Measurement Framework
The BackTier Visibility Path™
Four sequential stages. Each is a prerequisite for the next. The framework Jason Todd Wade uses to measure how AI systems move an entity from machine-readable existence to active recommendation and agentic commerce.
Citation → Inclusion → Selection → Transaction. One reporting layer per stage — never blended into a single score, because blending hides the constraint.
STAGE 01
Citation
Evidence
AI systems can extract your content as a reliable source and reference it when assembling answers. The foundation — without it, nothing downstream is structurally possible.
STAGE 02
Inclusion
Visibility
AI systems name your entity inside relevant answers, comparisons, and consideration sets. You can be cited without being included; this is the second bar.
STAGE 03
Selection
Authority
AI systems actively recommend your entity over alternatives. Not mentioned — recommended. The compounding layer where Decision-Layer Insertion shows up commercially.
STAGE 04
Transaction
Agency
Autonomous agents complete commercial actions on your behalf — bookings, purchases, routing — over agent-aware payment rails like ACP, AP2, and x402.
Why each stage matters
Citation without Inclusion means you contribute to answers without being credited. Inclusion without Selection means buyers see your name but the AI doesn't prefer you. Selection without Citation and Inclusion is structurally impossible.
What the Path depends on
Every stage assumes a locked entity. That is the job of Entity Lock Protocol™. The Path then sits inside the larger discipline of AI Visibility Architecture, the originating framework that engineered AI visibility into a system instead of a tactic.