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            Feedback Management and Sentiment Insights Recipes and Datasets to Predict Retail Banking Customer Churn

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            Feedback Management and Sentiment Insights Recipes and Datasets to Predict Retail Banking Customer Churn

            The app created by using the Feedback Management & Sentiment Insights Features template runs two recipes to generate example and prediction sets.

            Required Editions

            Available in: Professional, Enterprise, and Unlimited editions with the Revenue Intelligence for Financial Services license
            Feedback Management features are available with the Feedback Management - Starter license or the Feedback Management - Growth license.
            Sentiment Insights features are available with the Feedback Management - Starter license or the Feedback Management - Growth license, and the Sentiment Insights license.
            Recipes and Datasets
            Recipe Description Generated Dataset
            Example Dataset The recipe evaluates your customers’ account and contact data, their survey responses to customer satisfaction (CSAT) and Net Promoter Score (NPS) survey questions, and the sentiment behind their responses to create an example set (training set) that Einstein learns from. Example Dataset
            Prediction Dataset The recipe evaluates your customers’ account and contact data, their survey responses to customer satisfaction (CSAT) and Net Promoter Score (NPS) survey questions, and the sentiment behind their responses to create a prediction set (scoring set) for which Einstein gets predictions. Prediction Dataset

            You can modify the recipes in these scenarios:

            • Your schema deviates from the Financial Services Cloud schema.
            • A custom field of an existing entity changes.
            • The use of feature data changes from an existing entity to a custom entity.
            • The data doesn’t load properly.
            • The app stops working because of incorrect data values.

            See Also

             
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