.53 percent for fashion clothing and accessories in May 2026. Above 4.3 percent puts you in the top fifth of fashion stores, and above 6.1 percent in the top tenth, per Littledata.

What is the average return rate for online clothing?#

About 24.4 percent, according to Coresight Research (2023), which makes apparel the most returned major category online. That sits above the 19.3 percent return rate across all online purchases in 2025 reported by the National Retail Federation and Happy Returns. Size and fit is the top reason clothing comes back.

Why do benchmark numbers differ between sources?#

Because they measure different things. One source tracks Shopify stores, another a live retail network, another a shopper survey, and each defines "fashion" its own way and reports a different year. That is why a conversion figure can read 1.53 percent in one report and 1.9 percent in another and both be correct. Always check who measured it, when, and how before you treat a benchmark as your target.

Jason

Written by

Jason

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