At the 2024 CommerceNext, the Lily AI team was on the scene and helping brands and retailers bring humanity to shopping. In fact, our President Ahmed Naiem was joined on stage by Tapestry’s Vice President of Global Digital Product and Omnichannel Innovation, Mandeep Bhatia, to share how Lily AI is helping Tapestry do just that.
Their session “Results Your CFO Can Believe In: How Tapestry Is Winning With AI” illustrated two big problems in retail today, and the financial impact of solving it:
- Customer speak is vast: It’s trends. It’s styles. It’s occasions and micro-occasions. It’s vamp coverage and fabric quality, plus synonyms for each of these highly-detailed and often subjective attributes that matter since we all have our unique preferences and ways of describing what we want.
- Traditional “merchant speak” is narrow: It’s fabric. It’s color. It’s hardware. Most products are described today using a very common yet narrow taxonomy of product attributes that only begin to scratch the surface for how we discover and shop for new items.
The widening gap between the language of the customer and the language of brands and retailers can be a challenge—or an opportunity.
In their session, Ahmed and Mandeep went beyond ROI and ROAS to explore how Tapestry is approaching their investment in Lily AI to drive both significant and immediate impact. Specifically, Tapestry partnered with Lily AI to maximize product discovery via Google Search and Site Search. They are also planning to expand the partnership into e-commerce to further personalize customer shopping experiences across all of Tapestry’s brands.
How Lily AI Optimizes Search for Tapestry
Ahmed showed how Lily AI enriches product attributes with customer-centric language to connect people to products. He used the iconic Y2K-inspired Tabby Shoulder Bag by Coach as an example.
First, he showed off the product attributes that were initially associated with the bag. These attributes and images were fairly standard. 
From there, Lily used a combination of generative AI, computer vision, natural language processing, machine learning, and deep learning which all analyzed the item and suggested more thorough, customer-centric attributes. Dozens more attributes, attribute synonyms, and macro- and micro-fashion trends were then included in the handbag’s product attributes, supercharging its discoverability when distributed to Google Merchant Center and their e-Commerce platform
The results? Lily AI boosted Google Search performance for Tapestry!
Now, for example, products like this version of the Tabby bag are much more easily found on both Google Search and on Coach’s website via site search. When a consumer searches for something like “glamorous adjustable crossbody for luncheon” they’ll easily find relevant product results that lead to a sale.
The Lily AI-Tapestry collaboration drove high-single and double-digit lifts across SEM, SEO, and Site Search key metrics:
- ⬆️ Conversions
- ⬆️ Average Sales per View
- ⬆️⬆️ Avg. sales per SKU (SEO)
- ⬆️⬆️ Avg. PDP views per SKU (SEO)
- ⬆️⬆️ Avg. sales per SKU (SEM)
- ⬆️⬆️ Avg. PDP views per SKU (SEM)
If you’re ready to improve the effectiveness of both organic and paid advertising strategies on Google Search and beyond, let’s chat!
