What is predictive modeling?
Predictive Modeling (PREM) attributes app conversions to the marketing activity that likely drove them when deterministic identifiers aren’t available, and in contexts where its use is permitted by applicable platform policies, customer configuration, and user consent status. It compares a small set of signals from a link click and a later conversion event, and estimates whether they came from the same device. These signals are not used to create a stable or reusable identifier.
PREM is only used where platform privacy policies allow it, and only for measurement and attribution. PREM is not appropriate for authentication, fraud prevention, account recovery, creating persistent identifiers, or other critical user-level use cases.
How does predictive modeling work?
PREM records limited signals necessary for attribution. PREM evaluates permitted marketing interaction and conversion context to estimate campaign performance.
PREM uses statistical methods to support campaign performance reporting where permitted by applicable platform policies, customer configuration, and user consent status.
Limitations of predictive modeling
PREM is a measurement tool and is not designed for authentication or any decision that has user-facing consequences. Reporting precision varies with the available measurement context, customer configuration, and applicable platform policies.