There is no single magic tag that guarantees visibility in ChatGPT Search or Google AI Overviews. The practical approach is to make pages crawlable, answer-first, and trustworthy: use server-rendered HTML, expose crawlable links, publish concise question-answer content, keep metadata and sitemaps current, and build authority around the entities and topics you want cited.
Property data pages perform better in AI-driven discovery when they are easy for crawlers to access and easy for language models to extract. That means the page should answer the main question near the top, use clean headings, and keep paragraphs self-contained so they can stand on their own when quoted or summarized. It also means avoiding overreliance on client-side interfaces for critical navigation and making sure important pages are listed in sitemaps and linked internally. Google has said there is no special markup required for AI features beyond normal search eligibility, and OpenAI makes clear that inclusion depends on crawl access rather than magic tags. For property-data companies, the additional win is publishing source-specific explainers that demonstrate why your dataset is credible, current, and distinct.
Start with crawlability, because nothing downstream matters if the page cannot be read: server-rendered HTML, real links rather than script-driven navigation, a correct canonical, and a current sitemap. Then make the page answer-first, with a heading that matches the question and the answer stated immediately beneath it.
Add structured data next so machines can parse the page without inference, and keep it consistent with what a reader actually sees. Finally, work on entity signals — a clear Organization identity, consistent naming, and corroboration from sources outside your own domain. That last piece is slowest and hardest to fake, which is exactly why it carries weight.