Amazon DSP Attribution Was Broken. Here's What They Rebuilt and Why It Matters Now.

Amazon DSP had a credibility problem. Brands would spend $10K+, see incredible ROAS on the dashboard, pause campaigns, and sales stayed exactly the same. The attribution was lying, and everyone knew it. So they quit. They were right to.

In this episode, I break down exactly why DSP attribution was broken and how phantom conversions happened in the first place. Then I cover the three major upgrades Amazon made in 2025 and early 2026: multi-touch modeling, AI incrementality testing, five-year lookback windows, and randomized controlled trials that actually prove lift.

The new system uses control groups to measure what would have happened without your ad spend. That's a massive shift from the old model, which took credit for sales that were going to happen anyway.

I also walk through real brand case studies showing the pause test actually works now. Run campaigns, pause them, measure the difference, and the data lines up.

If you abandoned DSP in 2023 or 2024 because the numbers couldn't be trusted, the system that broke your trust got rebuilt from the ground up. This episode shows you exactly what changed and whether it's worth reconsidering.

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