Data-driven attribution
Also called DDA.
A model that learns how to split credit from your own conversion paths, instead of a fixed rule.
Data-driven attribution compares paths that led to a conversion with paths that did not, and gives more credit to touches that seem to raise the chance of converting. Google Ads and GA4 use it, and Google retired first click, linear, time decay and position-based models from both in 2023 (Google).
It adapts to your data, but it only sees touches inside Google's own measurement, and its weights cannot be checked by hand. Use it alongside a simple model you can explain.
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