Model Insights

To view model insights, in the Models Models interface in Mix Modeler:

  1. Select the name of a model with a Last run status of ● Success from the Models table.

  2. From the context menu, select Model Insights.

You see when the specified model is last refreshed and widgets are displayed using three tabs: Historical overview, Model insights, and Model quality.

You can change the date period on which the widgets on each of the tabs are based on. Enter a date period or select Calendar to select a date period.

Historical overview

The Historical overview tab shows widgets for:

  • Conversion and Spend by Fiscal Qtr and Product.

  • Spend by Channel.

  • Touchpoint Spend.

    You can select an alternative spend-based channel to display for this widget. Select a channel from Channels.

  • Touchpoint Volume.

    You can select an alternative volume-based channel to display for this widget. Select a channel from Channels.

Model - Historical overview

Model insights

The Model insights tab shows widgets for:

  • Contribution by date and base media. The stacked graph is ordered: Base at the bottom, Non-spend channels in the middle, and Spend channels on top.

  • Contribution by channel.

  • Marketing performance summary.

  • Marginal response curves.

Model - Model insights

You can hover over individual chart elements in each widget to display a popover with more details.

To download a CSV file containing the data for the widget, select Download .

To download full model insights data in Microsoft® Excel format, select Download Download data.

Model quality

Model quality assessment
The model quality tab shows a

  • Model Assessment visualization, which you can break down on Actual vs. Predicted or Residual conversions.

    To break down the visualization, select Actual vs. Predicted or Residuals from the Breakdown list.

  • Model fitting metrics table, showing the following columns for each conversion metric:

    • Actual Conversion

    • Modeled Conversion

    • Residual Conversion (difference between actual and modeled conversion)

    • Model quality score values:

      • R2 (R-squared), which tells how well the data fits the regression model (the goodness of fit).

      • MAPE (Mean Absolute Percentage Error), which is one of the most commonly used KPIs to measure forecast accuracy and expresses the forecast error as a percentage of the actual value.

      • RMSE (Root Mean Square Error): which shows the average “error”, weighted according to the square of the error.

    To download a CSV file containing the data for the table, select Download .

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