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Kevel Audience leverages machine learning to identify high-value users from their historic behavior. It provides access to Predictive Models that identify patterns in captured data and delivers recommendations or behavior predictions for specific users in the form of Predictive User Attributes, which are automatically generated and updated.

Kevel Audience provides two types of Predictions: Default and Event-based. Default Predictions are prebuilt for all customers and enable well-researched marketing strategies. Event Predictions provide the flexibility of defining a target event and leveraging predictive models to identify users likely to perform that event. Event Predictions can be configured under the Segment > Predictions option on the side menu.

Default Predictions

Kevel Audience provides a set of default Prediction that do not require any configuration and whose attributes are readily available for segmentation. For more information visit the Default Predictive Attributes section.

Event Predictions

Event Predictions have the goal of identifying users that are likely to perform a target event in the future. This event is defined by a event filter rule which is created through a dedicated builder in the dashboard, equal to the one found at the custom attributes creation. Optionally, you can also configure the interval in which the event is predicted to happen, which is set by default to the next 7 days.


The information about the latest train session can be seen in the dashboard in the specific page for each Event Prediction.


Usage in the Segment Builder

After creation, the event predictions are automatically and periodically trained. After each training session, the model output is stored in a Predictive User Attribute with the name pattern predictions.<event-prediction-id>.<prediction-interval>. The attributes generated by Event Predictions can be selected in the Segment Builder under Predictions > Event Predictions, as seen below.