Short answer: Analyst firms value the virtual try-on market at roughly USD 9–15 billion and expect about 26% annual growth to 2030. Returns are the cost try-on aims at: US retailers expected 19.3% of 2025 online sales to come back, and fit is the top apparel return reason. Conversion figures exist, but mostly from vendors.
Most "virtual try-on statistics" pages repeat the same handful of numbers, often without a year and usually without a link to where they came from. This page does the opposite. Every figure below was checked against its original source in October 2026, each one shows what it measures and when, and vendor-reported numbers are labeled as such. Where a popular figure couldn't be traced to a primary source, it isn't here.
How we checked these numbers
Every statistic on this page went through the same three checks in October 2026.
- Find the original. We followed each figure back to the organization that produced it: the analyst report, the retail association's release, the company's own announcement, or the published study. Blog posts quoting other blog posts didn't count.
- Confirm the exact number. We opened the original page and checked that it states the figure as quoted, including what it measures and over what period. If the page said something slightly different, we used the page's wording.
- Label the type. Analyst estimates, surveys, platform data, and vendor-reported results are labeled in the tables, because they deserve different levels of trust.
Several widely shared figures didn't survive this process. A frequently quoted "almost 20% sales lift" and "up to 64% fewer returns" traced back to a vendor's interviews with trade press, not to a study. A "60% of garments are returned" headline came from a brand-commissioned survey with an unclear measure. A few other figures sat behind pages we couldn't open, so we couldn't confirm them. Leaving those out makes this list shorter, and more useful.
Market size and adoption
Market size estimates come from analyst firms, and they disagree, partly because they define the market differently and use different base years. Read them as ranges, not facts.
| Statistic | Source | Year |
|---|---|---|
| The global virtual try-on market was valued at USD 9.2 billion in 2023, projected to reach USD 46.4 billion by 2030 (26.4% CAGR, 2024–2030). Analyst estimate. | Grand View Research | 2023 base |
| North America held 31.0% of virtual try-on revenue in 2023, and apparel and clothing was the largest application segment. Analyst estimate. | Grand View Research | 2023 |
| The virtual try-on market was valued at USD 15.18 billion in 2025, projected to reach USD 48.10 billion by 2030 (25.95% CAGR). Analyst estimate. | Mordor Intelligence | 2025 |
| Apparel accounted for 47.64% of the virtual try-on market in 2024. Analyst estimate. | Mordor Intelligence | 2024 |
| Google launched AI virtual try-on in the US across "billions of apparel items" in Search, Google Shopping, and product results on Google Images. | 2025 | |
| ASOS launched a hybrid virtual try-on on around 10,000 products in its iOS app for select UK and US customers, with each preview loading in 4–7 seconds. | ASOS plc | 2026 |
| More than 250 million Snapchatters engaged with AR shopping Lenses more than 5 billion times between January 2021 and April 2022. | Snap Inc. | 2022 |
What stands out is less the market totals than the adoption by large platforms. When Google puts try-on into ordinary product results and ASOS rolls it out across thousands of products, shoppers start to expect the feature rather than be surprised by it.
Conversion and engagement
This is where the evidence is thinnest. The largest published dataset comes from a try-on vendor comparing its own users with non-users, so every figure in this table is vendor-reported.
| Statistic | Source | Year |
|---|---|---|
| Shoppers who used virtual try-on were about 3× more likely to add items to cart than those who didn't. Vendor-reported, 1.2 million shoppers. | DRESSX | 2026 |
| Try-on users had 50% higher purchase conversion. Vendor-reported. | DRESSX | 2026 |
| Try-on users viewed 7× as many product listings as non-users. Vendor-reported. | DRESSX | 2026 |
These numbers compare people who chose to use try-on with people who didn't. Shoppers who bother to upload a photo are usually further along in their decision, so part of the gap is the shopper, not the feature. That doesn't make the data useless. It makes it a signal about who uses try-on rather than proof of what try-on causes. Our guide to how virtual try-on affects conversion explains how to separate the two on your own store.
Returns and fit
Returns are the cost virtual try-on most directly targets, and here the best data comes from retail associations and returns platforms rather than try-on vendors.
| Statistic | Source | Year |
|---|---|---|
| US retailers expected 15.8% of annual sales to be returned in 2025, totaling $849.9 billion. | NRF and Happy Returns | 2025 |
| An estimated 19.3% of online sales would be returned in 2025. | NRF and Happy Returns | 2025 |
| In 2024, returns totaled $890 billion, or 16.9% of sales. | NRF and Happy Returns | 2025 report |
| Gen Z shoppers (ages 18–30) averaged 7.7 online returns in the previous 12 months. | NRF and Happy Returns | 2025 |
| Fit or size accounted for 56% of apparel return reasons, and style or preference for 25%. Vendor data from the platform's merchants. | Loop Returns | 2026 |
| Fit or size accounted for 61% of footwear return reasons. Vendor data. | Loop Returns | 2026 |
| 59% of US online clothing shoppers said they'd felt dissatisfied with an item because it looked different on them than expected. Survey of 1,614 US adults, April 2023. | Google/Ipsos | 2023 |
Two things are worth separating here. Fit (the size is wrong) and appearance (it looks different than expected) are different problems. A size chart or size recommendation tool addresses the first, and a visual preview addresses the second. The Google/Ipsos figure is about appearance, which is the gap visual try-on is built for. For what these returns cost a clothing store, see our breakdown of apparel return costs and margins on Shopify, and for tracking return reasons in your own store, our guide to Shopify returns.
Shopper attitudes
Shoppers say they want to see clothes on someone like them, but enthusiasm for the technology is uneven, and privacy questions are real.
| Statistic | Source | Year |
|---|---|---|
| 42% of online shoppers don't feel represented by images of models. Survey of 1,614 US adults. | Google/Ipsos | 2023 |
| 19% of US respondents said they were excited about AR- and VR-enhanced online shopping, the same as in the UK, compared with 41% in India and 8% in Japan. | Statista | 2025 |
| Of 138 virtual try-on websites and 28 Android apps analyzed, 65% of websites and 18% of apps sent user images to servers, and 37% of websites used providers that extract facial geometry. | Concordia University | 2024 |
| 11% of websites and 25% of try-on providers didn't follow their own privacy policies, and 22% of websites used misleading disclaimers about data handling. | Concordia University | 2024 |
Academic work points the same way on what drives acceptance. A 2025 peer-reviewed study of 228 Italian consumers in the International Journal of Retail & Distribution Management tested how perceived usefulness, ease of use, and enjoyment shape attitudes toward virtual try-on. It's a small, single-country sample, but its message is practical: if the tool is easy and useful, people are more willing to use it. For merchants, that means the privacy promise and the experience both have to be clear before shoppers will upload a photo.
What these numbers don't tell you
A statistics page can make a topic look more settled than it is. Here's what to keep in mind before you quote any of the figures above.
Market sizes measure different things. Grand View Research and Mordor Intelligence don't define the market the same way. Mordor's figures, for example, include in-store smart mirrors and kiosks. That's why two "virtual try-on market" numbers for nearby years can differ by billions.
The conversion data is vendor-reported. The largest conversion dataset comes from a company that sells virtual try-on. That's normal for a young category, but it isn't independent research, and the users it describes chose to use the feature.
Return-reduction claims are the weakest of all. You'll find "try-on cuts returns by X%" figures almost everywhere. When we traced the popular ones, they led back to vendor interviews, vendor marketing pages, or nothing at all, so none made this list.
Surveys measure what people say. Saying you'd use try-on and uploading a photo on a Tuesday night are different things. The Statista excitement figures are a useful reality check on the more upbeat surveys.
Your store isn't the average. Category, price point, photo quality, and traffic mix all change the result. The only number that tells you what try-on does for your catalog is one you measure yourself, ideally with a split test across comparable products. Our guide to measuring try-on with a split test shows how to set that up, and the virtual fitting room guide for ecommerce stores covers how the technology works.
How to cite this page
Wherever possible, cite the original source linked in each table, with its year. To reference this page as a collection: "Virtual Try-On Statistics (2026)," Traion AI Virtual Try-On, updated October 6, 2026, https://www.traion.me/blog/virtual-try-on-statistics.
If you want to measure try-on on your own Shopify store rather than rely on averages, Traion is free to install with 10 free try-ons. Install free