Advertisers around the world want to understand how to measure and optimize their media spend across marketing channels. This can be challenging because customers may interact with multiple touchpoints before making a purchase or completing another valuable action on your website or app. This is where attribution comes into play.
Attribution is the act of assigning credit for conversions to different ads, clicks, and factors along users’ paths to completing a conversion. An attribution model can be a rule, a set of rules, or a data-driven algorithm that determines how credit for conversions is assigned to touchpoints on conversion paths.
To date, Google Analytics 4 has offered a set of models that use fixed rules to redistribute credit for a given conversion across multiple advertising touchpoints. Today, we are excited to fully roll out cross-channel data-driven attribution, an attribution model that uses machine learning end-to-end to deliver credit allocation that is customized (based on your account’s historical data) to each conversion. Since models are continuously improved, this solution also automatically adapts to the changes in performance of different touchpoint categories.
Cross-channel data-driven attribution will be available in all Google Analytics 4 properties in the Advertising workspace, as well as at the property level in Attribution settings. Advertisers can use the Conversion Paths and Model Comparison reports to see how the data-driven model allocates credit to each of their channels or campaigns. Selecting data-driven attribution at the property level will enable it in the Conversion details reports and in custom Explorations.
To learn more about data-driven attribution, visit the Help Center.
Posted by Chris Gorgolewski, Product Manager, Attribution and Anjali Raghavan, Product Manager, Google Analytics