📊 A 3 Layer Framework to Measure AI Presence, Readiness and Business Impact: Redefining Metrics for the AI Search Era - A new guide where I cover: How the old organic search measurement model, built largely around rankings, clicks, and sessions, is becoming less sufficient on its own in an AI search environment. I propose a structured way to measure, diagnose, and prioritize in an environment where observability is partial, platform behavior differs, and influence often extends beyond directly attributable clicks. The 3 layers of AI search success 1. Presence Whether the brand appears in the AI answers that matter, how it’s represented, cited, linked, and recommended. Replaces traffic only thinking with visibility and representation measurement Visibility KPIs: optimization and monitoring. 2. Readiness Whether the structural conditions needed for stronger visibility are in place. Explains why visibility is weak, strong, or unstable, the diagnostic layer. Diagnostic KPIs: diagnosis and prioritization. 3. Business Impact Whether visibility is translating into measurable value, using observed, proxy, and modelled signals. Connects AI search activity to commercial outcomes without overclaiming attribution. Outcome KPIs: executive reporting and decision-making. The point isn’t to run three disconnected audits. It’s that: * Presence tells you where the brand appears, * Readiness tells you why it looks that way, * and Business Impact tells you whether that visibility creates measurable value. Each layer hands off a hypothesis to the next. That’s what turns three reports into one diagnostic. Read it all: aleydasolis.com/en/ai-search… PS: I'll be speaking about this exact topic at #BrightonSEO next week, see you there 🙌