LLMO

ChatGPT handles over 200 million queries per week. LLMO is the discipline of formatting content specifically for citation in large language model outputs.

Unlike traditional SEO, LLMO optimizes for model preference during inference.

How LLMs choose which sources to cite

Large language models apply multiple filters: domain authority, content relevance, answerability, and recency. OpenAI research confirms clarity is the strongest signal. Anthropic concurs that structure drives citations.

The LLMO content checklist

Five checks: opening paragraph answers, key claims sourced, quotable passage exists, clear URL structure, related topic links. Connects to AEO principles and prompt optimization.

Positioning for LLMO: topic focus beats keyword breadth

LLMO rewards specificity. The narrower your focus, the more a model can trust authoritativeness. Topic clustering strategy has evolved for LLMO.

Earning LLMO citations through data and original research

Models prefer original sources. Make data quotable: lead with sample size, methodology, confidence interval, date. Entity recognition is critical.

Monitoring and iterating on LLMO performance

Search your top 30 queries in ChatGPT, Claude, and Perplexity manually. Look for patterns. GEO success requires consistent measurement.

Conclusion

LLMO is the most direct path to reaching users who have already decided to use AI tools. Systematically improve content gaps.