What is generative engine optimization (GEO)?

What is GEO, in one minute

When someone asks an AI engine a question, it doesn’t return ten blue links. It searches the web, reads a handful of pages, and writes one answer that names a few brands and links a few sources. If your brand isn’t in that answer, you don’t exist for that buyer, however well your page ranks below it.

GEO is the work of changing that answer. It has three parts: knowing which questions matter and what the engines say today, publishing content the engines can quote, and earning mentions on the other sites they already cite. The same discipline is also called answer engine optimization (AEO), AI SEO or LLM optimization (LLMO). The names differ; the work is the same.

How GEO differs from SEO

The two overlap more than the debate suggests: most engines search a live index before they answer, so pages that rank well are more likely to be read. But a ranking is not a mention. Our guide to GEO and SEO covers the overlap in detail; the table below is the summary.

How AI engines choose what to cite

Engines that answer from the live web work in roughly the same way. They turn the question into several searches (the query fan-out), read the top results, and write an answer from what they read. Two things follow. First, you have to be findable for the searches the engine actually runs, which are often longer and more specific than the question. Second, the answer is built from passages: a page that states the answer plainly, in a sentence that stands on its own, is easier to quote than one that buries it.

Which sites get read varies a lot by engine. In our October 2026 study of 150 AI answers, the 150 answers drew on 593 different domains. ChatGPT listed 16.6 domains as sources per answer on average, while Google AI Mode listed 2.5, so on Google’s AI surfaces fewer sources share the whole answer. Community and video sites came up again and again: reddit.com was among the sources of 22 answers and youtube.com of 13.

What the research says works

The study that named GEO is “GEO: Generative Engine Optimization” by Pranjal Aggarwal and colleagues, including researchers at Princeton, published at KDD 2024. They rewrote one source per query with nine different methods and measured how much of the AI answer came from that source afterwards.

Two findings matter most in practice. Evidence and clarity win: quotations, statistics, citations and more fluent writing all helped, while a more “authoritative” tone did little and keyword stuffing made things worse. And lower-ranked pages gained the most: when every source in the test was rewritten, citing sources lifted the fifth-ranked result’s visibility by 115%. That gives smaller sites a real chance to overtake bigger ones.

The study has limits worth knowing. It measured how many words of the answer came from a source, not whether a brand was named, and its test engine was built on GPT-3.5. Treat the numbers as direction, not as a forecast for your brand.

A GEO process you can run

1. Pick the prompts that make you money. Twenty to a hundred questions your buyers actually ask, such as “best payroll software for startups” or “boxing gym near Bedford Ave”, split by product, market and stage.
2. Measure where you stand. Ask each prompt on each engine, more than once, and record whether you are named, in what position, how you are described and which sources are cited. Our guide to measuring AI visibility explains each number.
3. Find the gap. For each prompt, list the sources the engines cite and check whether you appear in them. A “best of” list that names three competitors and not you is a gap you can close.
4. Publish what the engines can quote. Pages that answer the prompt in their first lines, back claims with numbers and sources, and compare options honestly. Our guides to getting cited by ChatGPT and in Google AI Overviews go step by step.
5. Earn the sources you are missing. Reviews, listings, community answers and roundups on the sites the engines already read.
6. Prove the lift. Compare the prompts you worked on with control prompts you left alone. If visibility rises only on the first group, the work caused it.

Common mistakes

• Measuring once. AI answers vary from one run to the next. One screenshot proves nothing; a trend across repeated runs does.
• Writing only for your own site. Many answers are built from third-party pages. If the lists and threads an engine reads never mention you, your own blog rarely fixes that alone.
• Chasing tricks. Hidden text, prompt injection and files that claim to steer models are fragile at best. The research rewards evidence and clarity.
• Forgetting Google. Google’s AI Overviews and AI Mode draw on the same index as its search results, so technical SEO still decides whether you are read at all.

Where Cited fits

Cited runs this process for you. We track your prompts across the engines and show the sources they cite; our strategists and copywriters write and ship the content that closes the gaps, and report every week on what moved. See how it works.