d-dat · agentic ai marketing TR·EN← glossaryen
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Data-Driven Attribution.

Multi-touch attribution model

Data-driven attribution (DDA) is Google Ads' default attribution model. It uses a machine learning model to estimate each touchpoint's contribution to conversion across multi-touch journeys. Unlike last-click or first-click, it measures actual incremental value.

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Difference from last-click: last-click counts only the final click; first impression, view-through, mid-journey touches receive zero. DDA measures touches at scale — a user who saw a YouTube ad, clicked Search, and was retargeted on Display before purchasing has the conversion attributed proportionally to all three.

Required for DDA to work well: sufficient conversion volume (30+ conversions/month per campaign), conversion window aligned with purchase cycle, clean GA4 + Google Ads data flow.

Example: SaaS account user journey over 30 days: Day 1 brand search → Day 5 YouTube ad → Day 12 retargeting display → Day 18 purchase. Last-click gives 100% to Day 18 traffic. DDA distributes proportionally across all four (e.g. 30%-15%-25%-30%).
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