Lily AI Fashion Retail Customer Placeholder Logo. Large Multi-Brand Retailer Boosts Product Discovery from On-site Search by 8.5%, Projecting to $22M Increase in Revenue Across Brands


increase in discoverability


increase in demand


increase in revenue

In 2021, a large, multi-brand speciality retailer had been encountering multiple challenges in ensuring that their extensive catalog of clothing and apparel was being discovered by shoppers on their online properties – most specifically via on-site search.

The retailer turned to Lily AI and its product data enrichment platform for help.

Fashion Retailers

The Problem

Given its challenges, the retailer saw a need for better product data as a huge value unlock for on-site search, one that might lead to an increase in the number of relevant products shown to a customer, thereby improving discoverability and ultimately demand for that product.  

A subset of CC’s were provided to Lily AI to add product attribute tagging to, with a control vs. product that was not tagged using Lily AI. The primary KPI this retailer sought to measure was demand and how it was impacted based on product views, product discoverability and search intent. 

The retailer was looking to improve their core customer journey with deep and consistent product attribution, from Lily AI, and to show an 8-digit lift in topline revenue. The approach needed to be a low lift integration and implementation on the brands side as well, which Lily AI was able to provide.

Lily AI’s output for this search test was then deployed into Bloomreach for full implementation.

A rack of various pieces of women's clothing from a fashion retailer.Image of a young woman ready to make an online retail purchase with her credit card.Various men's fashion retail and apparel items laid out on a table.


The multi-brand retailer saw very rapid and very measurable results in on-site search using the Lily AI platform. Product attributes assigned by using Lily AI increased by an average of 33% (and from 8 attributes to 24 in 1 particular product example). The increase in search-driven demand was determined to be all net additional topline revenue, and was not displacing sales from other avenues. 

This led to an 8.5% increase in discoverability, measured by the percentage of PDP views that came directly from search – thus increasing the likelihood of a relevant product to be shown to a customer based on their search query. This in turn resulted in a 3.3% increase in demand driven purely from search, projecting to a $22M increase in revenue across all brands.

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