Decide what to predict

When defining a model, each attribute in your Tealium AudienceStream CDP profile is reviewed to automatically determine the top attributes that have a predictive relationship for the action you want to predict.

Target attributes

A target attribute is a AudienceStream attribute that represents the visitor behavior that you want to predict with any Tealium Predict model. For example, for the boolean visit attribute “Has Purchased”, a value of true indicates that a purchase event has occurred during a visit while a value of false means a purchase event did not occur during a visit.

The target attribute must be either a boolean/flag or a badge type attribute, and be visit or visitor-scoped.

We recommend that you use a visit-scoped boolean attribute as the target. Enrich this attribute to false at the beginning of each visit, and then enrich it to true when the target event occurs during the visit (for example, the purchase event occurs).

We also recommend adding a visitor number attribute, incremented by one with the same rule that sets the target boolean attribute mentioned above, if you do not already have such an attribute.

Exclusion attributes

You can exclude attributes that are not relevant for your model. When deciding which attribute types to exclude, we recommend that you first train the model for initial insights with no attributes excluded.

Training without including exclusion attributes provides insight into which attributes the model finds the most relevant and can lead you to consider introducing new AudienceStream attributes to help future model trainings.

For example, after the initial training, you can exclude attributes with values that occur outside of the training period. After excluding these types of attributes, your training F1 score results may be lower when you retrain; however, your model produces better results when deployed.

• Attributes based on dates of visit or dates of purchase. These attributes do not repeat their values outside of the training period.
• Attributes based on unique user information, such as a User ID or Analytics ID. These attributes do not apply to other users outside of the training period.

Output attributes

The Output Attribute is created by default when a new model is created. It is a numeric Visit-scoped data-layer attribute that stores the Prediction value generated by a corresponding Deployed Model.