Shoe Returns in Europe: Find the Fit Problem Behind Each Model
A customer returns a shoe because it feels too tight. The next useful question is where: at the toes, across the forefoot, or over the top of the foot? Those answers lead to different changes in size advice and product information.
For European footwear retailers, reviewing returns by shoe model and size makes that distinction possible. An overall return rate shows the scale of the problem. A closer look at the shoes and the reasons they came back tells the team where to act.
Read Germany’s latest returns figures correctly
In its September 30, 2026 study summary, EHI Retail Institute reported that 67.5% of participating fashion retailers had an item-based return rate above 20%. This is the share of retailers above a threshold—not an average return rate of 67.5%.
The wider study surveyed 108 online retailers in Germany, Austria and Switzerland during summer 2026, with most headquartered in Germany. The fashion finding is useful context for a footwear business, but it is not a footwear-only benchmark or a rate to apply to every European store.
Share of fashion retailers surveyed by EHI. These are not average return rates. Source: September 30, 2026 release.
For a shoe retailer, the next step is to find out which models account for size-related returns, and why.
What Perfitt’s Mizuno EMEA work adds
PerfittSize combines information about a shopper’s feet and familiar shoe sizes with the fit characteristics of the particular model they want to buy. It recommends a size for that shoe. Smartphone foot measurement is also available as an optional input.
In the published Mizuno EMEA case, Perfitt reported lower return rates across selected products and markets during the initial rollout. That is a historical customer observation, not a forecast for another retailer. A return-rate improvement also does not translate directly into the same percentage reduction in return-processing costs.
The useful connection is specific: size guidance is based on the shoe model, so its results should also be examined by model. A brand-wide average can hide a problem concentrated in one style or size.
Original visual from Perfitt’s published Mizuno EMEA customer story, reproduced without changing the branding or product screen.
Keep research findings separate from customer results
A separate 2026 Journal of Retailing and Consumer Services study analyzed 58,412 shoppers, 1.27 million purchases and 243,000 returns at a European fashion retailer over twelve months. Buying multiple sizes, searching for fit information and mismatches in size preferences were informative signals in its return-prediction models.
Those predictive findings support looking at the shopping journey as well as the return reason. They do not establish that every shopper who checks fit information will return a purchase, or that using a recommendation causes a particular outcome. The research is separate from Perfitt’s customer evidence.
A practical review sheet for each shoe model
Start with a manageable group of models with enough completed orders and returns to compare. Use the same purchase period and allow enough time for returns to arrive. Keep countries separate initially, especially where the assortment or return policy differs.
The following template contains fields to fill from your own records. It is not customer data.
Shoe and market | Fit problem reported | Advice before purchase | Shoe information | Decision to make |
|---|---|---|---|---|
Model code, size, width option and country | Too short, too narrow, loose heel or the customer’s own words | Whether guidance was shown or used; recommended size and purchased size, if recorded | Verified measurements, construction and model-specific fit notes | Check size advice, clarify the product page or investigate a repeated fit issue |
Keep the number of pairs sold and the number returned alongside each row. Ten returns from a popular model mean something different from ten returns on a model with very few sales. Calculate the fit-related return rate using fit-related returned pairs divided by sold pairs from the same group and period. Record exchanges separately, including the replacement size and whether the customer kept it.
Use only the fit and purchase records your team is permitted to combine. This review requires agreed access to the retailer’s order and return data; it is a joint analysis, not an automatic returns-management feature of PerfittSize.
Editorial illustration created with AI: examining the individual shoe is the starting point for a fit review.
Turn the pattern into a specific change
If customers repeatedly report pressure across the forefoot, inspect width and toe-box information before recommending a longer shoe. If they report insufficient length and keep the next size up after an exchange, check the size recommendation and the measurements for that model. These are examples of decisions to investigate, not observations from a named customer.
If shoppers often buy two sizes of the same model, review what size advice they saw before checkout and which pair they kept. If complaints are concentrated in one country, first check the size labels and product information shown in that market.
Each finding should end with a named change: correct a size conversion, improve a fit description, check a model’s measurements, or test revised guidance. This makes the review useful to both the ecommerce team and the people responsible for the shoes.
Measure the change on comparable purchases
Agree on the model, market, purchase period and definition of a fit-related return before testing a change. Where practical, compare shoppers randomly assigned to the existing and revised guidance. Follow purchases through the return window and check both returns and purchases customers kept.
A simple comparison of people who used the tool with people who did not can be misleading: shoppers seeking size help may already be more uncertain. Promotions, product mix and available sizes can also change between periods. Keep those differences visible when deciding whether an improvement is convincing.
For a footwear team, the output should be clear: which shoe needs attention, what needs to change, and how the team will judge the result.
Perfitt brings model-specific size recommendations and foot-and-shoe fit information to that work. To review your own collection, request a footwear fit-and-return review. Tell us which models and markets you want to examine and what order and return records are available; we can agree on a focused analysis from there.