SEO, GEO, AIO, LLMO: The Marketing Acronyms Your Competitors Hope You’ll Ignore

Four acronyms. Roughly one job.

If you have been told your company now needs a GEO strategy, an AIO strategy, an LLMO strategy, and an AEO strategy on top of the SEO work you were already doing, someone is selling you four invoices for one project.

Here is what each term actually means, where it came from, and which distinctions are real.

The Short Answer

Acronym	Stands for	What it actually means	Genuinely distinct?
SEO	Search Engine Optimization	Getting found in search results. The base layer everything else sits on.	Yes. The original.
GEO	Generative Engine Optimization	Getting cited inside AI-generated answers rather than ranked in a list of links.	Yes, and it has an academic origin.
AIO	AI Optimization, or AI Overview Optimization	Depends who is talking. Sometimes it means structuring content for machines. Sometimes it means ranking in Google’s AI Overviews specifically.	Only partly. The term is ambiguous.
LLMO	Large Language Model Optimization	Being represented accurately when a language model answers a question about your category.	Barely. In practice it overlaps with GEO almost entirely.
AEO	Answer Engine Optimization	Formatting content so it can be lifted directly as an answer. Featured snippets, voice results, AI responses.	Partly. Predates the AI boom.
SXO	Search Experience Optimization	What happens after the click. Speed, clarity, navigation, conversion.	Yes, but it is really conversion work wearing a search label.

If you read nothing else: SEO is the foundation, GEO and AEO describe real shifts in how answers get delivered, and LLMO and AIO are mostly new names for work the first three already cover.

What Each One Actually Means

SEO: Search Engine Optimization

The practice of making your site findable and credible in search results. Crawlable structure, fast pages, content that matches what people are looking for, and enough authority that engines trust you as a source.

Nothing about AI has made this obsolete. Every AI system that cites web content is drawing on an index built with the same signals SEO has always cared about. If your site is slow, thin, or invisible to crawlers, no amount of AI-era tactics will rescue it.

GEO: Generative Engine Optimization

The practice of getting your content cited inside AI-generated answers rather than listed as a link.

GEO is the one term on this list with a real origin story. It was introduced in a November 2023 research paper by Pranjal Aggarwal, Vishvak Murahari, and colleagues, later published at KDD 2024. The paper defined “generative engines” as systems that answer a query by synthesizing and summarizing multiple sources, and it tested which content characteristics made a source more likely to be cited.

That matters. GEO is not a term a marketing agency invented to justify a retainer. It describes a measurable thing: whether a generative system picks your page as a source.

AIO: AI Optimization, or AI Overview Optimization

This is where the alphabet soup gets murky. AIO is used two different ways, and the people using it often do not specify which.

Some use it to mean optimizing content so machines can parse it cleanly. Others use it to mean ranking specifically inside Google’s AI Overviews. Those are related but not the same goal.

If someone pitches you AIO services, ask which definition they are using. If they cannot answer clearly, that tells you something.

LLMO: Large Language Model Optimization

The practice of making sure language models represent your company and products accurately when asked.

In practice, almost everything written about LLMO describes the same tactics as GEO: clear factual content, consistent naming, structured data, and corroboration from sources outside your own website. The distinction people usually draw is that GEO targets AI search products while LLMO targets the underlying models. That difference is real in theory. It rarely changes what you actually do on Tuesday morning.

AEO: Answer Engine Optimization

Formatting content so a system can lift a direct answer out of it. Lead with the answer, keep it short, mark it up so machines know what it is.

AEO is older than the current AI wave. It grew out of optimizing for featured snippets and voice assistants. AI answers extended the same idea rather than replacing it.

SXO: Search Experience Optimization

Everything that happens after someone arrives. Page speed, clarity, navigation, whether the visitor can do what they came to do.

Useful concept, misleading label. This is conversion rate optimization with a search prefix attached. If you want to improve it, you are doing conversion work, whatever you call it.

LLMO vs GEO: Is There Actually a Difference?

Not much of one, and less than most articles about them suggest.

The clean version of the distinction: GEO is about being cited by AI search products like ChatGPT search, Perplexity, and Google’s AI Overviews. LLMO is about what the model itself has absorbed about you, including from training data.

That distinction has one practical consequence worth knowing. Content published today can influence a live AI search product within weeks, because those products retrieve from a current index. Influencing what a model has internalized is slower and far less controllable, because you do not decide what goes into training data.

Everything else about the two is the same work. Publish clear factual content. Use consistent naming. Get mentioned in places other than your own website. Whether you file that under GEO or LLMO changes nothing about the task.

GEO vs AIO: Which Should You Care About?

GEO, because it means one specific thing.

AIO means either “structure content for machines” or “rank in Google’s AI Overviews,” depending on the speaker. The first is a subset of GEO. The second is a subset of GEO limited to one platform.

There is no version of AIO that is not already covered by doing GEO properly. Use the term if your team finds it useful shorthand. Do not buy it as a separate service line.

LLMO vs SEO: Do You Still Need SEO?

Yes, and this is the most expensive misunderstanding on the list.

Every retrieval-based AI system is drawing on an index. Being in that index, being crawlable, and being credible enough to be worth citing are SEO problems. A page that no crawler can read is not a candidate for citation by anything.

What changes is the target. SEO aimed at a ranked position and a click. GEO and LLMO aim at being the source behind an answer that may never produce a click at all. The work overlaps heavily. The measurement does not.

That is the genuinely hard part of this shift, and it is worth saying plainly: you can be more visible than ever and see flat traffic. Zero-click answers are a real outcome, not a reporting error.

So Which of These Are Real?

Three of them describe something that actually changed:

• GEO. Being cited inside a synthesized answer is a different outcome from ranking on a page of links. Real shift, real term, real research behind it.
• AEO. Leading with a direct answer so it can be extracted. Predates AI search, extended by it.
• SEO. Still the foundation. Nothing replaced it.

Two of them are mostly relabeling:

• LLMO. Nearly identical to GEO in practice.
• AIO. Ambiguous by construction. Ask anyone using it what they mean.

And SXO is conversion work with a search label on it. Worth doing. Not a search discipline.

What Actually Changes in Your Work

Strip the labels away and the AI era asks for four things. Only the last one is new.

Answer the question before you describe the product. Lead every important page with a direct response to the question someone actually typed. Then support it. This is the single highest-leverage change, and it is the same change that makes a page convert better for humans.

Structure content so machines can parse it. Question-formed headings. Short self-contained answers underneath. Schema markup, particularly Article, FAQ, and Product. None of this is exotic, and most companies have not done it.

Be consistent about who you are. One canonical product name. The same company description everywhere. Contradictory information across your site, your listings, and your profiles makes you harder to represent accurately, and a system that cannot resolve you confidently will cite someone it can.

Get corroborated somewhere other than your own site. This is the one that is genuinely harder than it used to be, and it is the one most companies skip. A claim only you make is a claim. The same claim in a trade publication, an industry association listing, or a technical forum is treated as established. Independence of sources matters more than volume.

Notice what is not on that list. There is no separate GEO workflow, no LLMO team, and no AIO tooling budget. There is content that answers questions, structure that machines can read, consistency, and outside corroboration.

What This Means If You Sell a Physical Product

Everything above applies to any company. This part does not.

Physical products companies have a structural disadvantage in AI search, and it has nothing to do with technology. Most product content was written to answer an engineer’s questions rather than a buyer’s. It leads with tolerances, materials, and specifications. All accurate. None of it what an AI system reaches for when a buyer asks which product survives their operating conditions.

That gap between how you describe the product and how a buyer asks about their problem is the same gap that stalls your sales conversations. We call it the messaging gap, and it is the main reason marketing a physical product is different from marketing anything else.

It is also, for the moment, an opportunity. The bar in most industrial categories is low, because almost every competitor is still publishing spec sheets.

If you sell a physical product, the practical version of this article is here: How Physical Products Companies Show Up in AI Search. It covers what buyers actually ask AI before they contact you, and what to change on your pages.

How to Measure Any of This

Rankings alone stop telling you the truth once answers are synthesized. Three things worth tracking instead:

Citation presence. Ask the AI tools the questions your buyers ask. Record who gets named. Do it monthly. This is manual and it is still the most honest signal available.

Impressions against clicks. A page gaining impressions while clicks stay flat is often being read and summarized rather than ignored. Search Console shows this clearly.

Branded search volume. If AI answers are mentioning you without linking, the effect shows up later as people searching your name directly.

None of these is as clean as a ranking report. That is the honest state of measurement right now, and anyone promising you a tidy AI visibility score is selling more certainty than exists.

The Bottom Line

You do not need four strategies. You need content that answers real questions, structure that machines can read, consistent facts about who you are, and a presence beyond your own website.

Everything else on this list is a label for part of that.

Here is a checklist that turns it into a one-page audit for your own site.

Twenty-five specific fixes across content and messaging, technical foundation, AI and generative search, and external authority. Free download.