Your website might be beautifully designed. It might rank on Google. But if it’s not structured in a way that AI models can read, understand, and re-use, it won’t be cited in AI-generated answers.
This section shows how to write and format pages that get picked up by ChatGPT, Perplexity, Bing Copilot, and other LLM-based answer engines.
Let’s break down the tactics that work.
Think like a model: What does it want?
Language models are fast but lazy. They want:
- Fast-loading pages
- Clear headings and structure
- Specific, data-rich paragraphs
- Easy-to-copy lists, tables, or comparisons
- Content that can be dropped into an answer with minimal cleanup
If your content feels like fluff, buried in waffle, or too abstract, it gets skipped.
Your job? Be the easiest source to cite.
Elements of an LLM-friendly page
| Element | Why it matters |
|---|---|
| Long, descriptive URL | Models often read the slug. /compare-top-crm-tools-2025 > /blog/crm123 |
| Clear H1 + H2s | Helps models skim for topic segments and pull correct chunks |
| Intro with summary | Gets the TL;DR up top. May be reused directly as answer summary. |
| Q&A structure | Especially useful for follow-up queries and feature-level answers |
| Comparison tables | Structured info > prose. Tables get copied, parsed, reused. |
| Schema markup | Helps engines interpret authorship, product info, FAQs, and reviews |
| Bullet lists | Easy for LLMs to lift pros, cons, steps, etc. |
| Author name + bio | Authorship boosts trust (especially with Google AI Overviews) |
Semantic chunking: Write answer-ready paragraphs
Break your content into self-contained paragraphs that each answer a micro-question.
Bad example:
“Our tool has a lot of great features. It’s flexible and powerful. You can use it in different ways.”
Better example:
“[Tool] lets users automate daily tasks by connecting Gmail, Notion, and Slack. Setup takes under 5 minutes, and no coding is required.”
Ask yourself:
- Would this paragraph make sense pulled out on its own?
- Would I sound smart if I quoted this in a report or newsletter?
That’s what LLMs are looking for.
Use structured data (schema)
Schema markup isn’t new, but it still helps. Focus on these types:
ArticleorBlogPosting– includeauthor,headline, anddatePublishedFAQPage– for Q&A sectionsProduct– for product spec pagesHowTo– if you’re writing tutorials or step-by-step processes
See Google’s Structured Data Documentation for the latest.
Even if AI models don’t rely only on schema, it reinforces trustworthiness.
Pro tip: Use HTML tables to dominate comparison queries
Models love structured comparisons. You should too.
Build pages that use tables like:
| Feature | Tool A | Tool B | Tool C |
|---|---|---|---|
| Free Plan | Yes | No | Yes |
| Integrations | Slack, Stripe | Zapier only | Slack, Teams |
| Languages | 5 | 1 | 3 |
| Support | Email, Chat | Email only | 24/7 Chat |
Tables like this often get reused verbatim.
Bonus: they make your content more human-friendly, too.
Refresh frequently, especially if your topic is seasonal
LLMs and search APIs often favor pages with recent timestamps or “2025” in the title/slug/meta.
If your content changes yearly (e.g. best tools for 2025), consider:
- Updating the year in your title and slug
- Redirecting from old URLs if needed
- Updating the publish date when making meaningful edits
But don’t abuse this. Misleading timestamps can backfire.
Test what actually gets picked up
Every niche behaves a bit differently. So:
- Track how often your URLs are cited (use a tool or manual queries)
- A/B test adding tables, author schema, FAQ sections
- Monitor which paragraphs are being reused (or ignored)
If the same 3 pages always get cited, study how they’re written and borrow the structure.
In the next section, we’ll look at how to earn citations from other sources – because sometimes, that’s even more important than your own site. Ready to proceed to Winning Mentions in Other Places (Off-Page & Citation Optimization)?
AEO & GEO Handbook 2026 by People, business, and AI systems clarity coach Mike Moisio