Virtual try-on conversion benchmarks for Shopify stores

2026年8月19日 · 5 min read

Any app that asks a shopper for something — in this case, a photo — has to pay for itself in conversion. Genlook's Q2 2026 report, based on first-party data from 577 Shopify stores, shows virtual try-on does, and the pattern is consistent enough to plan around.

Here are the benchmarks from that report — 577 active stores and 156,000+ completed try-ons — and how to measure the same numbers in your Shopify analytics.

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Virtual try-on conversion benchmarks for Shopify stores — generated try-on on a shopper

On shopper

29.2% vs 9.4%add-to-cart rate: try-on vs no try-on — Genlook, Q2 2026

156,000+completed try-ons across 577 stores — Genlook, Q2 2026

90%of try-ons happen on mobile — Genlook, Q2 2026

Source: State of Virtual Try-On: Q2 2026 — Genlook · Add-to-cart comparison · Median generation time

The headline numbers — Genlook, Q2 2026

29.2% add-to-cart rate in try-on sessions vs 9.4% without — a 3.1× difference

156,000+ completed try-ons across 577 active stores

37.7% of try-on shoppers try more than one item in a session

22.5% of try-on shoppers leave their email; 4.8% share a look

Median generation time of 9.2s; 90% of try-ons happen on mobile

Why the lift is structural, not cosmetic

Try-on shoppers aren't randomly more likely to buy — the mechanism is causal. The preview removes the specific uncertainty that stalls the purchase on your product page: will this look right on me?

That's also why the effect compounds with catalog size: the same photo unlocks the whole catalog, so each try-on session can vet multiple products at once.

How to measure it in your Shopify analytics

Segment conversion by try-on status: try-on sessions vs non-try-on sessions on the same SKUs

Track average order value for carts containing a tried-on item

Watch return rates on try-on orders separately — the second win

Attribute revenue to try-ons in the app's dashboard, not just to last-click channels

What moves the lift in your store

Placement: the try-on button should be obvious on your product pages, above the fold

Speed: the 9.2s median generation time keeps the shopper in the moment

Breadth: enable whole collections in the app, not isolated products, so one photo goes further

Follow-up: review try-on events in the dashboard so 'tried but didn't buy' gets a second chance

The honest caveats

The 3.1× add-to-cart difference compares try-on sessions against non-try-on sessions. Try-on users are engaged shoppers, so it describes their sessions — it's not a guaranteed uplift for every shopper you surface the button to.

Benchmarks are also averages across stores — your results depend on your category mix, traffic quality and how prominently you surface the try-on. Categories with high fit anxiety (dresses, denim, swimwear) see the biggest effects.

The cheapest way to know your number: install on your highest-traffic products and compare. The free plan exists for exactly that.

よくある質問

Adoption depends on button placement and traffic intent. Stores that surface the try-on button prominently on high-intent product pages see meaningful adoption — and the 3.1× add-to-cart difference between try-on and non-try-on sessions does the rest.

The direction is consistent; the magnitude varies. Fit-sensitive categories see the largest lifts — see our category pages for specifics.

さらに見る

Increase conversion (use case)The merchant playbook behind these numbers.What is AI virtual try-on?Start from first principles, Shopify edition.Swimwear try-onA fit-anxiety category, quantified.

Try it on your store

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Install in minutes, pick your products, and see try-on live on your product pages. Free plan included.

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Source

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