Pillar · Hub Page
Experience — the first E in E-E-A-T: first-hand knowledge
Systems that evaluate whether content reflects genuine, lived experience
The 'E' in E-E-A-T was added in December 2022. It asks: does the content creator have first-hand experience with the topic? For Google, this is the hardest dimension to measure algorithmically — it requires distinguishing content that demonstrates real experience from content that merely discusses a topic.
Primary systems (2)
Systems where Experience is the primary E-E-A-T dimension.
This score measures how much first-hand material a piece of content contains — information found only there, that an AI could not reconstruct from other sources. The higher the score, the more original the content. It is the closest machine equivalent to the E-E-A-T dimension 'Experience' (lived experience and direct observation).
Not a live signal used daily in ranking — but the foundation on which all quality models are calibrated. The IS-Score (Information Satisfaction) summarizes how well a page meets a user's information need, rated by trained human raters. The QRG (Quality Rater Guidelines) are the public rulebook by which these raters judge.
Indirect systems (4)
Systems that contribute to Experience indirectly.
Deep Dives (6)
NavBoost: How Google Uses Click Behavior to Re-Rank Search Results
From DOJ testimony to leaked API documentation — the most important ranking signal you can't directly manipulate
Q* and P*: The Two Pillars of Google's Ranking Architecture
The DOJ trial revealed that Google's ranking ultimately reduces to two top-level signals — Quality (Q*) and Popularity (P*). Here's what the evidence tells us about how they work.
IS-Calibration: The Human Rater System That Trains Google's Quality Models
The hardest evidence in the entire matrix — DOJ/sworn material confirms the rater system that calibrates every quality signal Google uses
OriginalContentScore: How Google Measures Content Originality
The leak field that measures how much original material a document contains — information that is only found there and that an AI couldn't reconstruct from other sources
contentEffort: How Google Estimates Editorial Effort
The AI model that estimates how much editorial work went into a page — and why 'effort' is becoming a ranking signal
Glue: How Google Measures Interaction with Special Search Features
The NavBoost counterpart for carousels, 'People also ask' boxes, and news features — measuring whether users interact with special elements, not just blue links