- AI BEST SEARCH
- AI Glossary & Keyword Index [AI BEST SEARCH]
- LLMO (Large Language Model Optimization)
LLMO (Large Language Model Optimization)
LLMO (Large Language Model Optimization) is the practice of optimizing your website and communications so that large language models such as ChatGPT, Gemini, Claude, and Perplexity understand your brand, products, and content correctly and mention, cite, and recommend them in the answers they generate. Where SEO tracks "rankings in search results," LLMO tracks "whether your name appears in the AI's answer, together with the evidence behind it." How it works: An LLM builds its answer from data absorbed during pre-training plus information it retrieves from web search at answer time (RAG). As a result, how easily you get mentioned or cited depends mainly on three things: • Whether accurate information about you appears on authoritative media, comparison sites, and review sites that are likely to be part of the training data (off-page) • Whether the pages retrieved at answer time are structured to answer the question concisely — conclusion first, headings, FAQs, structured data, llms.txt (on-page) • Whether the association between company name, product name, and category is consistent across multiple sources (entity consistency) In practice: A typical operation registers dozens to hundreds of expected questions (prompts), measures mention rate, position, cited sources, and sentiment per AI on a fixed schedule, and improves content and PR while comparing against competitors. The term is used almost interchangeably with GEO (Generative Engine Optimization), AEO, and AIO; "LLMO" is common in Japan, while "GEO" and "AEO" are more common overseas. Related tools: In Japan, Mieruca GEO, DolphinX AIO, AKARUMI, SUPER ACT, BringRitera, and User Insight; overseas, Profound, Peec AI, OtterlyAI, and AthenaHQ are used to measure and improve LLMO. The differences between the major tools are laid out in our "LLMO/GEO Tools Compared" article.
