Published 03-20-2026
LLM inclusion
For the purpose of LLM inclusion, information should be structured in a clear, machine-readable format, often resembling simple semantic relationships such as: [entity] is [assertion] that [related information]. This type of construction helps LLMs identify entities, understand their attributes, and connect related concepts during response generation.
Multichannel online marketing becomes essential because LLMs rely on statistical modeling and consensus across multiple sources to establish confidence in the information. Consistent signals across channels reinforce entity recognition and increase the likelihood of inclusion.
While inclusion may be sufficient for simple assertions such as [brand x] is [the best supplier of product Y], citation is typically reserved for the canonical or most complete authoritative source of the information.
Published 03-19-2026
AI: The 2000lb Elephant in the SEO Room
Entities are the foundation of modern search systems. Entity-based search engines rely on structured representations of people, businesses, and concepts to understand content beyond simple keywords. AI systems build and refine this entity data by identifying statistical patterns and applying probabilistic weighting to determine what an entity is, what services it provides, and which audiences are most likely to engage with it.