{"id":110356,"date":"2026-01-13T21:39:45","date_gmt":"2026-01-13T21:39:45","guid":{"rendered":"https:\/\/mailinvest.blog\/index.php\/2026\/01\/13\/how-simple-semantics-increased-our-ai-citations-by-642-new-results\/"},"modified":"2026-01-13T21:40:55","modified_gmt":"2026-01-13T21:40:55","slug":"how-simple-semantics-increased-our-ai-citations-by-642-new-results","status":"publish","type":"post","link":"https:\/\/mailinvest.blog\/index.php\/2026\/01\/13\/how-simple-semantics-increased-our-ai-citations-by-642-new-results\/","title":{"rendered":"How simple semantics increased our AI citations by 642% [New results]"},"content":{"rendered":"

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Like your bizarre uncle, no person is aware of precisely how AI engines select the sources they cite. However experiments are beginning to level to methods you may get on their radar.<\/p>\n

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And as customers more and more flip to AI seek for product and repair suggestions, you actually need to be on their radar. (Paradoxically, in contrast to your bizarre uncle, who you attempt to keep away from.)<\/p>\n

At present, I\u2019ve bought one such experiment that contributed to a 642% enhance in citations by AI instruments<\/strong> like ChatGPT.<\/p>\n

And to the delight of you phrase nerds, it\u2019s all about semantics. However first, everybody\u2019s favourite half: The disclaimer!<\/p>\n

The sum vs. the components<\/h2>\n

Earlier than you go any additional, it\u2019s necessary to know that this tactic is only one piece of a wider playbook our Progress workforce lovingly calls the \u201cevery little thing bagel technique.\u201d<\/p>\n

\u201cOur experimentation hasn\u2019t [shown that] this one <\/em>tactic is the important thing to higher AI visibility,\u201d says Amanda Sellers, HubSpot\u2019s head of EN weblog technique. \u201cWhat we\u2019ve discovered is that <\/strong>the sum of the components <\/em><\/strong>is what\u2019s good for AI visibility.<\/strong>\u201d<\/p>\n

But when I lined all of these components directly, this could be a novel, not a e-newsletter \u2014 so consider this extra like half 1.<\/p>\n

Just a little why behind the AI<\/h2>\n

\u201cA human would possibly have the ability to inform you what the sentence \u2018Paris is cool\u2019 means,\u201d Sellers says. \u201cHowever an AI engine with out [immediate] context wouldn\u2019t know if we\u2019re speaking about Paris, France, <\/em>or Paris Hilton.<\/em>\u201d<\/p>\n

AI instruments can sound very human, however the best way they perceive language could be very completely different from us.<\/p>\n

Retaining with Sellers\u2019 instance about Paris, earlier than studying, you’ll know from the beginning whether or not an article you clicked on was about journey suggestions or one about superstar gossip. That context can be all you wanted to know the phrase \u201cParis.\u201d AI fashions want a bit of extra handholding.<\/p>\n

One option to coddle their chilly, metallic fingers is with a framework known as \u201csemantic triples.\u201d<\/p>\n

As merely as I can clarify it: Semantic triples are a writing sample that creates context utilizing the sequence topic \u2013 predicate \u2013 object. <\/strong><\/p>\n

In case you additionally pushed third-grade English out of your mind to make room for Lord of the Rings trivia, right here\u2019s a really fast recap of what these imply:<\/p>\n