Live demo · synthetic data
DOOH Reach Planner
Select digital out-of-home venues across Dubai, set your flight length, and the planner estimates campaign reach, average frequency, and cost using a frequency-model reach curve — the same approach I used in a production venue-planning platform on BigQuery inventory data.
1 · Pick your screens
How it works
Why a frequency model?
Mobility-panel data for DOOH is often too sparse for venue-level dedup, so this planner uses the classic negative-exponential reach model: reach = U·(1 − e−I/(U·k)), where U is the addressable universe, I total impressions, and k a venue-mix frequency factor. It's transparent, defensible in front of a client, and converges to sensible saturation behaviour — which is exactly why I shipped it as v1 in production rather than waiting for perfect mobility data.
The production version sits on a BigQuery warehouse of screen inventory and audience data with a Next.js front end; this demo recreates the planning logic on 12 synthetic Dubai venues so you can feel how the model behaves.