AEO, GEO and LLMO Explained for PR and Comms Teams

Four acronyms arrived in comms decks at once, and most of them were used interchangeably by the end of the meeting. They are not the same thing, and the work each one requires is different.

The three definitions

How an AI answer is actually built

Simplified, most assistant answers follow the same shape:

1. Interpret the question and decide whether it needs fresh retrieval at all.
2. Retrieve candidate passages from whatever the system can access — an index, a live search, or cached pages.
3. Rank passages by relevance, authority and corroboration.
4. Generate an answer, citing sources when the product surfaces them.

Your release only matters at stages 2 and 3. That is why "we published a release" is not a strategy, and why a release that cannot be retrieved, or that no independent source repeats, produces no citations.

AEO in practice

• Open with a 40–60 word answer block that stands alone without context
• Write subheadings as the questions readers actually ask
• Pair every question subheading with a direct answer underneath
• Add FAQPage structured data to FAQ sections
• Use tables and lists for anything comparative — they survive extraction
• Avoid pronoun-heavy openings; name the subject explicitly

GEO in practice

Generative engines prefer claims they can corroborate. That is a distribution problem more than a formatting one.

• Get the same core facts repeated across independent outlets, attributed to you
• Publish original data — benchmarks, indices, survey results — that others must cite
• Keep canonical URLs stable so citations do not decay into 404s
• Name your organisation identically everywhere, including in boilerplates
• Label paid placements clearly, because undisclosed ones erode the trust GEO depends on

LLMO in practice

• Publish Organization structured data with legal name, address, contacts and sameAs profiles
• Provide an llms.txt file summarising your organisation for retrieval systems
• Allow the major AI crawlers explicitly in robots.txt rather than blocking them
• Keep machine-readable feeds (RSS, JSON) current
• State facts plainly — models reproduce hedging poorly and invent less when text is precise

Measuring it

Traffic analytics cannot see most AI citations, because the referral is often unattributed or absent entirely. You need a direct method:

• Define a fixed question set — 20 to 40 questions your buyers actually ask.
• Query each engine on a schedule and record whether you appear, citing which source.
• Score accuracy: whether the model's statements about you are correct and current.
• Track competitor share for the same questions, so movement is relative rather than absolute.

This is what our AI Visibility Suite automates across nine engines, and the methodology is the same one you would run manually.