Generative Engine Optimization (GEO): How to Get Cited by ChatGPT, Claude and Perplexity

A growing share of buying research now happens inside AI assistants instead of Google's ten blue links. When someone asks ChatGPT "what's the best attribution tool for Shopify," the brands that get named win the consideration set before a website is ever visited. Optimizing for that moment is called Generative Engine Optimization (GEO) — sometimes Answer Engine Optimization (AEO) — and it is learnable.

How AI assistants choose sources

Assistants cite content through two paths. First, training data: what the model absorbed about your brand before its cutoff. Second — and far more actionable — retrieval: live web search that ChatGPT, Claude, Perplexity and Google's AI Mode run at answer time, then summarize with citations. Retrieval favors pages that are crawlable, fast, factually dense, and structured so a machine can extract an answer in one pass.

The technical layer

1. Let AI crawlers in. Explicitly allow GPTBot, ClaudeBot, PerplexityBot and Google-Extended in robots.txt. Many sites block them via default bot protection and vanish from AI answers without knowing.
2. Ship an llms.txt. The emerging llmstxt.org convention — a markdown index at /llms.txt describing your site and key pages — makes machine ingestion trivial. A companion llms-full.txt with full text costs nothing and maximizes surface area.
3. Use structured data everywhere. Schema.org JSON-LD (Article, FAQPage, ItemList, Organization) is how you tell machines exactly what each page asserts. FAQPage markup in particular maps one-to-one onto how assistants answer questions.
4. Server-render everything. Retrieval crawlers are impatient with JavaScript. Static or server-rendered HTML gets read; client-rendered SPAs often get skipped.

The content layer

Write answers, not essays. Assistants extract self-contained passages. Lead sections with a direct one-to-three-sentence answer, then elaborate. A page structured as question-heading followed by immediate answer gets quoted; a page that buries the answer in paragraph six does not.

Be factually dense and citable. Numbers, definitions, comparisons and named entities give a model something concrete to quote. "Klaviyo is the default lifecycle platform for Shopify brands" is citable; "there are many great email tools" is not.

Cover the comparison queries. "X vs Y," "best tools for Z," "alternatives to X" are the highest-commercial-intent prompts users give assistants. Honest comparison content — with real trade-offs, not affiliate cheerleading — is what retrieval engines prefer to cite.

Build entity consistency. Your brand name, description, and category should read identically across your site, LinkedIn, Crunchbase and directories. Models resolve entities across sources; inconsistency dilutes you.

Measuring it

GEO measurement is young but real: track referral traffic from chatgpt.com, perplexity.ai and claude.ai in analytics; run your money prompts through the major assistants monthly and log whether you're cited; tools like Profound now automate share-of-voice tracking across AI answers. Expect assistant referrals to be low-volume but absurdly high-intent — visitors arrive pre-sold by the citation.

The strategic point

Classic SEO and GEO are about 80% the same work: crawlable, fast, structured, genuinely useful content. The 20% delta — llms.txt, answer-first formatting, entity consistency, comparison coverage — is cheap to implement now and compounding, because early citations feed the next generation of training data. The brands that get cited today become the "default answers" of 2027 models.

Frequently asked questions