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 present doing as a part of my routine advertising and search engine optimization efforts.
To date, it doesn’t seem to be it.
There appears to be large overlap in search engine optimization 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 optimization, one thing that doesn’t require devoted or separate effort. If you wish to improve your presence in LLM output, rent an search engine optimization.
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 price unpacking this a bit. So far as my layperson’s understanding goes, there are three foremost methods you’ll be able to enhance your visibility in LLMs:
1. Improve your visibility in coaching information
Massive language fashions are educated on huge datasets of textual content. The extra prevalent your model is inside that information, and the extra intently related it appears to be with the matters you care about, the extra seen you’ll be in LLM output for these given matters.
We are able to’t affect the info LLMs have already educated on, however we are able to create extra content material on our core matters for inclusion in future rounds of coaching, each on our web site and third-party web sites.
Creating well-structured content material on related matters is likely one of the core tenets of search engine optimization—as is encouraging different manufacturers to reference you inside their content material. Verdict: simply search engine optimization.
2. Improve your visibility in information sources used for RAG and grounding
LLMs more and more use exterior information sources to enhance the recency and accuracy of their outputs. They will search the net, and use conventional search indexes from firms like Bing and Google.
OpenAI’s VP Engineering on Reddit confirming the usage of the Bing index as a part of ChatGPT Search.
It’s truthful to say that being extra seen in these information sources will doubtless improve visibility within the LLM responses. The method of changing into extra seen in “conventional” search indexes is, you guessed it, search engine optimization.
3. Abuse adversarial examples
LLMs are susceptible to manipulation, and it’s attainable to trick these fashions into recommending you once they in any other case wouldn’t. These are damaging hacks that provide 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 optimization.
To summarize these three factors, the core mechanism for enhancing visibility in LLM output is: creating related content material on matters your model desires to be related to, each on and off your web site.
That’s search engine optimization.
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’s more likely to be much less divergence, and the boundaries between search engine optimization and GEO will develop into 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 one in all my latest LinkedIn posts:
“There’s solely so some ways you’ll be able to shake a stick at aggregating a bunch of data, rating it, after which disseminating your finest approximation of what the most effective and most correct outcome/data would be.”
I shared the above opinion in a LinkedIn put up and acquired some really wonderful responses.
Most individuals agreed with my sentiment, however others shared nuances between LLMs and search engines like google and yahoo which can be price 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 optimization. Unlinked mentions—textual content written about your model on different web sites—have little or no influence on search engine optimization, however a a lot larger influence on GEO.
Search engines like google have some ways to find out the “authority” of a model on a given matter, however backlinks are some of the essential. This was Google’s core perception: that hyperlinks from related web sites might perform as a “vote” for the authority of the linked-to web site (a.ok.a. PageRank).
LLMs function in a different way. They derive their understanding of a model’s authority from phrases on the web page, from the prevalence of explicit phrases, the co-occurrence of various phrases and matters, and the context by which these phrases are used. Unlinked content material will additional an LLM’s understanding of your model in a manner that received’t assist a search engine.
As Gianluca Fiorelli writes in his wonderful article:
“Model mentions now matter not as a result of they improve ‘authority’ immediately 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 linked 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 matter house.”
Many firms already worth off-site mentions, albeit with the caveat that these mentions needs to be linked (and dofollow). Now, I can think about manufacturers stress-free their definition of a “good” off-site point out, and being happier with unlinked mentions in platforms that cross little conventional search profit.
As Eli Schwartz places it,
“On this paradigm, hyperlinks don’t should be hyperlinked (LLMs learn content material) or restricted to conventional web sites. Mentions in credible publications or discussions sparked on skilled networks (good day, information bases and boards) all improve visibility inside this framework.”
Monitor model mentions with Model Radar
You should use our new device, Model Radar, to trace your model’s visibility in AI mentions, beginning with AI Overviews.
Enter the subject you need to monitor, your model (or your opponents’ manufacturers), and see impressions, share of voice, and even particular AI outputs mentioning your model:
I feel the inverse of the above level can be true. Many firms right now 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 website status abuse).
These ways provide sufficient search engine optimization 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 probability of it showing in outputs.
Some content material varieties have comparatively little influence on search engine optimization visibility however better influence on LLM visibility.
We ran analysis to discover the forms of pages which can be almost definitely 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 “choice” 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. Search 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 information, it appears the vast majority of citations fall into the “core website pages” class: a web site’s house web page, pricing web page, or about web page. These are essential elements of a web site, however not at all times massive contributors to look visibility. Their significance appears better for LLMs.
A slide from my brightonSEO discuss displaying how AI and non-AI site visitors is distributed throughout totally different web page varieties.
Inversely, listings pages—assume massive breadcrumbed Rolodexes of merchandise—which can be created primarily for on-page navigation and search visibility acquired far fewer visits from LLMs. Even when these web page varieties aren’t cited typically, it’s attainable that they may additional an LLM’s understanding of a model due to the co-occurrence of various product entities. However provided that these pages are often sparse in context, they might have little influence.
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 some other, and so they routinely cite them of their outputs.
Virtually, I can think about firms treating PDFs and different forgotten paperwork with extra significance, on the understanding that they’ll affect LLM output in the identical manner some other website web page would.
The purpose that LLMs can entry web site paperwork raises an fascinating level. As Andrej Karpathy factors out, there could also be a rising profit to writing paperwork which can be structured before everything 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 mainly render to some fairly .html static pages assuming a human will click on by them. In 2025 the docs needs to be a single your_project.md textual content file that’s supposed to enter the context window of an LLM.
Repeat for every little thing.”
That is an inversion of the search engine optimization adage that we should 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 data into extra accessible kinds for customers.
On this manner, there are particular info constructions that may assist LLMs appropriately perceive the data we offer.
For instance, Snowflake refers back to the thought of “international doc 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 title 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 presents small methods for manufacturers to enhance the probability that LLMs will interpret their content material appropriately.
LLMs additionally prepare on novel info sources which have historically fallen outdoors the remit of search engine optimization. As Adam Noonan on X shared with me: “Public GitHub content material is assured to be educated on however has no influence on search engine optimization.”
Coding is arguably probably the most profitable use case for LLMs, and builders should make up a sizeable portion of whole LLM customers.
For some firms, particularly these promoting to builders, there could also be a profit to “optimizing” the content material these builders are almost definitely 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. Standard AI crawlers like these utilized by OpenAI and Anthropic don’t even execute JavaScript. Which means they received’t see content material that’s rendered client-side by JavaScript.”
That is extra of a footnote than a significant distinction, for the easy motive that I don’t assume this can stay true for very lengthy. This drawback was solved by many non-AI net crawlers, and will probably be solved by AI net crawlers in brief order.
However for now, when 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 traditional remit of search engine optimization.
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 effectively in a single additionally do effectively within the different.
Even when GEO does finally 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 optimization.
