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            Create an App to Identify Retail Banking Customers Likely to Churn

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            Create an App to Identify Retail Banking Customers Likely to Churn

            By using the Customer Churn Risk for Retail Banking template, you can create an app that provides prediction scores about the likelihood of Retail Banking customers churning.

            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.
             

            Before you use the Customer Churn Risk for Retail Banking template, get the required snapshot datasets by creating an app using the Analytics for Retail Banking template. If you want to use Feedback Management & Sentiment Insights features for predicting customer churn, get the required datasets by creating an app using the Feedback Management & Sentiment Insights Features template.

            Important
            Important You can create an app by using the Customer Churn Risk for Retail Banking template only when snapshot data is available for at least 30 days.
            1. In Analytics Studio, click Create, and then select App.
            2. Select the Customer Churn Risk for Retail Banking template, and then click Continue.
            3. Review the preview page, and then click Continue.
            4. Choose to create an app or to use settings from an existing app, and then click Continue.

              Analytics runs a compatibility check of the data in Salesforce.

            5. Review the compatibility check results.
              • If the compatibility check fails, perform the instructions in the error message to resolve the issues, and then try to create the app again.
              • If the compatibility check completes successfully, click Looks good, next.
            6. Configure these settings in the next screen:
              1. Select an account app with a snapshot dataset containing past trends.
              2. Select the account app's snapshot dataset for the model to use to determine patterns.
              3. Select a financial account app with a snapshot dataset containing past trends.
              4. Select the financial account app's snapshot dataset for the model to use to determine patterns.
              5. Click Looks good, next.
              Note
              Note Select snapshot datasets generated by the app that’s created by using the Analytics for Retail Banking template.
            7. Configure these settings in the next screen.
              1. Select the number of days for which you want to predict the likelihood of customer churn.
              2. Select the record types of accounts for which you want to predict the likelihood of churn.
              3. Select the record types of financial accounts related to the accounts for which you want to predict the likelihood of churn.
              4. Click Looks Good, Next.
            8. Configure these settings in the next screen.
              1. Select account statuses that indicate that the account is inactive.
              2. Select account statuses that indicate that the account is active.
              3. Click Looks Good, Next.
            9. Specify if you want to include example and prediction sets with Feedback Management and Sentiment Insights features and click Looks Good, Next.
            10. If you chose to include Feedback Management and Sentiment Insights features, configure these settings in the next screen. Otherwise, move to the next step.
              1. Select the example set generated by the app that’s created by using the Feedback Management & Sentiment Insights Features template.
              2. Select the prediction set generated by the app that’s created by using the Feedback Management & Sentiment Insights Features template.
            11. Enter a name for your app, and then click Create.

              The process takes a few minutes.

            12. To view your app after the process is completed, refresh the page.

            The app now runs preconfigured recipes to generate example, historical, feature, and prediction datasets, and two dashboards.

             
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