What is Generative Engine Optimization?

When someone asks ChatGPT, Gemini, Perplexity, Claude or Google AI Overviews a question in your category, the engine does not return ten blue links. It writes an answer, and often names a short list of brands. GEO is everything you do to make sure your brand is on that list, described accurately, and positioned well.

GEO works across two layers. The first is the content and signals the engine reads about you, from your own site to the third party sources it trusts. The second is how clearly your brand is defined as an entity, so the engine understands what you do and who you serve. Strong GEO improves both.

Three shifts make this urgent. First, AI answers are replacing the first click. A buyer who asks for the best option gets a confident short list, and most of them act on it rather than scrolling further. Second, those conversations are private. You cannot read the chat where a competitor was recommended and you were not, so the loss is invisible without a tool that measures it.

Third, the engines move. A brand that is recommended today can drop next month as models update and sources change. GEO is not a one time project. It is an ongoing practice of measuring, fixing and holding your position, the same way SEO became a continuous discipline.

The foundations overlap. Clear, accurate, well structured content helps both. Authority and trusted citations help both. But the differences matter:

• The unit of success. SEO wins a rank. GEO wins a mention and a recommendation.
• The surface. SEO lives on a search results page. GEO lives inside an answer the user reads as a single, trusted response.
• The measurement. SEO uses rank tracking. GEO needs you to ask the engines real questions and read what they say, because there is no public ranking to scrape.

If you want the deeper comparison, read GEO versus SEO, what actually changed.

No one has the exact recipe, but the pattern is consistent across engines. They reward:

• Entity clarity. The engine must know what you are, what you do and who you serve. Ambiguity gets you left out.
• Corroboration. Facts repeated consistently across trusted sources are safer for the engine to state than claims that appear only on your own site.
• Relevance to the prompt. Content that directly answers the buying question, in plain language, is easier to lift into an answer.
• Authority. Mentions in sources the engine already trusts carry weight.

We go deeper in how AI engines decide which brands to recommend.

A practical GEO programme looks like this:

1. Measure first. Find out which prompts you are missing and which competitors win them. You cannot fix what you cannot see.
2. Answer the real questions. Publish content that directly answers the buying questions your market asks, with concise factual answers up top.
3. Earn corroboration. Get named in trusted third party sources, directories and comparisons the engines read.
4. Sharpen your entity. Keep your name, category and key facts consistent across your site and the web.
5. Track and iterate. Rerun your prompts and watch your score. Double down on what moves it.

For a ready to use starting point, see our starter checklist to get recommended by AI.

Because there is no public ranking for AI answers, measurement means querying the engines directly and reading the results. For each prompt you capture whether you were mentioned, your position in the answer, the sentiment, and which competitors were named. Aggregate that across prompts and engines and you get a visibility score you can track.

Learn how the score is built in how to measure AI visibility, the ONE Score explained.

Instead of guessing, you get a clear starting score, a named list of competitors beating you, and the specific actions most likely to raise your visibility. Then you rerun and watch the ONE Score climb. It is GEO measurement and prioritisation in one place.