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