Case Study: a large multi-brand retailer boosts revenue per visit with Lily AI

Large Multi-Brand Retailer lifts revenue per visit 0.65% with Lily AI

A large multi-brand retailer sought to improve its online shopping experience by offering personalized product recommendations akin to an in-store stylist. Their existing Certona recommendation engine, however, lacked the ability to leverage granular product details. The retailer turned to vendor Lily AI and its product Attributes platform to address this challenge.

Lily AI implemented a solution by layering its granular product attribution data onto the retailer's existing Certona engine. This provided more context and produced highly relevant recommendations. The results included a 0.65% increase in revenue per visit, a 0.6% lift in average order size, and a 0.62% increase in overall demand, which projects to an incremental $20-30M in annual revenue for the retailer.