GEO vs SEO vs AEO: What's the Difference?

SEO vs GEO vs AEO: the key differences

The clean way to break down the differences between SEO and GEO (and AEO between them) is by what each discipline earns you. Generative Engine Optimization targets AI-generated answers; Answer Engine Optimization is its content-structure half; SEO remains the search engine optimization everyone already runs. Every definition longer than a sentence blurs into the others, because the work overlaps on purpose.

Read the rows as a gradient rather than a wall: SEO focuses on being found, AEO focuses on being quoted, GEO focuses on being recommended, and the SEO rewards compound upward into both of the others.

LLMO, where you meet it, is a synonym for the GEO umbrella (large language model optimisation), and some agencies now sell the union of all three as search everywhere optimization. Neither has a separate practice behind it, and treating either as a new discipline is a tell that someone is selling vocabulary to the digital marketing crowd.

Will GEO replace SEO?

No. GEO extends SEO rather than replacing it, and the question is never GEO or SEO, because one sits on the other. Traditional SEO builds the retrievable, crawlable, well-linked site; generative engine optimisation adds the extraction structure and the off-page reputation that decide whether the generative AI systems composing answers ever name you. Strong SEO helps GEO everywhere the engines retrieve, and the reverse dependency does not exist.

The dependency is measured: in C-SEO Bench, moving a page to the top of the retrieved results improved its citation rank far more than rewriting the page did. What has genuinely changed is where the competition happens, keywords have become conversational queries that LLMs expand into dozens of sub-questions, so GEO and SEO now compete one level below the visible query. The work you approach SEO with survives; the surface it wins on has moved into generative search.

Why SEO still comes first

SEO is the floor the other two stand on. Google's AI Overviews retrieve from Google's index, so a page that traditional search engines like Google cannot crawl is a page the AI answers cannot cite. ChatGPT and Perplexity run their own indexes and AI crawlers, but being retrievable somewhere an engine looks remains the precondition everywhere, which is why good SEO fundamentals, clean site structure, internal links, server-rendered pages, still open every door.

What has changed is how far a ranking carries you. Ahrefs found only about 12 percent of assistant-cited URLs rank in Google's top ten for the prompt, and the share of AI Overview citations from the top ten fell from 76 percent in July 2025 to 38 percent by March 2026. You can rank well in traditional search and still lose the generated answer: ranking is entry to the pool, not the medal.

What AEO adds on top

AEO turns a retrievable page into a quotable one. The engine reads passages, not pages, so the work is passage-level: a 40 to 60 word direct answer at the top, headings phrased as the questions people ask, sections that name their subject and survive being quoted alone. Question-format headings carry the strongest single piece of evidence in content optimisation, about a 12 percent organic traffic uplift when an ecommerce site rephrased product-page h2s as questions in a SearchPilot split test, and the same structure is what query fan-out matches against.

What only GEO covers

Two things sit outside both SEO and AEO as usually practised. The first is the off-page half: AirOps found brands 6.5 times more likely to be mentioned through third-party sources than through their own domains on top-of-funnel commercial queries, and branded web mentions correlate with AI visibility far more strongly than backlinks (0.66 to 0.71, against very weak link correlations, across 75,000 brands). The second is measurement: single prompt checks are statistically noise, so GEO requires panel-based tracking across engines, which neither classic rank tracking nor analytics provides. Those two are what make GEO a practice rather than a rebrand.

What metrics measure SEO and GEO success?

The SEO metrics stay what they were: rankings, organic search sessions, conversions. GEO work adds its own set, because none of those can see inside a generated answer: how often you are cited in AI answers on a stable prompt panel, share of voice against named competitors per platform, AI Overview presence and citations on your tracked keywords, and AI-referred sessions as the small visible fraction. Measuring AI search visibility covers the full stack and its denominator traps; the one rule that transfers from SEO reporting is that a trend on a fixed method beats any single-day number.

How do you optimise for both SEO and GEO?

On one site, with one content strategy, in this order. The overlap is the good news for any marketer deciding where to spend: nothing on the list below hurts either discipline, so nobody has to choose between traditional SEO and GEO, and no GEO strategy requires abandoning the old one.

1. Fix retrieval first: server-rendered content, crawler access, clean indexing. Nothing downstream matters if the engines cannot read the page.
2. Apply AEO structure to every page that answers a question, starting with the pages closest to money. This is editing, not new content.
3. Then work the GEO-only layers: entity consistency, third-party presence where your buyers ask, and panel-based measurement so you can tell whether any of it moved.

One demand note for anyone choosing what to call this work: in our own Google Ads pull (August 2026), searches for generative engine optimization had fallen 45 percent from their 2025 peak while answer engine optimization held steady. The labels are still settling; the priority order above does not depend on which one wins. The free AI Readiness Score checks step one and step two on any page, and Google Rankings covers the classic half alongside the AI answer tracking.