Footwear. Shopify for ranges where fit makes the sale.

A shoe size is not a fixed length. It depends on the last, the form a model is built over. Two models from the same brand in size 42 can come out differently in length, width and volume. If you only explain that in a general size chart, you leave customers alone with the most important decision of the purchase.

That is why fit belongs on the individual model. Inner length per size, width, last shape, toe box and a note on whether the model runs small or large are structured information. In Shopify they sit in metafields or in a metaobject per last that several models share. That way you maintain a detail once, not again on every product page.

Widths make the variant problem sharper. Shopify allows three option dimensions per product. Colour, size and width already use them up. Add a material or a sole variant and it becomes a product of its own, linked to its siblings in the theme. That decision is made before the data import, not in day-to-day operations.

There is no universally valid conversion between EU, US and UK sizes. Manufacturers set their steps differently, US sizes differ between women and men, and half sizes do not exist in every system. A chart from the internet applied to the whole store therefore produces exactly the wrong purchases that come back later as returns.

The clean approach is a conversion per brand or per last, stored as data rather than as an image. The theme then shows the relevant system first in each market and lists the others alongside. Inner length in millimetres serves as a neutral reference, because it stays understandable regardless of the sizing system.

What matters is that the variant stays unambiguous in your inventory system. The SKU is tied to one size, usually the EU size, and the other systems are display only. If you create variants twice per market, you fragment your stock and oversell one size while the same pairs sit unsold in another market.

In footwear many customers order two sizes and send one back. That is not a question for the returns portal but a matter of uncertainty before the purchase. The better the product page answers which size fits, the less often people order twice just to be safe. We promise no number for this, because it depends heavily on the range.

Advice on the product page means something specific: a fit note right next to the size selector, a comparison with other models from the brand, instructions for measuring your foot and reviews that ask about fit. If you analyse return reasons, you quickly see which models need an extra note.

The processing itself should run automatically. At Groundies that is handled by 8returns, connected to Shopify, alongside Zendesk for automated tickets and Workato for the warehouse and fulfilment connection. A return then costs less manual work, and the reasons end up as data where the team can analyse them.

Barefoot shoes are bought on features: zero drop, a flexible sole, a wide toe box, sole thickness in millimetres. For running, hiking or work shoes, cushioning, waterproofing or tread come on top. As long as this information sits as running text in the description, no filter, no search and no AI assistant can read it reliably.

We set up these features as metafields with fixed values. From them come filters on the collection page, comparison details on the product page and structured product data for Google and AI search. The biggest effort lies in agreeing on terms and methods of measurement, for example whether sole thickness includes the tread or not.

Footwear ranges usually have two parts: core models that should stay available all the time, and seasonal colours or special editions that run out. On top of that comes the size curve. Middle sizes sell out fast, edge sizes are left over. A model missing a 39 and a 43 looks sold out in the store, even though pairs are still in the warehouse.

In the store it helps to manage this visibly: back-in-stock alerts for a specific size, clearly marked pre-orders with a delivery date for core models being reproduced, and filters that hide sold-out sizes. Shopify Flow can trigger tasks when stock runs low. Stock itself should come from the system that owns it, so store and warehouse see the same figure.

For footwear, going international is more than currency and language. Sizing system, tax rates, customs duty and return routes differ by market. Shopify Markets covers prices, taxes and domains. The size display belongs in the product data and the theme, so that a customer in the United States sees their US size first and does not have to convert it.

Groundies, a barefoot shoe brand with eight-figure revenue, previously ran on two systems: OXID for the United States and Shopware for international. We merged both onto one shared Shopify Plus codebase. The launch was staged, the United States first, international sixty days later. The project ran six months, and more than 100 orders came in within three days of the US launch.

According to the Groundies case study, costs fell by 50 per cent through consolidating the two platforms. That is an effect of the consolidation, not of any single feature. The staged launch was a method in itself: one market goes live, the team learns from real orders, then the rest follows on the same codebase.