Drop our widget on any product page. Shoppers pick their body type, skin tone, and style — garments render on a model that looks like them. No app. No AR headset. Just conversion.
Live Demo
Pick a body type, choose a skin tone, then browse the rack. Analytics below update in real time.
No items
Live Brands
The same widget, running against each brand’s own products, racks and default look.
What You Receive
An example of the report a brand receives each quarter. Every number below is illustrative — it is not measured data and not any brand’s real figures.
SXL · Q3 2026 · illustrative
Skin tone is selected by the shopper, not inferred. A try-on tool that only renders an image leaves tone in the pixels, where it cannot be grouped, filtered or put on an axis. Here it is a value the shopper chose for themselves — so it can be crossed with body fit, and the act of choosing is what makes it theirs to give. Nothing is guessed from a photo, a name or a face.
Which body fits each tone group tries, and how often a try-on became a saved look.
12,480 try-ons — every session in the quarter.
| Skin tone | M · Slim | M · Athletic | M · Plus | W · Slim | W · Curvy | W · Plus |
|---|---|---|---|---|---|---|
| Fair | 67420% saved | 47422% saved | 32817% saved | 69424% saved | 60526% saved | 47118% saved |
| Medium Olive | 56122% saved | 39824% saved | 30118% saved | 63425% saved | 57827% saved | 39820% saved |
| Light Brown | 42320% saved | 32221% saved | 27316% saved | 49523% saved | 49725% saved | 36117% saved |
| Brown | 39518% saved | 30420% saved | 26715% saved | 45322% saved | 46924% saved | 35816% saved |
| Deep Brown | 31818% saved | 24920% saved | 20414% saved | 34521% saved | 34723% saved | 28415% saved |
The same try-ons counted by what was tried rather than who tried it.
The same 12,480 try-ons — tone totals match the grid above exactly.
| Skin tone | Tops | Bottoms | Dresses | Outerwear |
|---|---|---|---|---|
| Fair | 132922% saved | 86318% saved | 57028% saved | 48421% saved |
| Medium Olive | 115624% saved | 77319% saved | 51628% saved | 42522% saved |
| Light Brown | 93822% saved | 64617% saved | 43126% saved | 35620% saved |
| Brown | 87921% saved | 61816% saved | 40924% saved | 34019% saved |
| Deep Brown | 69020% saved | 47015% saved | 32023% saved | 26718% saved |
Which fabrics each tone group gravitates to, across every product carrying them.
3,216 try-ons — a subset: only products offering more than one colourway. Column totals match “Most tried colourways” above.
| Skin tone | Tan / White | Blue / White | Black / White | Deep Navy | Sand / Ecru |
|---|---|---|---|---|---|
| Fair | 30923% saved | 23621% saved | 16519% saved | 10924% saved | 1718% saved |
| Medium Olive | 26323% saved | 20821% saved | 15419% saved | 10024% saved | 1520% saved |
| Light Brown | 20823% saved | 17221% saved | 13519% saved | 8424% saved | 1217% saved |
| Brown | 19323% saved | 16221% saved | 13019% saved | 8324% saved | 1118% saved |
| Deep Brown | 14723% saved | 12521% saved | 10419% saved | 6624% saved | <10 |
The same tone axis crossed three ways. Row and column totals reconcile with the Audience and Merchandising figures above, and the fit and category grids count the same try-ons — so their tone totals agree exactly. Any cell under 10 is withheld rather than printed — too thin to act on, and once these are real numbers, thin enough to point at a person.
Colourways are counted across all products by label, which assumes a shared palette — that “Tan / White” is the same fabric pairing wherever it appears. For a brand whose colourways are per-product one-offs, that grid would instead be scoped to a single garment and would mean something narrower.
The gap between tried and saved is the number a sales report cannot give you: it never hears about the shopper who tried a garment and walked away. Ranked by the share that did, not the raw count — otherwise the list just repeats whatever is most popular.
Skin tone is a shopper-chosen preference for which avatar a garment is shown on. No ethnicity is asked for, inferred or reported, and location is not reported. Return rates are not shown here — measuring the effect on returns needs your own returns data alongside try-on sessions, so it is something we would measure with you rather than something this report asserts.
Integration
Drop a single iframe onto your product page. Works on Shopify, Squarespace, Wix, or any custom stack. No SDK, no dependencies, no configuration required.
<!-- FYT Virtual Try-On — drop this anywhere on your product page --> <iframe src="https://fyt-app-six.vercel.app/try-on/your-brand ?bodyType=slim&gender=womenswear" style="width:100%;height:100vh;border:none;" allow="clipboard-write" title="FYT Virtual Try-On" ></iframe>
01
We onboard your brand
Upload garment cutouts via the admin panel. We handle categorisation and body-type mapping.
02
Paste the embed
One iframe. Point it at your brand slug. Customise body type and gender as defaults via URL params.
03
Watch the data
Access your live analytics dashboard to see garment engagement, skin tone splits, and session depth.
For Fashion Brands
Future Youth Theory gives shoppers a more personal way to discover how products look across different body types — directly from your digital storefront.