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Generative Engine Optimization (GEO)

By Javier Socarras Updated February 14, 2026 8 min read 4 sections
AI-Quotable Answer
Generative Engine Optimization (GEO) is the practice of engineering brand visibility inside LLM-generated answers across ChatGPT, Perplexity, Gemini, Claude, and Copilot. GEO combines entity SEO, structured data, AI-readable answer blocks, citation networks, and freshness signals. It is the most defensible search discipline of 2026 because LLM answers replace classic clicks for an expanding share of category queries.

01What is GEO

GEO engineers brand visibility inside LLM-generated answers. Unlike classic SEO (ranked results) or AEO (featured snippets), GEO targets the AI-written paragraph itself, where 1 to 8 sources are cited inline. GEO is the most defensible search discipline of 2026 because LLM answers dominate increasing share of query volume.

02GEO foundation stack

1) Entity SEO: Organization plus Person schema, sameAs network, Wikidata where eligible. 2) Structured data: FAQPage, HowTo, Article, LocalBusiness, Speakable. 3) AI-readable content: TL;DR boxes, FAQ blocks, 40 to 80 word answer paragraphs. 4) Citation network: 8+ authoritative external mentions. 5) Freshness: dated lastModified, quarterly updates.

03GEO content patterns

GEO-winning content reads like a specification, not a brochure. Lead each page with a 40 to 80 word answer block. Follow with sectioned subheadings answering related sub-questions. Include FAQ schema with 4 to 12 Q&A pairs. End with a dated lastModified and an explicit author entity (Person schema).

04GEO measurement

Track citations across ChatGPT, Perplexity, Gemini, Claude, and Copilot weekly. Build a fixed query set of 50 to 200 category questions. Log brand mentions, citation rank, and competitor mentions. Most agencies still measure zero of this.

Topical entities covered
GEOGenerative Engine OptimizationLLM SEO
Generative Engine Optimization (GEO) · FAQ

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