geo-experiments

Difference-in-Differences causal inference in Python. Callaway-Sant'Anna, Synthetic DiD, Honest DiD, event studies. sklearn-like API, validated against R.

This Python library implements Trimmed Match for analyzing randomized paired geo experiments and also implements Trimmed Match Design for designing randomized paired geo experiments.

Testing open source geo-experimentation tools for our readers

A curated, vendor-neutral list of tools, libraries, research, and resources for measuring marketing effectiveness — MMM, incrementality, causal inference, and attribution.

Three pre-launch checks for geo experiments: comparison strength, required spend, and whether the business can act. By Brinker Analytics.

Open-source tools for marketing measurement (MMM, geo experiments, causal inference), each with a plain-English 'use it when'.

Causal geo-experiment measuring incremental campaign lift with Bayesian structural time series (CausalImpact)

Geo-experiment design on top of augsynth-py: market selection, power-based design ranking, and experiment reporting

Four free calculators for A/B tests and marketing experiments (sample size, minimum detectable effect, peeking, geo holdout) and an interactive CUPED explainer. Each result comes with one plain sentence on what it means and what would invalidate it. Every formula is checked against scipy, statsmodels and numpy on every push.

Audited geo-experimentation and causal measurement benchmark with Meridian GeoX, GeoLift, econometric baselines, reliability analysis, and post-audit operational studies.

Benchmarking geo-lift estimators for ad incrementality: TBR, synthetic control, and TWFE DiD under simulated geo-panel experiments

No-code app for Google Meridian, the open-source marketing mix model. Upload weekly spend and sales to see each channel's return per $1, plan next year's budget and check it with a GeoX lift test. Runs on your computer with Docker; your data stays there.

Did the ads actually work? Incrementality study on a 14M-user randomised ad test: an estimated 54 of 100 attributed conversions were caused by the ads. Sensitivity analysis, uplift targeting, a sized budget-cut test and a geo-test methods benchmark. Python, SQL, Power BI.