8 Ways to Adapt Your SEO Strategy for LLM-Powered Search

If you haven’t started modifying your SEO strategy for LLM-powered search yet, now’s the time.

Because all of those SEO tactics you’ve relied on for years? Unfortunately, those tried-and-true tactics don’t really work on LLMs. You don’t have to throw them into the trash and start fresh, but they do need to be adapted for the way LLMs work.

Sure, you can still get some traffic from classic organic search for now, but the number of searchers switching to AI for all of their search needs is just going to keep growing. If you’re not adapting, you’re getting left behind.

Not sure what that means exactly, and wondering where you should start? In this article, I’ll go over the 8 ways you should modify your SEO strategy right now to update it for LLM-powered search.

But first, what does it really mean to optimize for LLMs, and how is it different from SEO?

Traditional SEO vs. LLMO

The main difference between traditional SEO (Search Engine Optimization) and LLMO (Large Language Model Optimization) is that SEO improves visibility on traditional search engines like Google, while LLMO focuses on optimizing content for AI-driven tools like ChatGPT, Claude, and Perplexity.

Traditional SEO focuses on ranking web pages for specific keywords in search engine results pages (SERPs). You optimize your website for crawlers that index your content and algorithms that determine its relevance to the searcher’s query based on hundreds of ranking factors.

LLMO, however, focuses on optimizing for AI systems that read, understand, and combine information from across the web to generate human-like responses. LLMs choose content to present to users at the passage level instead of the whole page, meaning individual paragraphs, sections, or “chunks” of your content might get quoted or referenced.

SEO	LLMO
Page-level optimization	Passage-level optimization
Keyword focused	Intent and context focused
Link-based authority signals	Content quality and trustworthiness
Click-through rates matter most	Mention and citation rates matter most
SERP visibility	AI response inclusion
User visits your site	User often gets answers without visiting your site

Measuring SEO vs. LLMO Metrics

Shifting both your strategy and measurement plan is crucial because traditional SEO metrics like organic traffic and search engine impressions won’t tell you how your brand is faring in LLMs.

So, now you’ll need tools that can track both traditional search performance and AI visibility metrics.

One toolset that does this exceedingly well is Semrush Enterprise AIO. While Enterprise AIO (AI Optimization) monitors your brand's presence across AI search platforms like ChatGPT, Perplexity, Gemini, and Claude, the Enterprise SEO Toolkit provides advanced SEO tools to keep up with keyword research, rank tracking, technical SEO auditing, and much more.

Now, let’s dive into those 8 important ways to adapt your SEO strategy for LLM-powered search.

1. Optimize for Conversational, Long-Tail Queries

AI-powered search heavily relies on natural language processing (NLP), which is what enables computers to understand, interpret, and generate human-like language.

And human language is conversational.

So, optimizing for conversational queries is hugely important in optimizing content for AI-generated search results.

While traditional SEO taught us to target shorter, high-volume keywords, AI search rewards content that addresses specific, nuanced questions users ask in their own words.

Think about how search behavior has evolved. Traditional searches looked like "best CRM software" or "email marketing tools." AI-powered searches are more conversational: "What's the best CRM software for a 50-person marketing team that integrates with HubSpot and costs under $200 per month?"

This shift creates massive opportunities for brands willing to create content addressing very specific scenarios and pain points. Long-tail queries have always been valuable for traditional SEO, but they're absolutely critical for LLMO because they match how people naturally communicate with AI.

For example, instead of just targeting "project management software," you'd optimize for queries like:

• "How do I choose project management software for remote teams?"
• "What project management tools work best for creative agencies?"
• "Should I use Asana or Monday.com for client work?"

I've found that the most successful LLMO content addresses the "why" and "how" behind user questions, not just the "what." AI prefers content that provides context, reasoning, and comprehensive answers over simple feature lists or basic definitions.

Is your content detailed and specific enough to be showing up in LLM answers? Or do you need to write more long-tail content? With Semrush’s Enterprise AIO, you can easily keep track of share of voice and benchmark visibility across all major LLM platforms.

2. Improve Content Clarity and Structure

Remember when I said that LLMs look for content to cite at the passage level? Because they’re looking for those “chunks” of relevant, helpful, unique content, improving the clarity and structure of your content can help it get cited in AI responses.

Start by front-loading your most important information in each article, section, and paragraph. LLMs often pull from the beginning of sections, so lead with summaries or direct answers to common questions.

Headings are also crucial here. Use clear, descriptive H2, H3, and H4 headings that directly state what each section covers. Instead of creative headlines like "The Secret Sauce," use specific descriptors like "Essential Features for Email Automation Platforms."

Keep paragraphs short—ideally 2-3 sentences each. AI systems prefer content they can easily parse and extract without losing the article’s context. Long paragraphs make it harder for AI to identify the most relevant information for specific user queries.

Bullet points, numbered lists, and tables help LLMs understand content structure and relationships. These formats help them figure out your content hierarchy and make information more usable for those conversational, nicely-formatted answers you’re used to seeing from LLMs.

Tables work particularly well for comparison content, which AI systems frequently cite. If you're comparing features, pricing, or specifications, structured tables make it easier for AI to extract that information.

To recap…

How to use clarity and structure to optimize your content for AI-generated search results:

• Front-load your most important information in each section and paragraph
• Use clear, descriptive headings in a hierarchy that makes sense
• Keep paragraphs short, around 2-3 sentences
• Use bullet points, numbered lists, and tables

If all of these content structure optimization tips sound similar to you compared to what you did when optimizing content for featured snippets, you’re right on point. This LLMO tactic mirrors that classic SEO strategy!

Although there are some big similarities here between writing for featured snippets and writing for LLMO, remember that LLMs are looking to grab just the most relevant chunk of your content, not the whole page.

3. Provide Balanced and Thorough Answers

LLMs love to cite content that’s very thorough and covers topics from all angles. So, you’ll need to create content that’s genuinely helpful and fully addresses user intent in order to gain visibility in LLM responses.

Incorporate Comparative Elements

One of the most effective ways to do that is by incorporating comparative elements into your content wherever they make sense. AI really likes to contextualize information through comparisons, alternatives, and opposing viewpoints, so adding them into your content can increase your chances of gaining some visibility.

For example, let’s say you’re writing a product comparison article between your own tool and a close competitor. If you review your own tool only by talking about how awesome every feature is and making sure not to mention features the other tool has that yours lacks, chances are, you won’t be cited by LLMs.

Instead of just explaining your product's benefits, you need to discuss how it compares to alternatives, when it might not be the best choice, and what types of users should consider other options.

This might seem counterintuitive from a marketing perspective, but AI systems favor balanced content that acknowledges limitations alongside benefits. If your content is super one-sided, that doesn’t come off as thorough or balanced and it’ll be ignored by LLMs.

Here’s a look at how we did this recently in our AI search monitoring tools article:

Because of the balanced details we included, we’re being used as a source by ChatGPT:

Address User Intent

Just like in traditional SEO, we want to think about user intent for LLMs, too. However, now it goes beyond the traditional informational vs. commercial vs. navigational kind of intent. Instead, think about how you can anticipate your searcher’s needs by predicting their follow-up questions.

For example, if someone is asking about email marketing platform features, they probably also want to know about pricing, integration options, learning curves, and support quality. Covering these related topics in depth makes your content more valuable for both users and AI systems.

4. Create Unique, Authoritative Content

Remember E-E-A-T (experience, expertise, authoritativeness, and trustworthiness) from traditional SEO? Well, this concept matters even more now in LLMO.

AI might be an incredibly powerful tool, but it can’t invent new information or have human feelings and opinions. This creates a great opportunity for you to leverage your first-hand experiences, original research, and unique insights.

In fact, original research provides some of the highest-value content for LLMs. User surveys, industry analyses, case studies, and experimental results give you quotable data that doesn't exist anywhere else. AI systems love to cite statistics and findings from original research when responding to relevant queries, so give them those reasons to cite you!

Case studies also work particularly well because they provide specific, real-world examples that LLMs can reference when users ask for proof points or examples. Instead of generic success stories, create detailed case studies that include specific metrics, challenges faced, solutions implemented, and lessons learned.

Also, make sure to cite and link to sources you use in your content.

Citations and references to authoritative sources demonstrate trustworthiness that LLMs love. When making claims or presenting data, include links to original sources, industry reports, and credible research.

Remember how AI can’t fake real human experiences? Personal experiences and first-hand testing provide authenticity that sets your content apart. Instead of rewriting existing information, share your actual experiences using tools, implementing strategies, or solving specific problems. This makes your content extra unique.

Finally, technical depth matters more than ever. Surface-level content gets overlooked in favor of comprehensive articles that thoroughly address user questions. Go beyond basic explanations to cover specific details, potential challenges, troubleshooting tips, and any other advanced considerations that make sense to include.

Sure, it takes longer to create content that dives deep, but it can really pay off in the end when your content has a lot of different, super-quotable passages the AI models like to cite.

To recap, add E-E-A-T to your content by:

• Conducting original research
• Including detailed case studies
• Adding citations and references to authoritative sources
• Including personal experiences and first-hand testing insights
• Adding technical depth

5. Dial in Technical SEO & Use Structured Data

Technical SEO is crucial for making your site discoverable by AI. Clean, accessible, fast sites make it easier for AI systems to crawl and understand your content, while technical issues can prevent them from properly extracting your content to use in replies.

First, a logical site structure helps both traditional crawlers and LLMs understand content relationships and hierarchy. Use clear navigation, internal linking, and “pretty” URLs.

Site speed and accessibility also impact how well AI can access and understand your content. While LLMs might be more patient than impatient users, faster-loading, well-structured sites get crawled more thoroughly and frequently.

In addition, pay special attention to any JavaScript used on your site. Many LLMs struggle with content rendered by complex JavaScript. Critical content should be accessible without needing to execute JavaScript.

Finally, Schema markup is super valuable for LLMs because it provides more context to them about your content. Product schema, FAQ schema, article schema, and review schema, for example, all help AI systems understand content types and get the information they want from your site more accurately.

• Organization schema helps establish authority and context for your brand. When LLMs read your schema, they can understand your organization on a deeper level and are then more likely to cite your content for relevant queries.
• FAQ schema also directly aligns with how AI systems present information to users. Well-structured FAQ markup provides question-and-answer pairs that LLMs can easily grab.

You can also consider implementing emerging protocols like llms.txt, though the verdict is still out on its effectiveness. This protocol allows websites to provide specific instructions or content summaries for AI systems, though adoption of this feature remains limited across the internet.

6. Build a Strong Brand and Entity Presence

Brand authority and entity recognition (entities are people, places, organizations, etc.) play an even bigger role in AI visibility than traditional SEO rankings.

While backlinks were super important in SEO, they’re not as important in LLMO. Instead, LLMs evaluate overall brand reputation, credibility signals, and the context of how you’re mentioned across the web.

To boost your brand and entity presence, look for positive coverage on influential media sites. These kinds of mentions send credibility signals that AI really likes! It’s these kinds of meaningful mentions that demonstrate your brand’s expertise and authority.

Another set of signals that contribute to AI’s perception of your brand are customer reviews and social media conversations. If you can grow your positive reviews across multiple platforms, engage with your audience on social media, and get users to participate constructively with you, you can really boost your brand’s authority signals.

Speaking of social media conversations, make sure you’ve rolled engaging on Reddit, Quora, and any popular industry forums into your LLMO plan. Helpful, expert-level participation in relevant discussions creates thought leadership content from your brand that AI can recognize and reference.

One thing that’s really important here is online reputation management. Because reviews and public conversations can sway AI’s perception of your business or brand so much, it’s incredibly important to keep an eye on.

Proactively addressing negative coverage, responding to criticism constructively, and maintaining positive customer relationships helps ensure LLMs present balanced or favorable information about your brand.

To recap, building a strong brand and entity can be done by…

• Building positive coverage and brand mentions on influential media sites
• Keeping a close eye on your customer reviews across the web and driving new, positive reviews
• Monitoring social media conversations about your brand and responding
• Engaging with your audience on Reddit, Quora, and other industry forums
• Engaging in online reputation management

Looking for a tool that makes it easy to manage your brand’s sentiment in LLMs?

Enterprise AIO's sentiment analysis features provide crucial insights into how AI systems are currently positioning your brand. The tool tracks mentions across major AI platforms, analyzes sentiment trends, and identifies the specific content sources that LLMs reference when discussing your brand.

It can also show you what LLMs are currently saying about your brand’s perceived strengths and weaknesses. If you’re seeing some weaknesses in the report you want to address, you can make sure your content addresses them (and create new content if necessary) to try to feed LLMs with the correct information.

7. Diversify Content Formats and Platforms

AI pulls information from across the open web, making an omnichannel content strategy a must-have for increasing your AI visibility. Adding channels to your content distribution stack is one of the biggest adaptations traditional SEO marketers need to make for AI optimization.

What’s the best way to expand your content across more platforms for AI visibility?

Converting your content into multiple formats.

For example, a comprehensive guide on email marketing might become a podcast episode, YouTube video, LinkedIn article series, and Reddit thread. Each format reaches different audiences and provides additional opportunities for AI to discover and reference your expertise.

For AI visibility, spread your content out far and wide by:

• Turning it into a podcast episode
• Creating a YouTube video about it
• Spinning up a series of LinkedIn posts
• Writing a super thoughtful, non-promotional Reddit or Quora post about it
• Creating an infographic for social media
• Writing a guest blog post about it
• Appearing on someone else’s podcast on the subject

8. Monitor AI Search Performance and Iterate

Measuring success in AI-powered search calls for new metrics and monitoring tools beyond the traditional SEO KPIs. You’ll want insights into how LLMs mention your brand, the context of those mentions, and the sentiment associated with your brand across the major AI platforms.

Use tools like brand mention tracking and sentiment analysis reports to track your overall AI visibility and whether those mentions are in a positive or negative context.

Beyond how you’re showing up in LLMs, it’s also important to track AI-driven traffic to your website. It might be a really small number now, but AI usage continues to grow exponentially. Start tracking it now to understand how AI interactions translate to website visits and conversions.

The best tool for tracking everything AI-related is Semrush’s Enterprise AIO.

The toolset analyzes responses from ChatGPT, Perplexity, Bing Chat, Google’s AI Mode, and more, so you can monitor your AI search presence across all the major platforms.

Plus, real-time monitoring capabilities help you quickly identify trending prompts and keywords where your brand appears, so that you can act quickly when trends appear.

When it comes to reporting, the customizable reporting features in Enterprise AIO let you create targeted reports for different stakeholders. There are many report options from executive summaries showing overall AI visibility trends to detailed performance reports for specific product lines or marketing campaigns.

Keeping any eye on your competitors? Compare your visibility and perception with your competitors, track competitor product mentions, and watch your share of voice compared to your top competitors:

AI tools, tactics, technology, and usage changes rapidly. A successful LLMO strategy requires ongoing monitoring, testing, and iteration of your AI dominance plan.

The shift to AI-powered search is a challenge for sure, but it’s also an enormous opportunity for marketers ready to embrace LLMO and adapt their strategies.

The shift to AI-powered search is here. If you wait, you’ll lose ground to competitors who are already optimizing for AI.

With Semrush Enterprise AIO, you can:

• Track brand mentions across ChatGPT, Perplexity, Claude, Gemini, and more
• Benchmark AI visibility against competitors
• Monitor trending prompts in real time
• Build authority with brand sentiment insights
• Get customized reporting to prove ROI

Don’t let your content be invisible in AI search. Take control of how LLMs see and cite your brand.

Explore Semrush Enterprise AIO today and secure your place in AI-powered search.