This page is a curated library of essays, research papers, case studies, and industry analysis on advertising experiments and measurement. It highlights work from academics, practitioners, and platforms that advances evidence-based marketing and rigorous incrementality testing.
Incrementality.net: “Everyone’s data-driven. Almost nobody’s evidence-based”
Talgat Mussin argues that modern marketing has collapsed into “measurement chaos,” with conflicting tools, biased models, and organizational incentives creating a system where everyone is data-driven but almost nobody is evidence-based. The author calls for abandoning bent “rulers” like attribution and platform dashboards in favor of clear, experiment-anchored measurement tied to real business outcomes—a shift that’s uncomfortable, but essential for growth. Link
GreyMatter Unloaded: “Lessons from The Innovator’s Dilemma”
Marc Ryan applies learnings from Clayton Christensen’s book The Innovator’s Dilemma to today’s market-research economy, noting how good management, strong margins, and listening to customers can undermine successful businesses during disruptive innovation. Link
IAB: “Guidelines for Incremental Measurement in Commerce Media“
The IAB and IAB Europe’s new best practices document offer a clear framework for evaluating the true business impact of commerce media investments. The report outlines when to use experiments, counterfactual models, econometrics, and hybrid approaches, grounded in principles of credible counterfactuals, bias control, and signal-to-noise separation. Link
Incrementality.net: “The Real Talk About Marketing Measurement”
Talgat Mussin argues that most businesses remain stuck in dysfunctional measurement habits—trusting platform-reported metrics, tolerating impossible attribution math, and resisting the organizational change needed to adopt experiments and baseline-driven decision making. The author outlines a four-stage “Measurement Consciousness” model and emphasizes that companies win not with perfect data, but by moving quickly from confusion to clarity and cutting waste they can finally see. Link
Meta: “Calibrating Marketing Mix Modeling with Incrementality Experiments for Cross-Channel Understanding”
Meta explains how MMM often misattributes channel performance when used on its own, and why incrementality experiments should be used to calibrate and validate those models. The piece outlines basic, intermediate, and advanced calibration approaches—all reinforcing that experiments provide the ground truth MMM needs for reliable cross-channel decision making. Link
Shelly Palmer: AdCP (Ad Context Protocol): A Real Attempt To Make Agents Buy Media
The author demystifies the latest acronym that media professionals need to know, leading us one step closer to the inevitable future where our media-buying bots are just serving ads to our personal shopping bots. Link
Hampus Poppius: “Don’t Be Fooled by Synthetic Controls”
A data scientist specializing in experimentation highlights how Meta’s GeoLift synthetic control package is prone to overfitting and spurious results. Link
Marketing Economics: “The ROI Illusion: How Pure Efficiency Worship Can Cripple Growth”
Entrepreneur Henry Innis’s essay explains how marketers can do great harm to their performance by overly prioritizing the ROI metric over absolute incrementality, a classic efficiency vs. effectiveness fallacy. Link
ADOTAT: “Retail Media’s Dirty Secret”
Essay describes how the “closed-loop” promise of retail media networks’ self-reported ROI can be a “Potemkin Village,” concealing double-counting or worse. Moral: on-platform lift reporting is always suspect. Link (registration required)
Momentum Commerce: “Amazon Ad Placements See Sudden Shift Away From Product Detail Pages”
This blog post how Amazon cut in half the impressions to its sponsored product pages, with no effect on their clients’ sales, a glaring example of why it’s imperative to regularly test ad investments. Link