GEO: Optimizing for LLM retrieval, not just Google

Search is splitting in two. Traditional Google SEO still matters, but a growing share of qualified traffic now comes from LLM-based search: ChatGPT with browsing, Perplexity, Claude web search, and Gemini.

These systems do not rank pages with PageRank. They retrieve and synthesize. The optimization playbook is different.

How LLMs retrieve content

Large language models with web access typically:

1. Rewrite the user query into search terms
2. Fetch top search results
3. Chunk and embed the content
4. Retrieve relevant chunks via vector similarity
5. Synthesize an answer with citations

This means your content must be retrievable and synthesizable.

Semantic density over keyword density

Traditional SEO teaches keyword placement: H1, first paragraph, image alt text, meta description. LLMs do not read meta descriptions. They read the actual text, chunk it, and compare embeddings.

What works:

• Clear topical boundaries: Each page should have a distinct, well-defined subject. LLMs struggle with pages that cover five unrelated topics.
• Entity-rich copy: Use precise nouns. "PostgreSQL 16" is more retrievable than "our database."
• Structured arguments: Use headings, lists, and tables. These create natural chunk boundaries.
• FAQ sections: Direct question-answer pairs match LLM query patterns exactly.
• Citations and sources: LLMs prefer content that references authoritative sources.

What to change

Restructure content with LLM retrieval in mind:

1. Split broad pages into focused, single-topic pages
2. Add explicit definitions for technical terms — LLMs reward unambiguous nouns
3. Restructure H2s as questions users actually ask
4. Include comparison tables for products and services
5. Surface author and expertise signals for E-E-A-T

What changes when it works

Over a few months, with consistent structural improvements:

• Citations in LLM answers rise meaningfully — the structural changes give models a clean chunk to pull from
• Referral traffic from Perplexity and similar systems becomes a measurable channel
• Brand mention rate in AI-generated answers climbs
• Traditional Google rankings also improve — structured content helps both kinds of retrieval

Where this goes

GEO is becoming a standard discipline alongside SEO. The fundamentals overlap: clear structure, fast loading, authoritative content. The execution differs.

Start by auditing your content for semantic clarity. If an LLM cannot chunk and retrieve your key points, you are invisible to a growing slice of search.