Every apparel merchant has watched this play out on a product page. A shopper likes the piece, opens the size chart, squints at a tape-measure diagram she hasn’t touched in months, and picks a letter that has usually worked before. The campaign photo looks great. The model isn’t her. Somewhere between wanting the piece and hitting Add to Cart, she makes a private bet: this size will probably be fine.
Often it isn’t. Size charts assume two things that don’t always hold: that shoppers measure themselves correctly, and that your chart actually matches how the garment fits. Wrong-size returns are the obvious cost. The quieter losses never show up as a line item anywhere. Shoppers who bounce off a chart that feels like homework. Shoppers who order two sizes and treat your warehouse as a fitting room. Shoppers who loved the look and still walked away, since naming a size felt like guessing out loud.
Closku is built for the other sequence. We pull body measurements from a single shopper photo, then recommend a size for a specific garment in your catalog. That call sits right next to virtual try-on on the same product page: see the piece on yourself, get a size for that exact SKU. One photo does both jobs. Look first, size next, before any money moves.
Why charts alone still fail careful shoppers
Charts aren’t useless, they’re just incomplete. A well-written size guide can tell a shopper that a medium fits a certain chest and waist range. It can’t tell her whether your medium sits the way last season’s medium sat, whether this brand’s “true to size” claim matches the brand she wears every week, or whether the rise on these trousers lands where she expects on her own body.
Self-measurement adds its own failure mode. Tape measures get pulled too tight, or left too loose. People measure over their clothes. They round up. They use numbers from a year ago. Reviews try to fill the gap and mostly cancel each other out: “runs small” stacked right above “true to size,” both written by shoppers who never stood in the same room as your sample.
Closku doesn’t ask you to delete the chart. Keep the chart, keep the model shots, keep the reviews. What we add is a product-page layer that starts from the shopper’s own photo instead of a table she has to interpret alone. The size call is tied to garments you’ve actually imported, not a generic chart pasted onto every PDP as if every SKU fit the same way.
Photo → measurements → size for that SKU
The shopper path is short on purpose. One full-body photo against a plain background. Closku uses that same photo for the measurements and for the try-on render. There’s no separate “size wizard” sending her into a second app, and no multi-angle photo homework that kills the session before she ever sees a result.
From that photo, Closku recommends a size for the garment she’s actually looking at, a call tied to the SKU in your Closku catalog. That distinction matters more than it sounds. A size letter with no garment attached is just branding. A size letter for this jacket, this dress, this pair of trousers is merchandising: it answers the question on the page instead of running a generic body-type quiz that has no idea how your assortment fits.
We don’t publish a lab accuracy percentage on this page. Anyone selling you a clean “X% measurement accuracy” number without knowing your catalog, your traffic, or your shoppers’ photo habits is selling theater. Closku’s job is concrete: recommend a size for garments in your catalog from that photo, next to a try-on of the same piece. What that does to your return rate depends on your assortment, where you place the experience, and whether shoppers actually use it, not on a number we made up for a headline.
Try-on + size together
Size alone doesn’t show drape and cut. Try-on alone doesn’t name a size. Put together, they answer the two questions that actually sit between wanting something and checking out: how does it look on me, and which size should I pick?
You’ve probably seen both half-answers fail already. A shopper can love how a dress drapes on her in try-on and still pick the wrong size if the only guidance left is a chart she measured against last year. Another shopper can get a clean size call and still send the piece back if she never saw the silhouette on her own body: shoulders, hem, sleeve length, the way the fabric actually falls on her instead of on a campaign model.
Closku runs both from the same photo, on the same product page. See the SKU on yourself. Get a size recommendation for that garment. The brand story stays in your photography. The fit proof moves into something the shopper does right next to Add to Cart. That’s the bet behind the product page: look and size as one loop instead of two tools competing for attention.
If returns are the pain you feel first, read Cut clothing returns with virtual try-on. If you need Shopify install specifics, see Virtual try-on for Shopify. The idea is the same in both: fewer guesses at checkout, more proof on the page where the money actually moves.
What this looks like for a merchant, not a demo avatar
Take a store selling structured blazers next to soft dresses. The blazer shopper cares about shoulder line and length. The dress shopper cares about drape and where the hem lands. Your size chart probably uses the same letter language for both, but the failure modes aren’t the same. Closku’s size call is garment-aware, since the catalog you import is garment-aware too: names, SKUs, images. So the recommendation answers the PDP in front of her, instead of running a one-size-fits-all body quiz.
A practical launch pattern looks familiar if you already export catalogs for other tools. Start with the SKUs that hurt the most: the styles with the loudest fit complaints, the bestsellers that still get returned, the pieces people buy in two sizes just to be safe. Import that slice first. Put try-on and size on those PDPs, then watch whether shoppers actually use the photo loop before you widen the import. You don’t need the whole assortment live on day one to find out whether photo-based size and try-on change the decision.
Closku is a merchant workspace built for that loop: catalog, storefront try-on, size from the same photo, not a marketplace widget you sit around waiting to get approved. The promise is simple enough to say in one sentence: fashion shoppers should see the piece on themselves and get a size for that SKU before they pay.
Catalog requirement
You need products in Closku before size recommendation or try-on can do anything on a live PDP. The path is CSV import: names, SKUs, images. Same path whether you’re on Shopify, WooCommerce, BigCommerce, or a custom storefront, then one script on the site so the experience shows up on product pages. There’s no live store sync yet, and Closku isn’t an App Store or marketplace app yet either. When your assortment changes, you re-import. That’s the trade: ship now, own the refresh yourself, skip waiting on a marketplace listing.
Merchants who pick this path usually care more about PDP confidence than an App Store badge. Teams that already export CSVs for other tools tend to treat Closku the same way, as one more feed to keep current. If your stack needs one-click marketplace install and live catalog sync today, that’s a fair thing to want, and a legitimate reason to look elsewhere. We wrote that comparison up in Closku vs Genlook.
Starter is $49/month for 145 try-ons. Unused try-ons don’t roll over. Growth and Scale raise the volume as your traffic and try-on usage grow. Compare plans on pricing. Full operational detail lives in the docs. Questions about catalogs, themes, or whether Closku fits your stack: hello@closku.com.
Cutting returns is the bigger merchant goal, see Cut clothing returns. Shopify-specific setup: Virtual try-on for Shopify. Plans start at $49/month: pricing.
Who this is for
Fashion catalogs where fit uncertainty isn’t a minor UX complaint, it’s a real gap between wanting something and actually buying it. Merchants who want size recommendation and virtual try-on running as one product-page experience instead of two separate experiments. Teams willing to paste a script and refresh a CSV instead of waiting on a marketplace listing.
It’s also for operators who are done trying to solve fit with more model shoots and denser charts. Another lookbook photo won’t show a size-medium buyer how a blazer sits on her shoulders. A longer size guide won’t show her the hem. Closku answers both from one photo: try-on for the look, recommendation for the size, both tied to the garments you actually imported.
If you need published measurement-accuracy percentages, competitor star ratings, or AggregateRating theater to feel comfortable, this page won’t invent them for you. If you want shoppers to see the piece on themselves and get a size for that SKU before they pay, on Shopify, WooCommerce, BigCommerce, or a custom storefront, Closku is built for that job. Start at pricing, read the docs, or watch the homepage demo before you touch your theme.