Radar Charts

Learn how to build radar charts to compare multiple variables

Radar charts (also called spider charts or web charts) display multivariate data on a two-dimensional plane with axes starting from the same central point. They're ideal for comparing the performance of multiple variables or showing how an entity performs across different dimensions.

When to use Radar Charts

Radar charts are ideal when you want to:

• Compare multiple variables for one or more entities

• Show performance across different dimensions

• Identify strengths and weaknesses in a profile

• Display data where multiple metrics are equally important

• Compare the "shape" or pattern of different items

Configuring Your Radar Chart

Radar charts work differently from most other charts. Each axis represents a different variable, and values are plotted from the center outward.

Setting the Axes (Variables)

Each axis represents a different metric or dimension you want to measure. In Noloco, you'll typically configure this using:

The Category/Dimension:

• Each unique value becomes an axis on the radar chart

• These should be your different metrics or evaluation criteria

Best practices for Axes:

• Evaluation criteria: Quality, Speed, Cost, Features, Support

• Skill categories: Technical, Communication, Leadership, Problem-solving

• Performance areas: Sales, Marketing, Operations, Finance, HR

• Product attributes: Price, Quality, Durability, Design, Functionality

Setting the Values (Series)

Series represent the entities you're comparing across all dimensions. Each series creates a different polygon on the radar chart.

For each series, you'll configure:

1. Y-Axis Value: The metric value for each dimension

2. Aggregation Method: How to calculate values (Sum, Average, Count, etc.)

3. Series Label: The name of the entity being measured

4. Filter (important!): Filter each series to show a specific entity

Example Configuration

Scenario: Compare performance of different teams across key metrics

Axes Configuration (Category):

• Field: Metric Name

• Values will be: Sales, Customer Satisfaction, Efficiency, Innovation, Quality

Series 1:

• Label: "Team A"

• Y-Axis Value: Score field

• Aggregation: Average

• Filter: Team equals "Team A"

Series 2:

• Label: "Team B"

• Y-Axis Value: Score field

• Aggregation: Average

• Filter: Team equals "Team B"

This creates a radar chart with 5 axes (one per metric) and 2 polygons (one per team), making it easy to compare their performance profiles.

Data Structure for Radar Charts

Radar charts typically require data in a specific format:

Example data table structure:

• Entity: Team A, Team A, Team A... (repeated for each metric)

• Metric/Dimension: Sales, Customer Satisfaction, Efficiency, Innovation, Quality

• Score/Value: 85, 92, 78, 88, 90

Each row contains one metric value for one entity.

Common Use Cases

Team Performance Comparison

• Axes: Different performance metrics (Sales, Quality, Speed, Innovation, etc.)

• Series: Different teams or individuals

• Shows where each team excels or needs improvement

Product Feature Comparison

• Axes: Key product attributes (Price, Quality, Features, Usability, Support)

• Series: Different products or versions

• Shows competitive positioning and feature balance

Skill Assessment

• Axes: Different skill areas (Technical, Communication, Leadership, etc.)

• Series: Different employees or candidates

• Shows skill profiles and development areas

Business Health Metrics

• Axes: Key business areas (Revenue, Profit, Customer Satisfaction, Market Share, Growth)

• Series: Different time periods or business units

• Shows overall health and balance across dimensions

Competitive Analysis

• Axes: Competitive factors (Price, Quality, Service, Innovation, Brand)

• Series: Your company vs. competitors

• Shows relative market position

Tips for Better Radar Charts

1. Use consistent scales: Ensure all axes use the same scale (e.g., 0-100) for meaningful comparison

2. Limit axes: 3-8 axes work best. Too many create a cluttered chart

3. Limit series: 2-4 series maximum. More than that becomes hard to read

4. Normalize values: Convert different metrics to the same scale (e.g., percentages or scores)

5. Order axes logically: Arrange related metrics near each other on the chart

6. Choose appropriate data: Use metrics that are equally important and comparable

7. Add context: Include a clear title explaining what's being compared

Interpreting Radar Charts

When reading a radar chart:

• Larger polygons: Indicate higher overall performance across dimensions

• Balanced shapes: Show consistent performance across all metrics

• Spiky shapes: Reveal strengths in some areas, weaknesses in others

• Similar shapes: Indicate entities with similar profiles

• Overlapping areas: Show where entities perform comparably

Radar Charts vs. Other Chart Types

Choose a radar chart when:

• ✅ You have 3+ variables to compare simultaneously

• ✅ You want to show the "profile" or "shape" of performance

• ✅ No single metric is more important than others

• ✅ You're comparing 2-3 entities across multiple dimensions

Choose alternative charts when:

• ❌ Bar charts: If you want to compare a single metric across many categories

• ❌ Line charts: If you're showing trends over time

• ❌ Scatter plots: If you're showing relationships between two variables

• ❌ Tables: If precise values are more important than visual patterns

Limitations and Considerations

Radar charts have some limitations:

• Hard to read with many series or axes

• Can be difficult to compare exact values

• Require all metrics on the same scale

• Axis order can affect perception

• Not suitable for negative values

For detailed value comparison, consider supplementing with a table or bar chart.

Advanced Usage

Year-over-Year Comparison

Create series for "This Year" and "Last Year" to show how performance has changed across all dimensions.

Benchmark Comparison

Add a series showing target or benchmark values to see how current performance compares to goals.

Weighted Metrics

If metrics have different importance, consider normalizing values based on their weight before charting.

Common Questions

Q: Can I use different scales for different axes? While technically possible, it's not recommended as it makes comparison misleading. Normalize all values to a common scale.

Q: How do I decide what metrics to include? Choose metrics that are independent, equally important, and relevant to the comparison you're making.

Q: Can I show more than 3-4 entities? You can, but the chart becomes cluttered. Consider showing top performers or creating multiple charts for different groups.

Q: What if my data doesn't fit this structure? You may need to transform your data or use a different chart type. Bar charts often work better for simpler comparisons.