What is LLMO?
Large Language Model Optimization shapes public content so LLMs — during pretraining, RAG retrieval, and live browsing — accurately understand and recall your brand.
How LLMs learn from web content
Foundational models train on massive web crawls (Common Crawl, C4, refined datasets). Pages that survive quality filters, get widely mirrored, and use consistent terminology have outsized influence.
Why LLMs cite some sources
In live retrieval, LLMs favor sources that are structurally clear, factually dense, and semantically aligned with the query. Authority (backlinks, brand mentions) is a strong prior.
Writing for machine comprehension
- Define terms before using them.
- Prefer specific nouns over pronouns.
- Use consistent capitalization for product names.
- Attribute numbers to dated sources.
Semantic density and entity coverage
Cover the whole entity graph around your topic: related people, products, events, standards. LLMs bind your page to the topic through co-occurrence.
Citation patterns in ChatGPT & Claude
ChatGPT tends to cite structured pages with tables and dated stats; Claude weights well-argued long-form; Perplexity prefers self-contained passages. Structure for the intersection.
Structuring data so AI remembers your brand
Publish a public brand entity page (About, Wikipedia, LinkedIn), keep NAP consistent, and repeat brand-as-category framing on high-authority third-party sites.
Key terms
- LLM
- Large Language Model — the underlying AI model.
- Training data
- The corpus a model learns from.
- Citation weight
- Relative influence a source has on a model's answer.
- Semantic clarity
- How unambiguously text conveys meaning.
- Entity recognition
- Identifying real-world things (people, brands, places) in text.
- Knowledge graph
- Structured web of entities and relationships.
- Structured data
- Machine-readable markup like JSON-LD schema.
Put this into practice, automatically
Eternity's Skill files codify your brand truth once, the Digital Twin enforces factual governance across every generation, and the LLMO score flags ambiguous passages before you publish.
Set up your Digital Twin