What GEO/AEO is and how it differs from SEO
GEO and AEO do not replace SEO — they are a layer on top of it: optimizing for how generative engines pick and cite sources, not only for position in the blue links.
Research on how AI search behaves and where it is heading.
GEO and AEO do not replace SEO — they are a layer on top of it: optimizing for how generative engines pick and cite sources, not only for position in the blue links.
An answer engine does not "read the whole internet" at the moment it answers. In a fraction of a second it pulls a handful of text fragments and retells them. Whether your content makes it into the answer follows directly from that mechanism.
A link under a ChatGPT or Perplexity answer is not proof that your text shaped it. This piece draws the line between "we were cited" and "we were actually used".
One question to ChatGPT is not a measurement of visibility — it is one observation drawn from a distribution. Visibility in AI search is a distribution, and it has to be measured as one.
AI Overviews is not a separate product with its own rules but a layer on top of Google's core ranking. Here is how sources get in, and what independent measurement says about traffic.
Organic traffic has stopped being the only currency of visibility: a brand now wins or loses inside the answer itself, before any click. Here is how far click-through has fallen, and how to rebuild your metrics for it.
robots.txt shapes the behaviour of specific crawlers; it is not a single switch. Google-Extended governs the use of content for training and grounding in Gemini Apps and Vertex AI, but it does NOT govern inclusion in Google Search AI Overviews — there, what matters is Googlebot and page eligibility (indexed, and able to show a snippet). To manage visibility properly you need the exact bot names and the places where the rules do not apply.
Structured data helps with rich results in classic search — it is not a ticket into AI answers. Here is where the markup works, and where the myth of "special AI markup" begins.
An AI assistant recommends specific products for a shopper's question — and the listing that best matches the intent and the constraints of that question can win, even where classic ranking does not explain the whole result. Here is what the research and the platform guides actually require.
The line is not drawn between optimizing and not optimizing. It is drawn between helping AI give the right answer and substituting your own. This piece draws it against specific criteria.