How to Structure Web Pages So AI Retrieval Systems Can Use Them

To structure content for retrieval systems, write each section so it can stand alone: a descriptive heading, a first sentence that states the point, and no reliance on text elsewhere on the page. Many AI search tools retrieve passages rather than whole pages, so a section that only makes sense with its neighbours is likely to be misread or skipped. Clean HTML, clear headings and plain-text facts make this much easier.

How Retrieval Sees Your Page

Retrieval-augmented systems typically break documents into chunks of text, turn them into numeric representations, and match them against the question. The best-matching chunks are passed to the language model. Exact methods differ between tools and are not all public, but the practical lesson is consistent: each part of your page may be judged on its own.

Rule 1: Headings That Describe, Not Decorate

A heading like “Our Approach” tells a retrieval system nothing. “How long does laser hair removal take per session?” tells it exactly what follows. Use headings that a reader could understand without seeing the rest of the page.

Rule 2: Repeat the Subject in Key Sentences

Inside a chunk, “it” and “this” may lose their meaning. Compare:

• Weak: “It costs between 80 and 120 euros.”
• Strong: “A single laser hair removal session for the lower legs costs between 80 and 120 euros at our Madrid clinic.”

This feels slightly repetitive to a human reader, but it makes each passage accurate on its own.

Rule 3: Keep Sections Focused and Moderate in Length

One sub-question per section. Very long sections mix topics; very short ones lack context. A few short paragraphs or a list under each heading is a good target.

Rule 4: Use Semantic HTML

• Real heading tags (<h2>, <h3>) in logical order, not bold text styled as headings.
• Real lists (<ul>, <ol>) for steps and options.
• Real tables with header rows for comparisons, not images of tables.
• Main content in the HTML, not injected only by scripts.

Rule 5: Put Facts in Text, Not Only Visuals

Prices, dimensions, opening hours and specifications should exist as plain text. If a chart shows a key trend, describe the trend in a sentence beneath it.

Rule 6: Reduce Boilerplate Noise

Huge menus, repeated cookie notices, long footers and sidebars full of links can end up in extracted text. Keep the main content clearly marked, for example inside a <main> or <article> element.

Rule 7: Make Tables Self-Explanatory

Each table should have a caption or heading above it saying what it compares, and column headers with units, such as “Price (EUR per month)”. A table of bare numbers loses its meaning when extracted.

Before and After Example

Before: a page titled “FAQ” with twenty questions in an accordion that loads by script, answers starting with “Yes, as mentioned”.

After: the same questions as <h3> headings in plain HTML, each answer starting with a full sentence that restates the question’s subject, grouped under <h2> topics like “Pricing” and “Delivery”.

For the bigger picture on retrieval, read content for RAG systems. If you are building your own internal system, see preparing content for a RAG implementation.

How Keboost Helps

Keboost tracks whether your pages are mentioned and cited for your customers’ prompts across ChatGPT, Gemini, Claude, Perplexity and Copilot, and creates focused content structured for retrieval. Structure improves the chances of being used; it does not guarantee it. Run a free AI visibility check to see which pages to restructure first.