Chapter 11: Keeping Score: Measuring AI Visibility
Chapter 11 replaces rank trackers with a simpler scoreboard: ask the machines and write down what they say.
Contents entry 14 of 17 in Recommended by AI.
What does this chapter argue?
Each month, ask a fixed set of money questions and entity questions across the systems customers use, and record whether you are named, what is said and who is named instead. The results are read as a diagnosis that points to the rule to work on. Single answers vary between sessions. The chapter tracks the trajectory over months, from absent to recommended first, alongside enquiries that arrive already sold.
How does the chapter open and close?
Chapter 11 opens and closes with these lines, as the book prints them.
The old game had rank trackers. The new game has a simpler, stranger scoreboard: ask the machines and write down what they say.
This is the slowest scoreboard in marketing and the most valuable, because what it measures, machine-held trust, is precisely what competitors cannot buy quickly at any price.
Which terms does the chapter define?
This chapter defines three terms:
The chapter names ChatGPT, Claude, Gemini, Perplexity, Grok and Google AI Overviews.
Where does it sit in the book?
It follows Chapter 10: The Local Goldmine and leads into Chapter 12: The First-Mover Decade.
