What Is LLMO? How to Optimise Your Content for AI

LLMO is a new acronym. The work behind it has been brewing for years.

LLMO — Large Language Model Optimisation — is the practice of adapting your content so that AI systems can find, understand, and cite it. It overlaps heavily with SEO. It's also distinct in a few important ways.

If you've watched organic traffic dip since mid-2024 without an obvious cause, LLMO is probably part of the explanation. Here's what it is and what to do.

What LLMO actually is

LLMO sits in the same family as SEO and AEO. The difference is what you're optimising for:

• SEO — ranking on a search results page.
• AEO — being pulled into answer boxes, snippets, and voice responses.
• LLMO / GEO — being mentioned or cited inside a generative AI's response.

The acronyms blur — LLMO, GEO, AI SEO — and many marketers use them interchangeably. The work is similar regardless of label.

Why traffic dropped after mid-2024

Three changes converged in 2024 and have compounded since:

1. AI Overviews launched broadly. Google's AI Overview feature began appearing on a large share of informational queries, pushing organic listings below the fold.
2. ChatGPT crossed 200M users. Conversational AI moved from novelty to mainstream research tool, eating into Google's informational query share.
3. Zero-click queries climbed. More than half of all searches in many categories now end without a click to any website.

None of these are reversible. They're structural shifts in how people find information.

What the research actually says works

Three early academic and industry studies (Princeton's GEO paper, Ahrefs and Semrush analyses, Peec AI's mention tracking) converge on a similar list of citation-driving factors:

• Quoting authoritative sources in your content increases citation likelihood by 30–40%.
• Including statistics with attribution raises mention rates substantially across all major AI platforms.
• Adding fluency and clear structure (descriptive headings, lists, tables) outperforms keyword stuffing.
• Establishing entity associations — repeated co-mentions of your brand with topical terms across the web.

The pattern: write like a credible source citing other credible sources, and you start to look like one.

Content changes that move citations

Lead with the answer

AI models often pull the first paragraph as their direct quote. If your opening paragraph buries the lead behind context, you lose. Inverted-pyramid structure wins.

Write standalone sentences

Each significant sentence should make sense without surrounding context. "This drops conversions by 23%" is useless to an AI — it can't tell what "this" refers to. "Adding more than three form fields drops conversions by 23%" is citation-ready.

Use specific, attributable numbers

"A lot," "many," "some studies show" — these all paraphrase away. Specific numbers with attributions get quoted verbatim.

Add comparison tables

Tables are extracted disproportionately often. A well-structured comparison table can drive citations for the page it lives on for years.

Technical changes

On the technical side, three signals matter most:

1. Server-side rendering. Many AI crawlers don't execute JavaScript. If your content only appears after hydration, it may be invisible.
2. Schema markup. Article, Organization, Product, FAQPage — the more explicit, the better.
3. Accessible HTML. Real `<h2>`, real `<ul>`, real `<table>` — not styled `<div>` soup.

Where to start this week

1. Audit your top 10 pages. Are the openings answer-first? Are claims attributed? Do they have schema?
2. Rewrite three pages using inverted-pyramid structure and quotable claims.
3. Add or update schema on those pages.
4. Run a prompt set against ChatGPT, Perplexity, and Gemini to baseline your current citation rate.

LLMO compounds. The pages you rewrite this quarter become the source the AI cites in 18 months — when its training data refreshes. Start now or start late.