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A data-driven attribution (DDA) model analyzes real data about user interactions, unique to your search campaign, to learn how to distribute credit for conversions across all interactions in a conversion path.
The data-driven attribution model assigns credit based on how the addition of each ad interaction to the path changes the estimated key event probability. The data-driven attribution algorithm uses features including time between the ad interaction and the key event, format type, and other query signals to calculate this credit.
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Based on your selected attribution model, you'll notice changes to the following metrics when used with event-scoped traffic dimensions: Key events, Total revenue, Purchase revenue, and Total ad revenue. When you switch to a data-driven attribution model, you may notice decimals or "fractional credit" for the first time in these columns.
We partner with cities, transportation authorities, broadcasters, businesses, and first responders to ensure our community-driven data helps as many people as possible, saving valuable minutes and even lives each and every day. Got questions? How does Waze work? By driving around with Waze open on your device, you share real-time information.
Chromatography Online: UPLC-HRMS Metabolomics of Gourami Hydrolysates Reveals Protease-Driven Bioactive Peptide Profiles