Data-Driven vs Last-Click Attribution: What's the Difference?

Last-click attribution gives 100% of the conversion credit to the final touchpoint before someone converted, ignoring everything else in the journey - even a display ad, an organic blog post, and a retargeting campaign that all played a role beforehand.

Data-driven attribution uses an algorithmic model, trained on a business's own conversion data, to distribute credit across every touchpoint based on its actual observed contribution to conversions - not a fixed rule like "first gets 40%, last gets 40%, middle splits the rest," but a weighting that reflects real patterns in that specific account's data.

Google Ads and GA4 have both moved toward data-driven attribution as the default, retiring simpler rule-based models like first-click and linear attribution for most accounts. The trade-off is transparency: last-click is easy to explain and audit by hand, while data-driven attribution is a black box that requires trusting the model. For most businesses with reasonable conversion volume, the more accurate credit distribution is worth that trade-off - but it does mean channel-level performance conversations need to reference the attributed model being used, since the same campaign can look very different under last-click versus data-driven reporting.