GEO vs SEO vs AEO: what actually changes

SEO gets a page ranked for a query on a search results page. AEO (answer engine optimization) aims to win the extracted direct answer, the snippet or answer box a search engine lifts from one page. GEO (generative engine optimization) targets a different surface entirely: being mentioned, recommended, and cited inside the answers that AI assistants like ChatGPT™, Claude®, Gemini™, and Perplexity™ generate.

The work overlaps more than the acronyms suggest, but the three disciplines compete for different units, define success with different metrics, and close the feedback loop with different data. This guide defines each term, shows what transfers from an existing SEO program, what genuinely changes, and where a team that already does SEO should start.

What do SEO, AEO, and GEO actually mean?

SEO: rank a page for a query

Search engine optimization is the established discipline: earn a position on a results page for a query with commercial or informational value. The unit of competition is the page. The scoreboard is position, impressions, and clicks, and the feedback loop is mature: Search Console, rank trackers, log files.

AEO: win the extracted answer

Answer engine optimization grew out of featured snippets, People Also Ask boxes, and voice assistants. The engine extracts a short passage from one page and presents it as the answer, above or instead of the classic list of links. You win AEO by making extraction easy: a question as a heading, a two sentence answer directly beneath it, tables and step lists for anything procedural. The unit of competition narrows from the page to a single extractable passage, and one site owns the answer at a time.

GEO: earn a place inside the generated answer

Generative engine optimization targets assistants that write answers rather than extract them. ChatGPT™, Claude®, Gemini™, and Perplexity™ synthesize a response from model knowledge plus, increasingly, live web retrieval, then cite a handful of sources. Your brand can appear in two distinct ways: as a mention or recommendation in the answer text itself, and as a cited source behind a claim. GEO is the practice of earning both, across the many phrasings of the questions your buyers actually ask.

How do the three compare side by side?

The table compresses the practical differences. The rows that matter most operationally are the last two: what you measure, and how you find out.

Dimension	SEO	AEO	GEO
Unit of competition	A page's rank for a query	The extracted answer box or snippet	A mention or citation inside generated text
Success metric	Position, impressions, clicks	Answer ownership for the query	Mention rate, AI share of voice, citation rate
Feedback loop	Search Console, rank trackers	SERP feature tracking	Scanning AI answers directly, on repeat
Content shape that wins	Comprehensive keyword-targeted page	Question heading plus a concise extractable answer	Answer-shaped explainer with clear definitions, comparisons, and quotable claims

What carries over from your SEO program?

More than the hot takes suggest. Four assets transfer directly:

• Crawlability and rendering. Retrieval-augmented assistants fetch pages much the way crawlers do. If your key content only appears after client-side JavaScript runs, or your robots rules block AI crawlers, you cannot be retrieved, and unretrieved pages do not get cited.
• Structured data. Schema markup does not guarantee a mention, but clean entity markup helps engines resolve who you are, what you sell, and how you relate to the rest of your category.
• Authority. Models and their retrieval layers lean on familiar authority signals: coverage on trusted third-party sites, consistent entity information, demonstrable expertise. Digital PR keeps paying off.
• Freshness. Retrieval favors current pages. Stale or undated content loses citations to newer explainers covering the same question.

What actually changes?

Three differences break instrumentation and habits built for classic search.

Answers are sampled, not ranked

Ask the same assistant the same question twice and you can get different answers, different brand lists, different citations. Generated answers are samples from a distribution, so a single check is an anecdote, not a measurement. Useful GEO metrics are rates across repeated runs: mention rate, average position in list answers, citation rate. See why AI answers change between runs for what drives the variance and how to measure through it.

Citations concentrate on answer-shaped explainers

When assistants cite, they overwhelmingly cite pages that look like answers: definitional guides, comparisons, methodology write-ups, FAQ style explainers. Product pages and homepages rarely earn citations because they rarely contain a liftable claim. This inverts a common SEO instinct: the pages that convert are usually not the pages that get cited.

Absence is invisible to your analytics

If an assistant answers a buyer's question without mentioning you, nothing happens in your analytics: no impression, no click, no query report. Classic tooling records the traffic you got, never the recommendation you missed. The only way to see the gap is to read the answers themselves, which is the core case for measuring AI visibility at all.

Where do AI visibility tools fit in?

An AI visibility tool closes the feedback loop that Search Console cannot. It runs a fixed set of prompts against assistants like ChatGPT™, Claude®, Gemini™, and Perplexity™ on a schedule, stores the full responses, and extracts structured signals from each one: whether your brand was mentioned, how favorably it was framed, where it sat in list-style answers, which competitors appeared alongside you, and which domains were cited.

Tools in the category differ in provider coverage, prompt management, and how they handle run-to-run variance, but the essentials are the same: consistent prompts, repeated runs, and extraction you can trend. Gen3 AI Visibility anchors every trend to a fixed prompt basket and reports per-provider rates with their run-to-run spread. The metric most teams anchor on is AI share of voice: your mentions as a fraction of all brand mentions in your category's answers.

Where should an SEO team start?

You do not need a new team, and you should not stop doing SEO. Add GEO in this order:

1. Baseline before you change anything. Write 20 to 40 prompts your buyers actually ask, weighted toward unbranded category questions. Run them across the major assistants more than once and record mentions, positions, and citations.
2. Fix retrieval blockers. Confirm AI crawlers can fetch your key pages, that the content renders without JavaScript, and that your most quotable pages are not blocked or paywalled.
3. Publish answer-shaped explainers. Cover the definitional and comparison questions in your category with pages built to be quoted: a direct answer in the first paragraph, question headings, tables, honest comparisons.
4. Measure share of voice, not just your own mentions. A rising mention rate means little if a competitor is rising faster. Track who else appears in the same answers.
5. Rescan on a schedule. Because answers are sampled, treat deltas across repeated scans as the signal and any single run as noise.

Measure it

The fastest way to ground all of this is to look at real answers about your own brand. Run a free Pulse visibility check to see how AI assistants describe you today, or keep going with the rest of the guides at /learn/.