---
title: 'State of Virtual Try-On: Q2 2026'
metaShorterTitle: State of Virtual Try-On Q2 2026
description: >-
  What actually happens when stores add virtual try-on: first-party data from
  577 Shopify stores and over 156,000 AI try-ons. Add-to-cart rates, shopper
  behavior, speed, and the categories shoppers try on most.
keywords:
  - virtual try-on statistics
  - virtual try-on conversion rate
  - virtual try-on data
  - AI try-on report
  - state of virtual try-on
author: thibault
publishedAt: '2026-07-17'
updatedAt: '2026-07-17'
noindex: false
canonicalPath: /reports/state-of-virtual-try-on-q2-2026
---

What actually happens when an online store adds virtual try-on? This report answers with measured data instead of estimates: **577 Shopify stores** running the Genlook try-on widget, **over 156,000 completed try-ons**, April 16 to June 30, 2026.

It is first-party data, measured on our own platform, and we document exactly how in the [methodology](#methodology) section. Every stat has a stable anchor, so feel free to cite any number here.

## Key findings

<StatGrid>
  <Stat
    id="atc-lift"
    value="3.1x"
    label="higher add-to-cart rate in sessions with a try-on"
    note="29.2% vs 9.4% for sessions without a try-on."
  />
  <Stat id="mobile-share" value="90%" label="of try-ons happen on a phone" note="8.8% desktop, 1.2% tablet." />
  <Stat
    id="median-speed"
    value="9.2s"
    label="median time to generate a try-on"
    note="95% finish within 14.4 seconds."
  />
  <Stat
    id="repeat-tryons"
    value="37.7%"
    label="of shoppers who try on come back for more"
    note="1.8 try-ons per shopper on average."
  />
  <Stat
    id="upload-rate"
    value="39.7%"
    label="of shoppers who open the widget add a photo"
    note="94% of them go on to generate a try-on."
  />
  <Stat
    id="email-capture"
    value="22.5%"
    label="of try-on shoppers leave their email address"
    note="54% of shoppers asked for an email submit one."
  />
</StatGrid>

## The sample

- **577 Shopify stores** with at least one completed try-on in the quarter, across fashion, eyewear, swimwear, footwear, wigs, and pet apparel, with shoppers worldwide.
- **Over 156,000 completed try-ons** in the quarter.
- Nearly **59,000 distinct products** were tried on.

## Shoppers try on from their phone

**90% of try-ons happen on mobile.** Desktop accounts for 8.8% and tablets for 1.2%.

The takeaway for merchants is simple: judge any try-on experience on a phone, on a normal connection, the way your shoppers will actually use it. A widget that demos beautifully on a laptop but stumbles on mobile misses 9 out of 10 real uses.

## One photo, several looks

Try-on is not a one-shot novelty. Shoppers who use it average **1.8 try-ons each**, and **37.7% try on more than one item**. Within a single visit, 29% of try-on sessions include two or more generations.

The first photo is also the last hurdle: about **61% of photo selections reuse a photo the shopper already uploaded**. After that first upload, trying the next product is a single tap, which is exactly what makes comparing looks possible.

## From open to cart

Here is the funnel across more than 275,000 sessions where shoppers opened the try-on widget:

| Step                     | Share               |
| :----------------------- | :------------------ |
| Opened the try-on widget | 100%                |
| Added a photo            | 39.7%               |
| Generated a try-on       | 94.4% of photo adds |

The pattern is clear: **the photo step is the gate**. Once a shopper has provided a photo, almost everyone generates. Anything that makes the first photo easier, clear guidance, a visible privacy promise, photo reuse, pays for itself through the whole funnel.

The funnel deliberately stops at the generation. After seeing their look, most shoppers add to cart back on the product page, where add-to-cart naturally lives, rather than inside the widget. The session-level comparison below is the honest way to measure the cart impact.

## Try-on sessions add to cart 3.1x more

Sessions that included at least one try-on ended with an add-to-cart **29.2%** of the time. Sessions without a try-on: **9.4%**. Measured across more than 16 million storefront sessions in the quarter.

Shoppers who take the time to try something on are, by definition, engaged shoppers, so this is a mix of the feature working and motivated shoppers choosing to use it. Both readings point the same way for a merchant: try-on identifies and serves your highest-intent visitors, and it does so at meaningful volume.

## Try-on turns shoppers into contacts

Try-on creates a natural moment to ask for an email: the shopper is waiting for their look, and the result is worth sending. In Q2, stores using Genlook's email capture collected an address from **22.5% of shoppers who tried something on**. When the prompt was shown, **54% of shoppers submitted their email**.

## Shoppers share their looks

Some try-ons are too good to keep private: **4.8% of try-on shoppers tap share**, and those who do share more than twice on average (2.3 share actions each). Of the shoppers who tap share, **61% complete it**, sending the look through their phone's share sheet or copying the link.

That is organic product marketing in its most credible form: your item, on a real person the recipient knows, sent peer to peer. Sharing happened on 236 stores in the quarter, so it is a broad behavior rather than a single viral store.

## Fast enough to sit in the buying flow

- Median generation time: **9.2 seconds**.
- 95% of try-ons finish within **14.4 seconds**.
- **98.6%** generate successfully.

Speed is what decides whether try-on lives inside the purchase flow or outside it. At around 9 seconds, a shopper stays on the product page and waits; at half a minute or more, they are gone.

## What shoppers try on

| Category                                        | Share of try-ons |
| :---------------------------------------------- | :--------------- |
| Clothing                                        | 87.4%            |
| Eyewear                                         | 3.7%             |
| Swimwear                                        | 3.5%             |
| Shoes                                           | 1.9%             |
| Hats                                            | 1.4%             |
| Other (jewelry, accessories, wigs, pet apparel) | ~2%              |

Demand concentrates on hero products: the median product gets a single try-on, while the most tried-on product of the quarter accumulated **1,591 try-ons** on its own. That concentration mirrors where conversion value and return risk sit in most catalogs, which is exactly where try-on earns its keep.

## When shoppers try on

Try-on leans toward evenings and weekends. The busiest hours fall between **15:00 and 20:00 UTC**, **Sunday is the busiest day** of the week (16.3% of the quarter's try-ons), and Wednesday the quietest (13.0%). The spread is moderate rather than dramatic: try-on happens all week, with a visible couch-shopping bump.

Times are UTC across a worldwide base of stores, so local patterns are stronger than these averages suggest. The practical read: try-on traffic peaks exactly when support is offline, which is an argument for keeping the flow self-serve.

## Q2 2026 at a glance

| What we measured                         | Q2 2026  |
| :--------------------------------------- | :------- |
| Active stores                            | 577      |
| Completed try-ons                        | 156,000+ |
| Unique Products tried on                 | ~59,000  |
| Median generation time                   | 9.2s     |
| Try-ons on mobile                        | 90%      |
| Shoppers who try on more than one item   | 37.7%    |
| Add-to-cart rate, sessions with a try-on | 29.2%    |
| Add-to-cart rate, sessions without       | 9.4%     |
| Try-on shoppers who leave their email    | 22.5%    |
| Try-on shoppers who share a look         | 4.8%     |
| Try-ons that are clothing                | 87.4%    |

## Methodology

- **Window:** April 16 to June 30, 2026, the first full quarter of measurement. We plan to publish a new edition each quarter.
- **Sample:** the 577 Shopify stores running the Genlook widget with at least one completed try-on in the window. Stores adopting try-on skew fashion-forward, so these numbers describe stores that chose VTO, not e-commerce at large.
- **Sources:** try-on counts, speed, success rates, and category mix are measured server-side and are complete. Funnel, session, and device numbers come from first-party widget analytics on storefronts.
- **The add-to-cart comparison** is session-level correlation over the same April 16 to June 30 window, not a controlled experiment: try-on users are self-selected, engaged shoppers, so treat 3.1x as what try-on sessions convert at, not as a promised lift from installing a widget.
- **Hour and day-of-week figures are UTC**, unadjusted for shopper time zones.
- **Sharing** is measured from in-widget share clicks and completions (native share sheet or copied link). Views of shared looks by recipients are not measured in this window.
- **Photo reuse** is measured from widget interactions (choosing an existing photo vs uploading a new one).
- **Email capture** is a per-store option. The stores with it enabled account for ~99% of try-on volume in the window, so rates are reported across all try-on shoppers; restricting to capture-enabled stores moves the headline rate from 22.5% to 22.7%.
- All numbers are aggregates. No shopper-identifiable data was used, and no store-level data is reported.

## How to cite this report

<CiteBlock>
  Genlook, State of Virtual Try-On: Q2 2026. First-party data from 577 Shopify stores, April 16 to June 30, 2026.
  https://genlook.app/reports/state-of-virtual-try-on-q2-2026
</CiteBlock>

Each stat card has a stable anchor (for example `#atc-lift`, `#median-speed`) you can link directly. If you quote the add-to-cart comparison, please keep its context: try-on users are engaged shoppers, and 3.1x describes their sessions, not a guaranteed uplift.

## Where to go from here

New to the technology? Start with [what virtual try-on is](/blog/what-is-virtual-try-on.md) and how it works. Choosing tools? We keep a category-by-category [comparison of Shopify try-on apps](/blog/best-virtual-try-on-apps-shopify-2026.md) up to date, including the honest trade-offs of our own. And if you want to see these numbers on your own catalog, [Genlook installs free](/get-started).

<Faq>
  <FaqItem question="How much does virtual try-on increase add-to-cart rate?">
    In Genlook's Q2 2026 data across 577 Shopify stores, sessions with at least one try-on added to cart at 29.2%,
    versus 9.4% for sessions without, a 3.1x difference. Try-on users are engaged, self-selected shoppers, so the number
    describes how try-on sessions convert rather than a guaranteed lift from installing a widget.
  </FaqItem>
  <FaqItem question="Can virtual try-on collect emails and leads?">
    Yes, and unusually well: in Q2 2026, stores using Genlook's built-in email capture collected an address from 22.5%
    of shoppers who tried something on, and 54% of shoppers shown the email prompt submitted one. The try-on moment,
    waiting to see a product on yourself, is a natural point to ask.
  </FaqItem>
  <FaqItem question="What products do shoppers try on most?">
    Clothing dominates with 87.4% of all try-ons in Q2 2026, followed by eyewear (3.7%), swimwear (3.5%), shoes (1.9%),
    and hats (1.4%). Within a catalog, demand concentrates on hero products: the most tried-on single product
    accumulated 1,591 try-ons in the quarter.
  </FaqItem>
  <FaqItem question="When are shoppers most active with virtual try-on?">
    Evenings and weekends. The busiest hours fall between 15:00 and 20:00 UTC, and Sunday is the busiest day with 16.3%
    of the quarter's try-ons. Activity stays spread across the whole week rather than spiking on one day.
  </FaqItem>
  <FaqItem question="How fast is AI virtual try-on in production?">
    Across more than 156,000 completed try-ons in Q2 2026, the median generation took 9.2 seconds, 95% finished within
    14.4 seconds, and 98.6% generated successfully.
  </FaqItem>
  <FaqItem question="Do shoppers use virtual try-on on mobile or desktop?">
    Overwhelmingly mobile: 90% of try-ons happened on a phone, 8.8% on desktop, and 1.2% on tablets. Evaluate any try-on
    experience on mobile first.
  </FaqItem>
  <FaqItem question="Where does this data come from?">
    From the Genlook virtual try-on platform: server-side generation records (counts, speed, success, categories) and
    first-party widget analytics on merchant storefronts (funnel, sessions, devices), across 577 active Shopify stores
    from April 16 to June 30, 2026. Genlook builds the widget, so this is first-party data with methodology and
    limitations disclosed above.
  </FaqItem>
</Faq>