How geo testing works
Split regions into test (channel suppressed) and control (unchanged), run for several weeks, and attribute the sales gap to the channel. Done cleanly, it is close to a true experiment.
Where geo testing breaks down
Regions are rarely comparable, you sacrifice real revenue in the suppressed geos, you need enough volume to detect an effect, and you wait weeks for one answer about one channel. For most DTC brands, that is too slow and too expensive to run routinely.
A faster alternative
Causal modeling reads the natural experiments already in your sales history - weeks you spent more or less, channels that paused - to estimate incrementality without suppressing anything, in minutes.
Frequently asked questions
Is geo testing the gold standard?
It is rigorous, but its cost and fragility mean most brands cannot run it often.Can I avoid the revenue loss of a holdout?
Yes - causal modeling on historical data needs no suppression.
The pillar this guide links up to: Incrementality Testing