Scales (EX)

About Scales

Many widgets display participant engagement and category scores through the use of colorful scales. Where on the scale a given color begins and ends is entirely up to you and can be configured in your dashboard settings.

But these colors are not just for show. Each color indicates favorability, which is used to calculate the engagement scores. In the example above, 67% of the participants gave favorable ratings on the engagement scale selected.

Navigate to the Settings tab and select the Scales section on the left to get started.

How to Change Your Scales

Click the arrows on the white sliders to adjust which scale points correspond to which colors, then click Save.

As a rule, the color on the far left indicates low favorability, the color in the center indicates neutrality, and the color on the far right indicates favorability. This affects the percentages calculated in the compatible widgets listed below.

Reverse-Scale

If you have questions with scales that are reverse-coded, click the dropdown arrow to reveal the different scale points, then select Reverse Scale next to each question that uses a reversed scale. This setting is especially helpful when configuring categories.

If you have mapped more than one source to your dashboard, these sources will share the same scale. You cannot set a different scale for your historical data sources.

Answers Excluded from Analysis

Sometimes scales have an option, such as “Not applicable” or “I don’t know,” that shouldn’t be included in the scale calculations. Choices that are excluded from analysis will appear as dark gray segments.

Many phrases, such as “Not applicable” and “I don’t know,” will automatically exclude the choice from analysis. But if you’d like to reverse this, or if you think a scale point should be excluded when it isn’t already, go to the Survey tab and use the answer dropdown.

Widget Compatibility

The following widgets use these scales:

• Engagement Summary Widget
• Scorecard Widget
• Comparison Widget
• Participation Summary Widget
• Heat Map Widget
• Demographic Breakout Widget
• Question List Widget
• Bubble Chart Widget

Error Messages & Troubleshooting

You may encounter a few different error messages when setting up your dashboard’s favorability scales. These errors are built to preserve your data’s integrity and prevent incorrect analysis of engagement results. Below is a list of common error messages, their causes, and how to fix them.

• • Your scales changes can’t be saved because some of them aren’t compatible with your recode values. This error message appears when you try to save a scale that contradicts your recode values. For example, if two points on your scale have the same recode value, they must have the same favorability on your scale. The scales editor will tell you which scales and fields are invalid by marking them with a red triangle. To fix this, you will need to recode your fields so that the scale points have different recode values. The same error can happen when your scale points don’t form a progressive set (i.e. they aren’t continuously increasing or decreasing), see the recode values troubleshooting section for more details.
    
    Qtip: Hover over a scale point to see its recode value.
    
  • There was an error loading your scales settings. You may see this message if the fields in the Data Mapper are misconfigured, or if you have any questions in your survey that use Carry Forward or Default Choices. These features are not supported in Scales.
    
  • All scales are neutral upon dashboard creation. While rare, this scenario occurs when the recode values in the survey editor would create invalid scales. When you create your dashboard, all of your scales will be neutral. There are two different ways you can fix this issue. If you haven’t yet built your dashboard, we recommend recoding the questions in your survey editor and then creating a new dashboard so that the scales auto-generate. You can also recode your fields in your dashboard data and then manually create your scales, but this method takes longer and is more work.
    
  • If your historical data source contains fields that are on a different numeric scale than your primary source, you’ll need to recode your historical data to match your primary data. For example, let’s say last year’s engagement project had a question on a 7-point scale. If this year’s engagement project has the same question on a 5-point scale, the historical data will need to be recoded to the 5-point scale so that it aligns with the current project’s scale.