Churn Model Predictions

The Churn Model Predictions screen displays customer-level churn prediction results generated by a churn model.

Figure 6-34 Churn Model


Churn Model

Search and Actions

The toolbar provides:
  • A Search control to choose the a specific field to search, such as:
    • Sr. No.
    • As Of Date
    • Model Id
    • Customer Code
    • Customer Name
    • Churn Probability
    • May Churn?
  • A search input field for entering search criteria.
  • An Actions menu for performing available operations on the displayed data.
The results are displayed in a table with the following columns:
  • Sr. No. — Sequential number of the record.
  • As Of Date — Date associated with the prediction.
  • Model Id — Identifier of the churn model used to generate the prediction.
  • Customer Code — Unique customer identifier
  • Customer Name — Name of the customer.
  • Churn Probability — Predicted probability that the customer may churn.
  • May Churn? — Churn classification based on the model prediction.
    • SAFE: Indicates that the customer is unlikely to churn.
    • CHURN: Indicates that the customer may churn.
Use the Actions panel to configure and manage the data displayed in the table. The panel provides the following options:
  • Columns: Show or hide table columns and adjust their display order.
  • Filter:Filter the dataset based on row and column properties.
  • Data: Use the Data menu to manage and update the dataset displayed in the table using the following options:
    • Refresh: Reload the data to display the most current information.
    • Flashback: View data as it existed at a specified time in the past.
  • Format: Use the Format menu to modify the visual presentation of data using the following options:
    • Control Break: Define grouping of table data based on a selected column.
    • Highlight: Highlight row or column based on defined conditions.
    • Stretch Column Widths: Manually adjust column widths to fit the available screen space.
  • Chart: Use the Chart menu to create a visual representation of the current dataset.
  • Report: Generate a formatted report based on the displayed data.
  • Download: Export the data for offline use in supported file formats.