The Virtual Mannequin Filter

A virtual mannequin filter lets shoppers filter a fashion catalog visually. Instead of ticking checkbox filters, shoppers adjust fit and silhouette directly on a mannequin, like tightening a sleeve or shortening a hem, and results update instantly. It works because of AI fashion tagging underneath. YesPlz automatically tags every product for attributes like silhouette, neckline, sleeve, and length, so the mannequin always has accurate data to filter against. No manual tagging by your team, and no facets missing because the product feed was thin. The result is a filtering experience built for how people actually shop fashion: by shape and fit first, words second. Stores using the Virtual Mannequin Filter see 1.7x higher basket sizes.

Faceted search lets shoppers narrow results by combining multiple attributes at once: category, size, color, fit, price, and brand. Instead of one filter at a time, shoppers stack facets to reach exactly what they want, like "midi dress, long sleeve, square neck, under $200." In fashion, faceted search only works as well as the product data behind it. If your catalog isn't tagged for silhouette, neckline, or fit, those facets can't exist. YesPlz auto-tags 1,100+ fashion attributes and turns the most-used facets into a visual filter, so shoppers adjust fit and silhouette on a mannequin instead of scanning checkbox lists. Stores using it see 1.7x higher basket sizes.

Filters decide how much of your catalog a shopper actually sees. Checkbox filters end sessions early: each dead-end combination is an exit point, and anything poorly tagged never appears at all. Visual filters do the opposite. When shoppers refine by fit and silhouette on a mannequin, they stay in the browsing flow, see more products that match their taste, and add the second and third item they would never have scrolled to. Stores using the Virtual Mannequin Filter see 1.7x higher basket sizes. W Concept started with exactly this filter, and the results led them to expand into YesPlz search and recommendations across their store.

Yes. YesPlz AI tagging goes beyond physical attributes like silhouette and sleeve. It also maps products to occasions such as wedding guest, office, and date night, plus seasons and dress codes. That means your filters can offer occasion facets without your team tagging a single product, and shoppers can narrow by the moment they're shopping for, not just the garment type. Occasion data also feeds YesPlz search and GEO, so one tagging pass improves discovery everywhere.

Not hard. The Virtual Mannequin Filter is a plug-and-play widget you add to your site, with API access if you want deeper control. It works on Shopify, Cafe24, and custom stacks, and most stores go live in about two weeks. No replatforming and no heavy engineering work on your side.

No. The filter is powered by YesPlz AI auto-tagging, which reads your product images and generates the fashion attributes itself. You don't need clean metadata, a taxonomy project, or manual tagging hours before launch. Connect your catalog and the AI builds the data the filter runs on.