How simple semantics increased our AI citations by 642% [New results]

"Like your weird uncle, nobody knows exactly how AI engines choose the sources they cite. But experiments are starting to point to ways you can get on their radar. And as consumers increasingly turn to AI search for product and service recommendations, you really want to be on their radar. (Ironically, unlike your weird uncle, who you try to avoid.)"

"Before you go any further, it's important to know that this tactic is just one piece of a wider playbook our Growth team lovingly calls the "everything bagel strategy." "Our experimentation hasn't [shown that] this one tactic is the key to better AI visibility," says Amanda Sellers, HubSpot's head of EN blog strategy. " What we've found is that the sum of the parts is what's good for AI visibility. ""

"AI tools can sound very human, but the way they understand language is very different from us. Keeping with Sellers' example about Paris, before reading, you would know from the start whether an article you clicked on was about travel tips or one about celebrity gossip. That context would be all you needed to understand the word "Paris." AI models need a little more handholding."

An experiment achieved a 642% increase in citations from AI tools like ChatGPT by focusing on semantics. The tactic is one component of a broader "everything bagel strategy" that combines multiple optimizations to improve AI visibility. AI models lack immediate contextual understanding humans take for granted, making ambiguous terms like "Paris" hard to disambiguate without clearer signals. Semantic triples are a writing pattern that injects explicit context to help AI determine meaning and source relevance. Combining semantic triples with other visibility tactics increases the chance AI search tools will reference a source.

Read at Hubspot