GEO vs SEO: The confusion explained — what e-commerce businesses really need to know
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GEO, AEO, LLM SEO: the fog that costs real money
I look at fifteen sites a week. All of them talk to me about GEO. None of them can actually explain what it means. This morning, an e-commerce owner called me: 8,000 € spent last year on a « SEO for generative AI » project, and after six months, zero citations in ChatGPT and not a single extra visit. I pulled up his pages in front of him: not a single filled Product schema tag, not one technical question answered. The vendor had churned out twenty generic articles unrelated to his catalog.
On Reddit, the thread « What actually is GEO? » in r/RankWithAI goes in every direction. Generative Engine Optimization, Answer Engine Optimization, LLM SEO — for some it’s the same thing as before with a new name, for others it’s a whole new discipline. One comment stuck with me: « I’ve been doing SEO for AI for six months, zero impact. » Another shot back that AEO is just featured snippets renamed. No one agrees on anything, and meanwhile budgets disappear into the void.
The acronym doesn’t matter one bit for e-commerce. What matters is whether an AI cites your product sheet when a buyer asks a question. I prefer to call it citation optimization. And you build it step by step — foundations first, then the facade.
What 47 e-commerce sites taught me in 18 months
I tracked 47 e-commerce sites continuously over the last eighteen months. Not rough impressions: I dig through Search Console every month, I spot which queries appear in AI cards, I cross-reference with clicks.
Out of 47, nine landed at least one product citation in Google’s AI Overviews. Three of those saw real traffic gains on the affected pages: +120% average compared to a year before. This « AI » traffic weighs 3.7% of total organic traffic — tangible, not massive. And two sites saw Perplexity send traffic to highly technical pages, with swings hitting +340% in variance, but in absolute terms we’re talking a few dozen sessions per month.
Bottom line: generative AI is starting to cite e-commerce pages. The volume is modest. It’s an extra layer on top of SEO, not a replacement.
GEO, AEO, LLM SEO: three acronyms, one rule
Let’s start with shared definitions so we’re on the same page.
GEO, Generative Engine Optimization, is optimizing your pages so a search engine picks them as a source when generating a summarized answer — Google AI Overview, Bing Copilot, Brave Summarizer. The mechanics look like featured snippets, with criteria that are still shifting.
AEO, Answer Engine Optimization, is broader: it covers voice search, smart speakers, no-click answers. For an e-commerce site today, the only channel that really moves the needle is Google’s AI Overview.
LLM SEO is optimizing for large language models like ChatGPT or Claude. These models don’t maintain a stable index, their citations are erratic and often unattributed. Investing specifically for ChatGPT in e-commerce right now is putting money on a target you can’t measure.
The underlying rule behind all three acronyms is the same: an AI cites the page that answers a buyer’s technical question with precision and authority. Rich structured data, explicit compatibility specs, visual proof (ImageObject, video), references to standards, in-house comparative tests. Everything else is noise.
The agricultural parts client: zero to 47 AI citations
A concrete case. Site selling spare parts for farm equipment. 4,000 organic sessions per month, zero citations in AI Overviews. Product sheets were technical but unreadable by machines: no semantic markup worth mentioning. We spent five months rebuilding the architecture.
First move: full schema.org audit. I corrected and enriched the Product tags (brand, gtin13, compatibility, review), added images as ImageObject. 82% of sheets had an error on availability or price — all fixed. For each complex product, I created a « Frequently Asked Questions » section in FAQ schema, answering the eighteen real questions that came in from customer support: tractor compatibility, torque specs, equivalent part numbers. We added assembly videos with the HowTo schema, and tightened the internal linking so each product sheet pointed to a buying guide page, and back again.
After five months: 47 distinct product queries cited in Google AI Overviews. Traffic from those 47 pages: +340% compared to the six months before. And — what surprised me most — regular SEO traffic from those same pages climbed 22% in parallel. The signals we strengthened for AI helped both channels.
No magic here. Clean semantic architecture, and five months of unglamorous work across 800 product sheets.
What most e-commerce sites miss
I see too many sites cranking out generic content thinking they’re « making content for AI. » Articles like « How to choose your [product] » or « Why your [product] is essential. » Flat, generic prose, no real connection to the catalog. That’s an expensive mistake.
Another client I tracked: he doubled his content budget to pump out fifteen guides like that in six months. His organic traffic dropped 22% over the period. Why? Because those new articles diluted the internal linking structure, and his product sheets sank deeper in the site hierarchy. Crawlers—AI or otherwise—lost the thread.
SEO for generative AI isn’t a separate new channel. It’s the same work as before, with one extra layer of rigor. If your product sheets don’t have clean structured data, if they take longer than two seconds to load, if no internal links point to them, no AI will cite them. Build the foundation first. Citations follow almost by design after that.
Your roadmap in 3 steps to enter the AI era
Three things to do now, in this order.
First, the structured data audit.
82% of sites I audit have critical errors in Product schema — missing price, wrong availability, no GTIN. Until those errors are fixed, Google AI Overview won’t pick you as a source. Run each product sheet through Google’s validator, and fix in priority order: price, availability, brand, gtin, and image.
Then, a real pillar page for each strategic category.
A buying guide that answers compatibility, maintenance, performance questions. Structured with FAQ schema, semantic HTML comparison tables, and deep links to the relevant product sheets. This is the kind of page models cite as expert source.
And finally, your E-E-A-T signals.
A byline signed by a named technician on every guide. Real photos of products in test scénarios, with captions. Verified customer reviews displayed. An AI hunts for the most trustworthy sources — these signals are your proof.
Nothing mysterious about it. This is what Google has been asking for ten years, just more demanding now.
And you? Are your product sheets being cited?
Go search Google for one of your products with « compatible with… » or « how to choose… ». Look at the AI card at the top of the page. Is your sheet cited, yes or no?
If the answer is no, you know where to start. I’m not selling you a method — I’m showing you your pages. If you want to dig into what’s blocking you, I’ll give you thirty minutes live.
Your AI-oriented SEO audit, live
I’ll spend 30 minutes examining your product pages in real time with you. I’ll show you where structured data is blocking you and what will unlock your citations in AI answers.
Book a strategic call — 45 minFrequently Asked Questions
What exactly is GEO for an e-commerce site?
For e-commerce, GEO means getting your product sheet picked as the source when Google AI Overview or Bing Copilot generate an answer to a buyer’s question. Concretely, that means three things: a complete schema.org Product, answering the exact technical question the buyer asks, and a site already recognized on the topic through regular SEO.
Should I create content specifically for ChatGPT?
No, and that’s what I tell every client who asks. ChatGPT doesn’t maintain a continuous index, its citations are erratic, often unattributed, and impossible to measure in Search Console. Whatever effort you’d put toward ChatGPT — put it on Google AI Overview instead, which runs on Google’s regular index. That’s the work SEO you’re already doing.
How do I measure the impact of AI citations?
In Search Console, open the Performance report and filter by appearance type « AI Overview »: you’ll see which queries you’re cited for and the clicks you get from them. Semrush and Ahrefs are starting to track this too, with some lag. The simplest method: search your product queries in Google in incognito mode and watch who shows up in the AI card.
Do backlinks still matter for being cited by an AI?
Yes, more than ever actually. Models evaluate a source by domain authority and brand recognition — exactly what backlinks and media mentions measure. Of the 47 sites I track, every one that lands AI citations has an above-average link profile for its sector. No shortcuts there.
Which schema should I start with for GEO?
Start with Product schema, specifically the six fields Google prioritizes: <code>name</code>, <code>image</code>, <code>price</code>, <code>availability</code>, <code>brand</code>, <code>gtin</code>. If any are missing or wrong, your sheet gets filtered out before content is even evaluated. Check with Google’s validator before going deeper.
