Schema Markup and AI Search - The SEO Debate скачать в хорошем качестве

Schema Markup and AI Search - The SEO Debate

Schema Markup and AI Search - The SEO Debate There's a right and wrong way to do it! Find out more: 10 SEO Moves That Get Websites to Page 1 — Free Google Ranking Blueprint: https://bit.ly/40ANbAY Overwhelmed? Contact us at 816-261-9194 for the Done for You. The sources present a discussion from a Reddit thread on r/SEO, focusing on a case study claiming that Large Language Models (LLMs) do not utilize schema markup for training or improving search visibility. Mark Williams-Cook's experiment suggests that the tokenization process used by LLMs "destroys" the structural integrity of schema data, making it indistinguishable from regular text. However, other commenters challenge this narrow conclusion, arguing that while tokenization may flatten the schema, it can still be used by pre-LLM retrieval systems, such as the Knowledge Graph, before the LLM processes the content. The conversation highlights a growing debate within the SEO community about whether structured data offers direct benefits for AI search results, with some suggesting that relying on schema for AI visibility is a misguided myth or a misunderstanding of how AI systems function. Ultimately, the thread explores the divergence between classic SEO strategies for rich snippets and optimization techniques for emerging AI search capabilities.