Data-Driven Attribution (DDA)
Data-Driven Attribution (DDA) explained — Google's default model, credited algorithmically across touchpoints. The 2026 standard.
Updated July 2026.
An attribution model that uses machine learning to distribute conversion credit across all touchpoints based on their actual measured contribution, rather than a fixed rule like first- or last-click.
Benchmark range
Now the default attribution model in Google Ads, having replaced last-click. Requires sufficient conversion volume to model accurately.
Why it matters
DDA reflects how conversions really happen across multiple interactions, giving fairer credit than single-touch models and better data for bidding.
2026 update
In 2026, with multi-touch journeys longer than ever — Dreamdata puts the B2B path at ~272 days and ~88 touchpoints — single-touch models badly misattribute credit. Google is also bringing marketing-mix modeling (the open-source Meridian) into its measurement stack to complement DDA as cookie signal weakens.
Where it applies
- Google Ads
- Google Analytics 4