Google uses modeling to estimate online conversions that can’t be observed directly. Modeling allows for accurate conversion attribution without identifying users (for example, due to user privacy, technical limitations, or when users move between devices). Including modeled conversions allows Google to offer more accurate reporting, optimize advertising campaigns, and improve automated bidding.
How modeled conversions work
Google’s models look for trends between conversions that were directly observed and those that weren’t. For example, if conversions attributed on one browser are similar to unattributed conversions from another browser, the machine learning model will predict overall attribution. Based on this prediction, conversions are then aggregated to include both modeled and observed conversions.
Google's conversion modeling approach
Check for accuracy and communicate changes
Holdback validation (a machine learning best practice) maintains the accuracy of Google’s models. Modeled conversions are compared to observed conversions that were held back, and the information is used to tune the models. Google will communicate changes that might have a large impact on your data.
Maintain rigorous reporting
Modeled conversions are only included when there is high confidence of quality. If there isn’t enough traffic to inform the model, then modeled conversions aren't reported (or, in the case of Google Analytics, are attributed to the "Direct" channel). This approach allows Google to recover loss of observability while also preventing over-prediction.
Customize for your business
Google’s more general modeling algorithm is separately applied to reflect your unique business and customer behavior.
Don’t identify individual users
Google doesn’t allow fingerprint IDs or other attempts to identify individual users. Instead, Google aggregates data (such as historical conversion rates, device type, time of day, geo, etc.) to predict the likelihood of conversions.
Modeled conversions in Google Analytics 4 properties
Your Google Analytics 4 property began including cross-channel modeled conversions around the end of July 2021. Data from before that date isn't impacted.
Core reports (such as the Event, Conversions, and Attribution reports) and Explorations where you can select event-scoped dimensions will include modeled data. These reports automatically attribute conversion events across channels based on a mix of observed data where possible and modeled data where necessary.
Examples of conversion modeling
- Browsers that don't allow conversions to be measured with third-party cookies will have conversions modeled based on your websites’ traffic.
- Browsers that limit the time window for first-party cookies will have conversions (beyond the window) modeled.
- Apple’s App Tracking Transparency (ATT) policy requires developers to obtain permission to use certain information from other apps and websites. Google won’t use information (such as IDFA) that falls under the ATT policy. Conversions whose ads originate on ATT impacted traffic are modeled.
- When the ad interaction and the conversion happen on different devices, conversions may be modeled.
- Conversion modeling covers both click-based events and engaged views for YouTube, to help with attribution for engaged-view conversions (EVCs).
- Any conversions imported into Google Ads from linked Google Analytics 4 properties will include modeling.