AEO vs GEO vs SEO: what's the difference?

The short answer

SEO is search engine optimization: getting a page to rank in a list of results. That one is well established and nobody argues about it. AEO is answer engine optimization, usually meaning you want to be the answer itself on surfaces that answer rather than list, such as featured snippets, voice assistants and AI responses. GEO is generative engine optimization, usually meaning you want to be cited, named or recommended inside an answer a model generates. You will also see LLMO, AI SEO and LLM SEO circulating for broadly the same idea.

Now the part most articles skip. These are industry coinages, not standards. No governing body defined them, the usage is genuinely contested, and different vendors draw the AEO/GEO line in different places partly because it suits their positioning to do so. If someone tells you AEO and GEO are cleanly separate disciplines, that is their opinion presented as fact. The two overlap heavily, and the underlying job is largely the same one: be the thing an assistant names and cites when a shopper asks it what to buy.

The terms, side by side

This table describes how the words are commonly used, not how they are officially defined, because there is no official definition to report.

Read down the last two columns and the overlap is obvious. AEO and GEO point at the same family of surfaces and get measured in roughly the same way. The cleanest real split in that table is between the first row and everything below it.

Does the distinction actually matter?

Mostly no. Here is the opinionated version.

The AEO versus GEO argument is a vocabulary argument. The work behind both labels is the same work: make your facts complete, structured and unambiguous, keep crawlers able to reach you, and give a model enough to confidently say what your product is and who it suits. Nobody has ever produced an AEO task list that meaningfully diverges from a GEO task list. Choosing a side does not change what you do on Monday.

The SEO versus everything-else distinction is different, and that one does matter. It changes what you measure, what counts as a win, and how you interpret a bad week. A merchant who tries to read AI visibility through a rank-tracking mental model will draw wrong conclusions, because there is no rank to track and the output moves between runs.

So the practical advice is simple. Stop optimizing the acronym and pick the outcomes you care about. Are you being named when a shopper asks an assistant for something you sell? Is that turning into sessions and orders? Those two questions survive whatever the terminology settles on.

What genuinely changes versus classic SEO

Set the acronyms aside. Regardless of which label you use, these are the real differences when the surface is an AI answer instead of a results page.

• No stable ranked list. There is no position four to hold. There is a paragraph, and you are either named in it or you are not.
• Output is generated per query. The same prompt can return different products on different days. That variance is the nature of the channel, not a bug to fix.
• Often no click. An assistant can describe your product, quote a price and summarise your returns policy without sending anyone to the store.
• The unit of competition is a mention. Not a URL and not a position. A brand, a product, a claim the model repeats.
• Structured facts beat keyword density. Models match on attributes. Vague, poetic copy that reads nicely to a human is often unusable to a machine.
• Queries are long and natural. Full sentences loaded with constraints: budget, size, material, use case, compatibility.
• Measurement is probe-and-trend. You send the same prompts repeatedly and read a mention rate over time, because a single run tells you close to nothing.

The "often no click" point is measurable rather than theoretical. Pew Research Center found users clicked a traditional result link on 8% of visits where an AI summary appeared, against 15% where none did — and just 1% of visits to a page carrying an AI summary produced a click on a cited source (Pew Research Center, July 2025). SparkToro's clickstream analysis put the zero-click rate at 68% of Google searches in early 2026, with AI Overviews present on 20%+ of all searches (SparkToro, June 2026).

SEO is not dead, and saying so is a sales tactic

The overlap with classic SEO is large and it is not going anywhere. Assistants have to reach your pages before they can cite them, so crawler access still matters. They have to parse your titles and structured data, so those still matter. Slow, broken or thin pages are still a problem. Brand authority signals still count, because a model that has seen your name in more credible places is more likely to repeat it.

Everything on the AI side sits on top of that foundation rather than replacing it. Treat it as a second scoreboard next to the first. Any pitch that opens with "SEO is dead" is selling you a category, not describing reality.

Google states this itself, in as many words: "From Google Search's perspective, optimizing for generative AI search is optimizing for the search experience, and thus still SEO" (Google Search Central, updated July 2026). The same page is blunt about the tooling hype: you do not need to create new machine-readable files, AI text files or special markup to appear in Google Search, and structured data is not required for its generative features.

Which should a Shopify merchant actually care about?

Care about the outcome, then use whichever word gets your team moving. In practice the work splits into three jobs, and we have a guide for each.

1. Understand the surface

   If you want the how-to rather than the terminology, start with GEO for Shopify. It covers what to change on a store, crawler access, and a practical starting workflow.

2. Fix the product data

   Most of the leverage is unglamorous catalog hygiene: taxonomy, barcodes, attributes, real descriptions. Shopify product data for AI is the field-by-field checklist.

3. Measure without a rank

   Then set up the scoreboard. AI share of voice explains how probing works, why one run is not a signal, and what to trend.

One more argument against over-indexing on a single assistant: the landscape is still moving. Similarweb's tracking put ChatGPT's share of generative-AI website visits at roughly 53% by May 2026, down from about 76% a year earlier, while Gemini climbed to around 27–28% and Claude to close to 9% (Similarweb, July 2026). Tuning a catalog to one assistant's quirks is a poor bet when distribution shifts that fast.

Cuebase is built around those three jobs rather than around a label. The Catalog Readiness Hub scores your products against an agent-readiness rubric and generates AI fixes you review before they are applied. Agent Channel Analytics uses a Shopify Web Pixel to capture AI-referred traffic and conversion by source. Share of Voice probes ChatGPT, Perplexity, Gemini, Claude and Google AI with real shopper prompts and tracks how often you are mentioned versus competitors.

If you have to pick a word

Pick one, write down what you mean by it, and move on. A one-line internal definition ends the argument faster than any blog post will. Something like: "GEO means being named in AI assistant answers, measured by mention rate across a fixed prompt set." That sentence is more useful than the acronym.

Where the vocabulary does earn its keep is in briefs and job specs, because agencies and tools use the words inconsistently. When you buy, ignore the label on the box and ask what it measures, which engines it covers, and how often it checks. Those answers are comparable. The acronym is not.

FAQ

Sources

Every figure quoted above is linked to its original publisher with the date attached, so you can check it and see how current it is. Where the underlying studies disagree, we have said so rather than picking the most flattering number.

1. Aggarwal, P., Murahari, V., Rajpurohit, T., Kalyan, A., Narasimhan, K., Deshpande, A. GEO: Generative Engine Optimization. Proceedings of the 30th ACM SIGKDD Conference (KDD 2024). arXiv:2311.09735.
2. Google Search Central. Optimizing your website for generative AI features on Google Search. Updated July 2026.
3. Google Search Central. AI features and your website. Updated December 2025.
4. Pew Research Center. Google users are less likely to click on links when an AI summary appears in the results. 22 July 2025.
5. Fishkin, R. In 2026, Less than One Third of Google Searches Still Send a Click. SparkToro, 9 June 2026.
6. Similarweb. Generative AI usage statistics. 29 July 2026.
7. Shopify Help Center. Shopify Catalog and product discovery for agentic storefronts.