How to use try-on data in buying decisions

What the analytics actually track

Looksy's published analytics cover three stages: what shoppers try on, what they add to cart, and what they buy. That gives each product a small funnel of its own, built from real behavior on your store rather than survey answers or industry reports. A try-on is a stronger expression of interest than a page view — the shopper stopped, uploaded a photo, and waited to see the piece on themselves. When you are deciding what to reorder, drop, or buy deeper, that intent layer sits usefully between traffic data and sales data.

Reading try-heavy products that do not sell

A product with many try-ons but few purchases is telling you interest exists and something downstream blocks it. Before cutting it from the next buy, work through the likely causes: price against comparable pieces, product photos that fall short of the clear, full-view standard try-on works best with, or results shoppers found unconvincing — they can leave feedback on results, so check in the app what came back for that product. If the block is something you can change, you may be holding a winner rather than a dud. If try-ons are low too, demand itself is the problem — a different buying decision.

Backing products that convert after try-on

The opposite pattern is the strongest signal this funnel produces: products shoppers try on and then buy at a high rate. Demand there has been confirmed by people engaged enough to picture the piece on themselves, which makes deeper buys, added colorways, or extended size runs easier to defend than decisions based on page views alone. The analytics also show which products get tried on most, so start with volume, then look at conversion. A high-try, high-buy product is your best case for stocking deeper; a low-try, high-buy product is simply selling on its photos.

Keep it directional, not decisive

This is a signal from your own store, not market research. Volumes on a single shop are small, and seasonality, promotions, and where the try-on block sits in your theme all shape the numbers. Looksy publishes no benchmark conversion or take rates, so compare your products against each other over time rather than against an imagined industry figure. Use try-on data alongside sell-through, returns, and margin — it earns a vote in the buying meeting, not a veto. Review the funnel in the app before each buying cycle and let repeated patterns, not single weeks, move real money.

Sources: the public Shopify App Store listing for Looksy. Last checked 27 July 2026.

Related questions: Which products make the best first try-on test? · Does virtual try-on increase conversion rate? · How do I read shopper feedback patterns on try-on?