Generative Engine Optimization.
When someone asks ChatGPT "best CRM for a small B2B sales team", the model writes a paragraph and cites a handful of sources. GEO is the discipline of being one of those sources — and being one of the brands the model names in the answer itself, not just a footnote nobody clicks.
It rewards different things than classic SEO. Depth over keyword density. Structured, fact-rich content over thin posts. Original data, frameworks, and named opinions over generic listicles. Models pull from content that looks like a reliable source — because that's what they were trained to surface.
Done right, GEO compounds the same way SEO does: a single well-built page can be cited hundreds of times across thousands of AI conversations, with no extra ad spend.
Answer Engine Optimization.
GEO is the strategy. AEO is the craft. It covers the technical formatting that makes a passage quotable by an answer engine — clean H2s phrased as the questions buyers actually ask, direct-answer paragraphs in the first 60–80 words, FAQ schema, comparison tables, and consistent entity references.
AEO predates GEO. Google's "featured snippets" and "People Also Ask" boxes have been running on the same principles for years. The difference now: ChatGPT, Perplexity, Claude and Google's AI Overviews use these same signals, but at 10× the volume and with their own ranking logic on top.
In practice you don't run "GEO" or "AEO" separately. You run both, as one workflow.
How it's different from SEO.
SEO ranks a URL. GEO and AEO get your brand named.
The category is still wide open.
AI search is where SEO was in 2003. Most B2B sites have done zero deliberate work to be cited by an answer engine. That's the window — for the next 12 to 18 months, it costs a fraction of what it does to compete on classic SEO terms.
One engine. Both surfaces.
Groath isn't a separate "GEO agency." We run a single content engine — expert strategy from humans (Rodrigo, Stefan) executed by three AI agents (Research, Writing, Execution) — and that engine is built so the same output ranks on Google and gets cited in AI answers.
That works because the things AI engines reward and the things Google rewards have converged: structured, fact-rich content libraries with real depth and a coherent entity behind them. Build the library the right way once, get paid on both surfaces.
The engine writes for the answer engines — clean question-form headers, direct-answer leads, FAQ schema, structured comparisons — and ships volume that compounds week over week.