Case Study: Large Multi-Brand Retailer boosts product discovery and revenue with Lily AI

Large Multi-Brand Retailer Boosts Product Discovery from On-site Search by 8.5%, Projecting to $22M Increase in Revenue Across Brands

Large Multi-Brand Retailer, a multi-brand specialty retailer, was struggling to make its extensive clothing and apparel catalog more discoverable on its online properties, especially through on-site search. To improve product data and better connect shoppers with relevant items, the retailer turned to Lily AI and its product data enrichment platform.

Lily AI added product attribute tagging to a subset of the retailer’s catalog and then deployed the enriched output into Bloomreach for full implementation. The result was a 33% average increase in product attributes, an 8.5% lift in discoverability, and a 3.3% increase in search-driven demand, projecting to a $22M increase in revenue across brands.