What is generative engine optimization (GEO)?

Generative engine optimization (GEO) is the practice of increasing how often, how prominently and how accurately generative AI engines, such as ChatGPT, Perplexity, Gemini, Microsoft Copilot, Claude and Google AI Overviews, mention and cite your brand when they answer questions. It covers both the content you publish and the third-party sources these engines rely on.

Where GEO came from

The term was popularized by the 2023 paper GEO: Generative Engine Optimization (Aggarwal et al., later published at KDD 2024). The researchers built a benchmark of queries, ran them through a generative engine, and tested which content changes made a source more visible in the generated answer. Methods such as adding citations to credible sources, adding quotations and adding statistics performed well, while keyword stuffing did not help.

Since then GEO has become the common name for the discipline, alongside answer engine optimization (AEO). If you want the short version of how they relate, see the difference between AEO and GEO.

How generative engines produce an answer

Understanding the pipeline explains what GEO can influence.

1. Query understanding. The engine interprets the prompt and often expands it into several sub-queries (sometimes called query fan-out).
2. Retrieval. Engines with web access search an index (Google’s, Bing’s or their own) and fetch candidate pages.
3. Selection. The engine picks the passages that best answer each sub-query, weighting relevance, clarity, freshness and source trust.
4. Synthesis. The model writes an answer that blends retrieved passages with what it learned in training.
5. Attribution. Some engines attach source links; others mention brands without linking.

GEO work targets steps 2 to 5: be retrievable, be the clearest passage, be corroborated, and be described correctly. For a deeper look at selection, read how AI engines choose which sources to cite.

What GEO work involves

On-site

• Answer-first pages for the questions buyers ask, with the direct answer in the opening paragraph.
• Citable facts: specific, verifiable statements about what your product does, who it is for, integrations, deployment model and pricing approach.
• Comparison and alternatives content that is fair and factual, because buyers ask engines to compare vendors.
• Structure: question headings, tables, lists and definitions.
• Technical access: server-side rendering, clean indexing, and allowing the search crawlers of engines you want to appear in.

Off-site

• Third-party presence on review platforms, analyst and industry sites, comparison articles, community discussions and partner directories.
• Consistency: the same category, positioning and facts everywhere. Engines notice when sources disagree.
• Earned mentions in publications engines already cite for your category.

Measurement

• A fixed set of prompts, tracked across engines over time.
• Metrics such as mention rate, citation rate, share of voice, average position and sentiment.
• AI referral traffic and conversions in analytics.

GEO vs SEO at a glance

Question	SEO	GEO
What are you optimizing for?	A ranking position	Inclusion and accuracy in a generated answer
What is measured?	Rankings, clicks, CTR	Mentions, citations, share of voice, sentiment
Where does authority come from?	Links and on-site signals	Links plus corroboration across trusted sources
How stable are results?	Fairly stable day to day	Varies by engine and between runs

The GEO vs SEO page covers this comparison in more depth.

A practical GEO starting plan

1. Build a prompt set. 30 to 100 questions across category, comparison, alternatives, use case and pricing intents.
2. Baseline. Run them across the engines your buyers use and record who is mentioned and which URLs are cited.
3. Diagnose gaps. For prompts where competitors appear and you do not, look at the cited sources. Is it their own page, a review site or a listicle?
4. Fix on-site content that should answer those prompts.
5. Target off-site sources that engines cite repeatedly for your category.
6. Re-measure monthly and report trends, not single snapshots.

How GEO differs by engine

Not every engine works the same way, so GEO priorities shift depending on where your buyers ask questions:

Engine	Main retrieval source	GEO implication
Google AI Overviews and AI Mode	Google index	Strong Google SEO is a prerequisite
Microsoft Copilot	Bing	Check Bing indexing, often neglected
ChatGPT search	Its own search system and crawler	Allow OAI-SearchBot
Perplexity	Its own crawler and index	Allow PerplexityBot; freshness matters

Answers generated without live search rely on training data, which only changes with new model versions.

Common misconceptions

• “GEO is a trick to game the model.” Durable gains come from being the clearest and best-corroborated source. Manipulative tactics tend to be short-lived.
• “One check tells you where you stand.” Answers vary between runs and engines. You need repeated sampling.
• “Only our website matters.” For many B2B prompts, third-party pages are cited more often than vendor sites.

Who should care

CMOs should care because AI answers shape shortlists early. SEO teams and agencies should care because their skills transfer but their reporting must change. Product marketers should care because engines repeat whatever positioning is most consistently stated across the web.

For the full framework, see what GEO is and the metrics on GEO metrics and KPIs. Tools such as GrackerAI track citations, share of voice and sentiment across up to 10 AI engines when you outgrow manual checks.