Notes on AI search & narrative
How AI models decide whose frame to recommend: visibility, narrative share, and the strategy behind being the answer, not just a mention.
How to Reclaim a Narrative from a Competitor: A Source-Level Strategy
Beating a competitor in AI search isn't about outranking their mentions. It's about finding the sources the model learned from and shipping better ones before it learns the same story again.
Read article →How to Win a Comparison Query in AI Answers: The Frame Beats the Mention
Being mentioned in an AI comparison isn't the same as winning it. The model already decided your role in the story before it wrote the answer.
Read article →Own the Frame in 90 Days: Building a GEO Plan Before AI Models Catch Up
Most GEO plans react to what AI already says about you. A frame-first plan gets ahead of the next training cycle instead.
Read article →Brand Accuracy in AI Answers: Why Mentions Don’t Equal Influence
Being named in an AI answer feels like a win, but the model can mention you and still recommend someone else. That gap is the whole game.
Read article →How to Report AI Visibility to Clients: Presence Isn’t the Proof They Need
Counting mentions tells a client you showed up. It doesn't tell them who's actually winning the recommendation, or why.
Read article →How to Run an AI Visibility Audit (That Actually Moves the Needle)
Showing up in an AI answer isn't the same as winning it: a real audit checks whose story the model is actually telling, not just whether your name appears.
Read article →How to Benchmark AI Visibility Against Competitors: Beyond Mention Counting
Showing up in an AI answer isn't the same as winning it. Real benchmarking measures whose story about your category the model actually learned.
Read article →Google AI Overview Visibility ≠ Narrative Control: Why Tracking Mentions Misses What Actually Wins
Showing up in a Google AI Overview feels like winning, but presence in the answer and control of the story behind it are two different games, and only one of them decides who gets recommended.
Read article →How to Track Perplexity Visibility: Why Mentions Aren’t Recommendations
Showing up in a Perplexity answer feels like a win, but if the frame around your category recommends someone else, you're just background noise with a citation number.
Read article →How to Track ChatGPT Visibility (And Why Mentions Aren’t Enough)
Appearing in a ChatGPT answer isn't the same as winning it. Here's how to track what actually decides the recommendation.
Read article →AI Sentiment Tracking Isn’t About Mentions, It’s About Which Frame Wins
Being mentioned positively in an AI answer doesn't mean you're winning it. The frame the model builds its answer on decides who gets recommended, and that's a different thing than tone.
Read article →What is AI Citation Tracking? Why Mentions Don’t Equal Influence
Being cited in an AI answer isn't the same as winning it. What matters is whose frame the model used to build that answer, and whether your citation reinforces your story or somebody else's.
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