What Is LLMO? Optimize Content for AI & Large Language Models

Chances are, you’ve seen clicks to your website from organic search results decline since about May 2024—when AI Overviews launched.

Large language model optimization (LLMO), a set of tactics for getting your business mentioned and cited more often in AI-generated responses, is somewhat of an antidote to that declining search traffic.

Why?

AI search usage is exploding—and website traffic from LLMs is on the rise because of it.

Plus, AI search visitors convert 4.4x better than traditional organic search visitors, Semrush research shows. And LLM traffic channels are projected to drive as much business value as traditional search by 2027.

So, getting mentioned by LLMs is something your business should start working on now.

In this article, you’ll learn how to make that happen. We’ll take a deep dive into the five pillars of LLMO and explore tactics you can start using today to get more mentions in LLM answers. 

What is large language model optimization?

LLMO is the practice of optimizing your content, website, and brand presence to appear in AI-generated responses from tools like ChatGPT Search, Google’s AI Overviews, and Perplexity. 

Whereas traditional search engine optimization (SEO) focuses on ranking in search results, the purpose of LLMO is to get your brand mentioned, cited, and recommended within conversational AI responses. It focuses on improving brand awareness, trust, and authority throughout the buyer’s journey—even when users don’t click through to your website.

LLMO signifies a huge shift toward the future of SEO, which involves optimizing for visibility—not necessarily for clicks.

SEO vs. AEO vs. GEO vs. LLMO: What’s the difference?

While these terms are often used interchangeably, each one actually has a distinct focus.

StrategyFocusPrimary GoalKey PlatformsSEOSearch rankingsDrive organic traffic to your websiteGoogle, BingAEOAI OverviewsAppear in Google’s AI summaries to drive awareness and trafficGoogle Search results pagesGEOAI answer enginesGet cited across AI search platforms to drive awareness and trafficGoogle AI Mode, Bing Chat, PerplexityLLMOConversational AIGet brand mentions in AI chat responses to drive awareness and trafficChatGPT, Claude, Gemini

SEO

SEO is the traditional method of optimizing website content. It targets higher search engine rankings and more organic traffic from platforms like Google and Bing. SEO is primarily keyword-driven, which means targeting certain keywords with each page or piece of content on your website. That said, while SEOs still speak in terms of keywords, the industry’s mindset is shifting toward entity SEO.

SEO involves tactics like keyword research, page title and meta description optimization, content creation, site speed fixes, link building, and more.

Example: Optimizing your blog post to rank in search engine results for “email marketing best practices” so people searching for this topic click through to your website.

Answer Engine Optimization (AEO)

AEO is a method of optimizing content to appear in Google’s AI Overviews—the AI-generated summaries that appear at the top of search results—as well as featured snippets.

The goal? To drive awareness of your brand and clicks to your website. This requires structuring well-written content in ways that Google’s AI can easily extract and use in its answers.

AEO involves tactics like providing direct answers to questions; including relevant statistics and data; and formatting content using descriptive headings, bullet points, numbered lists, and charts.

Example: Structuring your content with clear headings like “Email Marketing Conversion Rates by Industry” and presenting data in an easily scannable format—so Google’s AI Overview cites your statistics article when someone searches “email marketing conversion rates 2025.”

Generative Engine Optimization (GEO)

GEO is a method of optimizing website content for any AI answer engine that generates responses—including search engines with AI features. It focuses on getting cited and mentioned across all the major AI search platforms that pull information from the web.

GEO involves tactics like creating authoritative content with links to trusted sources, building domain authority, optimizing for AI Overviews, and making sure your entire website is easily accessible by AI.

Example: Ensuring your brand appears in AI-generated responses across multiple platforms—like Google’s AI Mode, ChatGPT search, Bing Chat, and third-party AI tools—when users search for topics in your area of expertise.

LLMO

LLMO is a method of optimizing content specifically for LLMs like ChatGPT, Claude, and Gemini. The goal is to get brand mentions, recommendations, and citations (links to your content) in conversational AI responses.

LLMO involves building brand authority through mentions on high-authority sites, creating deep content, and writing content with information gain.

Example: When someone asks ChatGPT “What’s the best email marketing tool for small businesses?” your brand gets recommended in the response with specific reasons why.

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The 5 pillars of LLMO

To get more mentions and citations in LLMs, you need to know the main components of LLMO. The optimization process has some crossover with traditional SEO methods—plus some tactics that are unique to LLMs.

There are five main pillars of LLM optimization:

1. Information gain

Information gain means making sure your content provides unique value that users can’t find elsewhere. LLMs prioritize content that offers original, one-of-a-kind insights over repeated information that already appears in existing content.

The results of using information gain to optimize for LLMs can be significant: one study found that content that includes quotes, statistics, and links to credible data sources is mentioned 30-40% more often in LLMs (compared to a baseline of unoptimized content).

Here’s how to create content with strong information gain:

Offer unique value, not regurgitated info. Instead of writing another “10 top SEO tips” post, consider something like “How we increased organic traffic 300% using unconventional SEO tactics competitors ignore.”

Add analysis, frameworks, points of view, data, or stories that others haven’t covered. Share your proprietary methodology, original case studies, or sprinkle in your contrarian viewpoints backed by real data.

What does information gain actually look like?

To find out, we ran a ChatGPT search asking “How do marketers use AI?” and found this Sprout Social article ranking among the results. It uses information gain to help its LLM visibility.

Specifically, the part of the article mentioned in ChatGPT search results is the section featuring real-life AI usage examples:

This section uses unique examples, links to the original sources, a statistic, and clear explanations of AI technology. These elements all add unique value to the article—which helps it stand out as a great source for the LLM. 

2. Entity optimization

An entity is a person, place, brand, or concept in Google’s Knowledge Graph and in LLMs. 

Entity optimization is the process of improving how search engines and LLMs recognize and connect entities. It strengthens your brand’s relevance by helping LLMs understand who you are and what topics you’re knowledgeable about.

Think of it as building your brand’s “identity card” for AI systems. 

For example, here’s what happens when you search “Moz” in Google search:

Moz is an entity that Google knows a lot about—from the company’s website and Chrome extension to its social media accounts and company overview. Because of how strong and well-known the Moz brand is, it’s likely to show up more often than some competitors in AI Overviews and LLMs.

To help Google and LLMs understand what your brand is all about, try these entity optimization tactics:

Use schema markup to define who or what you are

Implementing schema markup like Organization and Person schema can help search engines and LLMs better understand your brand identity. 

Beyond Person and Organization schema, you might also use:

• Product schema
• Service schema
• Author schema
• Brand schema
• LocalBusiness schema
• Review or AggregateRating schema

Check for a Google Knowledge Panel

Run a search for your own brand name to see if Google brings up a Knowledge Panel for your business. If it does, make sure you’ve claimed it. Then, optimize it by making changes to things like:

• Featured images
• Titles
• Subtitles
• Descriptions
• Social media profiles

Don’t have a Knowledge Panel? Learn what a Google Knowledge Panel is and how to get one.

Connect to established, recognizable entities

Make sure your brand is listed on and/or linked with authoritative platforms that LLMs recognize and trust.

Here are a few of the top platforms to start with:

• Wikipedia or Wikidata: If your brand is notable enough to be listed on Wikipedia or Wikidata, create or update your entry. Be sure to follow the Wikipedia guidelines.
• LinkedIn: Maintain complete company and personal profiles with detailed descriptions. Link to your LinkedIn page in your schema using the sameAs property.
• Crunchbase: List your company and include as much information as possible about your brand and team. Like your logo, founded date, description, industries, and social media links.
• Industry directories: List your business in any relevant trade association directories and industry databases

The goal is for your brand to appear consistently across the platforms that LLMs commonly reference. When your brand information appears across multiple authoritative sources, LLMs are more likely to recognize it as a legitimate entity worth mentioning.

Build mentions of your brand across the web

The more your brand appears alongside relevant topics across authoritative sites, the stronger your entity associations become.

Say you run a cookieless, independent website analytics tool. Here are some ways to get mentioned alongside your most relevant topics:

• Podcast appearances: Get featured on podcasts relevant to your industry, where you can talk about topics related to website analytics and traffic measurement.
• Press coverage: Seek mentions in, say, a TechCrunch article about the changing ways people are measuring their website traffic as AI technology advances.
• User-generated content platforms (social media): Engage authentically by contributing to industry discussions without over-promoting your brand on platforms like Reddit, Quora, and LinkedIn.
• Speaking engagements and conferences: Deliver a talk about web analytics at an industry conference.
• Industry roundups and “best of” lists: Work to get included in articles like “Top 10 Web Analytics Tools” or “Best Analytics Experts to Follow.” These list-style articles are frequently referenced by LLMs.
• Research collaborations: Partner with other brands or publications on industry studies to get your brand mentioned as a contributor or data source.

3. Structured and semantic content

LLMs largely prefer well-organized content. One study found that “stylistic changes such as improving fluency and readability of the source text…resulted in a significant visibility boost of 15-30% [compared to unoptimized content].” 

Using a clear structure in website content improves readability for both humans and AI systems, making it easier to extract and cite specific information. Which is why structured formats (think headings, bullet points, and comparison tables) seem to consistently outperform dense text blocks in AI responses.

Why content structure matters for LLMs

LLMs can better understand and cite content that’s logically organized with clear signposts.

In fact, research by AirOps shows that:

• ChatGPT cites content with a sequential heading structure (e.g., H1 > H2 > H3) nearly three times more often
• Of the articles cited in ChatGPT results, almost 80% include at least one section with a list—whereas only 28.6% of Google’s top results contain a list
• Pages cited by ChatGPT have an average of almost 14 list sections. That’s more than 17 times as many list sections than average for pages ranked in Google SERPs. 

The data is clear: deliberately structuring your content with headings, lists, tables, schema, and more will help you get more LLM visibility.

Here’s how to structure content for maximum LLM visibility:

• Use descriptive headings that answer specific questions. Instead of vague headings like “Tips” or “Best Practices,” try question-based headings that mirror how people actually search. Like “How to optimize meta descriptions for AI search” or “What makes a good email subject line?”
• Create comparison tables for complex topics. When explaining differences between tools, strategies, or concepts, use tables that clearly show features, benefits, and use cases side by side.
• Use FAQ blocks throughout your content. Don’t just add FAQs at the end. Instead, weave question-and-answer sections into relevant parts of your content. According to the AirOps study, FAQ schema is more than twice as common in LLM-cited content than in Google search engine results pages (SERPs).
• Use numbered lists for processes and step-by-step guides. When explaining how to do something, break it into clear, actionable guidelines using numbered steps.
• Add definition lists for industry terms. When introducing technical concepts, format them clearly so LLMs can easily extract and cite your definitions. For example, “[Term] is [definition].” If your content includes multiple terms that need defining, consider including them in a list.

A real-life example of structured content

Let’s look at the layout of another Search Engine Land article as an example of structured content:

This article snippet includes:

• Hierarchical use of headings (H2 > H3)
• A question-style heading
• A definition (Long form content is…)
• Bullet points
• A separated, highly relevant tip

This structure makes it easy for LLMs to extract specific information. When someone asks ChatGPT about long-form content formats, it can quickly cite Search Engine Land’s clear list of examples. 

And it does:

4. Clarity and attribution

LLMs favor content that’s both easy to understand and properly sourced. AI answer engines cite this type of content more often because they prioritize information they can quickly and confidently verify.

A GEO study by researchers at Princeton University and the Indian Institute of Technology Delhi found that adding quotes, citations, and links to sources are the most effective ways to improve LLM visibility.

Why?

When LLMs generate responses, they need to quickly extract key facts and understand source credibility. Content that’s written clearly and cites authoritative sources makes this process easier, increasing your chances of being mentioned or cited.

Here’s how to incorporate clarity and attribution into your content:

Write concise, factual paragraphs. Keep paragraphs short (around two to three sentences) and frontload the most important information. This makes it easier for LLMs to quickly identify and extract key facts from your content.

Include proper citations and outbound links. Link to authoritative sources like industry studies, government data, academic research, and expert opinions. This helps improve your credibility.

Use formatting that aids clarity:

• Bold key terms and important concepts to help LLMs identify crucial information
• Use numbered lists for processes and sequential information
• Create summary boxes or callouts for key takeaways
• Include transition words (therefore, however, this means, additionally, firstly, etc.) that guide readers and LLMs through your content

5. Authoritativeness and mentions

Your brand’s visibility in LLMs is largely determined by how often you’re mentioned and cited across the web, especially on high-authority platforms like Wikipedia, major news outlets, and industry publications that AI systems commonly reference in their training data.

Your brand’s search volume also plays a role. A recent study by Kevin Indig reveals a correlation between how often a brand is mentioned in LLMs and how often people search for it by name:

Why mentions and authority matter for LLMs

LLMs learn about brands and their expertise by analyzing patterns across millions of web pages. When your brand consistently appears alongside specific topics on authoritative sites, AI systems begin to associate your brand with authority in those topics.

Think of it like building a reputation in real life. The more credible sources that mention your expertise, the more likely others are to recommend you. LLMs work similarly, but at a much larger scale.

And the more your business builds a reputation, the more branded search volume you can gain. Which gives you another vote of confidence in LLMs.

How to build your brand’s authority for more LLM visibility

Get referenced on high-authority sites. Work to earn mentions on platforms that LLMs commonly cite, such as industry publications, news sites, and authoritative forums. 

You can do this by creating newsworthy content like original research or industry surveys, responding to journalist queries through services like HARO (Help a Reporter Out), and contributing valuable insights to industry discussions on Reddit and professional forums.

Great platforms for building mentions include:

• Industry publications: Websites and sources that are popular for your industry (like TechCrunch, Forbes, and G2 Learning Hub)
• News outlets: Major publications like Inc.
• Online forums: Reddit and Quora are heavily referenced by LLMs, according to Semrush research
• Academic and research sites: Educational institutions like Harvard Business Review and research organizations like the Pew Research Center carry high authority
• Government websites: Official .gov sources like the Bureau of Labor Statistics are considered highly authoritative

Earn unlinked brand mentions and citations. Not every mention needs a link to your website to be valuable for LLM optimization. When journalists, bloggers, or industry experts mention your brand name in articles, LLMs can still associate your business with those topics.

Focus on becoming a go-to expert source for journalists and content creators in your space by:

• Responding to HARO requests
• Building relationships with industry journalists and podcasters
• Sharing unique data or insights that others want to reference
• Participating in industry surveys and research studies

Publish consistently within your core topic clusters to build a semantic footprint. Create content around your business’s areas of expertise rather than publishing thin content across many topics.

What is a semantic footprint?

“Semantic” refers to the meanings and relationships between words and concepts. In the context of AI and LLMs, semantic relationships are how systems understand that “email marketing” is related to “newsletters,” “automation,” and “conversion rates.”

When you consistently write about email marketing, for example, LLMs learn that your brand is semantically connected to related concepts like:

• Email automation
• Newsletter design
• Email deliverability
• List building
• Email analytics

The more you publish about these related topics, the stronger your semantic connections become. Then, LLMs start to see your brand as integral to this cluster of topics.

Use these four practical steps to start building brand authority:

1. Audit your current mentions: Use tools like Google Alerts or Semrush’s Brand Monitoring tool to track where your brand is already being discussed
2. Identify target publications: Make a list of 10 to 15 sites where your ideal customers get information
3. Create a content calendar: Plan to publish a few thorough, well-researched content pieces each month in your core expertise area
4. Engage authentically: Participate in industry discussions in online forums (like Reddit) without always promoting your brand

How to measure LLMO success

The way people search for information online has transformed with the advent of AI search features and LLM web search models. You’ve already seen what this means for organic search traffic from Google: a big decline due to zero-click search.

But you’re sitting on the precipice of this new source of potential brand awareness and traffic. LLMO is opening up new opportunities for brand visibility and business growth.

The question is: How do you know if your efforts are working?

On the surface, AI’s influence on your business’s success seems difficult to track. If some AI mentions don’t include a link, how do you know if that mention is contributing to your growth? 

After all, a single mention in a ChatGPT response could influence dozens of purchase decisions. But if there’s no link to your site, you’ll never find those users in Google Analytics as ChatGPT referrals.

Instead? They’re lumped in with direct traffic.

But don’t give up hope—here are five key performance indicators (KPIs) you can use to determine what influence LLMs are having on your bottom line.

1. Brand mention frequency across AI platforms 

A big part of LLMO is increasing your mentions and citations across all the major LLMs. So, track how often your brand appears in responses to relevant queries and prompts across ChatGPT, Perplexity, Google AI Overviews, and other platforms.

How?

There are a few different tools you can use to track your LLM mentions. 

In Semrush’s AI SEO Toolkit, you can track mentions and citations (along with sentiment) for your brand across major LLMs like ChatGPT, Google’s AI Mode, and Perplexity: 

Then, you can use this data to establish your baseline, identify which platforms favor your brand, track improvements over time, and spot any negative sentiment that needs addressing.

Other tools that can track mentions include Ahrefs, Peec AI, and more.

2. Share of voice in AI responses 

Your brand’s share of voice goes hand-in-hand with mention frequency. What percentage of AI mentions in your industry or topic area reference your brand versus your competitors?

Think of share of voice tracking like monitoring keyword rankings in SEO. Rank tracking shows your position in search rankings vs. your competitors. Since there’s no hierarchical list of links in LLM responses, share of voice is the next best metric to reveal how you’re doing compared to the competition.

Many of the tools that measure mentions also measure share of voice, including both the Ahrefs Brand Radar tool and Semrush’s AI SEO Toolkit:

You can use this data to identify where competitors are dominating conversations you should be part of and track your progress over time.

3. Sentiment and context of AI mentions 

One of the biggest differences between traditional SEO with position tracking and LLM mention tracking is that AI can mention your brand in many different contexts.

In traditional search, your content typically ranks for your brand name. Sure, other sources that you don’t own (like review sites) can mention your business in a positive or negative light. But you can see those (and in some cases, respond to them) when you search for your own brand.

In LLMs, it’s a totally different experience. People might ask ChatGPT different questions about your brand, for example, and you don’t necessarily get to see all the different ways it responds.

How do you know whether LLMs are mentioning you with positive sentiment or negative?

First of all, start chatting with the different AI-powered models about your brand. Start with ChatGPT, Perplexity, and Gemini. Ask questions like these to gauge the response:

Basic brand awareness questions:

• “What do you know about [Your Brand]?”
• “Tell me about [Your Brand].”
• “What is [Your Brand] and what does it do?”
• “What are the pros and cons of [Your Brand]?”

Competitive comparison questions:

• “What’s the difference between [Your Brand] and [Main Competitor]?”
• “[Your Brand] vs [Competitor]—which is better?”
• “Compare [Your Brand] to other companies in [your industry].”

Recommendation and purchase intent questions:

• “What’s the best [product/service category] for [specific use case]?”
• “I’m looking for a [product/service] that does [specific need]. What do you recommend?”
• “Should I choose [Your Brand] for [specific use case]?”

Problem-solving and expertise questions:

• “I’m having trouble with [problem your brand solves]. What should I do?”
• “How do I [achieve a goal related to your expertise]?”
• “What’s the best way to [task in your domain]?”
• “Who are the top experts in [your industry]?”

Reputation and trust questions:

• “Is [Your Brand] reliable?”
• “What do people say about [Your Brand]?”
• “Are there any issues with [Your Brand] I should know about?”
• “What are the common complaints about [Your Brand]?”
• “What are the most trusted [industry] brands?”

As you run these questions through LLMs, pay attention to the mention frequency and sentiment—positive, negative, or neutral recommendations.

Look for patterns in how your brand is described, whether it’s mentioned at all, and the context. This gives you a baseline to track sentiment changes over time.

The top AI mention tracking tools do track sentiment. But you should also run some of the questions above for yourself to get a handle on how LLMs talk about your brand.

4. AI referral traffic and conversion rates 

The average LLM referral visitor to your site is worth 4.4x more than the average traditional organic visitor, according to a Semrush study. That’s because AI better equips users with the information they need before deciding to visit your site.

Plus, this value is only projected to increase over time:

This is the most straightforward measure you can get for how LLMs are affecting your bottom line.

To track referrals and conversions from AI models in GA4, create a custom Explore report that shows exactly how much traffic you’re getting from all the models you want to track—plus how many conversions you’re seeing from that traffic:

To set up your report, follow this step-by-step tutorial.

5. Topical authority expansion 

Tracking and growing your topical authority means measuring how your brand’s expertise is reflected across different subject areas over time. Unlike sentiment, topical authority focuses on which subjects and expertise areas LLMs associate with your brand.

Growing your topical authority is important because it means that your semantic footprint is expanding—which can lead to more mentions in more relevant queries.

How to monitor topical authority expansion

• Topic mapping: Create a spreadsheet to keep track of which topics LLMs associate with your brand for each month. Ask questions like “Who are the top experts in [specific topic]?” across 10-15 relevant topics in your industry to see if you’re mentioned.
• Breadth of expertise: Track how many different subject areas LLMs associate with your brand. Are you known for just one topic, or do they recognize your expertise across multiple related areas?
• Authority ranking: For core topics, track whether LLMs mention your brand first, second, or further down when listing experts or authorities

Tools to track topical authority expansion

You can use tools like Semrush’s AI SEO Toolkit to automatically track questions about your brand.

But you can also monitor progress manually. Create a monthly manual audit using the same set of questions across ChatGPT, Claude, and Perplexity. Then, check variations like “who are the best [topic] experts” or “what are the top [topic] companies.”

Key metrics to measure topical authority expansion

• Number of questions or topics where you’re mentioned as an authority (goal: increase month-over-month)
• Position in the response (top, middle, near the bottom) when multiple experts are listed (goal: move from 4th to 1st or 2nd mention in a list of experts, for example)
• Expansion into adjacent topic areas (shows growing semantic footprint)

What is in-context learning and how does it work?

In-context learning is an AI prompting technique that teaches LLMs new tasks by providing input → output examples within the prompt itself. It doesn’t require additional training or parameter updates to get the result (output) you’re looking for.

How in-context learning works

When you give an LLM a prompt with examples, it uses them to better understand the context so it can complete very similar tasks. Here’s the basic process:

1. Give the model examples: Provide a few input-output pairs that demonstrate the task you want completed
2. Add your specific input: Include the new case you want the model to handle
3. Let the model predict: Allow the LLM to analyze the examples and generate an appropriate response based on the patterns it identifies

A simple example:

Here are some examples of good email subject lines: 

• “Your invoice is ready” → “Invoice #1234 ready for review” 
• “Meeting tomorrow” → “Tomorrow’s planning meeting: Conference Room A at 2pm”
• “Quick question” → “Quick question about the Johnson project timeline” 

Now write a better subject line for: “Update”

Why in-context learning matters for LLMs

The logic behind in-context learning shows how LLMs actually process and use information when generating their responses.

LLMs find patterns

When an LLM recommends your brand, it doesn’t just recall stored information. Instead, it identifies patterns in the data about when and why your brand gets mentioned. Then, it applies those patterns to new queries.

Context shapes recommendations

The examples and information that LLMs process influence how they describe your brand in different contexts.

If your brand consistently appears alongside “budget-friendly” or “enterprise-level” in training data, those associations can influence future recommendations.

The quality of surrounding content matters

Since LLMs learn from context, the quality and authority of content that mentions your brand affects how the LLM perceives and recommends it. Getting mentioned in high-quality, well-structured content improves your chances of positive recommendations.

Is in-context learning an LLMO tactic?

Although some thought that feeding in-context content to LLMs could influence outputs years ago, it’s no longer a common LLMO tactic. Instead, you should focus your LLMO strategy on tactics like earning high-quality mentions across the web and publishing in-depth, original, well-structured content.

How to optimize for LLMs: A checklist

You’ve learned what LLMO is, how it works, and how to measure it. Now, you’re ready to apply what you’ve learned. Follow our LLMO checklist to hit all of the most important tactics and strategies.

1. Audit how LLMs view your brand: Test questions about your brand across ChatGPT, Claude, Perplexity, Gemini, and any other LLMs you want to monitor. Document current sentiment, mention frequency, and topical associations to establish your baseline. You can also use an AI mentions tracking tool here to get a baseline.

2. Launch a digital PR and brand mention/citation strategy: Work on getting your brand mentioned and cited on high-authority industry sites that LLMs commonly reference. Focus on industry publications, news outlets, and research sites—and track results with a tool like Semrush Enterprise AIO. This pivot reflects the new era of SEO strategy, which has to take a more holistic view of your brand.

3. Build an authentic presence on Reddit and Quora: Engage genuinely in relevant subreddits and Quora threads where your expertise adds value. Build a Reddit strategy that isn’t overly promotional to avoid getting banned.

4. Establish or improve your Wikipedia presence: If your brand is notable enough, create or optimize your Wikipedia entry. LLMs heavily reference Wikipedia in their training data. Just be sure to adhere to their guidelines.

5. Incorporate quotes, statistics, and citations in your content: These add to the information gain of your content. LLMs prefer content with unique value over content that repeats information already covered by other sources.

6. Demonstrate your expertise with original research and case studies: Create proprietary data, conduct industry surveys, or publish detailed case studies that other sites and individuals will want to reference and cite.

7. Actively provide feedback to LLMs: Report inaccurate information in LLM responses. If you’re asking questions about your brand and the LLM gets something wrong or shares outdated information, click the thumbs down at the bottom to report it:

8. Optimize your content structure: Structuring your content with clear headings, subheadings, lists, callouts, FAQ blocks, and logical flow. This way, both humans and AI systems can understand it better.

9. Minimize JavaScript dependencies: Most AI crawlers can’t execute JavaScript, so make sure your important content is accessible in HTML. Use server-side rendering for maximum crawlability.

10. Include relevant images and video content: Multimodal content (with text, images, and video) provides richer context for LLMs. It also increases your chances of being cited in multimodal AI responses.

11. Add FAQ and other structured data schema markup: Add FAQ schema, How-to schema, and other relevant structured data to help LLMs better understand and extract information from your content. This structures your content for AI SEO and makes your content more likely to be cited in AI responses.

12. Create FAQ sections throughout your content: LLMs frequently pull from FAQ-style content when answering questions in their output. Weave Q&A sections into relevant parts of your articles (such as using a question-based heading with an answer directly following), not just at the end.

13. Build topic clusters around your expertise: Publish consistently in your core expertise areas rather than spreading content across too many topics. This builds stronger topical authority signals.

14. Monitor and respond to online reviews and mentions: Your online reputation directly influences how LLMs describe your brand. Actively manage reviews and respond to mentions across the web to protect your brand reputation.

15. Create comparison and “best of” content: LLMs often reference list-style and comparison content when making recommendations. Create thorough comparisons that favorably position your brand against the competition.

16. Publish useful, high-quality content: All the LLMO tactics in the world won’t help if your content doesn’t provide genuine value. Focus on solving real problems and answering real questions for your audience. Make your content unique with clear added value for your readers.

Keep up with the evolution of LLMO

The AI, GEO, and LLMO space is evolving incredibly quickly. The more you start following best practices now, the better you can position your business in the near future as AI and LLM usage continues to rise meteorically. This is how you stay on top of your search visibility to power organic growth.

Want to keep on top of all the latest news, emerging tactics, and trends in GEO? Bookmark this GEO guide hub now and sign up for the Search Engine Land newsletter.