Confidential brandWinter Sports9 mo

Sizing a boot that fits nothing like a shoe

Size-related returns 27% → 9%

A winter sports brand sold boots in mondopoint while its customers think in shoe sizes, and absorbed a quarter of orders back every season. A proper sizing system fixed the returns and the reviews with them.

Sizing a boot that fits nothing like a shoe

At a glance

Category
Winter Sports
Marketplaces
US, CA
Revenue at start
$246k / month in season
Problem
27% returns, nearly all size-related
Engagement
Creative & content + listing SEO
Timeframe
9 months, spanning one full season

Results

Size-related return rate-18 pts27% 9%
Net season revenue+44%$1.42M $2.05M
Conversion rate+20%4.9% 5.9%
Reviews mentioning sizing-23 pts31% 8%

The challenge

The boots are sized in mondopoint, which is the correct way to size them and a system almost no online shopper uses. The listing printed the mondopoint value, a converted shoe size from a chart of unclear origin, and nothing about width, volume or how a performance fit is supposed to feel — which is snugger than any shoe the buyer owns.

A quarter of every season's orders came back. Worse, the reviews carried the confusion forward: a third of them discussed sizing, which meant the next shopper arrived already unsure, and either bought a size up to be safe — producing a boot that performs badly and gets returned for a different reason — or did not buy at all.

Our approach

We replaced a conversion chart with a measurement method.

  • Measure, don't convert — a foot-length-in-centimeters guide as the primary instruction, since mondopoint is that measurement and the shoe-size detour is where the error enters.
  • Width and volume stated separately, with plain guidance on which model suits which foot shape.
  • Fit expectation set explicitly — what a correct performance fit feels like on day one versus after packing out, which prevents the size-up reflex.
  • Variation family and size charts corrected, so the size selected in the dropdown matches the size described in the content on every listing.

How we worked

  1. 1

    Code the returns

    One full season of returns categorized: 89% size-related, two thirds of them a boot returned as too large after the shopper had sized up to be safe.

  2. 2

    Rebuild the chart

    A measurement-based chart produced from the actual lasts rather than a generic conversion table.

  3. 3

    Rewrite the content

    Measurement guide, width guidance and fit expectation added to the image stack and A+ on every boot listing.

  4. 4

    Fix the catalog data

    Size attributes and variation families corrected so the dropdown, the chart and the copy finally agree.

  5. 5

    Watch the season

    Returns tracked weekly through the season; two models still over-returning were re-measured and their guidance corrected mid-season.

Inside the ad account

Anonymized account view, rebuilt from the figures reported above: ad sales growing from $111k to $160k a month while ACoS falls from 34% to 22% across the 7-month engagement.

Anonymized account view, rebuilt from the figures reported above: ad sales growing from $111k to $160k a month while ACoS falls from 34% to 22% across the 7-month engagement.

The results

Size-related returns fell from 27% to 9%, and net revenue for the season rose 44% against the same season a year earlier — most of it from orders that previously came back rather than from new demand.

Conversion rose 20% because the page now gives a shopper a way to be confident before ordering, and the review body changed with it: sizing mentions fell from a third of reviews to under a tenth, which removes the doubt the next shopper used to inherit.

“We'd been publishing a conversion chart nobody could trace. Telling people to measure their foot in centimeters was the entire fix.”
Product Manager, Winter sports brand

Ready to scale your Amazon brand?

Talk to a senior strategist and leave with a growth plan for your store — no obligation.