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Notes from the answers.What the engines say, measured.
8 posts
How to read your first LLM Visibility Report
Start with one number, then distrust it a little. The order the report was written in, and why.
Reading the reportMentioned is not recommended
Two rates that look alike and mean different things — and what the gap between them tells you.
EnginesWhy ChatGPT, Gemini and Perplexity disagree about the same brand
Different retrieval, different sources, different reasons you show up — or do not.
EnginesPerplexity shows its sources. Use that.
Numbered citations next to every claim make it the easiest engine to audit — and to act on.
MeasurementOne answer is a data point, not a measurement
The same prompt answers differently between runs. Why the report repeats every prompt.
MeasurementWhat the AI Visibility Score does and does not tell you
One number to track over time, and the three ways people misread it.
PlaybooksTwenty prompts: how to pick them
The prompt list decides what the report can see. A method for choosing it in twenty minutes.
PlaybooksThe first month after the report
Empty heatmap rows, product pages and the sources the engines cite — in that order.
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