Definition
A geo experiment measures lift by varying spend across regions and comparing outcomes against controls.
How to use it
- Use geo tests when user-level holdouts aren't feasible (e.g., offline or privacy constraints).
- Ensure regions are comparable and avoid cross-region spillover.
Common mistakes
- Using too few regions (low power) and over-interpreting noise.
- Changing major campaigns mid-test (confounds).
Measured as
Measure Geo Experiment with a fixed attribution window, conversion event, and spend basis before comparing campaigns or creative tests.
Misused when
- Using too few regions (low power) and over-interpreting noise.
- Changing major campaigns mid-test (confounds).
Operator takeaway
- Use geo tests when user-level holdouts aren't feasible (e.g., offline or privacy constraints).
- Ensure regions are comparable and avoid cross-region spillover.
- Use Geo Experiment only inside a stable attribution rule, conversion definition, and time window so campaign comparisons stay honest.
- If performance changes, check whether the metric moved for a real business reason or because the measurement setup changed underneath you.
Next decision
- Quantify the impact with Incrementality Lift Calculator if you need to turn the definition into an operating assumption.
- Read Incrementality: how to tell if ads are actually driving growth if the decision depends on interpretation, policy, or trade-offs beyond the raw formula.
Where to use this on MetricKit
Calculators
- Incrementality Lift Calculator: Estimate incremental conversions, incremental ROAS, and incremental profit from a holdout test.
Guides
- Incrementality: how to tell if ads are actually driving growth: Platform-reported ROAS can overstate impact. Learn what incrementality means, when it matters, and practical ways to test it.
- Incrementality lift: how to compute incremental ROAS from holdouts: Turn an exposed vs holdout test into incremental conversions, incremental ROAS, and incremental profit for decision-making.
- Paid ads measurement hub: ROAS, MER, marginal ROAS, and incrementality: A practical hub for paid ads measurement: connect ROAS to profit, use MER for top-down truth, watch marginal ROAS for scale, and validate incrementality with holdouts.
- Attribution vs incrementality: what to trust, when, and how to test: A practical guide to attribution vs incrementality: common attribution models, window pitfalls, how MER/marginal ROAS fit in, and how to run holdout/geo tests.