LLMO.
LLMO explained: what it is, how it works and how to optimise for ChatGPT, Gemini, Claude and AI Overviews. Also known as GEO and AEO.
Large Language Model Optimisation (LLMO) is the new frontier of search. Millions of B2B buyers now start their research on ChatGPT, Perplexity and Claude instead of Google. I restructure your content, authority signals and technical architecture so your brand is cited, not your competitors, when AI models answer your customers' questions.
Everything you need to
dominate search.
What is LLMO?
LLMO stands for Large Language Model Optimisation. It is the practice of shaping your content, brand data and online presence so that AI tools like ChatGPT, Gemini, Claude and Google's AI Overviews mention, cite and recommend your business when users ask relevant questions.
- LLMO = Large Language Model Optimisation, also called GEO and AEO
- Traditional SEO ranks you in blue links; LLMO ranks you in AI-generated answers
- Targets ChatGPT, Gemini, Claude, Perplexity and Google AI Overviews
- Requires structured content, entity signals, schema markup and AI crawler access
- First-mover advantage: most brands have not yet invested in LLMO
LLMO vs GEO vs AEO: What's the Difference?
There is no difference. LLMO, GEO (Generative Engine Optimisation) and AEO (Answer Engine Optimisation) are three names for the same discipline. The terminology varies depending on who writes about it, but the practice is identical.
- LLMO, GEO and AEO are three names for the same practice
- LLMO targets the technology, GEO targets the output, AEO targets the surface
- Google's AI Overview defines LLMO as the primary term
- All three require the same fundamentals: structured content, entity signals and technical access
How LLMs Choose What to Cite
Large language models do not work like Google's traditional algorithm. They generate responses by predicting the most likely next token based on patterns in their training data and, increasingly, real-time retrieval from the web.
- LLMs generate responses by predicting tokens, not ranking pages like Google
- Authority comes from entity signals: brand mentions, knowledge graph presence and E-E-A-T
- Relevance comes from content structure: clear headings, answer blocks and parseable formatting
- Technical access requires allowing AI crawlers (GPTBot, ClaudeBot, PerplexityBot) to index your content
- Blocking AI crawlers prevents citation regardless of content quality
AI Crawler Access Management
If AI crawlers cannot access your content, you cannot be cited. This is the most overlooked aspect of LLMO. Many sites block AI crawlers in their robots.txt file, either intentionally or because their default configuration was set before AI search existed.
- robots.txt audit ensuring GPTBot, ClaudeBot and PerplexityBot can access citable content
- Meta robots directive review for page-level AI crawler access
- Informed trade-off analysis: blocking protects training data but prevents citations
- Google-Extended access management for AI Overviews and Gemini citations
- Ongoing monitoring as new AI crawlers emerge and existing ones evolve
LLMO for B2B and Fintech
LLMO in regulated industries like fintech and iGaming requires stronger E-E-A-T foundations than other verticals. AI systems apply stricter caution when citing financial content due to the potential impact on users' financial decisions.
- Fintech LLMO: FCA registration links, verifiable author credentials and regulatory disclosures
- iGaming LLMO: responsible gambling messaging, licensing information and trust signals
- YMYL content requires stronger E-E-A-T foundations for AI citation
- Compliance-friendly content structures that satisfy both regulators and AI models
- LLMO for B2B is built on fintech SEO foundations and specialised link building authority
Measuring LLMO Success
Measuring LLMO is different from measuring traditional SEO because AI models do not provide the same analytics as Google Search Console. I track LLMO success through multiple signals.
- Brand mention frequency tracking in ChatGPT, Gemini, Claude and Perplexity
- AI Overview appearance monitoring for target keywords in Google
- Referral traffic tracking from AI platforms (Perplexity and ChatGPT send traffic)
- Share of voice analysis in AI-generated responses for your target keywords
- Monthly LLMO reporting with actionable insights on citation wins and losses
Common questions about LLMO.
What does LLMO mean?
LLMO stands for Large Language Model Optimisation. It is the practice of shaping your content, brand data and online presence so that AI tools like ChatGPT, Gemini, Claude and Google's AI Overviews mention, cite and recommend your business when users ask relevant questions.
What is the difference between LLMO, GEO and AEO?
There is no difference. LLMO, GEO and AEO are three names for the same discipline. LLMO targets the technology (large language models), GEO targets the output (generative responses) and AEO targets the surface (answer engines). The practice is identical regardless of which term you use.
How do LLMs choose what to cite?
LLMs cite sources that demonstrate the strongest combination of authority, relevance and structured clarity. Authority comes from entity signals: consistent brand mentions, knowledge graph presence and E-E-A-T signals.
How do you measure LLMO success?
LLMO success is measured through brand mention frequency across major LLMs, AI Overview appearances in Google for target keywords, referral traffic from AI platforms, and share of voice in AI-generated responses.
Does LLMO replace traditional SEO?
No. LLMO builds on traditional SEO foundations. Strong technical SEO, quality signals and helpful content remain prerequisites for LLMO success. The same structured content that ranks in traditional Google also feeds AI search engines.
Should I block AI crawlers from my site?
It depends on your strategy. Blocking AI crawlers (GPTBot, ClaudeBot, PerplexityBot) protects your content from training data use but prevents your site from being cited in AI-generated responses. I help you make informed decisions about what to allow and what to block.
How long does LLMO take to show results?
LLMO results depend on your existing SEO foundations. Sites with strong entity signals, structured content and schema markup can see AI citation improvements within 4-8 weeks. Sites that need foundational work typically take 3-6 months.
Do you offer LLMO for regulated industries?
Yes. I specialise in LLMO for fintech, iGaming and other regulated industries where AI systems apply stricter YMYL caution before citing content. This includes FCA-compliant entity signals, verifiable author credentials and regulatory disclosure integration.
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