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Generative Engine Optimization (GEO) – The Guide
Framework, playbooks, and measurement so AI searches pick you as the source.
GEO Playbook
Strategy + execution for AI visibility
GEO optimizes content and tech so LLMs pull answers directly from your domain. This guide connects strategy, IA, content briefs, technical hygiene, and measurement in one flow.
Definition & goal
GEO = Generative Engine Optimization. Goal: be the trusted source in AI/answer engines. Core: clarity, structure, machine signals, and trust.
Why now? AI replaces click lists with direct answers. If you’re not in the context window, you lose reach. GEO creates precise snippets, structured data, internal link signals, and technical stability.
Framework (Strategy → Structure → Signals → Shipping)
Strategy: topic fields, persona/intent mapping. Define clusters, pillar + spokes + glossary.
Structure: IA with hubs, breadcrumbs, DE/EN URL logic, sitemaps, robots, llms.txt.
Signals: Schema.org (DefinedTerm, Article, FAQ), consistent hreflang, canonicals, clean headings/anchors.
Shipping: Editorial + dev playbooks, QA pipelines, monitoring (logs, CWV, AI bot crawls).
Execution (Answer-first templates)
Open with a 1–2 sentence definition. Follow with impact, steps, measurement, examples.
Build internal links: Pillar ↔ Spokes ↔ Glossary. Each term links back to the pillar plus 3–6 related terms.
Tech: 308 redirects for language canonicals, consistent slugs, stable render paths, fast TTFB.
Measurement & KPIs
AI visibility: citations in answer engines, GPTBot/Perplexity logs, zero-click share.
User signals: scroll depth, time to CTA, conversion per cluster/locale.
Tech: render times, CWV, error rates, redirect coherence.
Examples & playbooks
Templates: answer-first layout, JSON-LD snippets (DefinedTerm, Article, FAQ), redirect map.
Checklists: pre-launch QA (links, schema, hreflang, canonical), post-launch monitoring.
Use cases: SaaS (feature explainers + glossary), e-commerce (category hubs + FAQ), local (service hubs + schema).
Next step