GADT — Attention Design
GADT (The Attention Architect)
GADT explains with mathematical certainty why some advertising placements naturally command attention while others, seemingly identical, become invisible.
How It Works
Attention in public space is not a lottery; it's a predictable outcome of physics, geometry, and human behavior. Where a person walks, how fast they move, where their eyes are naturally drawn, and what else competes for their gaze all determine if they will see your ad. The Geometric Attention Design Theorem (GADT) models these factors to calculate an "Attention Probability" for any given placement.
It moves beyond the simplistic "is it big and bright?" to ask: Is it on the natural sightline of someone coming around that corner? Does a person have enough time in their field of view to process it before they pass? Is it placed at the right height and angle to be legible without strain? Is it drowned out by a brighter, flashier sign next to it? GADT turns placement from a real estate decision ("we got the big one!") into an engineering decision ("we got the effective one").
Real-Life Example
In a busy airport, consider two digital screens of the same size and specification, both for rent at similar prices.
Screen A: Located immediately after the security checkpoint belt. People here are flustered, gathering laptops, belts, and bags, looking anxiously for their gate directions. Their gaze is down and scattered.
Screen B: Located at the seated waiting area by a departure gate. People here are settled, waiting 10-40 minutes. They have exhausted their phone, scanned the room, and are now passively observing their environment, making eye contact with various objects and signs.
GADT would calculate a vastly higher Attention Probability for Screen B, despite it potentially being in a "less trafficked" spot in a pure footfall count.
Example Breakdown
Let's calculate for Screen B (the gate waiting area):
Field of View: The screen is well-positioned in the central sightline of most seats. Probability a viewer is oriented toward it = 0.6.
Dwell Potential: The average wait time is 20 minutes, providing ample opportunity for viewing. Probability they have sufficient time = 0.8.
Clarity: The screen is at a good distance, with high contrast and no obstructions. Probability the message is legible = 0.9.
Competition: There are a few other signs and ads in the area, but none directly adjacent. Competition score = 0.1.
Calculation:
0.6 × 0.8 × 0.9 × (1 - 0.1) = 0.6 × 0.8 × 0.9 × 0.9 = 0.3888 ≈ 0.39
Interpretation
An Attention Probability of 0.39, or 39%, is exceptionally strong for out-of-home advertising. It means that under these specific conditions, we can predict that nearly 4 out of every 10 people in that waiting area will meaningfully notice an ad on that screen. This isn't a guess or a creative director's hunch; it's the predictable outcome of human factors engineering. It allows a media buyer to confidently invest in this screen, knowing its inherent effectiveness, and to price it accordingly based on its proven attention yield, not just its size and location name.