AI mentions and citations have become the default AI search KPIs.
The problem: they fluctuate from one query run to the next, and nothing about them tells you whether that visibility consistently produces the expected website visitors.
Marketing teams are reporting numbers they can’t connect to traffic, and allocating budget on top of them.
Benchmarks Are Not Performance Signals
Share of voice (SOV), mentions, citations, and sentiment are useful for comparison: where you stand against competitors, how you trend over time. What they can’t do is guide decisions.
They don’t show which pages AI systems actually read, what content gets consumed, or whether machine attention converts into human visitors. Data that answers those questions already exists in your own logs and analytics, and this webinar will teach you how to mine it.
What You’ll Learn
On September 2, Stas Levitan, Founder of LightSite AI, will share what AI bot and crawler data from hundreds of websites reveals about what is actually working in AI search. You’ll learn:
- Why mentions, citations, SOV, and sentiment are benchmarks, not reliable KPIs for budget decisions.
- Which 4 signals from your own data, including AI crawler activity, pages consumed by AI bots, and AI referral traffic, actually guide budget and content decisions.
- How machine attention relates to human visits, and what that means for prioritization.
- How to turn these signals into an action plan: which pages to improve, what content to create, and where to build authority.
About the Speaker
Stas Levitan is the Founder of LightSite AI, where his team tracks AI bot, crawler, and agent activity across hundreds of websites to measure how machine attention converts into human traffic. The session draws directly on that dataset, not on platform-side visibility estimates.
If your AI search reporting is built on mentions and citations, this session will show you what to measure instead.
