Radar Chart - Flowboard

What it is

Radar Chart compares several dimensions in one visual shape so users can quickly see strengths, gaps, or patterns.

What it’s best for

Use it when comparison matters more than exact numbers.

When to use it

Show a skill profile
Explain readiness or maturity scores
Compare current state versus target state
Visualize a product fit assessment

When not to use it

Do not use it when users need exact values more than a quick comparison.
Do not add too many axes. The chart becomes harder to read as complexity grows.

How to add it in the dashboard

Open the screen in the dashboard.
Add Radar Chart from the Components panel.
Select the chart on the canvas.
In the properties panel, define the chart dimensions, datasets, and visual styling.
Review the final chart on the canvas to confirm the labels and shapes stay readable.

Key parameters

Parameter	What it changes	When to adjust it
Axes	Defines the dimensions being compared	Use clear labels that users can understand quickly
Datasets	Adds one or more comparison shapes	Use it when comparing current, target, or segment views
Width and height	Controls the overall chart size	Increase it when labels or comparisons feel cramped
Padding	Adds room around the chart	Use it to prevent labels from feeling crowded
Shape	Switches between visual chart styles	Choose the style that best fits the rest of the screen
Grid levels	Controls how many guide rings appear	Use fewer levels for a simpler look and more for analytical detail
Axis labels	Styles the text around the chart	Adjust it when readability is weak
Legend visibility and position	Shows which dataset is which	Use it when you compare more than one dataset
Background	Changes the chart container look	Use it when the chart needs separation from the page
Animation	Adds motion when the chart appears	Use it lightly to make the result feel more polished

Example use cases

Show how a user scores across several onboarding readiness dimensions
Compare current product usage against an ideal profile
Present a before-and-after improvement snapshot after setup

Best practices

Keep axis names short and easy to recognize.
Limit the number of dimensions so the chart stays readable.
Use contrasting dataset colors when comparison is important.
Add a short text explanation so users know what the chart means.

Common mistakes

Trying to show too many dimensions at once
Using similar colors for different datasets
Dropping the chart into a screen without explaining the takeaway