We all know the way consumers discover products is undergoing its most profound transformation since the advent of digital commerce.
For decades, SEO shaped visibility through keywords, backlinks, and crawlable content. Now, generative engines try to understand products the way people do by looking at their details, purpose, and context. That level of comprehension relies on connected data: granular attributes, clean schema, structured metadata, and contextual language that together help AI understand what a product is, when it’s relevant, and who it’s for.
This report gives retailers a clear framework for structuring product data so generative engines can reliably understand, match, and surface their products across modern search and shopping environments.
Sponsored by Lily AI
Lily AI is ushering in the age of “AI-first” modern retail by bridging the gap between how merchants describe products and how customers actually search, speak, and shop–at scale. Founded by female entrepreneurs, Lily harnesses the power of generative AI, computer vision, natural language processing, machine and deep learning to transform search and product discovery, everywhere. The no-code retail AI platform decodes the language of today’s consumer for fashion, home, and beauty retailers and seamlessly integrates the customer perspective and vernacular across the entire retail ecosystem and the product life cycle. From eCommerce to Google Ads and beyond, Lily is accelerating revenue growth while delighting shoppers with intuitive, relevant experiences.