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            Configure Einstein Decisions

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            Configure Einstein Decisions

            Einstein Decisions analyzes many unique data points when determining the right experience to present to a particular user. This data includes user behaviors as well as contextual data, such as device type, time of day, and demographic data. Einstein Decisions can also reference segment membership and user attribute data, along with catalog objects you create in your catalog. To determine which data Einstein Decisions references, you define the machine learning features on the Feature Engineering page. Typically, a data science or analytics team member configures the feature engineering options for Einstein Decisions.

            Required Editions

            Available in: Premium edition
            Permissions Needed
            To configure Einstein Decisions: A role with Contextual Bandit Create/Edit permissions
            1. From the Machine Learning section of the main navigation, select Einstein Decisions | Feature Engineering.
            2. Select the training target from the Bandit Target dropdown—Click, Conversion, or Goal Completion.
            3. Select the features you want to use while training the machine learning models.
            4. To include specific user segments, click +Segment in the Segment Membership section and select options from the dropdown.
            5. To include specific locations, click +Geography in the Geography section and select options from the dropdown.
            6. To include custom attributes, click +Attribute in the Custom Attribute section and select options from the dropdown.
            7. To include recent user actions with catalog objects, click +Catalog Object in the Catalog Object Interaction History section and select options from the dropdown.
            8. Click Save.
              After configuring the training target and feature engineering options, you can create campaigns with promotions that use Einstein Decisions.
             
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