Features
Breakdowns
Slice data into multiple series with breakdowns
Breakdowns allow you to slice your data into multiple series, creating more detailed and comparative visualizations. This feature works across line charts, horizontal bar charts, and timebar charts, automatically grouping your data by different dimensions.
How breakdowns work
Breakdowns take your main metric and split it into multiple series based on a categorical field. This creates more granular insights by showing how different segments contribute to the overall data.Supported chart types
Line charts
Breakdowns create individual lines over time, allowing you to compare trends across different categories:- Each category becomes a separate line
- Lines are color-coded for easy identification
- Perfect for comparing trends across segments
Horizontal bar charts
Breakdowns create stacked bars showing the composition of each category:- Each bar is divided into segments
- Segments represent different breakdown categories
- Shows both total values and composition
Timebar charts
Breakdowns group data for each time period, showing daily or period-based breakdowns:- Each time period shows grouped data
- Multiple series within each time period
- Perfect for seeing how segments change over time
When to use breakdowns
Perfect for:
- Comparative analysis: See how different segments perform
- Composition insights: Understand what makes up your totals
- Trend comparison: Compare how segments change over time
- Segment analysis: Deep dive into specific categories
- Performance comparison: See which segments are performing best
Not ideal for:
- Simple totals: Use regular charts for single metrics
- Too many categories: Can become cluttered with 10+ breakdowns
- Unrelated data: Categories should be logically related
- Very small datasets: May not provide meaningful insights
Prompt examples
User analytics
Website analytics
Sales and revenue
Marketing performance
Operational metrics
Breakdown syntax
Basic breakdown
Examples:
- “Revenue broken down by product”
- “Users broken down by country”
- “Orders broken down by status”
Advanced breakdowns
Examples:
- “Sales over time broken down by region”
- “Signups over time broken down by source”
- “Activity over time broken down by type”
Best practices
Category selection
- Meaningful categories: Choose categories that provide business value
- Reasonable number: Aim for 3-8 breakdown categories for clarity
- Consistent naming: Use clear, consistent category names
- Logical grouping: Ensure categories are logically related
Data preparation
- Clean categories: Handle null or missing category values
- Consistent formatting: Use consistent category naming
- Appropriate aggregation: Choose the right aggregation method
- Handle outliers: Consider how to handle extreme values
Visual design
- Color coding: Use distinct colors for each breakdown
- Clear legends: Include clear legends for breakdown categories
- Consistent styling: Maintain consistent visual style
- Accessibility: Ensure colors are distinguishable
Common use cases
Business intelligence
- Revenue analysis by product line
- Customer behavior by segment
- Performance metrics by team
- Regional performance comparisons
Marketing analytics
- Campaign performance by channel
- Lead quality by source
- Conversion rates by landing page
- Customer acquisition by demographic
Product analytics
- Feature usage by user type
- Engagement by platform
- Retention by cohort
- Performance by device
Operational metrics
- Support volume by category
- System performance by component
- Resource utilization by department
- Process efficiency by team
Chart type considerations
Line charts with breakdowns
- Best for: Time-based trend comparisons
- Example: “Revenue over time broken down by product category”
- Result: Multiple lines showing how each product category’s revenue changes over time
Horizontal bar charts with breakdowns
- Best for: Categorical composition analysis
- Example: “Total sales broken down by region”
- Result: Stacked bars showing how each region contributes to total sales
Timebar charts with breakdowns
- Best for: Time-based composition analysis
- Example: “Daily signups broken down by source”
- Result: Grouped bars for each day showing signup composition by source
Advanced breakdown techniques
Multiple breakdowns
You can combine breakdowns with other filters:Comparative breakdowns
Compare breakdowns across different time periods:Conditional breakdowns
Use breakdowns with specific conditions:Common pitfalls
Avoid these mistakes:
- Too many categories: Keep breakdowns to 3-8 categories for clarity
- Unclear categories: Use descriptive, consistent category names
- Irrelevant breakdowns: Choose categories that provide business value
- Poor color choices: Ensure breakdown colors are distinguishable
- Missing context: Provide context for what the breakdowns represent
Technical considerations:
- Data quality: Ensure category data is clean and consistent
- Performance: Large datasets with many breakdowns may be slower
- Clarity: Too many breakdowns can make charts hard to read
- Interpretation: Help users understand what the breakdowns show
Related features
- Filters and variables: Combine breakdowns with dynamic filters
- Line charts: Use breakdowns for trend comparisons
- Horizontal bar charts: Use breakdowns for composition analysis
- Timebar charts: Use breakdowns for time-based grouping