GeoLift vs. Meridian vs. Bell: Choosing a Geo Testing Method

When a user-level A/B test isn't possible, geo experiments are one of the most reliable ways to measure what your marketing actually caused. Treat some markets, hold others back, and compare what happened with what would have happened otherwise. The idea is simple. Getting it right is not. In this session we compare three approaches to geo testing: Meta's GeoLift, Google's Meridian GeoX, and Bell. We walk through how each one chooses treatment and control markets, builds the counterfactual, guards against designs that only look good on historical data, estimates the minimum detectable effect, and calculates significance once the campaign has run. Then we show what happened when we gave all three the same 1,000 simulated datasets, once with no real effect and once with a true 5% lift. The differences were large: one method reported a significant result in more than 40% of tests where nothing had happened, while another missed a real lift in nearly 4 out of 10 tests. We explain why, and what it means for anyone making budget decisions from a geo test. You will leave knowing which questions to ask of any geo methodology, how to recognize inference you can't trust, and which approach fits your markets, your history and your appetite for false alarms. For marketing analysts, data scientists and growth leaders who run or rely on incrementality tests.