Google DDA uses ML for attribution. Needs 300+ conversions. Black box—validate with other metrics.
By The Ad Spend
Machine learning attribution model assigning credit based on actual statistical contribution of each touchpoint to conversions. Google Ads default since 2021.
Formula
ML-calculated credit distribution
Benchmark range
Requires 300+ conversions and 3,000+ ad interactions in 30 days. Falls back to last-click if insufficient data.
Why it matters
DDA is theoretically superior but a black box—you can't audit how credit is assigned. Use DDA for optimization while tracking platform-agnostic metrics (MER, blended ROAS) to validate. Don't trust any single attribution model.
