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            Store Predictions in Records

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            Store Predictions in Records

            View your generated predictions contextually by storing them in records. To write back a prediction, select a preconfigured output connector and then select an object and field to store the prediction in. You can write back predictions only if you’ve trained and deployed the model for a template configuration.

            Required Editions

            Available in: Lightning Experience
            User Permissions Needed
            To set up a Data Cloud template configuration: Scoring Framework Admin

            Before you configure the write-back of predictions, configure an output connection in Analytics Studio to write the prediction.

            1. From Setup, in the Quick Find box, enter Industries Cloud Einstein, and then select Scoring Framework.
            2. On the card of the template configuration that you want to use, click Quick actions menu button, and select Edit.
            3. For Configure Write Back of Predictions, click Set Up.
            4. Select the output connection to write the prediction.
            5. Select the object and field that you want to store the prediction in.
              Note
              Note You can purchase more licenses to increase the base limits. See Data Pipelines Limits.
            6. If the writeback object isn’t the object selected for training and scoring, specify join keys from the writeback object and the object used for training and scoring.
              The join keys define the relationship between the two objects.
            7. To continue to define the template configuration, click Save & Continue.
              To return to the Scoring Framework Setup page, save your changes.
            Example
            Example An insurance company uses Scoring Framework to get predictions about the customers who aren’t likely to renew their insurance policy. In Salesforce, customer details are stored in Account records. The insurance company’s Salesforce admin creates a custom field on the Account object to store the predicted non-renewal likelihood score. The admin then selects Account and its custom field as the object and field to store the predictions in. So, financial analysts can take the right steps by viewing this prediction score within the context of the customers’ details.
             
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