As a marketer, I need to know if there are particular issues I ought to do to enhance our LLM visibility that I’m not at the moment doing as a part of my routine advertising and search engine optimisation efforts.
To date, it doesn’t look like it.
There appears to be huge overlap in search engine optimisation and GEO, such that it doesn’t appear helpful to think about them distinct processes.
The issues that contribute to good visibility in search engines like google and yahoo additionally contribute to good visibility in LLMs. GEO appears to be a byproduct of search engine optimisation, one thing that doesn’t require devoted or separate effort. If you wish to enhance your presence in LLM output, rent an search engine optimisation.
Sidenote.
GEO is “generative engine optimization”, LLMO is “massive language mannequin optimization”, AEO is “reply engine optimization”. Three names for a similar thought.
It’s value unpacking this a bit. So far as my layperson’s understanding goes, there are three primary methods you possibly can enhance your visibility in LLMs:
1. Enhance your visibility in coaching knowledge
Massive language fashions are skilled on huge datasets of textual content. The extra prevalent your model is inside that knowledge, and the extra carefully related it appears to be with the subjects you care about, the extra seen you can be in LLM output for these given subjects.
We are able to’t affect the information LLMs have already skilled on, however we are able to create extra content material on our core subjects for inclusion in future rounds of coaching, each on our web site and third-party web sites.
Creating well-structured content material on related subjects is likely one of the core tenets of search engine optimisation—as is encouraging different manufacturers to reference you inside their content material. Verdict: simply search engine optimisation.
2. Enhance your visibility in knowledge sources used for RAG and grounding
LLMs more and more use exterior knowledge sources to enhance the recency and accuracy of their outputs. They will search the online, and use conventional search indexes from corporations like Bing and Google.
OpenAI’s VP Engineering on Reddit confirming using the Bing index as a part of ChatGPT Search.
It’s honest to say that being extra seen in these knowledge sources will doubtless enhance visibility within the LLM responses. The method of turning into extra seen in “conventional” search indexes is, you guessed it, search engine optimisation.
3. Abuse adversarial examples
LLMs are susceptible to manipulation, and it’s potential to trick these fashions into recommending you once they in any other case wouldn’t. These are damaging hacks that supply short-term profit however will most likely chew you within the lengthy time period.
That is—and I’m solely half joking—simply black hat search engine optimisation.
To summarize these three factors, the core mechanism for enhancing visibility in LLM output is: creating related content material on subjects your model desires to be related to, each on and off your web site.
That’s search engine optimisation.
Now, this is probably not true without end. Massive language fashions are altering on a regular basis, and there could also be extra divergence between search optimization and LLM optimization as time progresses.
However I believe the other will occur. As search engines like google and yahoo combine extra generative AI into the search expertise, and LLMs proceed utilizing “conventional” search indexes for grounding their output, I feel there may be prone to be much less divergence, and the boundaries between search engine optimisation and GEO will turn out to be even smaller, or nonexistent.
So long as “content material” stays the first medium for each LLMs and search engines like google and yahoo, the core mechanisms of affect will doubtless stay the identical. Or, as somebody commented on certainly one of my recent LinkedIn posts:
“There’s solely so some ways you possibly can shake a stick at aggregating a gaggle of data, rating it, after which disseminating your greatest approximation of what one of the best and most correct outcome/data would be.”
I shared the above opinion in a LinkedIn post and acquired some really glorious responses.
Most individuals agreed with my sentiment, however others shared nuances between LLMs and search engines like google and yahoo which are value understanding—even when they don’t (for my part) warrant creating the brand new self-discipline of GEO:
That is most likely the largest, clearest distinction between GEO and search engine optimisation. Unlinked mentions—textual content written about your model on different web sites—have little or no affect on search engine optimisation, however a a lot larger affect on GEO.
Engines like google have some ways to find out the “authority” of a model on a given subject, however backlinks are one of the vital essential. This was Google’s core perception: that hyperlinks from related web sites may operate as a “vote” for the authority of the linked-to web site (a.ok.a. PageRank).
LLMs operate differently. They derive their understanding of a brand’s authority from words on the page, from the prevalence of particular words, the co-occurrence of different terms and topics, and the context in which those words are used. Unlinked content will further an LLM’s understanding of your brand in a way that won’t help a search engine.
As Gianluca Fiorelli writes in his excellent article:
“Model mentions now matter not as a result of they enhance ‘authority’ straight however as a result of they strengthen the place of the model as an entity inside the broader semantic community.
When a model is talked about throughout a number of (trusted) sources:
The entity embedding for the model turns into stronger.
The model turns into extra tightly related to associated entities.
The cosine similarity between the model and associated ideas will increase.
The LLM ‘study’ that this model is related and authoritative inside that subject area.”
Many corporations already worth off-site mentions, albeit with the caveat that these mentions needs to be linked (and dofollow). Now, I can think about manufacturers enjoyable their definition of a “good” off-site point out, and being happier with unlinked mentions in platforms that move little conventional search profit.
As Eli Schwartz places it,
“On this paradigm, hyperlinks don’t must be hyperlinked (LLMs learn content material) or restricted to conventional web sites. Mentions in credible publications or discussions sparked on skilled networks (hi there, data bases and boards) all improve visibility inside this framework.”
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I feel the inverse of the above level can be true. Many corporations at present construct backlinks on web sites with little relevance to their model, and publish content material with no connection to their enterprise, merely for the site visitors it brings (what we now name site reputation abuse).
These ways provide sufficient search engine optimisation profit that many individuals nonetheless deem them worthwhile, however they are going to provide even much less profit for LLM visibility. With none related context surrounding these hyperlinks or articles, they are going to do nothing to additional an LLM’s understanding of the model or enhance the chance of it showing in outputs.
Some content material sorts have comparatively little affect on search engine optimisation visibility however better affect on LLM visibility.
We ran analysis to discover the varieties of pages which are more than likely to obtain site visitors from LLMs. We in contrast a pattern of pageviews from LLMs and from non-LLM sources, and in contrast the distribution of these pageviews.
We discovered two massive variations: LLMs present a “desire” for core web site pages and paperwork, and a “dislike” for itemizing collections and listings.
Quotation is extra essential for an LLM than a search engine. Engines like google typically floor info alongside the supply that created it. LLMs decouple the 2, creating an additional must show the authenticity of no matter declare is being made.
From this knowledge, it appears the vast majority of citations fall into the “core website pages” class: an internet site’s house web page, pricing web page, or about web page. These are essential components of an internet site, however not all the time massive contributors to go looking visibility. Their significance appears better for LLMs.
A slide from my brightonSEO discuss displaying how AI and non-AI site visitors is distributed throughout completely different web page sorts.
Inversely, listings pages—suppose massive breadcrumbed Rolodexes of merchandise—which are created primarily for on-page navigation and search visibility acquired far fewer visits from LLMs. Even when these web page sorts aren’t cited usually, it’s potential that they may additional an LLM’s understanding of a model due to the co-occurrence of various product entities. However on condition that these pages are normally sparse in context, they might have little affect.
Lastly, web site paperwork additionally appear extra essential for LLMs. Many web sites deal with PDFs and different types of paperwork as second-class residents, however for LLMs, they’re a content material supply like another, and so they routinely cite them of their outputs.
Virtually, I can think about corporations treating PDFs and different forgotten paperwork with extra significance, on the understanding that they will affect LLM output in the identical means another website web page would.
The purpose that LLMs can entry web site paperwork raises an fascinating level. As Andrej Karpathy points out, there could also be a rising profit to writing paperwork which are structured firstly for LLMs, and left comparatively inaccessible to folks:
“It’s 2025 and most content material continues to be written for people as a substitute of LLMs. 99.9% of consideration is about to be LLM consideration, not human consideration.
E.g. 99% of libraries nonetheless have docs that principally render to some fairly .html static pages assuming a human will click on by way of them. In 2025 the docs needs to be a single your_project.md textual content file that’s meant to enter the context window of an LLM.
Repeat for every little thing.”
That is an inversion of the search engine optimisation adage that we must always write for people, not robots: there could also be a profit to focusing our power on making info accessible to robots, and counting on the LLMs to render the knowledge into extra accessible varieties for customers.
On this means, there are particular info constructions that may assist LLMs appropriately perceive the knowledge we offer.
For instance, Snowflake refers back to the thought of “global document context”. (H/T to Victor Pan from HubSpot for sharing this text.)
LLMs work by breaking textual content into “chunks”; by including further details about the doc all through the textual content (like firm identify and submitting date for monetary textual content), it’s simpler for the LLM to know and appropriately interpret every remoted chunk, “boosting QA accuracy from round 50%-60% to the 72%-75% vary.”
Understanding how LLMs course of textual content provides small methods for manufacturers to enhance the chance that LLMs will interpret their content material appropriately.
LLMs additionally prepare on novel info sources which have historically fallen exterior the remit of search engine optimisation. As Adam Noonan on X shared with me: “Public GitHub content material is assured to be skilled on however has no affect on search engine optimisation.”
Coding is arguably essentially the most profitable use case for LLMs, and builders should make up a sizeable portion of whole LLM customers.
For some corporations, particularly these promoting to builders, there could also be a profit to “optimizing” the content material these builders are more than likely to work together with—knowledgebases, public repos, and code samples—by together with further context about your model or merchandise.
Lastly, as Elie Berreby explains:
“Most AI crawlers don’t render JavaScript. There’s no renderer. Well-liked AI crawlers like these utilized by OpenAI and Anthropic don’t even execute JavaScript. Which means they gained’t see content material that’s rendered client-side by way of JavaScript.”
That is extra of a footnote than a significant distinction, for the easy purpose that I don’t suppose this can stay true for very lengthy. This downside was solved by many non-AI net crawlers, and might be solved by AI net crawlers briefly order.
However for now, in case you rely closely on JavaScript rendering, a superb portion of your web site’s content material could also be invisible to LLMs.
Ultimate ideas
However right here’s the factor: managing indexing and crawling, structuring content material in machine-legible methods, constructing off-page mentions… these all really feel just like the basic remit of search engine optimisation.
And these distinctive variations don’t appear to have manifested in radical variations between most manufacturers’ search visibility and LLM visibility: typically talking, manufacturers that do properly in a single additionally do properly within the different.
Even when GEO does ultimately evolve to require new ways, SEOs—individuals who spend their careers reconciling the wants of machines and actual folks—are the folks best-placed to undertake them.
So for now, GEO, LLMO, AEO… it’s all simply search engine optimisation.
