<\/p>\n
Google and Bing publish guidelines for traditional search engine optimization and provide tools to measure performance.<\/p>\n
We have no such instruction from generative engine providers, making optimization much more challenging. The result is a slew of misleading and uninformed speculation.<\/p>\n
The importance of Schema.org markup is an example<\/a>.<\/p>\n I\u2019ve seen no statement or indication from a large language model regarding structured data markup, including Schema.org\u2019s.<\/p>\n Google has long advised using such markup for traditional organic search, stating<\/a>:<\/p>\n Google Search works hard to understand the content of a page. You can help us by providing explicit clues about the meaning of a page to Google by including structured data on the page.<\/em><\/p>\n The search giant generates rich snippets<\/a> from select structured data and gathers info on a business from additional markup types, such as Schema.org\u2019s Organization<\/a>, FAQPage, and Author.<\/p>\n While answers from Google\u2019s AI Mode tend to come from top organic rankings, we don\u2019t know the impact of structured data on AI agents or crawlers.<\/p>\n Unlike Google, LLMs have no native indexes. They generate answers based on their training data (which doesn\u2019t store URLs or code) and from external search engines such as Google, Bing, Reddit, and YouTube.<\/p>\n To access a page, LLMs can (i) query traditional search engines, indirectly relying on structured data markup such as Schema.org, and (ii) crawl a page directly to fetch answers.<\/p>\n Many businesses don\u2019t understand Schema.org markup, and thus retain the GEO services that claim implementing it will increase AI visibility.<\/p>\n Don\u2019t be misled. I\u2019ve seen no reputable case studies demonstrating that structured data improves AI mentions or citations. Implementation, moreover, is easy (and cheap) with apps and plugins<\/a>.<\/p>\n Instead, focus on the proven long-term tactics:<\/p>\nSchema for LLMs?<\/h3>\n
AI Visibility<\/h3>\n