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Guide

Geo Testing for Marketing Incrementality

A geo test (geo holdout) measures incrementality by turning a channel off in some regions and comparing against matched control regions. It is one of the most rigorous methods available - and one of the hardest to run well. This guide covers how it works, where it breaks, and how to get the same answer from data you already have.

By Joris van Huët, Founder & CEOUpdated 2026-06-13

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.

Find your wasted ad spend in 2 minutes.

Upload 90 days of Shopify and GA4. Get incremental ROAS with confidence intervals. No pixel, no SDK.

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, with confidence intervals.

Frequently asked questions

Is geo testing the gold standard?

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It is rigorous, but its cost and fragility mean most brands cannot run it often.

Can I avoid the revenue loss of a holdout?

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Yes - causal modeling on historical data needs no suppression.

Causal attribution check

Find your wasted ad spend
in 2 minutes.

Upload 90 days of Shopify and GA4. Get incremental ROAS with confidence intervals. No pixel, no SDK, no integration project. €99 per run.

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