Fashion5 min read
Three kinds of virtual garment fitting technology compared
Body scanning, size recommendation and avatar try-on are all sold as virtual fitting. What each one solves, what it costs to run and where it fails.
By CharpstAR · 4 Oct 2023 · Updated 9 Oct 2026
Three different technologies are sold under the name virtual fitting. One measures the shopper's body. One predicts a size from data without measuring anything. One shows the garment on an avatar so the shopper can see how it looks. Vendors rarely say which of the three they are selling, and buyers end up with a tool for a problem they did not have.
The two problems called fit
Two different customer problems are called fit, and they need different answers.
The first is sizing. The shopper is between a 38 and a 40 and does not know which to order, so they order both or neither. It is an information problem, and it drives most size returns.
The second is appearance. The shopper cannot tell how the garment will hang, whether the cut suits them or whether the colour works. That is a confidence problem, and it drives abandoned carts more than returns.
Most disappointment with virtual fitting comes from buying a tool for the second problem and expecting it to fix the first.
The three technologies
Body scanning
The shopper photographs or films themselves, usually turning on the spot, and software estimates body measurements from the images. Some systems ask for height and weight and infer the rest. The output is a set of measurements, which the retailer maps to size charts.
What it solves: sizing, in principle, and better than anything else here.
What goes wrong: the shopper has to do work. Standing against a blank wall in tight clothing and turning around is a lot to ask in the middle of a purchase, and completion rates show it. Accuracy is uneven across body types and clothing, and an estimate three centimetres out on a chest measurement puts a customer on the wrong side of a size boundary. Scanning also collects body data, so there is a privacy and consent conversation with your legal team before it ships.
Best use: high-value or made-to-measure items, where the customer will spend two minutes on it. It makes much less sense on a fifteen euro t-shirt.
Size recommendation
No camera. The shopper enters height, weight, age and perhaps their usual size in another brand, and the system recommends a size from past purchases and returns. The good ones improve over time because they learn from what came back.
What it solves: sizing, statistically, for most ordinary body shapes.
What goes wrong: it needs volume. A new brand with a small order history gets generic recommendations, which is not much better than a size chart. It also has no marketing value, since there is nothing to show on a product page or in a campaign.
Best use: any catalogue with enough sales history. It is the least glamorous option here and usually the most cost-effective one for reducing size returns.
Avatar or AR try-on
The garment exists as a 3D model and is shown on an avatar, either a generic body, a body adjusted to the shopper's rough proportions, or the shopper themselves through the phone camera.
What it solves: appearance and confidence. The shopper sees the drape, the length and how a print sits on a body.
What goes wrong: it measures nobody. Fabric simulation is convincing to look at and not accurate enough to be a fitting room. Building a garment as a simulation-ready 3D asset is also the most expensive option here, because every fabric needs physical properties as well as a texture.
Best use: styling-led categories, marketing and social. It also works very well for rigid accessories, where the physics problem disappears.
The comparison, in one table
| Body scanning | Size recommendation | Avatar or AR try-on | |
|---|---|---|---|
| Solves | Sizing | Sizing | Appearance and confidence |
| Shopper effort | High | Low | Low to medium |
| Data needed from you | Accurate garment measurements | Sales and returns history | A 3D model per garment |
| Cost to run | High | Medium | High per item |
| Privacy exposure | Significant, body imagery | Low | Low to medium |
| Effect on size returns | Potentially large | Reliable and moderate | Small |
| Marketing value | None | None | Real |
Rigid accessories are the easier case
The physics problem that makes garment fitting hard does not exist for glasses, watches, bags, jewellery or shoes seen from above. They are solid objects. A phone tracks a face or a surface accurately, and a correctly scaled 3D model appears at true size.
That is why eyewear AR works so much better than trouser AR, and it is where most fashion retailers should put their first money. The technology is mature and the delivery path is standard.
Delivery is simple. A GLB model runs in the browser through a viewer, and the AR button hands the same product to the phone's own AR, Scene Viewer on Android and Quick Look on Apple devices. There is nothing to install.
The numbers behind the business case
Returns are the number that justifies these projects. The National Retail Federation and Appriss Retail put United States returns at 743 billion dollars in 2023, 14.5 percent of sales, with the online rate at 17.6 percent. Apparel sits at the expensive end of that.
On conversion, Shopify's merchant data from 2020 showed product interactions with 3D or AR content converting 94 percent more often than comparable products without, and Rebecca Minkoff reported that shoppers who viewed a product in AR were 65 percent more likely to buy and 44 percent more likely to add a 3D-viewed product to cart.
Both sets are conversion figures. Neither says anything about returns, and anyone quoting a precise reduction in garment returns from avatar try-on should be asked for the study.
A sensible sequence
Put real garment measurements and fit notes from your returns data on every product page. It costs almost nothing and goes at the sizing problem directly. Add size recommendation once your order history is big enough to feed it. Build 3D and AR for your rigid accessories, where it works reliably. After that, and as a measured test on a handful of styles, look at avatar try-on for garments.
We build the 3D side of that, mostly for furniture, eyewear and home products, and the same pipeline applies to any product with a fixed shape. Sweef and Contura both use it so that size and space questions get answered before checkout. The range of what we build is on the solutions page, and the plans start at 10 dollars per product per month.
To see the quality for yourself, send one product through the free sample form and we will model it at no cost.
Sources
- National Retail Federation and Appriss Retail, 2023 Consumer Returns in the Retail Industry.
- Shopify, merchant data on 3D and AR content, September 2020, AR shopping, and 3D ecommerce.
- Google, Scene Viewer.
- Apple, AR Quick Look.
