Visualization Design Patterns

Sometimes the hardest part of creating an effective data visualization isn't the data or the tool — it's knowing what structure fits the story. This guide provides reusable patterns, or design templates, for common analytic goals.

Think of these patterns as recipes: they provide a proven structure that you can adapt to your specific data and audience needs. Each pattern is suited to particular types of analytical questions and goals.

For each design pattern, we'll cover:

  • The analytical goal it best serves
  • Recommended chart types
  • Common use cases
  • Design tips for implementation
  • Interactive examples

Before/After Comparisons

Goal: Show change over time, especially due to an intervention or key event.

Bar/Column Charts Dumbbell Plots Slope Graphs

Use Cases

  • Impact of a new policy or initiative
  • Sales before vs. after a marketing campaign
  • Employee engagement pre/post workplace initiative
  • System performance before and after optimization

Design Tips

  • Align axes to emphasize proportional change
  • Use consistent scales to avoid misleading comparisons
  • Use color to distinguish before/after states (muted vs. bright)
  • Add labels or callouts to clarify what changed and why
  • Consider showing the percentage or absolute change explicitly

Example: Department Store Sales Before and After Renovation

Side-by-side bars make it easy to compare before and after values across multiple categories. This works well when you have multiple metrics or categories to compare.

Dumbbell plots emphasize the change by connecting the before and after points. This format works especially well when you want to focus on the magnitude and direction of change.

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