Simple Chart Widget (CX)

About Simple Chart Widgets

The Simple Chart Widget allows you to display data in a range of basic charts. Changing the chart type, setting colors, and choosing display options allows you to tailor charts to fit a wide range of situations.

Field Type Compatibility

The Simple Chart Widget is compatible with the following field types:

• Number Set
• Date
• Text Set
• Multi-Answer Text Set
• Drill Down
• Field Group

Only fields with the above types will be available when selecting your X Axis Dimension or Data Series for a Simple Chart.

Widget Customization

Chart Type

Choosing a chart type allows you to decide the format in which you would like your data to be displayed. The Simple Chart Widget has four chart types:

• The Bar chart type creates a simple vertical bar chart.
• The Horizontal Bar chart type creates a bar chart that is oriented horizontally.
• The Line chart type displays the data points connected by a continuous line. Check Spline under Display Options to smooth this line.
• The Area chart type fills the area beneath the data with a solid color. This chart type is particularly useful if you are breaking out your data using a data series.

Basic Setup

When setting up your Simple Chart widget, at minimum, you will need to define a metric. If you decide to use a metric other than Count (which does not require additional specifications), you will be required to specify a field for the metric. You can then add an X Axis dimension, if desired. This acts as a breakout for your selected metric and appears as the additional labels that display at the bottom of your chart. To add an additional breakout on top of your X Axis dimension, you can select a Data Series. A Data Series will allow you to examine your data on an additional granular level.

When selecting a metric, every metric except Count will need a field specified. Only a field with the type Number Set or Multi-Answer Text Set will be available. You can also select Options to specify whether or not you would like your metric in a Number, Percent, or Currency format, as well as the number of decimal places you would like displayed. In addition, you can select Filters to add a filter to your widget on the metric level. These filters are set up similarly to the ones that you set up in your dashboard.

You will only be able to specify your X Axis dimension when using a single metric. If you use more than one metric in your chart, the X Axis dimension will automatically display Metrics and use your selected metrics as a breakout instead.

If you choose to add a Data Series, you will only be able to add fields with the type Text Set, Multi-Answer Text Set, Number Set, or Date. If you do not add a Data Series and only have a single metric and X Axis dimension added, you will have the option to Only show top/bottom N values. Check this box to specify whether you would like to show only Top or Bottom values and to specify how many of these values you would like shown.

Count Metric Options

When you select Count as your metric type and have both an x-axis and data series defined, additional options will be available for displaying your metric. To navigate to these options, click your metric and select Options.

The different options are as follows:

• Metric value (default): The chart will show the numeric count of each data point. The chart will display a number.
  Example: In this screenshot, each bar is displaying the number of responses that fit each data point. For example, there were 10 responses in Customer Success that indicated they were “extremely satisfied.”
  
• Metric value/ Total: The chart will show the result of the calculation (numeric count/total number of responses). The chart will display a percentage.
  Example: In this screenshot, each bar displays the number of responses for each data point divided by the total number of responses. For example, the bar for Customer Success that indicated “extremely satisfied” displays 5% since (10/193) = 0.05 or 5%.
  
• Metric value/ Row total: The chart will show the result of the calculation (numeric count/total number of responses in the x-axis dimension). The chart will display a percentage.
  Example: In this screenshot, each bar displays the number of responses for a data point divided by the number of responses in the same x-dimension. For example, the bar for Customer Success that indicated extremely satisfied displays 15%. This is because the bar is showing the result of this calculation: (10/(10+13+14+14+14)) = 0.15 or 15%. To get these numbers, we add up each of the metric values from the default chart for Customer Success only. So, we see that 10 said they were “extremely satisfied,” 13 said “somewhat satisfied,” 14 said “neither satisfied nor dissatisfied,” 14 said “somewhat dissatisfied,” and 14 said “extremely satisfied.” These responses make up the denominator of our equation. The numerator is the metric we’re interested in, which is the number of Customer Success that said they were “extremely satisfied.”
  
• Metric value/ Column total: The chart will show the result of the calculation (numeric count/total number of responses in the data series). The chart will display a percentage.
  Example: In this screenshot, each bar displays the number of responses for a data point divided by the number of responses in the same data series. For example, the bar for Customer Success that indicated “extremely satisfied” displays 23%. This is because the bar is showing the result of this calculation: (10/(10+12+21) = 0.23 or 23%. To get these numbers, we add up each of the metric values from the default chart for responses that indicated “extremely satisfied” only. So, we see that 10 were from Customer Success, 12 were from Engineering, and 21 were from Recruiting. These responses make up the denominator of our equation. The numerator is the metric we’re interested in, which is the number of people in Customer Success who indicated they were “extremely satisfied.”
  

Normalize Chart

Switching Normalized Chart to Yes will display each data point in the chart as a percentage out of 100%. This is useful if your data is broken out with a data series and you would like to view the fraction of respondents that selected certain values as relative percentages instead of explicit counts.

Stack Chart

Switching Stack Chart to Yes will condense the bars in your chart into a single stacked bar. If you have your widget broken out with a data series, there will be a stacked bar for each value of the data series field. This is particularly useful if you are normalizing the widget. In this case, the length of the bar will be 100% and it will be divided into sections to match the percentages of each data point.

Metric Filters

Let’s say you’ve loaded many different metrics into your table – NPS, average, minimum, maximum, and so on – and you want to be able to filter this data for easier viewing. Furthermore, maybe you want some dashboard users have permission to see a certain metric, but others not to.

Metric Filters are a special Simple Chart filter that allow you to decide who sees what metrics.

Adding a Metric Filter

1. Turn on editing mode by clicking Edit Page.
   
2. Click the filter icon.
   
3. Click Add Filter.
4. Select Metric Filter.
5. Under the Metric Filter dropdown, decide which metrics to include or exclude.
   
6. To prevent dashboard users from modifying this filter, select Lock Filter.

Mapping User Attributes to Metric Filters

You can make the default metrics users see vary based on User Attribute. Users will still be able to select different filters, but what they see by default will vary.

1. Set up a User Attribute. As displayed in the image below, the value should be the exact name of the metrics you want to include in this filter, separated by commas.
   
2. Navigate back to your dashboard on editing mode.
3. In your Metric Filter, select Set default value from user attribute.
   
4. Select a user attribute from the dropdown.
   
5. Make sure the Attribute Value and Data Value correspond to the desired information.
6. To use the User Attributes exactly as they’re saved, click Use User Attribute values directly.
7. Click Save.
8. Once a User Attribute is set, you can also limit the default value by role. If desired, select Limit default value by role.
   
   Qtip: When you choose to “Limit default value to role,” you are determining a single role whose default metrics will be limited by the members’ User Attribute. This means that members of the role will see what you set as their User Attributes by default, whereas everyone outside the role will just see all the metrics by default.
9. If you selected Limit default value to role, select a role from the dropdown.

Adding Benchmark Goal Lines to Widgets

You can also use aggregate data to set goal lines on Simple Chart widgets displaying your company’s data. This provides a nice visual key of where your company’s data stands against industry leaders.

1. Create a Simple Chart widget.
   
2. Set the Chart Type.
   
   Qtip: Generally, goal lines work best with the Line Chart type.
3. Set your Metric and X-Axis breakout.
   Qtip: In this example, we use an Average metric of our company’s NPS data, and set the X-Axis to a date field. We then organize this date by Quarters to show how the data has changed from fiscal quarter to fiscal quarter.
   
4. Click Add Reference Line.
   
5. Click your newly made reference line.
6. Label your line.
7. Leave the Line Type as Based on value.
8. Type the value of the benchmark you’d like to use as a goal line.
9. Repeat Steps 4-7 as needed.
   
10. Change the colors of your reference lines.
    
11. Select Show Tooltip.
    
12. Add a description designating the goal lines by color. This will appear as a tooltip your dashboard users can hover over.
    

FAQs