Composition Stacked Charts

Who this is for

Data Analysts and anyone who needs to explain how parts contribute to a whole across categories or over time. Useful for product analytics, marketing, finance, operations, and reporting.

Prerequisites

• Comfort with basic charts (bar, line)
• Understanding of categorical vs time-series data
• Ability to summarize data with totals and percentages

Why this matters

Stakeholders constantly ask what drives totals: revenue by product, traffic by channel, cost by department. Composition stacked charts quickly answer how parts build the whole and how that mix shifts. Clear composition visuals lead to better allocation decisions (budget, focus channels, product bets).

Concept explained simply

A stacked chart piles categories on top of each other to show a total and the parts inside it. Each bar/area is one whole; the colored segments are the parts.

Mental model

Think of each bar as a box of fixed height (the total). You place colored bricks (categories) inside the box. With 100% stacks, every box is the same height (always 100%), so you compare mix. With regular stacks, box heights vary, so you compare totals and see parts.

When to use stacked charts (and when not)

• Use when the sum matters and you want to show its breakdown
• Use 100% stacked when mix/percentage share is the main story
• Use stacked area for composition over time (few categories, smooth variation)
• Avoid stacking if you need to precisely compare individual categories across many groups; try grouped bars or small multiples
• Avoid more than 4–6 categories; combine smaller ones into Other

How to design an effective stacked chart

1. Define your base: groups or time. One bar/area per group or time period.
2. Choose absolute vs 100%: totals vs percentage mix.
3. Limit categories: 4–6 max; group the rest into Other.
4. Order segments: consistent order across all bars (e.g., largest on bottom, or logical order). Consistency reduces eye strain.
5. Use clear colors: distinct hues for different categories; keep brightness consistent.
6. Label smartly: show total at top (for absolute), show category labels in a legend, and add data labels only for key points.
7. Highlight the message: bold one segment or annotate a change; do not decorate everything.
8. Consider a baseline risk: only the bottom segment shares a common baseline across bars, so it is easiest to compare. For precise comparisons across segments, prefer 100% stacks or a different chart.

Worked examples

1) Website traffic by source (time series)

Data: months with Direct, Organic, Paid, Referral sessions. Goal: total traffic trend and which sources grew.

• Chart: stacked area for absolute totals
• Why: shows overall growth while revealing the contribution of each channel
• Tip: emphasize Organic by making it the bottom layer if it is a key KPI

2) Quarterly revenue by product (mix)

Data: Q1–Q4 revenue by Product A, B, C. Goal: did share shift?

• Chart: 100% stacked columns to compare share
• Why: normalizes different totals and highlights mix change
• Add: thin total labels above columns to not lose context of growth

3) Survey results (Likert scale)

Data: Strongly disagree to Strongly agree.

• Chart: diverging stacked bars; place neutral at the center, negatives to the left, positives to the right
• Why: quickly shows sentiment balance
• Tip: use a single color hue with lighter tints for negative and darker for positive

Your turn: Exercises

Do the exercise below. Hints and a sample solution are available, but try first.

• Success checklist:
• Each bar is 100% tall; totals align
• Consistent category colors and order across months
• 2–3 brief annotations for key changes
• No more than 5 categories (use Other if needed)

Common mistakes and self-check

• Too many segments: Combine long-tail categories into Other
• Changing colors across views: Fix the color mapping once
• Inconsistent segment order: Use the same order everywhere
• Comparing non-baseline segments precisely: Use 100% stacks or another chart
• No totals on absolute stacks: Add a total label to each bar
• 3D or heavy gradients: Avoid; hurts readability

Self-check before sharing:

• Can someone read the legend and identify each color in 1–2 seconds?
• Is the main takeaway clear in the title/annotation?
• Would a grouped bar or small multiples answer the question better?
• Are units and time period obvious?

Practical projects

• Marketing dashboard: Build a monthly 100% stacked column of traffic by source plus a small total line above it
• Finance report: Stacked bars for department spend with a toggle between absolute and 100% (mix) views
• Product usage: Stacked area of active users by plan tier over time; annotate plan migrations

Quick test

Take the quick test below. Everyone can take it; only logged-in users get saved progress.

Tip: If you miss a question, revisit Common mistakes and the Worked examples, then retry.

Learning path

• Before this: basic bar/line charts, sorting and color fundamentals
• This lesson: choose between stacked vs 100% stacked vs diverging; ordering and color consistency
• Next: grouped bars, small multiples, and highlighting change over time

Next steps

• Refactor an existing chart into a 100% stacked version to test if the mix story is clearer
• Standardize a color legend for your common categories and reuse it across reports
• Create a one-page guide that states when to use stacked vs grouped vs small multiples