Learn how modern MMM uses Bayesian modeling, geo-level data, and priors to produce transparent, reliable measurement and forecasting results.
Archives
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Learn how Google’s Meridian applies Bayesian causal inference to model marketing performance while accounting for uncertainty, confounding factors, and real-world complexity.
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Learn how adstock, saturation curves, and advanced sampling methods model carryover, diminishing returns, and media efficiency over time.
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Deep dive into statistical correlation analysis, synthetic control creation, and quality assurance metrics.
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Technical considerations for Google Ads, Meta, and other platforms, including common pitfalls and solutions.
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Guidelines for test length by campaign type, power analysis, and ensuring statistically valid results.
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How MMT enhances MMM accuracy through validation, calibration, and continuous improvement loops.