How to Structure a Web Page So AI Can Extract the Right Facts

AI assistants extract facts from pages in small pieces: a sentence, a list item, a table row. A page with a clear heading order, short answer-first paragraphs, real HTML lists and tables, and basic schema markup is much easier to extract from correctly. A page that relies on design alone, with facts scattered across sliders and images, is easy to misread.

Think in Extractable Units

Ask of each important fact: could it be lifted out on its own and still make sense? “It costs €40” is unclear outside its context. “A standard bike service at our Nantes workshop costs €40” stands alone. Write key sentences so they carry their own subject.

Use a Logical Heading Order

• One main heading per page that states the topic.
• <h2> headings for the main questions the page answers.
• <h3> headings for sub-points under those questions.

Headings written as questions or clear labels (“Prices for Residential Clients”) help AI connect a heading to the answer below it. Avoid headings used only for styling, such as a large “Discover More” above unrelated content.

Put the Answer Directly Under the Heading

The first one or two sentences under each heading should answer it. Details, exceptions and examples come after. This mirrors how assistants often build answers: they look for a direct statement, then supporting points.

Use Real Lists and Tables

When content is a set of items or steps, use proper HTML lists (<ul>, <ol>). When you compare plans, sizes or prices, use a real HTML table rather than an image of one. Page builders sometimes create lists out of separate text boxes; check the page source to be sure.

Keep Facts in Text, Not Only in Visuals

1. Opening hours shown only in an image: add them as text.
2. Prices inside a carousel that loads after a click: add a plain summary.
3. Product specs in a downloadable PDF only: add the key specs on the page.
4. Important details revealed only by JavaScript tabs: make sure they are present in the HTML.

Add Schema Markup for the Basics

Structured data in JSON-LD format tells machines what a page describes: an organization, a local business, a product, an FAQ. It does not guarantee anything, but it reduces ambiguity about names, addresses, prices and ratings. Common types include Organization, LocalBusiness, Product and FAQPage. Make sure the markup matches what is visible on the page. Our guide to optimizing schema markup for AI extraction goes deeper.

Reduce Noise

Long cookie banners, repeated menus and pop-ups do not usually stop extraction, but very heavy pages with little real text can. Keep the main content near the top of the HTML and make sure the page loads without requiring a login.

Test a Page in Five Minutes

• View the page with styles turned off or in reader mode. Is the order still logical?
• Copy only the first sentence under each heading. Do they answer the headings?
• Run your structured data through a schema validator.
• Ask an assistant that browses to summarise the page, and check for errors.

For broader formatting advice, read LLM content formatting guidelines.

How Keboost Helps

Keboost shows how AI assistants currently describe your business and where facts are missing or wrong, which points to the pages that need better structure. It then helps you create and distribute well-structured content. Run a free AI visibility check to find the pages to fix first.