Attribution in Google Analytics brings free, cross-channel data-driven attribution to all customers. An Attribution project allows you to:
- Accurately report conversion totals, de-duplicated across all digital channels
- See a consolidated, consistent view of all digital performance
- Build understanding of your brand’s customer journey.
Overview of attribution modeling
Attribution is the act of assigning credit for conversions to different ads, clicks, and factors along a user's path 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. There are two types of attribution models available in Attribution: rules-based models and a data-driven model.
Attribution models available in Attribution
Rules-based attribution models
Rules-based attribution models follow fixed rules for assigning conversion credit regardless of the conversion type or user behavior. The following rules-based attribution models are available in Attribution:
Last click: Gives all credit for the conversion to the last-clicked event.
First click: Gives all credit for the conversion to the first-clicked event.
Linear: Distributes the credit for the conversion equally across all clicks on the path.
Time decay: Gives more credit to clicks that happened closer in time to the conversion. Credit is distributed using a 7-day half-life. In other words, a click 8 days before a conversion gets half as much credit as a click 1 day before a conversion.
Position-based: Gives 40% of credit to both the first- and last-clicked event, with the remaining 20% spread out across the other clicks on the path.
Data-driven attribution distributes credit for the conversion based on observed data for each conversion type. It's different from the other models because your account's data is used to calculate the actual contribution of each click interaction.
Each Data-driven model is specific to each advertiser and conversion type.
How data-driven attribution works
Attribution uses machine learning algorithms to evaluate both converting and non-converting paths. The resulting Data-driven model learns how different touchpoints impact conversion outcomes. The model incorporates factors such as time from conversion, device type, number of ad interactions, the order of ad exposure, and the type of creative assets. Using a counterfactual approach, the model contrasts what happened with what could have occurred to determine which touchpoints are most likely to drive conversions. The model attributes conversion credit to these touchpoints based on this likelihood.
To read about data-driven attribution methodology in greater detail, download the Data-driven attribution methodology in Attribution (Beta) PDF (which is only available in English).
Requirements for data-driven attribution
Data-driven attribution requires a certain amount of data to create a precise model for how your conversions should be attributed. Because of this, not all advertisers will have a Data-driven attribution model in their account. In general, an account must have at least 600 conversions within 30 days for the Data-driven model to be available.
Attribution starts generating a Data-driven model from the moment you receive the minimum necessary attribution data after the project has been created. Once Attribution has collected sufficient data, data is available for reporting. If you don't have enough data, you won't be able to use data-driven attribution.
Eligibility for data-driven attribution is determined by the data for each conversion type, so you may see a Data-driven model for some of your website and Google Analytics conversions but not for others.
Maintaining eligibility for data-driven attribution
In order for a Data-driven model to remain accurate, the model must be refreshed with new data. If your conversion volume drops below the minimum data requirements over a 30-day time period, data-driven attribution results will no longer be available in reporting.
Compare Attribution and Multi-Channel Funnels
Attribution is a separate feature than Multi-Channel Funnels. Depending on your specific attribution needs, Attribution or Multi-Channel Funnels may be a better fit.
|Attribution in Google Analytics||Multi-Channel Funnels
|Bidding integration with Google Ads for Data-driven attribution||Yes (closed beta)||No|
|Impressions included as events||No||
Beta feature (impressions that lead to sessions)
|Data-driven attribution model||
|Reporting time||Toggle between Interaction and Conversion time (Interaction aligns reporting with Google Ads)||Conversion time only|
|Google Ads cost and click data for reporting||No||Yes|
|Custom rules-based models||No||Yes|
*Only available to Google Analytics 360 customers
†All attribution models in Attribution exclude direct visits from receiving attribution credit, unless the path to conversion consists entirely of direct visit(s). The Analytics cookies used to store information about your website interactions may not always be available due to factors including browser settings. Therefore, some conversions may be misattributed to the Direct channel. To mitigate this, Attribution (beta) models conversions based on privacy-safe data from users, and Google will include modeled conversions in your Attribution (beta) reports as estimates for all applicable attribution models.