LLMO, or Large Language Model Optimization, revolves around optimizing your content so that it is visible and understandable within AI-driven search engines such as ChatGPT, Bing Copilot, and Google’s AI Mode. In essence, LLMO is the same as GEO (Generative Engine Optimization), but known under a different name.
Large Language Models (LLMs) collect and interpret information based on prompts (questions) that users ask. Optimizing for these models therefore means structuring and writing your content in such a way that it is easily understood and prominently displayed in AI-generated responses.
Although LLMO and traditional SEO have many similarities, they cannot be considered entirely equivalent. In practice, there is approximately 60-70% overlap between the two strategies. This means that many principles of classic SEO also apply to LLMO, but at the same time there is room for specific points of attention that are important when optimizing for AI-driven search engines. The similarities include:
Although LLMO shares many elements with traditional SEO, there are also fundamental differences that change the playing field. These differences arise because generative AI handles content, user intent, and source selection differently than classic search engines. As a result, LLMO requires different emphases in your strategy and approach:
An important difference that often goes unnoticed is that Google actively uses user behavior via the Navboost algorithm (such as click behavior and user data from Chrome). ChatGPT and other LLMs do not have access to this data. This means that the way you optimize for LLMs differs: qualitative content and brand authority become more important, because AI models (outside of Google) do not have behavioral data to refine results.
With the growing adoption of AI tools such as ChatGPT and the upcoming widespread rollout of Google’s AI Mode, it is important for companies to optimize their findability within these new interfaces. Users increasingly expect immediate, accurate, and in-depth answers. LLMO helps you keep up with this trend.
Conduct prompt research: understand how your target audience formulates questions and the context they provide. Write nuanced, in-depth, and informative content that responds to complex search queries. Strengthen your online brand authority through mentions, reliable reviews, and clear branding.
ChatGPT uses Bing to gather up-to-date information. This means that optimizing for Bing becomes part of your LLMO strategy. Ensure you are visible in Bing by optimizing your website via Bing Webmaster Tools and content that matches user intent within Bing.
The next step after LLMO (such as searching via ChatGPT) is Google’s AI Mode, where generative search results become the norm. But the rise of AI agents that search and perform actions for you are also an important part of the future. By investing in LLMO now, you will be prepared for this transition. In concrete terms, this means that your content must focus even more strongly on relevance, authority, and clear structuring.
At SmartRanking, we usually talk about GEO (Generative Engine Optimization), but we see that this is the same as LLMO. In our view, GEO is a strategic approach that fits within both traditional and generative search environments.
Want to get started with LLMO/GEO?
LLMO/GEO is not a thing of the future, but a strategy for online visibility that deserves your attention today. By adapting and optimizing your content strategy for AI search experiences, you will be ready for the future. Need help? SmartRanking is happy to support you in this important step. Feel free to contact us without obligation.