Optimizing Shopping Ads for Natural Language Search

Quick start guide to harnessing AI for enriching product data with customer-centric attributes

Download Lily AI’s quick start guide for Optimizing Shopping Ads for Natural Language Search to see how AI can automatically optimize Performance Max (PMax) + Shopping campaigns with natural consumer language.

The secret? Using AI to operationalize natural consumer language at the product micro-attribute level to capture all the ways that consumers speak, shop, and search today. CMOs will love that, in addition to better shopping ad performance, product attribute enrichment also boosts SEO and organic product listing performance as well as on-site search results. A true Paid+Organic+Owned triple threat!

Download the quick start guide for an overview, plus case studies.

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.

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