Filters for features, fit and activity, not just size and price
What they do
The filter panel runs eleven groups with 77 options in total (counted 10 Aug 2026): the usual product type, size, colour and price, then the ones most stores never build. Features (lightweight, sweat wicking, seamless, breathable, non restrictive, reflective branding), Fit (compression through extreme oversized), and Activity (lifting, running, conditioning, rest day), plus collection, pattern and discount.
Why it works
The deep facets match how people actually shop the category. Nobody thinks "medium, under £30" first; they think "something breathable for running". Filtering by intent (activity) and by attribute (fit, features) lets a 374-product grid collapse to a personal shortlist in three taps, which is the difference between filtering and leaving. The facets are also a merchandising census: they only work because every product is tagged with fit, feature and activity data, and that discipline pays everywhere else too.
Makes sense when
Catalogues where products genuinely vary by use case or attribute. The filters are only as good as the product data behind them, so this is really a product-tagging project wearing a UX hat. Start with the two or three facets shoppers actually decide on, not all eleven. Mind crawlable filter-URL bloat on Shopify; keep faceted URLs out of the index unless deliberately targeted.
More like this
More collection patterns
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