GEO vs AEO vs LLMO
Mostly labels. One distinction is real.
GEO, AEO and LLMO are used interchangeably by most practitioners, and a vendor's choice of label tells you nothing useful about their method. What does matter is one distinction hiding inside them: whether the work targets what a model retrieves at answer time, or what a model absorbed during training.
That distinction determines what you can promise about timing — and it is the reason "guaranteed results in X days across all platforms" is not a claim anyone can honour.
Where they actually differ.
| GEO / AEO | LLMO | |
|---|---|---|
| What it targets | What the model retrieves while answering | What the model absorbed during training |
| Time to effect | Days, on platforms that search the web | Vendor release cycles — cannot be scheduled |
| Verifiability | High — web-backed answers usually show cited sources | Low — no way to confirm what was absorbed |
| What the work looks like | Publishing accurate material where models look; fixing crawlability | The same publishing, with a much longer and unverifiable feedback loop |
| What can be promised | A measurable change against a frozen question set | Nothing with a date attached |
When to pick GEO / AEO
- Almost always. Retrieval-targeted work is measurable, verifiable and has a feedback loop short enough to correct course.
- It is also what makes the other side more likely to happen: material that gets retrieved and cited today is material that may be absorbed later.
When to pick LLMO
- Not as a purchasable deliverable. Treat it as a by-product of doing the first properly, not as something with a timeline.
- Be suspicious of any proposal that prices it separately or attaches a date to it.
Questions teams ask before they start
A vendor says they do LLMO, not GEO. Is that better?
It is a naming choice, not a capability. Ask instead how they measure results, whether the question set stays fixed, and whether they will show you the raw answers. Those three answers separate vendors; the label does not.
Does the naming affect what we should buy?
No. What differs between providers is the measurement method, not the label. Ask how results are measured, whether the question set can change mid-engagement, and whether raw answers are provided.
Can training-data influence be measured at all?
Not directly. There is no way to confirm what a model absorbed, only what it retrieves and cites. Any figure presented as measuring the training side is inferred rather than observed.
Is one of these more expensive?
The publishing work is the same work; it is the feedback loop that differs. Where a proposal prices the training-data side separately, what is being sold is the same activity with an unverifiable outcome attached.
Which one do you actually do?
The retrieval side, because it is measurable and correctable within a useful timeframe. The other side is treated as a by-product of doing that properly, and is not sold as a deliverable with a date on it.
Will this distinction still hold next year?
The mechanism may change; the question behind it will not. Whether a given piece of work has a verifiable feedback loop is the thing worth asking about any method, under any name it is given.
Other comparisons
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