Frequently asked questions
What is Generative Engine Optimization (GEO)?
GEO is the practice of structuring website content — through schema markup, direct-answer paragraphs, and machine-readable positioning — so that AI assistants like ChatGPT, Perplexity, and Google AI Overviews can extract and cite it. Unlike traditional SEO, which targets human search rankings, GEO targets the retrieval and reasoning layers of language models.
How is GEO different from traditional SEO?
Traditional SEO optimizes for PageRank signals: backlinks, keyword density, Core Web Vitals. GEO optimizes for machine extractability: structured JSON-LD schema, explicit subject-verb-object sentences, FAQ sections that mirror AI query patterns, and external citations that establish topical authority. Both matter — but GEO signals drive AI citation where Google signals do not.
What is an A2A endpoint and why does my business need one?
An A2A (Agent-to-Agent) endpoint is a machine-readable JSON file at /.well-known/agent-card.json that describes your business to AI procurement agents. As buying increasingly moves through AI intermediaries, an A2A endpoint ensures your brand is discoverable, accurately described, and contactable by the machines making shortlist decisions on behalf of your buyers.
How quickly will AI assistants start citing my brand after implementing GEO?
Based on WebFlur's 2026 Sprint cohort data (12 clients), the median day of first AI assistant citation after implementing the full GEO stack is day 23. Perplexity typically cites first (often within 2 weeks), followed by Google AI Overviews (3–5 weeks), then ChatGPT (4–8 weeks). Speed depends on your existing domain authority and how competitive your category is.
Which AI assistants should I prioritize for GEO?
Prioritize Perplexity first — it performs live web retrieval, so schema changes reflect quickly and its citation methodology is the most transparent. Google AI Overviews second — it drives the highest B2B traffic volume. ChatGPT third — its retrieval layer is less predictable but highly influential in the enterprise buying cycle. All three respond well to Organisation JSON-LD, FAQPage schema, and machine-readable positioning.