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Brand Drivers Analysis Quadrant Chart Widget

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About the Brand Drivers Analysis Quadrant Chart Widget

The brand drivers analysis quadrant chart allows you to test how independent driving variables affect a key metric and analyze your brand’s performance in comparison to the industry.

This widget looks like a scatter plot on a grid, where a data point's placement on the grid represents how it falls within score gap and importance

The y-axis of the chart represents the importance score, which indicates how important each of your drivers is within the industry.

The x-axis represents the score gap, which is the difference between your target brand (usually your own brand) and the industry average. A score gap can be positive (meaning your target brand scored higher) or negative (meaning your target brand scored lower).

Data Requirements for Drivers and Outcome Metrics

There are two important kinds of fields to think about when building this widget: drivers and outcome metrics.

Data requirements for the quadrant chart are extremely similar to the data requirements for the other brand drivers analysis widget. We recommend reading the following sections for guidance on formatting your survey and mapping your dashboard data to meet these needs:

Widget Setup

The steps described in the widget editing pane

  1. Determine whether to get brand names from Driver questions or a Mapped field. See Data Requirements for Drivers for more information on the requirements for each.
  2. If you selected Mapped field, click Select field to specify the brand where you store the brand evaluated in each response (usually just “brand,” but naming might vary).
    Qtip: See Data Requirements for Outcome Metrics and look under “Mapped Fields” for more details.
  3. Click Select driver to add each driver.
    Qtip: Drivers are usually questions related to brand imagery and product-specific concerns like reputation, performance, reliability, and so on.
  4. Click Configure outcome metric.

Configuring the Outcome Metric for Driver Questions

Read these steps if you indicated that you would “Get band names from” “Driver questions.”

a new window that opens for outcome metric configuration

  1. Label the outcome metric.
  2. First, define the target brand and its outcome metric. The target brand is the one you want to compare to all the others. On the left, select the field you created for the outcome metric, and on the right, specify which brand that field measures.
  3. Next, you’ll be defining the brands you want to compare your target brand with. The “field” column on the left is where you choose the field you created for the outcome metric.
  4. The “Brand” column is where you specify the brand that field measures.
  5. Click the plus sign ( + ) to map another field. You should have a separate field for each brand, as pictured.
  6. Select Include the target brand in the comparison list. This determines whether or not the target brand will be aggregated into the comparison set when performing the calculation.
    Qtip: Best practice is to always include the target brand in the comparison list.
  7. Click Save.
Qtip: Look carefully at the screenshot. Notice how for each field added (e.g., “MusiQ NPS”) the corresponding series (“MusiQ”) has the same brand name listed.

Configuring the Outcome Metric for a Mapped Field

Read these steps if you indicated that you would “Get band names from” a “Mapped field.”

a new window that opens for outcome metric configuration

  1. Label the outcome metric.
  2. Choose the field you created for the outcome metrics.
  3. Define the target brand. This is the brand you want to compare to all the others.
  4. Select the brands you want to analyze in the widget.
  5. Select Include the target brand in the comparison list. This determines whether or not the target brand will be aggregated into the comparison set when performing the calculation.
    Qtip: Best practice is to always include the target brand in the comparison list.
  6. Click Save.

Widget Customization

For general information on how to add and edit widgets, visit the Building Widgets page. Continue reading for information about how to customize this specific widget.

Warning Thresholds

Warning thresholds in the widget editing pane

If results are statistically insignificant, you’ll want to take that into account before making decisions based on what you see in the widget. Therefore, it’s possible to add a warning that will appear on your widget when responses aren’t within a particular statistical range. When you hover over this icon, it will elaborate on the warning, as shown above.

The coefficient of determination (R2) is set to 0.2 by default. The sample size (N) is set to 300. You can adjust these as needed.

Point Color

You can adjust the color of all points on the widget.

Driver labels

If desired, you can click on each driver to change how it is named.