LLM SEO
LLM SEO: get cited and recommended inside AI answers
LLM SEO is the work of getting large language models like ChatGPT, Gemini, Claude, and Perplexity to name, cite, and recommend your brand inside the answers they generate. The unit of value is a groundable passage with clear provenance, not a ranked link. You win by making your content the source the model reuses.
How LLM SEO works
LLM SEO has three jobs that run together. Engineer your own pages for passage extraction and clean retrieval. Influence the third-party sources models already cite for your category, including Reddit, G2, analyst round-ups, and comparison sites. Measure citation share and recommendation rate on a fixed prompt set across every major model, and respond within days when something drifts.
- •Open every priority page with a 40 to 60 word answer block, then supporting evidence with numbers and named sources.
- •Ship FAQPage, Article, Product, and Organization schema in the initial HTML, not the hydrated DOM.
- •Keep facts fresh and dated; models down-weight stale or undatable claims.
- •Earn presence in the sources the models already trust, because they quote the strongest third party, not the loudest brand.
LLM SEO: common questions
What is LLM SEO?
LLM SEO is the practice of optimizing your content so large language models like ChatGPT, Claude, Gemini, and Perplexity name, cite, and recommend your brand inside the answers they generate. The unit of value is a groundable passage with clear provenance, not a ranked blue link. It overlaps with traditional SEO infrastructure but optimizes for a different outcome: being the source an AI reuses, not the page a user clicks.
Is LLM SEO the same as GEO or AEO?
Effectively yes. LLM SEO, GEO (generative engine optimization), and AEO (answer engine optimization) describe the same discipline with different labels. LLM SEO is the search-friendly term buyers type; GEO and AEO are the technical names practitioners use. The deliverables are identical: passage-level answer blocks, schema, source-pool influence, and citation measurement across the major models.
How is LLM SEO different from traditional SEO?
Traditional SEO asks which page should rank for a query. LLM SEO asks what information a model can responsibly reuse to construct an answer. A page can rank well in Google and never be cited by ChatGPT because the answer-grade evidence is buried, the schema is missing, or a stronger third party is quoted instead. LLM SEO favors a 40 to 60 word answer near the top of the page, structured FAQs, factual density, freshness, and presence in the sources models already trust.
How do you measure LLM SEO results?
On a fixed prompt set run across every major model: share of model (how often you are named), citation rate (how often your URL is cited), recommendation rate (how often you are actively recommended on buying-intent prompts), and citation drift (week-over-week movement in the cited source pool). Cite Solutions ships these as a weekly dashboard with a written readout.
How long does LLM optimization take to work?
Most programs show measurable share-of-model lift within 60 to 90 days on prompts that already have a healthy source pool. Reliable recommendation rate on commercial prompts is typically a six to twelve month effort. Because models refresh their cited sources continuously, LLM SEO works best as an ongoing managed program rather than a one-time project.
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