How it differs from rule-based models
Rule-based models such as last-click, first-click and linear apply the same fixed logic to every conversion. DDA instead learns from your account which interactions actually moved buyers toward converting and weights credit accordingly, so two campaigns with identical click counts can receive very different credit.
What to watch for
DDA works at any conversion volume but models more reliably with more data; Google recommends around 200 conversions and 2,000 ad interactions in 30 days. Because the model is specific to your account, its numbers will not match a CRM's first-touch record or Meta's window-based counts. We treat a platform's DDA number as a signal that a campaign is working, and reconcile the count of record back to the CRM. We unpack why those numbers never reconcile, and which one to steer by, in Google, Meta, and your CRM disagree on conversions. DDA and Smart Bidding work off the same conversion data, so a broken conversion action degrades both at once.
Common questions
What is data-driven attribution in Google Ads?
It is an attribution model that uses your account's own data to assign conversion credit across the ad interactions on the path to conversion, instead of a fixed rule. It is the current default model in Google Ads.
Is data-driven attribution better than last-click?
For most accounts it reflects the real contribution of each touch more accurately than last-click, which over-credits the final interaction. It needs sufficient conversion volume to model well, and its numbers still differ from CRM first-touch records.