GEO (Generative Engine Optimization) is the discipline of getting a brand mentioned and cited inside the responses produced by generative AI systems such as ChatGPT, Gemini, Perplexity and Claude. Classic SEO is concerned with your position on the search results page; GEO is concerned with whether you are inside the response itself.
Why has it become important now?
The shift in user behavior is simple, but its consequences are large: you used to ask a question and pick from among ten links; now you ask a question and get a single response. That response usually mentions between three and five brands. If you are not on that list, you effectively do not exist for the user — and there is no classic tool that lets you measure it.
- An AI response often settles the decision without sending the user to your site at all.
- Google Analytics and Search Console don’t report mentions in this layer.
- The same question can return completely different brands on different platforms.
- You don’t know which questions your competitors get recommended for.
The difference between GEO and SEO
GEO doesn’t replace SEO; it is built on top of it. A site that can’t be crawled, is slow and has weak authority won’t be cited in AI responses either. But the units of measurement and the content formats are different.
| Dimension | SEO | GEO |
|---|---|---|
| Unit of measurement | Ranking, clicks, organic traffic | Mention rate, share of voice, citation share |
| Goal | A top position on the results page | Being mentioned inside the response |
| Content format | Long, keyword-focused | Clear, structured, answering directly |
| Signal of success | Clicks | Being cited and recommended |
| Speed of change | Weeks | Anywhere from days to months |
How is AI visibility measured?
The core of the measurement is simple: ask real questions and analyze the responses that come back. The difficulty is doing that in a way that is statistically meaningful and repeatable.
- 1Defining the brand and its competitors together with their spelling variants.
- 2Building a question set that represents the buying journey (discovery, comparison, purchase, reputation).
- 3Sending the questions to more than one platform, language and region.
- 4Extracting the brand mentions in the responses, their positions, their context and the cited sources.
- 5Reducing the results to a single score and tracking it over time.
One important warning: generative models are not deterministic. The same question can give two different responses on the same day. That is why you have to look not at a single response but at the sum of many queries and at the trend. One-off manual checks are misleading.
Which metrics should you look at?
- Mention rate: the share of responses that mention the brand, out of all responses.
- Share of voice: your share of all brand mentions.
- Position: how high up in the response you are mentioned.
- Citation share: your own domain’s share among the cited sites.
- Sentiment: whether the mention is positive, neutral or negative.
- Factual accuracy: whether what AI says about your brand is accurate.
Where should you start?
- 1Check whether AI bots can reach your site — this is the most common problem, and the easiest one to fix.
- 2Take a baseline measurement: 20-40 questions, 3-5 competitors, at least three platforms.
- 3Audit what AI knows about your brand; correct the wrong information.
- 4Turn the questions you don’t appear in into content opportunities.
- 5Repeat the measurement; look at the trend, not the absolute value.
In GEO the biggest risk isn’t being invisible, it’s showing up inaccurately. Becoming more visible with wrong information costs more than not being visible at all.