Search is changing faster than ever. With ChatGPT, Google’s AI Overviews, and Perplexity taking center stage, users no longer rely solely on the “10 blue links.”
Instead, answers are synthesized directly in the SERP or app interface — often without a click.
This shift creates a new discipline: LLM SEO (Large Language Model SEO). The goal is challenging yet straightforward: ensure your brand and content are cited, mentioned, and linked within AI-generated responses.
But how do you get there? Is it still about backlinks and content clusters? Or do new rules apply?
In this article, we’ll dive into LLM SEO optimization and everything you need to be taking action on to be a first mover when it comes to ranking.
LLM SEO (Large Language Model Search Engine Optimization) is the practice of structuring and presenting your information in a way that makes it more accessible, understandable, and useful to AI language models like ChatGPT, Claude, or Gemini.
Unlike traditional SEO, which focuses heavily on keywords, backlinks, and metadata, LLM SEO is about shaping your content so these advanced models can:
Sure, there’s a lot of overlap with traditional SEO, but with a bit of a twist:
Large language models don’t “rank” results the way Google does. Instead, they pull from vast amounts of text to generate the most valuable and relevant answer.
If your content is unclear, inconsistent, or buried in jargon, an LLM may bypass it entirely, even if you are an authority in your space.
Traditional SEO often focuses on optimizing for specific keywords.
LLM SEO shifts the focus toward context—providing well-rounded explanations that models can rely on to answer a wide variety of related questions.
Language models thrive on unambiguous input.
Writing in plain, structured language increases the chances your content is understood and used correctly.
Credibility signals—such as citing authoritative sources, being factually accurate, and maintaining consistent branding—help LLMs identify your content as reliable.
LLMs cross-reference data. If your brand voice, facts, and claims remain steady across websites, social profiles, and publications, the model is more likely to “trust” and cite you.
The rise of AI-driven chat platforms has been nothing short of explosive. In just a few months, ChatGPT surged past 100 million users, while other tools like Claude, Perplexity, and DeepSeek have been steadily pulling in tens of millions of visits each month.
People are turning to LLMs for highly specific, in-depth answers that go beyond a quick web search.
Industry forecasts suggest that by 2026, as much as 10–15% of traditional search traffic will shift toward generative AI tools.
Across the client accounts we manage, the sheer number of inbound demos and trials attributed to finding a business via ChatGPT and other LLMs is already substantial, and is only growing:
It’s not uncommon for us to see 10-15%+ of all site-wide conversions being attributed to LLM search.
Not only that, but within the data, we’re actually seeing these self-attributed LLM leads converting at a higher conversion rate vs. traditional organic search leads.
More on that later; let’s first focus on the core ranking factors and how to start to gain visibility in LLM search.
The findings are reinforced by an Ahrefs study on brand visibility in Google’s AI Overviews, which analyzed more than 75,000 websites.
The study revealed that branded web mentions, branded anchor text, and branded search volume are the most powerful predictors of inclusion in AI-generated answers.
Source: Ahrefs
In fact, web mentions had a correlation of 0.664 with AI Overviews, making them an even stronger signal than backlinks.
Traditional SEO factors, such as domain rating, total referring domains, and backlink volume, still matter, but their correlation was significantly weaker, indicating that AI relies more heavily on brand popularity and contextual mentions than on pure link authority.
The takeaway is clear: brand visibility is no longer just an SEO metric—it is a momentum metric that determines whether your business shows up in the emerging ecosystem of AI search.
The more people talk about your brand online and actively search for it, the more likely it is to surface in both generative AI responses and Google’s AI Overviews.
These efforts enhance your branded web mentions—the strongest signal identified in AI visibility studies.
Kevin Indig analyzed 7,392 citations from LLMs across ChatGPT, Perplexity, and Google’s AI Overviews.
Instead of guessing what “might” matter, he compared the top 10% of most-cited pages against the bottom 90% to identify patterns.
Source: Growth Memo
The surprising finding:
LLMs appear to prioritize extractable, easy-to-digest, and comprehensive text, not “SEO’d pages” with strong link profiles.
Traditional SEO often balances two extremes:
But in LLM SEO, you need both at once.
The models want text that:
This explains why the top 10% of cited pages aren’t necessarily the ones with the most backlinks or traffic — they’re the ones that give the model exactly what it needs to “sound smart.”
Imagine two SaaS companies both targeting the query “best CRM for startups.”
Even if Page A ranks higher in organic Google results because of backlinks, Page B is far more likely to be cited in Google’s AI Overview or ChatGPT’s answers.
Why?
Because the LLM can easily pull list-formatted, readable, and comprehensive snippets that directly answer user intent.
In practice, LLMs reward the SaaS brand that writes for clarity and completeness, not the one that just plays the traditional SEO game.
LLMs don’t rely on keyword frequency. They rely on semantic similarity — how closely your content’s meaning matches the way the LLM phrases an answer.
Google’s AI Overviews, for example, rewrite content into natural, simplified language.
Pages that align with that semantic output are the ones cited.
Unlike classic SEO, being #1 isn’t a prerequisite to being cited in AI Overviews.
Kevin Indig’s research shows that sources ranked 11–20 are still cited if they are semantically strong and readable:
A SaaS company’s Zapier integration guide may not rank top 5 in Google but could still be cited in an AI Overview on “how to connect Slack to CRM” — if it’s the most thorough and clearly formatted explanation.
LLMs “decide” which brands to mention based on the type of query.
Prompts with words like “best,” “top,” “recommended,” and “trusted” increase the likelihood of lists and brand mentions.
We highly recommend leveraging competitor comparison pages for targeting BOFU keywords.
If an LLM or its upstream engine can’t crawl your content, it will never be cited.
Many SaaS companies unknowingly block Bingbot (hurting Copilot visibility) or rely on JS-heavy websites that models can’t parse.
In fact, the latter is a significant issue that we consistently encounter when analyzing technical blockers at the outset of a campaign.
Again, as you see, there’s a lot of overlap here with traditional SEO and the technical component.
LLMs prefer structured, quotable text blocks. Google’s AI Overviews average ~90–170 words, often in list format.
Pages with clear TL;DRs, lists, and answer blocks are more likely to be cited.
LLMs don’t limit themselves to your website.
They disproportionately cite YouTube, Wikipedia, and LinkedIn. That means LLM SEO is multi-surface — you need to create content across platforms.
Across our client base, we’re seeing a notable shift: direct-sourced conversions are increasing, while organic attributions are declining.
What’s driving this change? Two main forces: LLMs and AI Overviews.
We validated this trend across three accounts over the past 90 days: each showed an uptick in demo conversions from direct traffic, paired with a nearly equal decline in SEO-attributed conversions.
Listicles are emerging as critical for bottom-of-funnel visibility in LLM results.
When users ask LLMs for “best [product category]” or “top [service providers],” the models often draw from these structured articles.
To capitalize on this, we’re leaning heavily into outreach-based link building, targeting placements in listicles and industry roundups.
This not only boosts traditional SEO but also ensures brand presence when LLMs surface recommendations.
On average, LLM-driven traffic now accounts for ~7% of total traffic across client accounts.
Importantly, this share has been steadily increasing throughout 2025, and we anticipate continued growth as LLM adoption accelerates.
LLM-driven traffic isn’t just growing—it’s also converting at a higher rate than traditional organic.
The reason: users are conducting deeper pre-qualification within the LLM itself.
By the time they reach a site, they’ve already explored product details, features, pricing, and even review sentiment (via G2, Capterra, and similar sources).
As a result, prospects arriving via LLM are further along the decision-making journey, reducing on-site browsing time and accelerating demo or trial requests.
To understand the speed at which LLM visibility can translate into revenue, we ran a test with a newly launched product priced at ~$3,000 per month.
Within just 30 days, the product scaled from zero to $9,000 in MRR, almost entirely through LLM-driven discovery.
Every closed deal self-attributed with “LLM search” (specifically, ChatGPT) when asked how they found us, except one (Google).
This was a fresh site launch, approx 60 days prior.
No LLM/SEO optimization efforts until day 30.
In the past 30 day period:
We’re averaging 4.25 leads per week, almost all attributed to LLM search.
This test underscores how quickly LLM presence can drive both pipeline creation and revenue growth—especially for higher-ticket products where buyers rely on in-depth research before converting.
In-house we’re using Scrunch.ai to track LLM visibility across accounts as a leading indicator for driving LLM-based conversions.
Scrunch provides a deep dive at the query level into daily rankings across:
Scrunch reveals exactly which websites or domains AI search platforms are drawing from when they provide answers that mention your brand, competitors, or third-party content.
It essentially tracks attribution of information in AI-generated responses.
Now we can take actions based on the data to drive LLM visibilit, i.e.
By monitoring shifts in source attribution and exporting performance data, you can prioritize content updates and outreach efforts that steadily increase the likelihood your assets appear in AI-generated answers—essentially creating a playbook for ranking in LLM-driven discovery the same way SEO does for Google.
Rock The Rankings manages dozens of SEO and LLM campaigns for top SaaS brands, helping them drive traffic, pipeline, and revenue growth.
When you partner with us, you work directly with our founder, not junior analysts, ensuring senior-level strategy and precise execution.
If you want your brand cited and recommended in ChatGPT, Perplexity, and Google AI Overviews, now is the time to act.
The first movers in LLM SEO will set the standard for SaaS growth in the years ahead.
Book an intro call and let’s chat.
The search landscape is changing faster than ever, driven by the rise of LLMs and AI-powered answers. Traditional SEO fundamentals remain important, but success now depends on clarity, brand visibility, and creating content that AI systems can easily reference.
Companies that adapt early are already seeing higher conversion rates from LLM-driven traffic, as buyers arrive with deeper research completed.
LLM SEO is no longer optional, it is the new frontier for growth.
Founder of Rock The Rankings, an SEO partner that helps B2B SaaS brands crush their organic growth goals. An avid fan of tennis, and growing micro-SaaS businesses on the weekend. 2x SaaS Co-Founder – Currently working to build and scale Simple Testimonial.
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