Marimekko Charts: Examples, Best Practices, and How to Create

A Marimekko chart displays both category size and segment composition in a single view, making it a powerful tool for portfolio analysis and market share comparisons when used correctly.

Key findings about Marimekko charts

A Marimekko chart (also called a Mekko chart) is a variable-width stacked column chart that shows both the size of categories and the composition within them. This means you can see how big each market is and what it's made of, all in one view.

• Use this chart when: You need to show both the total size of each category (like total revenue per region) and the mix inside it (product mix) at the same time.
• Avoid this chart when: You need precise comparisons, have more than seven categories, or need to show period-over-period change.
• Primary decision supported: Choosing which segment (within which category) deserves investment.
• Most common misuse: Using it for time-series data, where changing widths can make growth look larger (or smaller) than it is.
• If you only remember one risk: People often misread areas when columns have different widths.
• Best alternative if this fails: Use a 100 percent stacked bar chart for composition-only comparisons, or a treemap when you have lots of small segments.

What is a Marimekko chart?

A Marimekko chart is a stacked column chart where the width of each column varies based on the category's total value. This differs from a standard stacked bar chart, where every column is the same width regardless of how much that category contributes to the total.

You might hear this visualization called a few different names. "Marimekko chart" comes from the Finnish design company known for bold rectangular patterns. Business folks often shorten it to "Mekko chart." Statisticians call the same structure a "mosaic plot."

The chart encodes data in three ways:

• Width: Shows the category's total value relative to the grand total.
• Height: Shows each segment's percentage share within that category.
• Area: Represents the segment's absolute contribution to the grand total.

Here's the tradeoff. A 100 percent stacked bar chart hides size differences between categories because all columns look identical. The Marimekko reveals this dimension, but it demands more from viewers. People judge length accurately, but they struggle with area comparisons.

When to use a Marimekko chart

Choose this chart only when both the size of categories and the mix within them matter equally to your decision.

The chart works well for comparing market share across regions while analyzing product mix within each region. It's also useful for reviewing investment portfolios where fund size and asset class breakdown both inform strategy. Competitive landscape presentations benefit from this format when you need to show competitor size alongside their segment focus.

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When to avoid a Marimekko chart

This chart creates problems in specific situations. If you're tracking change over time, shifting column widths can create a "funhouse mirror" effect, where growth is hard to compare from one period to the next. When you need precise segment comparisons, people can misjudge area—sometimes by a meaningful margin—because comparing areas is hard. More than seven categories makes the chart cluttered and unreadable. Tiny segments become invisible slivers that get ignored entirely.

If you use it anyway, some stakeholders may confuse height with width and ask, "Why is that one bigger?" Teams can also misallocate resources to segments that look dominant because of column width but are smaller in absolute value.

Key components and data requirements

Before building or interpreting a Marimekko chart, confirm your data fits the requirements. Negative values break the chart because you can't have negative column widths. Segments that don't sum to 100 percent break the chart's math and make the results misleading.

Your data needs three elements: one categorical column for the categories that become columns (regions, products, competitors), one segment column for the breakdown within each category (product lines, customer types), and one numeric value column for the measure being visualized (revenue, units, headcount).

If you're missing segment breakdown, use a standard bar chart. For negative values, try a waterfall chart. Too many small segments? A treemap handles that better.

Columns and width

Each column represents a category, and its width is proportional to that category's total value relative to the grand total. If Region A contributes 40 percent of total revenue, its column takes up 40 percent of the chart's horizontal space.

Watch for one category dominating the data. If one column takes up 80 percent of the width, remaining columns become too narrow to label. Group smaller categories into "Other" or switch visualizations entirely.

Segments and height

Within each column, segments stack vertically. The height of each segment corresponds to its percentage of that column's total. All columns reach the same height (100 percent), but internal breakdowns differ.

Keep segment order consistent across all columns. If "Product A" sits at the bottom of the first column, it must be at the bottom of every column. Inconsistent ordering forces viewers to hunt for data points.

Axes and scaling

The x-axis represents cumulative percentage (0 to 100 percent) with category names centered under each column. The y-axis runs from 0 to 100 percent for segment composition.

Note that the x-axis doesn't have equal intervals. Tick marks align with variable column widths. This is intentional but confuses viewers expecting uniform spacing.

How to create a Marimekko chart in Excel

Excel doesn't have a native Marimekko chart type, which can make it a tough fit for live data dashboards. Building one requires a workaround using stacked area charts and helper columns. The process is manual but achievable without add-ins.

The technique involves creating a stacked area chart where the x-axis represents cumulative category width. You'll duplicate x-boundary points so each column appears as a rectangle rather than a sloped area.

Step 1: Prepare the data

Start with a summary table where categories are rows, segments are columns, and values fill the cells. Add a "Category Total" column summing each row. Add a "Width Share" column as a decimal share of the grand total (so the total equals 1.0). Add a "Cumulative Width" column as the running total of those shares, starting at 0 for the first row.

For each segment, calculate the percentage within each category by dividing segment value by category total. Your cumulative width should end at 1.0 (or 100 percent, if you choose to work in percentages), and segment percentages within each category must sum to 100 percent.

Step 2: Insert a stacked area chart

Select the cumulative width column and all segment percentage columns. Navigate to Insert, then Charts, then Area, then Stacked Area. Excel creates a chart where the x-axis is cumulative width and each area band represents a segment.

The chart will look wrong at this point. You'll see sloped transitions between categories rather than crisp vertical lines.

Step 3: Duplicate x-boundaries for rectangular columns

For each category, you need two x-values: the start point and end point. Duplicate each row so each category appears twice. The first row of each pair uses the starting cumulative width. The second row uses the ending cumulative width. Keep segment percentage values identical for both rows in the pair.

This duplication tells Excel to draw the area flat across the category width, creating vertical edges where categories end.

Step 4: Format and validate

If Excel gives you spacing controls for your chart type, reduce spacing so columns read as continuous blocks. Add data labels by right-clicking each series and selecting Add Data Labels, positioning them inside segments. Format the x-axis bounds to minimum 0 and maximum 1.0 (if you used decimal width shares). If you used percentages instead, set the maximum to 100. Add category labels below each column using text boxes.

If your chart still shows slopes like a mountain range, you forgot to duplicate x-boundaries. Each category needs distinct start and end points with identical y-values to appear rectangular.

This workaround takes upkeep. If you add a new category next month, plan to update the helper columns and reselect the chart's data range. For ongoing reporting, many BI platforms support Marimekko charts with data refreshes. In Domo, you can build a Marimekko and have it update automatically as the data refreshes, which can save you from rebuilding Excel helper columns.

Best practices for Marimekko charts

Every design choice should reduce cognitive load and prevent misinterpretation.

Limit categories to six or seven maximum. More categories create columns too narrow for labels, turning segments into indistinguishable slivers. Keep segments to four or five per category. Too many segments create a patchwork quilt where viewers can't track anything across the chart.

Use consistent segment order across all columns. Inconsistent ordering breaks visual comparison by forcing viewers to hunt for the same segment in different positions. Label segments directly when space allows. Legends make people look back and forth, which adds friction and slows comprehension.

Group small segments (less than five percent) into "Other." Tiny segments create visual noise without adding insight. Use distinct, accessible colors with high contrast between adjacent segments. Sort categories by size with the largest on the left, providing logical flow for the eye.

Marimekko chart examples

Consider a dataset with four regions and three product lines. Region A is your largest market. Region C is small but wealthy. Product Line X is your premium offering.

In the Marimekko chart, Region A appears as the widest column. But Region C shows an extremely tall segment for Product Line X (high percentage). A standard stacked bar would show the high percentage but hide that Region C is tiny. The Marimekko reveals that while Region C loves the premium product, the total addressable market there is small.

For portfolio analysis, imagine five product categories and four customer segments. Category 1 is the legacy product driving most revenue. Category 3 is a new innovation. The chart shows Category 1 as very wide, but its segments might be dominated by a single customer type, indicating high risk. Category 3 might be narrower but show evenly distributed segments, revealing a healthy, diversified customer base.

Limitations and common mistakes

The biggest limitation is perceptual. People judge length accurately but struggle with area. When comparing a tall, narrow segment to a short, wide segment, viewers consistently misjudge which is larger.

Common mistakes include using the chart for time-series data where width changes imply false growth or decline. Viewers often assume taller segments are "bigger" even when shorter segments in wider columns contain more value. Too many small segments create visual noise. Inconsistent segment ordering breaks visual tracking. Presenting without stating the key takeaway leaves interpretation to chance.

Alternatives to consider

For precise segment comparison, use a 100 percent stacked bar chart where equal-width columns enable accurate length comparison. For many small categories, treemaps handle dozens of segments without clutter. For change over time, line charts or small multiples avoid false growth signals from width changes.

How to explain a Marimekko chart in 30 seconds

Don't assume your audience knows how to read this chart — only 29% of employees use analytics and BI tools on average. Guide them through it.

Start by explaining what the chart shows: "This chart shows our revenue broken down by Region and Product Line." Explain the width: "The width of each column shows the total size of the Region—wider means bigger." Explain the height: "The height of each colored band shows the Product Line's share within that Region."

State your takeaway: "Region A is our largest market, but Region C has the highest concentration of premium products." Warn against misreading: "Don't conclude that the tall segment in the narrow column is larger than the short segment in the wide column." Offer alternatives: "If we need to track how this changes over time, we should use a line chart instead."

Final thoughts

The Marimekko chart solves a specific problem: visualizing the relationship between category size and segment composition. When used correctly, it reveals the "vital few" segments that matter most.

The chart carries high misinterpretation risk. Always state your key takeaway explicitly rather than letting viewers interpret shapes on their own. While Excel requires manual workarounds, modern BI platforms handle Marimekko charts natively for ongoing reporting.