GEO vs AEO vs SEO: what is actually different

What do GEO, AEO and SEO mean?

SEO gets your pages ranked and clicked in search results. AEO shapes pages so a search feature or voice assistant can lift a direct answer from them. GEO gets your content retrieved and cited inside answers that a language model writes.

In one line each:

• Search engine optimization (SEO) is the work of getting pages crawled, indexed and ranked so people click through to them.
• Answer engine optimization (AEO) is the work of structuring pages so a featured snippet, a voice assistant or an AI answer can quote a direct answer from them.
• Generative engine optimization (GEO) is the work of getting your content retrieved, quoted and cited in answers written by tools such as ChatGPT search, Perplexity, Claude, Copilot and Google AI Overviews.

Our working view, after reading the platform documentation closely: these are 3 scoreboards for one body of work. Most of what improves one improves the other two. The differences are real, but they sit at the edges, and a buyer who pays for 3 separate programs usually pays for the same page edits more than once.

Where did each term come from?

SEO dates to the commercial search engines of the 1990s. AEO came out of the featured snippet and voice assistant era of the late 2010s. GEO was named in a research paper first posted in November 2023, and it has since entered Bing's official guidelines.

SEO grew up around crawling, relevance and links. The craft has changed many times, but the core question has stayed the same: will a search engine find this page, understand it and rank it above the alternatives?

AEO came into use when Google started answering questions directly on the results page through featured snippets, and when voice assistants started reading one answer aloud. The goal was to be the single lifted answer. The term has since stretched to include AI answers, which is most of the reason people now use AEO and GEO interchangeably.

GEO has a precise origin. Pranjal Aggarwal and colleagues introduced it in GEO: Generative Engine Optimization (opens in a new tab), accepted at KDD 2024. They described generative engines as systems that retrieve sources and then write an answer, built a benchmark of queries to test rewriting tactics, and reported that GEO methods can "boost visibility by up to 40%" in generative engine responses.

Two platform statements since then frame the debate. In February 2026, Bing's Webmaster Guidelines named GEO and defined it as "focused on content eligibility for grounding and reference in AI responses" (Search Engine Journal (opens in a new tab)). In July 2026, Google's AI optimization guide (opens in a new tab) took the opposite framing: "optimizing for generative AI search is optimizing for the search experience, and thus still SEO." Both can be true. Bing is describing a goal, and Google is describing the method.

What stays exactly the same?

Nearly all the foundations stay the same: crawl access, indexing, text in the HTML, fast and stable pages, original content and a reputation that other sites confirm. Google's AI features documentation (opens in a new tab) says a page needs to be indexed and eligible for a snippet to appear in AI Overviews or AI Mode, with "no additional requirements."

The shared work, in the order we do it:

1. Technical access: robots rules, an XML sitemap, canonical URLs, real 404 responses and no redirect chains.
2. Text in the HTML that arrives from the server, not text that appears only after scripts run.
3. One topic per URL, with a title, H1 and description that agree with each other.
4. Original content that answers a real question better than the pages already ranking. Google's guide describes unique, experienced takes "that go beyond common knowledge" as what matters most over time.
5. Reputation: links and mentions from sites your buyers already trust.

If a provider proposes GEO work before these 5 are in order, the sequence is wrong.

What actually changes?

Four things change: how success is counted, the shape of the query, the weight of off-site mentions and the number of crawlers you have to plan for. The page edits underneath change less than the vocabulary suggests.

Citations and mentions sit next to clicks

In classic search, a result means a ranking and, with luck, a click. In an AI answer, the result can be a citation link, a mention of your company name with no link, or nothing visible even when your page shaped the answer. Clicks per appearance are lower. A mention inside a shortlist answer ("three firms that build n8n automations for law firms") can still be worth more to a services business than a ranking on page two.

Prompts are longer and get split up

Buyers type longer prompts into assistants and add context, such as company size, location and budget. Google's AI features use "query fan-out," which means "issuing multiple related searches across subtopics and data sources." Ahrefs data reported in March 2026 (opens in a new tab) found that only 38 percent of AI Overview citations came from pages in the top 10, down from 76 percent in its July 2025 data, with a warning that the two datasets are not directly comparable. The practical change: pages that answer the sub-questions well get cited even when they do not rank for the head term. Google also warns that publishing a page for every variant is scaled content abuse, so the answer is better pages, not more of them.

Off-site descriptions of you matter more

When an assistant builds a shortlist, it pulls from pages that compare vendors: directories, review sites, comparison articles and community threads. If those pages describe your company inconsistently, or not at all, there is little for the model to repeat. Bing's guidelines now ask that "entity names should be clear and consistent." This is entity SEO work, and in GEO it moves from a nice extra to a core task.

More crawlers, and most of them do not render JavaScript

SEO mostly meant planning for Googlebot and bingbot, both of which render JavaScript. GEO adds OAI-SearchBot, PerplexityBot, Claude-SearchBot and their user-fetch agents, each with its own robots token. Vercel's crawler study (opens in a new tab) found that none of the major AI crawlers render JavaScript. A site that looks fine in Google can be blank to ChatGPT. Our guide to getting cited by ChatGPT, Perplexity and AI Overviews lists every token and what blocking each one does.

GEO vs AEO vs SEO side by side

The table compares the three on the points that change decisions. Rows where all three columns say nearly the same thing are the shared foundation.

How do you measure each one?

Measure SEO with Search Console clicks, positions and conversions. Measure AEO with snippet ownership and AI feature impressions. Measure GEO with Bing's citation data, a fixed prompt panel and AI referral traffic. None of the GEO measures is complete on its own.

Neither Google's AI report nor Bing's dashboard shows clicks, so put a pipeline number next to the visibility numbers: qualified inquiries from organic search and from AI referrals, counted the same way each month. That is the figure a COO will ask about. Our glossary entry on AI visibility covers how to report share of voice across assistants without overstating it.

Do you need a separate GEO program?

No. Run one program with 3 sets of measures. Splitting SEO and GEO between 2 providers usually means 2 teams editing the same pages toward the same goal, and arguing about credit.

How we package it: an SEO and GEO audit at $3,500 to $8,000 covers technical health, AI crawler access, content and entity consistency in one pass. A monthly retainer at $3,000 to $8,000 runs all three scoreboards from one plan and one report. A separate answer engine optimization sprint at $6,000 to $15,000 makes sense in one specific case: the site is technically sound and ranks, but its key pages were not written to be quoted. They have no direct answers, no tables and no sources.

If someone offers GEO as a line item on top of an existing SEO retainer, ask what work it contains that the SEO scope does not. If the answer is a prompt-tracking dashboard and an llms.txt file, you are paying twice for reporting.

What should you do this quarter?

Spend the first month on access and baselines, the second on rewriting the pages that carry revenue, and the third on entity cleanup and a re-measure. This 12-week plan covers SEO, AEO and GEO together.

Twelve weeks is short for citation changes. Treat week-12 numbers as an early signal and judge the program on 2 quarters. If you want this run for you, the work fits inside the retainer above, and content operations covers the rewriting when the page count is high. The AI search content engine blueprint shows that system end to end, from buyer question to reviewed, published page.

When do the labels stop mattering?

The labels stop mattering once you are doing the shared work well, and they never matter when the basics are missing. Four limits are worth stating plainly.

First, nothing in GEO helps a page Google has not indexed. Fix indexing and rendering before anything else.

Second, check whether your buyers research in assistants at all. A firm that wins work through referrals, repeat clients or formal RFPs should run a prompt panel before paying for citation work. Software buyers are a different case, which is why we cover it on our SaaS and technology page.

Third, the evidence base is young. The GEO paper is a lab benchmark from before current production engines, AI answers change between runs, and model updates shift results without notice. Any "GEO hack" that comes with a precise number and no source is folklore.

Fourth, the shortcuts are traps. Hidden instructions aimed at models are abuse under Bing's guidelines, and a page for every prompt variant is scaled content abuse under Google's. The durable version of all three disciplines is the same: be the clearest, best-sourced answer to a question your buyers actually ask, on a page every crawler can read.