Introduction to Large Language Model Optimization (LLMO)
Key Takeaways
- Current statistics show that a growing number of people use either AI tools like ChatGPT and Perplexity, or AI summaries to search for information, products and services, and this is where LLMO comes in.
- LLMO means optimizing your content so that AI chatbots can understand and rate it as valuable. Ultimately, the goal is for the chatbots to use the content to generate responses to people’s queries and link your website.
- LLMO is not completely replacing SEO, but it’s on the way to taking the winning position. Optimizing for large language models is critical as AI-driven search is on the rise.
- LLMO, SEO and even AEO and GEO are closely linked, so understanding their relationship and how to implement and prioritise them in your marketing strategy is crucial.
- Content is still the key ingredient in LLMO with the only difference of how it is optimized for AI tools. Use clear headings, schema markup, internal links and showcase author expertise and credible sources for large language models to favour your content.
- Implementing LLMO means staying up to date on your content, statistics, and trends. You also need to optimize for natural language queries and use a conversational tone to stay relevant.
- When implementing LLMO, move beyond keyword rankings and instead monitor LLM mentions, AI citations, and engagement. Testing in real time by asking AI tools questions related to your brand will help you immensely.
Introduction
One of the most important questions for any business owner is how to make sure people find you. For a long time the answer to that question was SEO and companies that implemented and mastered it had a strong edge against their competitors. But SEO isn’t the winning move anymore, with its strong contender LLMO rising fast and steady.
LLMO, or large language model optimization, is the new marketing move that can improve your business’s discoverability and generate more and better leads. LLMO is also still relatively new and is just gaining momentum. Currently, very few businesses are using it, so achieving results with LLMO is much easier and faster than with SEO. It is especially beneficial for small and medium-sized businesses to start with it now rather than wait until it becomes more widespread and the competition gets overwhelming.
But what even is LLMO? How to implement LLMO? What are your winning strategies? And where does LLMO go in regard to SEO, AEO, and GEO?
Let’s dive right in and answer all of these questions.
What Is LLMO?
ChatGPT, Gemini, Claud, and Perplexity are all large language models. Large language model optimization, or LLMO, is a set of strategies and techniques to make your content more understandable and accessible to these AI language models.
It is very similar to how SEO optimizes content for search engines, but for AI chatbots like ChatGPT or Google’s Gemini. Such chatbots and language models don’t come up with information on their own, but scour the internet for a suitable answer to people’s queries. LLMO means optimizing your content so that it is understandable by these AI models when scanning a certain page on your website. That way large language models can assess the value of your content better and ultimately your business’s information can appear within AI-generated responses. Today, for your brand to remain visible and relevant to people, it is necessary to adapt your marketing strategies to the rise of AI and implement LLMO. But why?
Think about how many times you’ve heard “ask ChatGPT” instead of “Google it” lately. How do you as a business make sure you show up when people look for something? The truth is, AIs are still being trained on content and all of these models constantly scrape the internet looking for information.
If you are already putting out a lot of content out there you already have a good starting point. The act of creating and publishing content stays the same. What is changing are the technicalities of how we actually make sure that content is in the right format and structure for AI. This is where LLMO comes in.
Why Does LLMO Matter Now?
Why should you care for LLMO, especially if you have already successfully implemented SEO? The truth is, people just don’t search the same way anymore – neither for information nor for products and services.
SEO is not dead, as many claim, but is certainly losing its winning position. In its place now we find LLMO, or large language model optimization. Although it is yet another thing you are going to have to add to your marketing strategy, your traffic will not survive without it.
The Decline of SEO-driven Traffic and Rise of AI Search
Observations are one thing, but numbers cannot lie.
We have already established that the average user nowadays doesn’t search as before. The goal now is to find the needed information as fast as possible and preferably with one click. Numbers already show that on traditional search engines, about 60% of searches end without the user progressing to another destination.
At the same time, about 80% of search users rely on AI summaries at least 40% of the time. This reduces organic web traffic by 15% to 25%. Even if you have mastered SEO to perfection and your website shows up among the top results, the chances of users going to your website go significantly down.
Gone are also the days users go to multiple websites and make multiple queries to find what they need. Roughly 68% of LLM users rely on these platforms for researching, gathering, and summarizing information. As a result, businesses that do not appear in AI-generated responses may experience a decline in web traffic. Additionally, AI platforms now often include links to the sources from which they obtain information and many users click on these links to verify the accuracy of the answer. So if a user asks ChatGPT or Perplexity a question regarding the value offered by your brand and it does not reference your website, you are missing out on more valuable traffic.
Already, 56% of marketers say their company is taking an active role in implementing and using AI. However, from those businesses which have already adopted generative AI only 1% believe their investments have reached maturity. These numbers suggest that adoption will continue to soar in the coming years and we’ve yet to see generative AI’s full potential. Which also makes this the perfect moment to be among the firsts to implement LLMO.
You also may think only big companies can use these tools. But surveys show small and midsize businesses use AI tools like ChatGPT every day. In fact, 27% of small business owners use these tools, and 70% of them pick ChatGPT to work better.
What is the Difference Between SEO, AEO, GEO, and LLMO?
Now that it’s clear LLMO is the way to go, does that mean you should just forget about SEO? And what about AEO and GEO? Should you choose only one of them or implement all four?
At their core, they all have the same goal – making sure your product or service is showing up when people are searching, whether that is on Google, with Siri, or on ChatGPT. While SEO remains the foundation, AEO, GEO, and LLMO represent newer approaches focusing on how search engines, particularly AI-powered ones, respond to queries and generate content.
SEO, or search engine optimization, is still the biggest player in the field, although its importance is slowly diminishing. SEO aims to improve your content for the classic search engines and bring more organic search traffic to your website.
AEO, or answer engine optimization, optimizes content for direct, concise, and authoritative answers for AI-driven platforms with the goal of attracting traffic from them to you, like Siri and Alexa.
GEO, or generative engine optimization, sometimes used interchangeably with LLMO, specifically targets optimization for generative AI search engines. GEO encompasses tactics to ensure that AI systems choose your content as the basis for their responses. This might include strategic use of authoritative language and structured data to build trust and association.
LLMO, or large language model optimization, refers to the specialized strategies used to ensure that content is processed correctly by large language models. By optimizing language, context, and semantic signals, LLMO aims to boost your content’s relevance in AI-generated search results.
Now the question is should you choose only one of them or implement them all?
In practice, SEO, AEO, GEO, and LLMO often overlap, and a comprehensive approach to search optimization involves considering all of them. For example, strong SEO practices will likely support better performance in AEO, GEO, and LLMO. However, optimizing specifically for AI-driven search requires a more nuanced approach that considers the specific ways AI models understand and process information. But how to implement LLMO?
Core LLMO Strategies (Structure, Content, Brand, Citations)
The good news about the shift from SEO to LLMO is that content is still the key. As long as you produce high-quality relevant content, whether that’s blog posts, videos, guides, you are still on track. The tricky part here is how you optimize it, as there are key differences between LLMO and SEO in terms of strategies and technicalities.
Structuring and Formatting for AI Understanding
For your content to get picked up by LLMs it is essential to ensure it is well-structured, uses clear language, and includes relevant keywords to aid AI understanding. One of the simplest tricks for structuring you can implement is using clear heading based on real user questions.
Focus on using short, focused paragraphs with clear topic sentences that make it easier for AI to summarize and extract information. Provide definitions for key terms and include links to connect related topics within your website. This will ensure a logical flow of information which is crucial for better AI comprehension. Your website content should be a structured knowledge base which serves both human readers and AI models.
Content Creation and Optimization
When it comes to content creation and optimization, there are a few important things to consider. Make sure to produce in-depth, long-form comprehensive content which not only answers the “what”, but also the “why” and “how”.
To stand out in AI search, the content needs to answer real questions, not just repeat popular keywords. Ultimately, it should offer something truly useful, whether that’s an expert opinion, proprietary data or unique context.
LLMs also favour natural conversational tone. Focus on phrases that users actually speak or type in natural language. Include synonyms and related terms to capture broader semantic intent. Another thing to keep in mind is to anticipate follow-up questions. What is important for your target audience and what would they be asking?
Credibility, Authority and Trust
Transparent authorship, expertise, references, and domain authority are crucial when it comes to LLMs. Always include author names, their credentials and experience. If you need to cite sources, choose ones that are reliable and that AI can check.
Highlighting original research and including case studies and first-hand examples will make your content more authoritative and increase your credibility. Lastly, but most importantly, focus on creating content that AI cannot easily replicate. The goal is to be cited by LLM and to bring people to you.
Technical Excellence and Content Maintenance
Your content should always be fresh and up to date. If you already have materials on certain topics, make sure to go over them regularly, and update stats, prices, links, and data as necessary. If there is something missing, add it.
Additionally, you need regular technical maintenance and this is where technical SEO is still relevant. Make sure your website is loading fast, has accessible pages, and is mobile-friendly. If you are not sure what works best, test content with A/B methods and adjust based on the results.
Content Types That Perform Well in LLMO
For best results, focus mainly on content which performs well on LLMs. This includes product comparisons and buying guides, interactive tools, FAQs, how-tos, and step-by-step guides. Essentially, you need content that anticipates the questions and problems of your target audience and offers clear answers and solutions.
Tools & Metrics To Track LLM Visibility
Tracking your LLMO efforts and LLM visibility will require you to rethink the traditional metrics. With SEO, the focus was on keyword ranking, raw traffic, and click-through rates (CTR), but these metrics were designed for a search environment centered around ranked web pages. While they are still relevant for traditional search results, they often fail to measure the visibility within LLM responses.
Instead, focus on indicators that show you how your content performs in AI-driven searches. One of the most direct ways to monitor this is by using tools like ChatGPT, Perplexity, or Claude to ask questions related to your product or industry.
Check whether your content is cited, which sources are referenced, and what gaps exist, then adjust your strategy accordingly. This kind of LLM visibility testing offers real insight into what AI prefers in terms of content, information, citations, etc. You can implement this not only for conversational AI tools, but also in AI overviews on traditional search engines.
Another thing that might help you is regular testing and feedback loops. You can ask LLMs directly why it didn’t recommend your business or service to find out what can be improved and adjusted.
Additionally to understanding if, how and when your business appears in AI-generated content and responses, you should also track associated traffic and conversions. One way to do this is with Google Analytics. Pay close attention to the behavior of people who come to a given website from AI platforms and use that to finetune your strategy. You can also track associated traffic and conversions by using specialized LLM tracking tools, analyzing website traffic patterns, and observing shifts in brand searches and sales calls. After all, the goal is not to just appear in AI results, but to bring valuable leads to you.
Although LLMO tracking and analysis has a long way to go before reaching the level of SEO, some tools are already available for monitoring AI output and tracking visibility, which might help you. Some examples include spyfu, GPT for Sheets, Brandlight, and more monitoring platforms will emerge over time, as LLMO continues to grow in popularity and significance.
LLMO FAQs
What is LLMO?
LLMO is a set of strategies and techniques to make your content more understandable and accessible to AI language models like ChatGPT or Google’s Gemini, and it ensures that it appears within AI-generated responses. The end goal is to provide enough information so that people come to your website for more.
Why is LLMO important?
The importance of LLMO grows with the number of people using AI tools instead of the traditional search engines when looking for information or recommendations for services and products. To make sure your business stands out and can be found by your target audience you need to adapt to the customers’ behaviour and preferences.
How is LLMO different from SEO?
LLMO (large language model optimization) focuses on making your content more accessible and appealing to AI tools like ChatGPT or Google’s AI Overviews, the same way SEO does with traditional search engines. For example, unlike SEO which targets exact-match keywords, LLMO prioritizes natural language, entity clarity, and trustworthy sources. However, LLMO is still closely connected with SEO.
Why should small and medium-sized businesses care about LLMO?
LLMO can drive visibility and traffic and can influence people. A lot of users trust large language models like ChatGPT when they are looking for recommendations and want to make an informed purchase. That way for example a small business selling sports equipment, which has optimized their content for LLM, can reach potential buyers, even without big ad budgets.
Can I use my existing SEO content for LLMO?
Using your existing SEO content for LLMO is a great starting point and it will make your transition to LLMO easier. However, this type of content will need adjustments. Keyword-heavy blog posts should be turned into more conversational and well-structured content that answers real questions. Additionally, you should update any outdated data to ensure your content remains relevant and up to date.
Is technical SEO still important for LLMO?
Yes, site structure, speed, and schema still play an important role. Don’t neglect fast loading times, mobile responsiveness, semantic HTML, and structured data – they all help LLMs process your content more effectively.
What types of content perform best for LLMO?
Clear, comprehensive, and useful content is your best bet when it comes to LLMs. Some of the best choices for types of content are step-by-steps and how-to guides, product comparison tables, case studies with real data, FAQs, answer-rich content, and expert commentaries, especially in niche industries.
How do I get my content cited by LLMs like ChatGPT?
Focus on authority, clarity, and relevance. Use schema markup, link to credible sources, and provide expert-level insights. LLMO isn’t a one time fix, but rather a continuous effort. If something doesn’t work, adapt, readjust and try again.
What role do citations and author credibility play in LLMO?
Transparent authorship, expertise, references, and domain authority are crucial when it comes to LLMs. Always list the author, their credentials, and cite reliable sources. (For instance, a fitness blog written by a certified trainer with sources from PubMed will rank better in AI answers than an anonymous, unsupported article.)
How often should I update my content for LLMO?
Your content’s chances of being mentioned by LLMs rely a lot on its freshness and relevance. Regularly update stats, refresh product links, and adapt to changing questions. For example, a blog post from 2023 on a topic that is still relevant should be updated in 2025 with new tools, pricing, and feature changes to remain relevant to LLMs.
How do I know if my brand is showing up in AI-generated search results?
There are a few practical ways to check LLM outputs and monitor your visibility. Ask AI tools like ChatGPT, Claude, or Perplexity questions you want to rank for and see what brands or sources they mention. If your business isn’t listed, you may need better structured content or more credible citations. This type of research can also show you what type of content does get picked up by LLMs.
What tools can I use to track LLMO performance?
You can track your LLMO performance by using a mix of SEO tools (e.g., Semrush, Moz) for visibility tracking, and manually testing AI tools. Google Search Console won’t show LLM-specific rankings, but you can monitor mentions using brand alert tools or run periodic LLM checks. For example, track how often your brand is cited when you ask relevant questions on ChatGPT.
Implementing LLMO in your Marketing Strategy
As user search behavior changes, your marketing strategy must change too if you want your business to succeed. Large language model optimization, or LLMO, is an effective way to adapt to the rise of AI and attract potential customers.
LLMO is still relatively new and few businesses have it mastered. Although that means there is still much to learn about it, that also makes it a perfect tool for businesses looking to grow and stand out.
If you are struggling to get started or optimize your strategy, consider getting professional help – our team of experienced inbound marketing consultants can assist you with anything.
Just drop us a line and we’ll find a simple solution to any complex marketing problem you’re having.