Customer-centric product recommendations that boost revenue per visitor.

Lily AI’s extensive product data enrichment and AI-powered product taxonomy helps bring online shoppers product recommendations that meet the moment. We ensure your customers are being presented with items that truly match the attributes that make up their personal style and preferences, giving them all the right reasons to make that second click.

Results for Soft Living Top
Complete Your Look - Powered by Lily AI
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Complete Your Look - Powered by Lily AI
Results for Neotenic Accent Chair
Complete Your Room - Powered by Lily AI

How it works

Lily AI uses its extensive product data to train its AI models, which means we know more about what customers are actually browsing and buying – and why. Now, you can deliver better product recommendations with visually similar matching and algorithms based on Lily AI’s 20,000+ product attribute taxonomy.

Woman smiling who is happy after online shopping a fashion website's recommendations.

Start matching shoppers to the products they actually want.

Increase your recommendation relevance by presenting a product set that’s been built by understanding how shoppers really describe the products they’re looking for – as well as the relationships between product attributes.

You can now increase the number of relevant products shown to each customer – and just as important, stop recommending items that don’t match what they truly want.

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Men's jacket with attribution hotspots highlighting product details.

Supercharge social UGC with AI-powered recommendations

Now your users can upload a picture, and see all of the products in the catalog that closely match what’s in the photo. This drives highly-relevant recommendations for users, and makes user-generated images instantly shoppable, moving beyond text-based keyword searches and connecting with a customer’s eyes, not their fingers.

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The Practical guide to e-commerce product recommendations.

The Practical Guide to E-Commerce Product Recommendations

Matching shoppers to the products they actually want via recommendations is a constant challenge across the e-commerce landscape. With Lily AI’s platform and product attribution data, brands can recommend products more effectively based on style, trend, and occasion.  
Fashion model posing a gray sweater representing the power of Lily AI's recommendations.

Lily AI Recommendations Increase RPV for Large Multi-Brand Retailer by +0.65%, Leading to Additional $20-30M in Incremental Demand

The challenge of matching shoppers to the products they actually want via recommendations is a constant across the retail e-commerce landscape.
A female influencer holding her phone taking an selfie for social media.

Product Discovery in the Influencer Age: How to Capitalize on Social Media Fads

Glow-up your product discovery strategy and convert Gen Z social media fads into sales with the help of Lily AI’s domain expertise and robust product attribution taxonomy.
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