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Matched Market Testing (MMT) uses a robust statistical framework to measure the true causal impact of marketing campaigns. By pairing markets based on historical performance and creating a synthetic control group, we can isolate the effect of a marketing intervention from natural market fluctuations
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What is Matched Market Testing?
Matched Market Testing (MMT), also known as geo-testing, is a causal inference technique used to measure the incremental lift of a marketing campaign. We divide a set of geographic markets (e.g., DMAs, states) into two groups:
Test Markets: A group of markets where we apply a specific marketing treatment (e.g., increased ad spend, a new channel, or withheld spend).
Control Markets: A group of similar markets where we do not apply the treatment.
By comparing the performance of the test markets to the control markets during the campaign period, we can determine the marketing intervention’s causal effect, or lift.
Why MMT Matters for Your Business
Unlike platform attribution, which often overstates performance, MMT provides true incrementality measurement. This controlled experimental approach ensures you understand what revenue and conversions are actually driven by your marketing investments versus what would have happened naturally.
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Leaders & Executives
Chapter 1: Understanding MMT Test Types and When to Use Them
Learn the difference between holdout and growth tests, plus when each approach makes sense for your business goals.
Leaders & Executives
Chapter 2: MMT Investment Require ments and Budget Planning
Understand minimum spend thresholds, risk profiles, and what investment levels are needed for reliable results.
Leaders & Executives
Chapter 3: Reading and Acting on MMT Results
How to interpret confidence intervals, iROAS metrics, and make scaling decisions based on your test outcomes.
Leaders & Executives
Chapter 4: MMT Limitations and Alternative Approaches
When MMT isn't suitable and what measurement alternatives work better for specific situations.
Scientists & Analysts
Chapter 5: Market Selection and Synthetic Control Methods
Deep dive into statistical correlation analysis, synthetic control creation, and quality assurance metrics.
Scientists & Analysts
Chapter 6: Platform-Specific MMT Implementation
Technical considerations for Google Ads, Meta, and other platforms, including common pitfalls and solutions.
Scientists & Analysts
Chapter 7: Test Duration and Statistical Rigor
Guidelines for test length by campaign type, power analysis, and ensuring statistically valid results.
Scientists & Analysts
Chapter 8: Integrating MMT with Media Mix Modeling
How MMT enhances MMM accuracy through validation, calibration, and continuous improvement loops.