Enterprise e-commerce sites struggle to leverage product catalog data effectively for search optimization. Ryland M Bacorn from Boca De shares his proven framework for implementing vector embeddings across large-scale product catalogs, demonstrating measurable improvements in site search relevance and internal linking strategies. The discussion covers his three-phase implementation approach: establishing specialized database infrastructure with tools like Pinecone, building proof-of-concept prototypes using the 80/20 rule for high-impact product segments, and scaling embeddings beyond SEO into site search, product recommendations, and automated content generation systems.

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