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Generative Engine Optimization (GEO)
Generative Engine Optimization, or GEO, is the practice of structuring information so search engines and AI systems can find, understand, verify, and cite it in the right context.
In plain language
GEO is not a trick for forcing AI to mention a brand. Its foundation is straightforward: clear answers, checkable evidence, consistent publisher identity, and pages that both people and machines can access.
People increasingly ask search engines and AI assistants before making decisions. Well-structured, sourced information is easier to assess than an appealing claim that cannot be verified.
A practical framework
- Answer the main question directly.
- Show who wrote it, when it was reviewed, and which sources support it.
- Use consistent headings, links, and structured data.
- Review the content when facts, technology, or sources change.
Learning path
- Evaluating Outputs · AI for Everyone
- Retrieval and Tools · Prompting
- Rubrics and Test Sets · Prompting
- Quality and Provenance · Data Literacy
- TF-IDF · Data Literacy
- Embeddings and Similarity · Data Literacy
- Golden Sets and Rubrics · Applied AI
- Monitoring · Applied AI
Sources you can check
- AI features and your website: Google Search Central. Explains how standard search foundations apply to AI search features.
- Introduction to structured data markup in Google Search: Google Search Central. Explains entity markup and machine-readable clues for search systems.
- Data on the Web Best Practices: W3C. Supports data provenance, metadata, quality, access, and reuse.