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On-Page Optimization (for AI Search)

Editing an individual page (its structure, schema, and content) so AI engines cite it, based on the pages they already cite for a given prompt.

On-page optimization for AI search is the practice of changing one page to close the gap between it and the competitor pages AI engines actually cite for a question. Where traditional on-page SEO optimizes for keyword rankings, AI on-page optimization optimizes for retrieval and citation: adding the FAQ schema, comparison table, concrete statistics, entity mentions, freshness, or heading structure that the cited sources have and your page lacks. Because the changes are grounded in real cited pages rather than generic best practices, and verified against those sources so nothing is invented, each edit maps to a specific answer you're trying to win, and the result can be measured after you ship it.

A pricing page isn't cited for "best CRM for startups." Adding a paste-ready FAQ schema block and a comparison table (the two elements every cited competitor page has) turns it into a candidate for the answer.

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