Visual AI recommendations that increase AOV by 15–28%

Manual Shopify collection blocks show the same products to every shopper regardless of their intent. RecoMelon personalises discovery dynamically per session - adapting recommendations based on what each shopper is looking at, filtering for, and visually drawn to. Two shoppers on the same PDP see different recommendations based on their behaviour. This is what makes RecoMelon an active conversion tool rather than a static curated list.

Dealbreaker™ Filters are RecoMelon's intent-led refinement system. They let Shopify shoppers filter the recommendation panel by the attributes that actually drive their buying decisions - sleeve length, neckline, fabric, fit, or colour - rather than broad category filters. When a shopper signals they only want V-neck or relaxed fit, Dealbreaker™ eliminates everything that doesn't qualify before it's shown. This reduces bounce and increases purchase confidence.

RecoMelon improves Shopify store performance by converting the product detail page (PDP) from a dead end into a discovery engine. When shoppers land on a product and don't convert, RecoMelon surfaces visually matched alternatives at that exact moment - filtered by what matters most to that shopper. Brands using RecoMelon typically see 28-55% AOV uplift and a 40%+ reduction in PDP bounce rate within the first 30 days of installation.

RecoMelon starts with the product, not purchase history. Most recommendation engines use collaborative filtering - recommending what similar buyers bought. RecoMelon uses VisualDNA™ to read each product image and understand how it actually looks - cut, colour, silhouette, print, material - then recommends based on visual similarity. This means new products are recommended from day one with zero sales data, and a shopper viewing a floral midi dress sees more floral midis, not whatever happened to be in the same basket. The result is a product intelligence engine, not a personalisation engine built on historical behaviour.

RecoMelon is an AI-powered product recommendation engine for Shopify that replaces generic "You Might Also Like" carousels with visually matched alternatives. VisualDNA™ reads each product image to understand cut, colour, silhouette, and style - surfacing the products a shopper is most likely to buy next. Dealbreaker™ Filters let shoppers refine recommendations by the attributes that actually matter to them, like sleeve length, neckline, or fabric. Together they convert the product detail page from a dead end into a discovery engine.

No technical skills are needed. RecoMelon installs from the Shopify App Store in under 60 seconds - no developer time, no code changes, no downtime. ColdStart™ scans the product catalogue automatically on installation, and most merchants see their first recommendation-influenced orders within 60 minutes of going live. New merchants start on a $1/day, 30-day trial - full feature access from day one, with a money-back guarantee if it doesn't perform. For Shopify Plus merchants or custom theme stores, the RecoMelon team handles onboarding directly.

RecoMelon has no measurable impact on Shopify store load time. The recommendation engine runs asynchronously using Shopify App Embeds, meaning it never blocks page render or delays the critical path. RecoMelon's architecture is designed to meet Shopify's Core Web Vitals standards - pages load at full speed, and recommendation widgets appear without affecting Largest Contentful Paint (LCP) or Cumulative Layout Shift (CLS) scores.

RecoMelon's visual AI matching analyses fine-grained product attributes including fabric texture, colour harmony, silhouette structure, and print pattern. Rather than relying on broad category tags, the system identifies nuanced visual relationships between products - making recommendations feel precise and intuitive rather than generic. Accuracy improves over time as RecoMelon learns from how shoppers engage with the recommendation panel on your specific Shopify store.