Beauty shoppers are visual. They choose products by shade, finish, and packaging — not by ingredient lists. Visual AI surfaces similar products the way a knowledgeable beauty advisor would, driving larger baskets and complete routines.
Shade matching drives purchase decisions. A customer buying a warm-toned foundation wants bronzer, blush, and lip colour in the same colour family. Standard "frequently bought together" recommendations are driven by crowd behaviour, not the individual shopper's palette — and they often miss the mark entirely.
Complete routine discovery is the real revenue opportunity. Skincare and makeup shoppers buy in routines, but most stores show individual products in isolation. Recommending the serum alongside the moisturiser that shares the same texture and packaging aesthetic drives basket sizes that single-product views never will.
Warm nudes, cool berries, deep plums — the AI reads colour from product imagery and recommends within the same palette family, so every suggestion feels intentional.
Matte, satin, glossy, metallic, shimmer — each finish appeals to a different customer. The AI keeps recommendations within the customer's preferred finish profile.
Lightweight serums stay with other serums. Rich creams connect to balms and butters. The AI reads product texture from packaging and description cues to group by formula type.
Clean, minimal skincare brands share a visual language. Maximalist, colourful cosmetics attract a different buyer. The AI groups by brand aesthetic so recommendations feel curated, not random.
Warm tones connect to warm tones. Cool palettes stay together. Customers see their whole colour world, not a random product list.
Cleanser, toner, serum, moisturiser — if they share a brand aesthetic, the AI connects them automatically on every product page.
Foundation shoppers discover bronzers and blush. Eye palette shoppers find matching mascaras and liners.
AI analyses product images immediately on install. No shade tagging, no formula mapping, no manual rules.
Shade-matched recommendations across lip, eye, and face products led customers to build complete looks rather than single-product purchases.
Grouping products by texture and packaging aesthetic meant shoppers explored 4–5 products per visit, discovering the full routine rather than one item.
Customers who built complete routines in one session returned within 45 days to replenish or extend — at significantly higher lifetime value.
Recommends within the same shade family — warm tones stay warm, cool tones stay cool, always.
Matte, gloss, shimmer — customers who prefer one finish see more of what they love, not random products.
Connects products that belong in the same routine, driving multi-step basket builds automatically.
New shades and formulas get recommendations immediately — no purchase history or tagging needed.
Help customers build complete routines and find their perfect shade matches. Free plan available.
Install simage — Free