Case Study: Large Multi-Brand Retailer boosts revenue per visit with Lily AI

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

Large Multi-Brand Retailer, a large multi-brand specialty retailer, wanted to improve the relevance of its online product recommendations so shoppers could find items that better matched their style and preferences. The company turned to Lily AI and its Attributes platform after finding that its existing recommendation engine could not capture granular product details well enough to personalize suggestions.

Lily AI added more detailed product attribute data to the retailer’s existing Certona recommendation engine, enabling more hyper-personalized product recommendations. As a result, the retailer saw a 0.6% increase in AOS, a 0.65% increase in RPV, and a 0.62% increase in overall demand, translating to an estimated $20–30M in additional incremental demand.