In this lesson you’ll cover:
- Why rankings and traffic are the wrong scorecard for agent-mediated search
- How AI influence is misattributed — ~70% arrives as “direct” (no referrer), and true influence is ~3–5× what you can measure
- The three ways standard metrics miss AI influence: zero-click influence, synthesis without attribution, and delayed attribution
- The metrics to add alongside traditional ones: citation frequency, mention quality, branded-direct growth, and unexplained direct uplift
- The platform trackability spectrum (Perplexity trackable, ChatGPT desktop partial / mobile dark, AI Overviews dark, copy-paste dark)
- Four signals that surface the “dark” AI traffic hiding in your direct channel
- Seven upstream proxy signals of AI visibility (citation audit, branded-direct gap, crawl volume, Knowledge Graph score, NLP salience, AI Overview presence, competitor gap)
- Citation quality scoring (0–3: absent, listed, described, primary) and five qualitative dimensions
- Wrong-context citations and how scope declarations prevent them
- Three analytics patterns of indirect AI visibility — how to interpret and act on each
- The weekly/monthly/quarterly measurement stack, a free-tools setup, and the four-tier scorecard (technical health → recognition → citation → business impact)