A customer lands on a product page, likes the jacket, isn’t sure if their usual size 12 in this brand is a 12 or a 14, guesses, and orders. Three days later it doesn’t fit, and now you’re paying for a return, a replacement shipment, and possibly a discount to keep the sale. Multiply that by every uncertain buyer and sizing becomes one of the most expensive, least discussed problems in Shopify apparel stores.
Most of the fix isn’t a discount or a better product photo, it’s structural. It’s how your Size and Colour options are set up as variants, how (and where) your size chart actually displays, and whether it’s explicit about which sizing standard you’re using. For Australian stores in particular, that last point matters more than most merchants realise, because “size 12” means something different depending on which country’s chart the customer has in their head.
This post covers how to structure variants properly within Shopify’s limits, the practical options for displaying size charts, the AU-specific sizing traps to avoid, and why getting this right is a genuine return-rate lever, not just a UX nicety.
How Shopify Variants Actually Work for Apparel
Every apparel product on Shopify is typically built around two option types: Size and Colour. Shopify allows up to 3 option types per product (for example Size, Colour, Material) and up to 100 variants per product, meaning if you have 10 sizes and 10 colours, you’re already at the ceiling, before adding a third option.
A few structural things worth knowing:
- Each variant combination needs its own SKU, price (if it differs), and inventory tracking. A “Small / Red” and “Small / Blue” are two separate variants even though the size is identical, this is what allows Shopify to track stock per size/colour combination correctly.
- The 100-variant cap is a real constraint for larger size runs. A store offering XXS through 5XL (10 sizes) in 12 colourways would need 120 combinations, over the limit. Common workarounds include splitting the product into separate listings by colour (each with its own 10 sizes), or using a third-party variant/options app that supports more combinations than native Shopify allows.
- Variant images matter for apparel specifically. Each colour variant can have its own image (or set of images) attached, so customers see the actual colourway they’ve selected rather than a generic product shot, this is set from the product’s Media section in the Shopify admin by associating specific images with specific variant values.
- Metafields extend what a “variant” can carry. Beyond the standard price/SKU/inventory fields, metafields let you attach structured extra data to a product or variant, fit notes, fabric composition, model measurements, or a reference to which size chart applies. This is particularly useful when different product types (say, dresses vs shoes) need different size chart data attached to the same product type.
For stores with genuinely complex size grids, think bra sizing with band and cup combinations, or footwear with half-sizes and width fittings, native Size/Colour options can get unwieldy fast. In these cases, a dedicated sizing or product options app (layered on top of standard variants) is usually a cleaner solution than trying to force every combination into the native 3-option/100-variant structure.
Displaying Size Charts Without Rebuilding Them on Every Product
Once variants are structured, the second half of the problem is making sure the customer actually sees accurate sizing guidance at the point of decision, on the product page, before they add to cart, not buried in an FAQ page they never visit.
There are two broadly common approaches:
Metafield-driven tables on the product page
A size chart is built as structured metafield data (or a referenced metaobject) and rendered directly in the product template via Liquid, appearing as a static table on the page itself, often placed near the variant selector. Done well, this means one chart, defined once per product type or category, that pulls into every relevant product page automatically rather than someone manually building a table on each listing.
This approach tends to work best when:
– Sizing is broadly consistent across a product category (all your t-shirts use the same chart)
– You want the chart visible without an extra click, which tends to reduce the number of customers who skip it
– You’re comfortable with (or have a developer for) some theme-level Liquid work to wire the metafield data into the template
Popup or modal apps
A “Size Chart” or “Size Guide” link sits near the variant selector and opens a popup or modal on click, usually via an app that manages chart data and assigns charts to products or collections in bulk.
This approach tends to work best when:
– You want a no-code way to manage and update charts without touching the theme
– You have many different chart types across very different product categories (shoes, tops, bottoms, kids’) and want a simpler assignment interface
– You’re willing to accept that a popup only helps customers who actually click it, and some won’t
Whichever approach you use, the single most common mistake is rebuilding the same chart manually, product by product. Whether it’s metafields tied to a product type, or an app that lets you assign one chart to an entire collection, the chart should be maintained in one place and applied broadly, not copy-pasted into a hundred individual product descriptions where it will inevitably drift out of sync when sizing changes.
Australian Sizing Conventions: Where Stores Get It Wrong
This is the AU-specific trap, and it catches out both new stores and established ones expanding into international sourcing.
Australian apparel sizing broadly follows its own standard for womenswear and menswear, but it doesn’t map cleanly onto US, UK or EU sizing, and the gaps aren’t small. A US size 6 is roughly equivalent to an Australian size 10 in many womenswear brands; UK sizing is closer to AU but still not identical across every category; EU sizing uses an entirely different numbering system again (36, 38, 40…). Footwear has its own separate conversion problem on top of that.
The practical risk: if your supplier’s tech pack, your product descriptions, and your size chart aren’t explicitly labelled with which standard they’re using, customers will assume it’s their usual size and be wrong. This gets worse specifically for:
- Dropshipped or imported stock where sizing was originally specified in US or EU sizing by the manufacturer, and the store hasn’t clearly relabelled or converted it for an Australian audience.
- Stores that source from multiple countries, where different product lines genuinely use different sizing standards under the same store, meaning there’s no single universal chart that works for the whole catalogue.
- Generic “S/M/L” labelling without corresponding measurements, which forces the customer to guess an equivalence that may not exist consistently across brands.
The fix isn’t complicated, but it does require discipline: every size chart should state plainly which standard it’s using (“AU sizing,” “US sizing, see conversion,” etc.), and wherever possible, chest/waist/hip measurements in centimetres should sit alongside the size label rather than replacing it. A measurement in centimetres removes the ambiguity entirely, because it doesn’t depend on the customer knowing which country’s numbering system your “12” refers to.
A Practical Checklist for Fixing Apparel Sizing on Shopify
- Audit your current variant structure. Confirm Size and Colour are set up as proper option types (not buried in product titles or descriptions), and check whether any products are near or over the 100-variant limit.
- Decide your size chart delivery method, metafield-driven table or popup app, based on how consistent your sizing is across the catalogue and your team’s comfort with theme edits.
- Centralise chart data so it’s maintained once per product type or collection, not duplicated across individual listings.
- Label every chart with its sizing standard explicitly (AU, US, UK, EU) rather than assuming it’s understood.
- Add centimetre measurements alongside size labels wherever the product category benefits from it (tops, bottoms, outerwear especially).
- Attach variant-specific images so customers can see the exact colourway, reducing colour-related returns alongside size-related ones.
- Review return reason data periodically, if “wrong size” is a recurring return reason for a specific product or category, that’s a signal the chart or variant structure needs revisiting, not just a one-off customer error.
Why This Is Worth Fixing Properly
Sizing-related returns and exchanges carry real cost beyond the obvious reverse shipping fee, restocking, discounting to save the sale, and the customer service time spent on “what size should I get” messages that a clear chart would have answered upfront. For growing Australian fashion stores, especially ones scaling product range or sourcing internationally, getting variant structure and size chart display right early avoids a compounding problem where every new product adds to an already inconsistent sizing experience.
This is squarely the kind of build-and-merchandising work that benefits from category-specific experience, knowing where Shopify’s variant limits will actually bite, and how apparel stores typically solve for it. If you’re weighing up how to structure sizing for a growing range, our team’s Shopify agency work for fashion and apparel covers exactly this kind of variant, metafield and size-chart setup.
Frequently Asked Questions
How many size and colour variants can a single Shopify product have?
Shopify allows up to 3 option types per product and a maximum of 100 variant combinations. For a product with 10 sizes and 10 colours, that’s already the full 100, adding a third option (like a fit type) would exceed the limit unless the range is reduced or split across separate listings.
Should I use a size chart app or build charts into the theme with metafields?
It depends on how consistent your sizing is and how comfortable you are editing the theme. Metafield-driven tables tend to suit catalogues with consistent sizing per category and give more control over how the chart looks. Popup apps suit stores wanting a faster, no-code way to manage many different chart types across varied product ranges.
What’s the difference between Australian and US or UK clothing sizes?
The systems don’t map directly onto each other, a US size 6 is commonly closer to an Australian size 10 in womenswear, and UK sizing, while closer to AU, still isn’t identical across every brand and category. Because the gap varies by brand and garment type, the safest approach is always to state the sizing standard explicitly and provide measurements in centimetres rather than relying on size-number equivalence alone.
Can I have a different size chart for each product category?
Yes, this is one of the main reasons to use metafields or a size-chart app rather than manually writing a chart into each product description. Charts can be built once per category (dresses, shoes, outerwear) and applied to every relevant product or collection, so updates only need to happen in one place.
Does a better size chart actually reduce returns, or is that overstated?
In our experience running Shopify builds for apparel merchants, unclear or inconsistent sizing information is one of the most common drivers of size-related returns and exchanges, alongside genuine fit issues with the garment itself. A clear, correctly labelled chart won’t eliminate returns, but it removes the guesswork that causes a meaningful share of them.
Ready to Tighten Up Your Sizing Setup?
If sizing confusion is showing up in your return data or support inbox, it’s worth having a specialist look at how your variants and size charts are actually structured. Book a call with our team to talk through your current setup, or start with a Shopify audit to see where sizing and other on-page issues are costing you conversions.
