The High Cost Of Bad Measurement: Why Randomized Geo Experiments Are The Gold Standard | AdExchanger

"The number-one job of a marketer is to invest budget wisely to drive sales. That inherently requires accurately measuring the performance of that spending. Yet most advertisers still rely on flawed measurement methods that systematically overstate performance and misallocate resources. The measurement crisis Even the smallest Fortune 500 companies generate roughly $10 billion in revenue, meaning they likely spend at least $1 billion on advertising. Whether you're spending billions or mere millions, the stakes are too high to rely on half-measures when optimizing ROI."

"Attribution modeling, matched-market tests, synthetic control methods and other quasi-experimental approaches dominate the measurement landscape despite well-documented limitations, including their being subject to bias and overfitting to pleasing results. Scientific guidance is clear: quasi-experiments - where test and control groups aren't assigned strictly at random - should only be used when randomized controlled trials (RCTs) are infeasible or unethical. In advertising measurement, RCTs are rarely unethical and almost always feasible."

"The geographic experiment solution Geographic experiments using Nielsen's Designated Market Areas (DMAs) offer a remarkably straightforward and effective way to measure true incremental return on ad spend (iROAS). Unlike user-level experiments, which have been compromised by privacy changes and were never as accurate as claimed, geo experiments are independent of media platforms and provide deterministic results without personal data or expensive infrastructure like user ID graphs, tra"

Accurate ad measurement is essential for investing budget to drive sales and optimizing ROI. Many advertisers rely on flawed attribution models, matched-market tests, synthetic controls, and other quasi-experimental methods that are prone to bias and overfitting, leading to overstated performance and resource misallocation. Scientific standards reserve quasi-experiments for situations where randomized controlled trials (RCTs) are infeasible or unethical. RCTs are rarely unethical in advertising and are often feasible, yet marketers avoid them due to misunderstanding or perceived cost and complexity. Geographic experiments using DMAs provide platform-independent, deterministic estimates of incremental ROAS without personal data or costly identity infrastructure.

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