LLMO (Large Language Model Optimization)

LLMO is optimizing your brand's presence inside large language models. It's what happens when you realize ChatGPT is recommending your competitors and you want to change that.

Same goal as AEO and GEO. Different name. The industry hasn't settled on terminology yet, which tells you how new this all is.

LLMO vs AEO vs GEO

These terms overlap so much that people use them interchangeably. But there are subtle differences:

Term	Focus	Scope

AEO	Answer engines (search + AI)	Broadest — includes Google snippets, voice assistants, and AI
GEO	Generative AI responses	AI-generated content specifically
LLMO	Large language models	ChatGPT, Claude, Gemini — the models themselves

Think of it this way: LLMO is a subset of GEO, which is a subset of AEO. LLMO targets the models. GEO targets any generative response. AEO targets any system that gives direct answers.

In practice? The tactics are nearly identical. The measurement differs slightly depending on which platforms you're tracking.

Why People Use Different Terms

The field is young. Different communities coined different terms:

AEO came from the SEO world, extending existing answer-optimization frameworks

GEO came from academic research (Princeton's 2024 paper put it on the map)

LLMO came from practitioners focused specifically on ChatGPT and Claude visibility

Pick whichever term makes sense for your audience. Just know they're all pointing at the same problem: AI is recommending brands, and you need to be one of them.

Core LLMO Tactics

1. Understand How LLMs Learn About You

LLMs build knowledge from training data (web crawls, books, articles) and retrieval systems (real-time web search, RAG). You need to show up in both.

Training data: Get on authoritative sources that LLMs crawl — Wikipedia, major publications, industry sites

Retrieval: Ensure your website and key pages are crawlable, structured, and up to date

2. Build Consistent Brand Signals

LLMs synthesize information from many sources. If your messaging is inconsistent across your website, G2, LinkedIn, press mentions, and review sites, the LLM gets confused. Confused LLMs either hallucinate or skip you entirely.

3. Create Content LLMs Can Extract From

• Direct, factual statements about what you do
• Comparison content that positions you clearly
• Statistics and data points LLMs can cite
• FAQ-style content that matches how users query LLMs

4. Monitor Each LLM Separately

ChatGPT, Claude, and Gemini have different training data, different update cycles, and different opinions about your brand. What works on one might not work on another. Track them individually.

Does the Terminology Matter?

Not really. What matters is whether AI recommends you.

Call it LLMO, GEO, AEO, AI SEO, or "that thing where we make ChatGPT like us." The work is the same: build authority, create citable content, show up on trusted sources, and measure the results.

The brands winning aren't debating terminology. They're doing the work.

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Related: AEO | GEO | LLM | AI Visibility