What Is Generative Engine Optimization (GEO)?

Traditional SEO optimizes for a ranked list. You're competing for position one through ten on a results page, and the mental model is fairly stable: match search intent, build authority, earn links, structure your pages so crawlers and readers both understand them.

GEO optimizes for something looser: inclusion in a generated answer that might synthesize five, ten, or twenty sources into two paragraphs, with no guarantee your brand name even appears next to the citation.

That difference changes what "winning" looks like.

A page can rank on page one of Google and still get skipped entirely by an AI Overview, because the model favored a source that answered the specific sub-question more directly, or came from a domain it treats as more authoritative for that topic.

Conversely, a page with modest traditional rankings can get pulled into an AI answer because it's structured in a way that's easy to extract and quote.

Here's where it gets genuinely confusing, and we think it's worth saying so plainly: the industry has not settled on consistent terminology.

You'll see "GEO" (generative engine optimization), "AEO" (answer engine optimization), and occasionally "LLMO" or "AIO" used almost interchangeably by different agencies and publications, sometimes to describe the exact same set of tactics, sometimes with subtly different scopes.

Some practitioners use AEO specifically for optimizing toward direct-answer formats like featured snippets and voice assistants, and GEO for the newer generative/chatbot layer. Others use the terms as pure synonyms.

There's no governing body standardizing this the way there once was for, say, meta tag conventions. If a vendor tells you their "AEO strategy" is fundamentally different from their "GEO strategy," ask them to be specific about what tactically changes. Often, not much does.

What both approaches share with SEO is the underlying respect for genuine expertise and clear structure. What's different is the target: SEO earns a ranking position, GEO earns a mention inside someone else's generated sentence.

Nobody outside the AI labs has full visibility into these citation algorithms, and any agency claiming a proprietary "GEO score" that predicts citation likelihood should be treated with some skepticism. This space doesn't have a standardized measurement methodology yet, and probably won't for a while. That said, there's useful pattern-level research to draw on.

One widely cited study analyzing large-scale AI citation behavior found that Wikipedia was the single most-cited source across ChatGPT, Perplexity, and Google's AI Overviews combined, which tracks with what you'd expect from models trained to favor broad, well-structured, frequently-updated reference material.

The same research found Reddit punching well above its weight specifically inside Google's AI Overviews, likely because Google has direct data-sharing arrangements with Reddit and because forum threads often contain exactly the kind of first-person, specific detail that generic marketing copy lacks.

YouTube showed up as a particularly strong source inside Perplexity and AI Overviews as well, suggesting video content with good transcripts or descriptions is getting pulled into answers more than most brands assume.

None of that means you need a Wikipedia page or a Reddit strategy to matter here (though a genuine, non-spammy presence in relevant subreddits or forums isn't a bad idea for a startup with limited authority).

What it suggests is a more general pattern: these systems favor sources that are specific, well-structured, and independently corroborated across multiple places on the web, rather than a single polished page that only exists on your own domain.

Original data, direct answers to narrow questions, and content that other sites reference or quote all seem to matter more than keyword density ever did in classic SEO.

Research from firms like Ahrefs that track which domains and sources large language models cite most often is worth checking periodically: these numbers move quickly as models get retrained and as AI search products change how they source answers, so treat any specific figure you read (including the ones in this article) as a snapshot rather than a fixed rule.

You don't need to abandon your SEO work to start on this; in fact, most of the foundation overlaps. Here's where we'd start if you're beginning from zero and want to know how to optimize for AI Overviews and similar tools without guessing:

• Answer the actual question in the first two sentences. AI systems extract concise, self-contained answers more easily than they extract conclusions buried under three paragraphs of preamble.
• Structure content with clear headers and lists. The same formatting that helps a human skim a page helps a model parse it into extractable chunks.
• Publish original data or firsthand experience where you can. A specific number from your own work, a screenshot, a real process you followed: these are the details generic AI-written content can't replicate, and they're exactly what tends to get pulled into a citation.
• Get mentioned outside your own domain. Genuine coverage, guest posts, forum answers, and directory listings all build the kind of cross-site corroboration that seems to matter for citation likelihood.
• Keep technical SEO fundamentals solid. Fast load times, clean HTML structure, and crawlable pages remain the entry ticket. A model can't cite what it can't reliably access or parse.
• Add structured data (schema markup) where it's genuinely applicable. It doesn't guarantee a citation, but it gives machines an unambiguous read on what your page is about.
• Track brand mentions in AI answers manually for now. Ask the tools directly about your category and see who gets cited. It's crude, but until third-party monitoring tools mature further, it's a reasonable gut check.

The most common mistake we see is treating GEO as a switch you flip once: a plugin, a checklist item, a "GEO audit" that produces a certificate, and then you move on. It's closer to a habit you build into how you already write and publish, and it needs revisiting as the AI products themselves change (which they do, often).

The second mistake is chasing a number nobody can currently verify. Because there's no standardized way to measure "GEO performance" the way there is for search rankings, be wary of any report that hands you a precise score with a false sense of scientific rigor attached.

Early research in this space is genuinely early, and honest measurement right now looks more like directional tracking (are we getting mentioned more often in spot checks over time) than a clean dashboard number.

The third is ignoring traditional SEO because GEO feels newer and more interesting. The two are not competing budgets.

A technically sound, well-structured, genuinely useful page tends to perform reasonably in both traditional rankings and AI citations, because both systems are ultimately trying to reward the same underlying qualities: clarity, relevance, and evidence that a real person with real expertise wrote it.

We treat GEO as an extension of solid content and technical SEO practice rather than a separate discipline bolted on top, mostly because that's what the evidence currently supports.

Our approach starts with the same technical groundwork any good SEO engagement needs: clean site structure, fast pages, accurate schema markup.

From there it layers in the specific things that seem to correlate with AI citation: direct, well-formatted answers to the exact questions your audience is typing into these tools, original detail that can't be found word-for-word anywhere else, and a presence beyond your own domain that gives independent systems a reason to trust what you're saying.

We're upfront that this field doesn't have mature measurement tools yet, and we won't hand you a proprietary "GEO score" and pretend it's an industry standard. It isn't one, for anybody.

What we can do is build the underlying fundamentals correctly, monitor citation behavior by hand as the tooling catches up, and adjust as this space matures, which it will, quickly.

If you want to look at where your site currently stands and what a realistic first quarter of work would involve, our AI search optimization (GEO) service page walks through how we scope that engagement.