Visual AI search and merchandising for Shopify fashion
Fashion shoppers rarely think in exact product names. They look for a silhouette, color, occasion, neckline, sleeve or fit. RecoMelon interprets those visual characteristics across search, collections and PDP recommendations, helping more of a fashion catalog become relevant without a manual tagging program.
Search that understands what shoppers mean. Conversational and contextual search interprets style, color, attributes and intent. Dynamic merchandising balances commercial and catalog priorities, while inline Shop Similar and integrated LiveGrid™ UGC keep shoppers discovering without returning to a static results grid.
Shop Similar, directly from the product image. When a product is "almost right", Reveal™ offers visually aligned alternatives from within the primary product image, above the fold. Shoppers stay on the PDP and keep their intent while finding an alternative without the attribute stopping the purchase.
Turn “almost right” into another relevant option. Shop Similar keeps high-intent shoppers exploring with visually matched alternatives based on the product they are already considering - helping them refine their choice without starting their search again.
Turn one product into a complete look. Complementary recommendations create multiple looks around a chosen product, with configurable discounts and multi-buy offers to increase AOV. Bundle Rescue swaps unavailable or unsuitable items for visually similar alternatives without breaking the set. Integrated LiveGrid™ content helps shoppers visualize the combination.
Abandoned Cart Email Rescue. Sending shoppers back to rejected products repeats the problem. SecondLook™ restores the abandoned basket and offers visually matched alternatives for each item - helping shoppers find a better fit while preserving basket intent and cross-sell opportunities.
The discovery problem
Fashion shoppers often recognize a promising silhouette before they know the product name. A neckline, sleeve, color or print can then become the reason that an otherwise suitable item is rejected.
Treat that moment as a refinement task. A useful next step should retain the visual qualities the shopper likes while making alternatives easy to explore. New drops and low-history styles also need a route into that journey before popularity data accumulates.
Where RecoMelon fits
VisualDNA™ matches visible characteristics such as cut, silhouette, color and pattern. IntentWeave™ supports usable visual attributes, while Shop Similar and Reveal™ let shoppers explore alternatives from the product already in view. Bundles™ can be evaluated separately for complementary looks.
Catalog data remains the source of truth for size, price, availability, composition and market eligibility. Images can support visual relevance; they should not be used to infer an exact fit, material specification or product claim that the catalog does not establish.
Coexistence and implementation
Choose a category with a useful range of silhouettes, colors and variants. Review image quality and product grouping, confirm how size availability and market eligibility are supplied, and inspect recommendations across new arrivals as well as established products.
The existing search and collection experience can remain in place while a PDP surface is tested. Agree who owns exclusions, brand rules, presentation and analytics, and check the interaction on mobile where visual comparisons need to remain easy to navigate.
Evaluation and evidence
Assess whether shoppers move from the original item to relevant alternatives and continue towards a purchase. Review recommendation engagement, products explored, new-product exposure and conversion within the selected category.
If testing complementary looks, include basket value and the quality of the combinations in the review. Account for size availability, promotions and seasonal assortment changes, and distinguish incremental results from orders merely associated with recommendation interactions.
RecoMelon analyzes product imagery and catalog context to identify characteristics that influence fashion decisions. These can include silhouette, cut, color family, sleeve, neckline, pattern and style intent.
No. Visual product relationships can support new and long-tail products before substantial behavioral history exists. Behavior can add context as shoppers interact.
Use the intelligence in The Index™ search, Smart Collections, Reveal™ PDP alternatives, RecShelf recommendations and complementary Bundles™.
Share a category, new drop or discovery journey. We’ll show how visual intelligence can make more of the range reachable.
Request a catalog review