Written by Oskar Mortensen on Mar 11, 2025
Master LLM SEO strategies to enhance your search engine optimization for future success.
Back in 2024, I wrote about what was then called “GEO”: Generative Engine Optimization. I coined this term to capture how content might rank or appear in outputs from artificial intelligence systems.
I took ideas from a Princeton study that tracked how large language models were sourcing and paraphrasing content. Now, in 2025, the situation has changed a lot. With ChatGPT, Claude, Perplexity, DeepSeek, and other LLM-based search experiences making significant progress, it is time to look closer at LLM SEO.
Today I will share major insights on how you can have your content recognized, and more importantly, understood, by these AI platforms.
I will also show real-life examples, practical tips from experts, and three core strategies to shape your content plan. Get ready.
There has been a huge increase in AI-powered chat systems. Last year alone, ChatGPT passed the 100 million user mark in just a few months, while Claude, Perplexity, and DeepSeek quietly attracted tens of millions of monthly visits. People treat them as useful tools, they are asking very specific and detailed questions.
Some experts expect that 10-15% of traditional search queries will slowly change into generative AI queries by 2026.
Early users are even choosing an AI chatbot over Google for quick, context-rich answers.
For content creators like us, this means we need to find new ways to make sure our work is noticed by these AI models. Regular SEO still matters, but it is only part of the picture. LLM SEO focuses on getting your content into the data sources that these powerful models use.
In my post last year, I mentioned a Princeton study on GEO. The study found that:
This led to the idea that we should optimize for both traditional search engines and for generative AI—especially if we want brand mentions, quotes, or domain authority to show up in AI responses.
The idea of LLM SEO expands on GEO by making sure your brand’s or site’s content is easy for LLMs to include, fetch, and trust.
LLM SEO means structuring your information so that AI language models can:
LLM SEO goes beyond link building or metadata. It is about context, clarity, trustworthiness, and consistency. We want these models—with billions of parameters—to confidently use our content as a reliable source.
I have noticed that queries have become more conversational. Instead of “best coffee shop in NYC,” people might ask, “What is the best hidden coffee spot in New York with late-night hours?” They expect one clear answer rather than 10 blue links.
That means context matters a lot.
Chatbots do not just rank your site first; they process numerous answers and then combine them. If your content is well-organized and includes the right indicators, you might be chosen as the snippet or summary. That is LLM SEO at work.
I like comparing the two side by side. Here is a quick table:
SEO Aspect
Traditional SEO
LLM SEO
Ranking
SERP position, domain authority, link-building
Relevance in training data, citations in AI answers
Keywords
Targeted by usage and volume
Targeted by context, semantics, question-based phrases
Updates
Frequent fresh content helps rank
AI training cutoffs matter; real-time retrieval is still developing
Structure
Headings (H1-H3), meta tags, alt text
Clear sections, definitions, bullet points for easy parsing
Linking
External + internal links boost rank
Trusted references, consistent brand mentions across multiple sites
Content Depth
Enough for user queries though sometimes broad
Must be thorough and context-rich so LLMs can quote or paraphrase well
Here are five practices that have become important in the past 24 months, along with insights from recognized SEO experts who have tested how LLMs pick source content:
Lily Ray from Amsive Digital tested how ChatGPT selects sources. She found that content with consistent heading levels (H2 followed by H3 and bullet points) was 40% more likely to be rephrased.
Tip: Give each sub-topic its own H2 or H3, and use bullet lists or short paragraphs.
Marie Haynes stressed the importance of “fact-checkable snippets.” If your content includes clear facts, LLMs are more likely to trust it.
Tip: When possible, include a snippet such as “According to X research, 35% of workplace injuries occur in Y environment.”
Glen Gabe observed that AI references are more consistent if brand details are repeated across channels like the website, social platforms, and even third-party sites.
Tip: Keep naming, product details, company history, and key messages consistent across all your digital properties.
Kevin Indig’s research shows that LLM-based search is less about the number of inbound links and more about targeted content.
Tip: Use synonyms and varied language. LLMs benefit from content that covers multiple angles or uses different terms around the same topic.
Over the past year, many have noticed that LLM queries often come in the form of “What are the best ways to…” or “How do I handle….”
Tip: Build content sections with Q&A formats or short headings like “What to do if…” It helps to use natural, conversation-like language rather than just repeating keywords.
Here are three major strategies that are set to shape LLM SEO in 2025:
What this means: Instead of creating single, loosely related blog posts, group your content around a main subject. Then cover it from different angles—such as a beginner’s guide, advanced tips, common mistakes, expert interviews, use cases, and similar topics.
How it helps: LLMs prefer content that is connected. They are more likely to see your brand as knowledgeable when you cover a topic in depth and link relevant pieces together.
Real example: One B2B SaaS client organized content around “Predictive Maintenance.” They developed about 10 interlinked posts ranging from definitions to advanced applications. ChatGPT-4 began citing these posts as a resource on predictive maintenance. This strategy increased their web traffic by 28% in three months.
Bullet list:
What this means: LLMs perform better with unique, verifiable data points. If you include your own research, statistics, or study results, your content stands out. Include data tables, brief notes on methodology, and provide a reference link to a reputable source when you can.
How it helps: LLMs partly pick content based on unique facts that can be checked. For example, if you mention that “36% of HR managers observe a doubling in retention with our solution,” an LLM might use that specific data point.
Case study: SEO professional Aleyda Solis shared that including brand-specific or survey data in long guides helped her content appear in generative search previews. She explained that when an LLM discovered a unique statistic reported only by her, it used that snippet for its response.
That is very valuable.
Steps:
Sample table:
Retention Metric
Pre-Implementation
Post-Implementation
6-Month Retention
52%
71%
Annual Staff Turnover
12%
7%
Cost Savings (Est.)
$150,000
$250,000
What this means: Traditional SEO taught us about schema markup and structured data. For LLM SEO, we also want to mark up or organize our content so that an AI can easily understand it. There are new or extended metadata protocols now—a JSON-LD snippet, for example, to clarify a concept or list pros and cons.
How it helps: The more ways you provide for an AI to understand your text, the more reliable it appears. Some emerging practices even suggest using special microdata for definitions, roles, or disclaimers.
Advice from experts: Cindy Krum has said that structured data is a hidden champion when working with AI systems. She explains that well-labeled definitions, bullet points, and microdata assist AI systems in performing better.
Steps:
Here i have gathered the most asked questions about LLM SEO
LLM SEO refers to leveraging large language models to optimize search engine strategies, enhancing content relevance and user engagement.
Large language models improve SEO by generating high-quality, contextually relevant content, and understanding user intent more accurately.
LLM SEO is crucial as it aligns with evolving search algorithms, ensuring content remains competitive and visible in search results.
Businesses can implement LLM SEO by integrating AI-driven tools to analyze data, optimize content, and personalize user experiences.
Challenges include staying updated with AI advancements, managing data privacy, and ensuring content authenticity and accuracy.
Our AI SEO assistants helps write and optimize everything – from descriptions and articles to product feeds – so they appeal to both customers and search engine algorithms. Try it now with a free trial→
This is an article written by:
Oskar is highly driven and dedicated to his editorial SEO role. With a passion for AI and SEO, he excels in creating and optimizing content for top rankings, ensuring content excellence at SEO.AI.
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