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Set Up and Maintain Retail Execution
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            Update the Prediction Data in Salesforce Org

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            Update the Prediction Data in Salesforce Org

            Use Einstein Discovery predictions to generate visit recommendations. You can do so by creating an output connection to map the predictions to your Salesforce org, and then creating a recipe that writes the revenue prediction data in the output connection. The output node in the recipe contains the output connector, a custom object, and the mapping from the dataset to the Salesforce object.

            Required Editions

            Available in: Professional, Enterprise, and Unlimited editions where Consumer Goods Cloud is enabled.

            When you use custom objects to map predictions to Salesforce org, always map the data to these custom fields.

            Custom Field Name Description API Name Custom Field Type
            Id To load insights into the AI Visit Recommendation reason, in the Map node of the Next Best Action strategy, map Record Id to the EDInsightsId field.    
            model_score Contains the score from the model. For example, the revenue uplift score of retail_store for the interval between start_date and end_date (both inclusive). model_score__c Number
            predictor1 Contains the value of the top contributor for model_score. predictor1__c Text
            predictor2 Contains the value of the second top contributor for model_score. predictor2__c Text
            predictor3 Contains the value of the third top contributor for model_score. predictor3__c Text
            impact1 Contains the impact of the top contributor for model_score. impact1__c Number
            impact2 Contains the impact of the second top contributor for model_score. impact2__c Number
            impact3 Contains the impact of the third top contributor for model_score. impact3__c Number
            start_date Contains the start date of the interval in yyyy-mm-dd format for which model_score is valid. start_date__c Date
            end_date Contains the end date of the interval in yyyy-mm-dd format for which model_score is valid. end_date__c Date
            retail_store Contains the retail store ID for which model_score is applicable. retail_store__c ID or Text
            Tip
            Tip If you want the visit recommendation object to display appropriate predictions, configure the model score, top three predictors, top three impacts, and the retail store in the output node.
             
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