Business

Inside LLM SEO: How to optimize and measure your brand’s visibility

By Sarah Berry for WebFX Stacker

Updated April 20, 2026 2:09 PM

Inside LLM SEO: How to optimize and measure your brand's visibility

"The only sustainable competitive advantage is to learn faster than your competition." That quote (from former GE CEO Jack Welch) rings true now more than ever.

With large language models (LLMs) like ChatGPT and Gemini redefining the search experience, it's become imperative for businesses to adapt and adopt LLM SEO, WebFX reports.

Getting that competitive advantage, though, starts with understanding LLM SEO.

What is LLM SEO?

LLM SEO is the practice of optimizing a brand's online presence in order to appear in large language model responses, whether via a mention or citation. It stands for search everywhere optimization for large language models.

There are a few other names for LLM SEO, including:

Generative engine optimization (GEO)
Answer engine optimization (AEO)
Large language model optimization (LLMO)

Why does SEO for large language models matter now?

With a 14% annual growth rate, the global AI search engines market is growing rapidly.

Analysts now value the market at more than $40 billion - and expect it to reach $100+ billion by 2032. Google's AI Overviews and AI Mode have only accelerated this valuation (and growth), creating an urgent need for sophisticated AI visibility tools that can track brand performance across this expanding ecosystem.

LLM SEO matters because people are no longer reliant on traditional search - ChatGPT, Gemini, and other AI models are helping them discover brands, solve problems, and purchase products.

Just as important is how users have adopted LLM-powered search:

80% of users rely on AI-powered summaries 40% of the time
68% of users use LLMs to research and summarize information
58% of users now use LLMs for product and service recommendations

For businesses, these shifts translate to a 15-25% decrease in organic traffic. Companies like NerdWallet and HubSpot have seen these traffic decreases play out publicly, with NerdWallet reporting a 20% year-over-year traffic loss in 2024.

While companies can focus on regaining that lost traffic, it's an incomplete approach because it overlooks AI's growing role in how people discover brands, research solutions, and purchase products.

Instead, businesses need to expand their thinking to how they'll meet users in traditional and AI-powered experiences on ChatGPT, Google, and Perplexity - and that starts with LLM SEO.

How does LLM SEO compare to traditional SEO?

LLM is not the end of traditional SEO. In fact, traditional SEO is considered foundational to LLM optimization. That's why SEO-optimized websites appear more often in AI-powered experiences.

You can see how the two overlap (and differ) below:

The core difference between the two is their targeted search experience. While SEO targets traditional search experiences, LLM SEO targets large language model search experiences.

How to do LLM SEO

You know optimizing for LLMs matters. Now, learn how to do LLM SEO for your business based on industry practices for managing LLM SEO campaigns:

Nurture traditional SEO efforts

First, continue to nurture traditional SEO efforts by:

Allowing search (and AI) crawlers to crawl and index your website
Producing keyword-targeted SEO content (organic is still a leading traffic source)
Claiming local listings, like Google Business Profile and Bing Places
Optimizing existing content, from product pages to blog posts, for traditional search
Improving page speed to streamline the user experience
Outreaching publishers to earn links to your website's content

Produce original content

Original content is one of the most powerful optimizations available to businesses looking to appear in LLM responses. That's because LLMs (like Google) love content that brings something new to the conversation using:

Statistics
Quotes
Insights

Businesses can lean into this optimization by:

Evaluating third-party studies
Running data studies
Analyzing internal data
Interviewing senior leaders or front-line workers

Get ideas for how this could look at your organization below:

Optimize content for clarity

When it comes to SEO for LLMs, it's not just writing content that brings something new to the conversation. It's also about formatting that content so it's concise for users and digestible for LLMs.

For example, content should use the following:

Headings (H1, H2s, H3s, etc.)

Lists
Tables
Schema markup

You can use headings, for example, to write concise answers to questions like:

What are the best pillows for neck pain?
What are the main benefits of remote work for businesses?
How often should you replace your windshield wipers?

Businesses should also evaluate their content's readability. In most cases, it's worth writing at an eighth-grade reading level, though this can vary for more niche industries.

Enhance content with visuals

Visuals are an underused optimization for appearing in LLM responses, like in AI Overviews or ChatGPT. With visuals, whether it's a graphic or interactive experience, businesses can build their visibility and even referral traffic.

Examples of how organizations can use visuals for LLM SEO include:

Build brand mentions

Brand mentions are one of the most important LLM SEO optimizations.

That's because - like traditional SEO, where ranking on page two means next-to-nothing traffic - not being mentioned in LLMs means you're not a part of the conversation.

There are a few elements to brand mentions, including:

You'll notice these elements all relate to context - which is vital to LLMs. Understanding your brand's nuances, like whether it's a good mattress for side sleepers, helps LLMs deliver personalized responses.

Even more important, these nuances help you reach your target audience.

Creating these mentions overlaps with traditional SEO, which uses off-page SEO to build a brand's online reputation and backlink profile, which helps the site rank in search results.

For example, businesses can consider the following optimizations:

How to measure LLM SEO results

When it comes to measuring LLM SEO results, there are three factors:

Metrics
Tools
Timeframe

You can learn more about these factors below:

Metrics

LLM SEO focuses mostly on visibility metrics, like:

Referral traffic, or the number of visits from LLMs
Mentions, or when an LLM mentions your brand
Citations, or when an LLM links to your brand's website
Share of voice, or the percentage of brand mentions across models vs. a competitor's
Share of model, or the percentage of brand mentions within a model vs. a competitor's
Share of search, or the percentage of brand searches vs. a competitor's

These metrics introduce a significant shift for traditional SEOs, which often focus on rankings and traffic. However, they demonstrate what companies like NerdWallet and HubSpot are seeing - traffic is down, but revenue is up.

Tools

Tools are key - but limited - when it comes to tracking LLM performance.

Google Analytics 4

In Google Analytics 4, the best way to measure LLM traffic is through a custom channel group. With a custom channel group based on source, businesses can extract LLM visits from referral traffic to measure LLM performance at a glance.

Use regex - based on source - to create this custom channel group. An LLM (like ChatGPT) can help create the regex, which will change as new LLM platforms get released.

OmniSEO

OmniSEO is a platform that tracks LLM SEO metrics. The tool provides a way to measure brand visibility across several experiences, including:

ChatGPT
AI Overviews
Perplexity
Claude
Meta AI
Copilot
xAI
Apple Intelligence
And more

Companies can also benchmark their performance against competitors.

The OmniSEO platform can be used to measure how LLMs perceive a brand's:

Cost
Expertise
Performance
Product and/or service
Reputation
And more

As a result, you get a complete picture of your brand's performance.

Examples of real LLM SEO campaigns

Some examples of real LLM SEO campaigns include:

This story was produced by WebFX and reviewed and distributed by Stacker.

This story was originally published April 20, 2026 at 10:00 AM.