The Hard Truth About Marketing Measurement Landscape

In this episode of the DTC Podcast, Constantine reviews the three core types of marketing measurement and explains why so much of what’s being sold to DTC brands today is either flawed, biased, or impractical.

Constantine reviews the three core types of marketing measurement and explains why so much of what’s being sold to DTC brands today is either flawed, biased, or impractical.

He also makes the case for evidence-based attribution strategies and explains why incremental lift studies and MMMs often mislead more than they reveal.

In this episode:

• The 3 Types of Measurement: Empirical attribution, statistical modeling (MMM), and causal testing, and why only one is useful for most brands.
• Why MMM is Misunderstood: How fast MMMs use “priors” (aka  assumptions) to feed marketers the results they want to see, and the dangers of confirmation bias in model-driven decisions.
• The Limits of Incrementality Testing: Why confidence intervals make most claims about exact lift misleading.
• The Case for First-Click Attribution: Why tracking the first click (plus robust identity graph) offers a clearer view of what’s actually acquiring new customers. “Everyone complains about last-click attribution. But nobody’s asking why we don’t talk about first-click.”
• Re-Attribution Using Self-Reported Data: How SegmentStream pairs self-reported attribution with actual behavior to uncover awareness channels like YouTube, podcasts, and word-of-mouth.