Stacked Area Chart: When (Not) to Use It

A stacked area chart is one of the most popular ways to show how a measure in multiple categories changes over time. You’ve probably seen them in dashboards and reports many times, everywhere from Excel to tools such as Power BI and Tableau.

Today, we’ll show you what a stacked area chart is and what its best use cases are, as well as some things you should avoid when using this chart type.

What is a stacked area chart/stacked bar chart?

A stacked area chart or stacked area graph is a data visualization type that shows the cumulative contribution of different categories or series to a total over time or another continuous variable.

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It’s a variant of the basic area chart, where the different values are “stacked” on top of each other to show how individual components contribute to the overall trend.

Stacked area chart: best use cases for data visualization

Here are some of the best use cases for stacked area charts in dashboards or reports.

Tracking changes in composition over time

A stacked area chart is ideal for showing how different segments contribute to the total value over a certain period.

For example, stacked area charts can be used to break down revenue by product line throughout a couple of years, or to highlight market share by a competitor in the same period.

Platforms like Luzmo Studio make it easy to build dashboards with stacked area charts and embed them directly into software applications, while Luzmo IQ and Luzmo AI help users explore trends, analyze category performance, and generate insights automatically using AI-powered and natural language interactions.

Comparing proportions in a dataset

With a stacked area chart, you can compare the proportions of relative categories against the total value instead of focusing on the growth of an individual group.

In this chart example, these charts are useful when doing customer segmentation, to show the relative contribution of segments to the whole user base growth.

Showing the impact of categories on the total value

When you want to emphasize how individual categories add up to form a larger total value, a stacked area chart is one of the best choices. 

For example, if you’re showing total sales numbers, you can break down the value into sales by region.

Visualizing the contribution of multiple variables

When you want to compare how several variables contribute to the total value while still showing the overall trend, a stacked area chart fits right in.

For instance, you’ve launched a new product, and a stacked area chart shows the cost breakdown of the launch, divided into each relevant numeric variable, such as research and development, marketing, operational expenses, etc.

Highlighting overall trends and individual components

Besides tracking the total trend, a stacked area chart allows you to track the individual evolution of different subcategories, independent of the main goal.

For example, it can show you different traffic sources that are contributing to the total value of website traffic.

Monitoring resource allocation

When you need to monitor how different resources are used up over time (such as budget or time) across different tasks or projects.

For example, how the budget is allocated over different departments in a fiscal year.

When not to use stacked area charts

This chart type is powerful, but it has certain limitations. Here is when you should avoid it.

When comparing individual category trends is important

It’s difficult to compare the performance and trends of individual categories in a stacked area chart because only the bottom category has a consistent baseline. In this use case, a line graph would be a better choice.

When you have too many categories

With a large number of categories, the stacked area chart becomes cluttered and tough to read. E.g., if you have more than 10 product categories in a stacked area chart, it would be hard to draw conclusions from it.

When your data is highly volatile

If there are large fluctuations in data over time, it’s challenging to extract meaningful insights. For example, comparing daily stock prices with a stacked area chart would be a challenge.

When proportional relationships are not important 

If the proportion of individual categories is irrelevant to the main target, using a stacked area chart is often unnecessary. In this case, a line chart would be a better choice.

When you need to highlight exact values

Only the bottom layer (x-axis) has clear values, while the layers stacked on top of it are harder to interpret. Use bar charts or line charts if you want to highlight an exact value.

When data is negative or involves subtractions

Datasets that contain negative values or have substractions and complex additions will not display well in stacked area charts. Instead, use a waterfall chart or a bar chart.

For short time periods or small data sets

If the time frame is too small or the dataset is too small, the stacked area chart won’t show any meaningful values. Instead, use a pie chart or a bar chart.

Top tips for using this chart type

• Limit the number of categories: the number of stacked layers should ideally be between 3 and 5. Anything more than that will be cluttered and difficult to interpret.
• Order categories logically: the categories should be listed in order of importance or size. For example, the largest category would be placed at the bottom.
• Use consistent time intervals: the x-axis should have consistent intervals (e.g. months or years). Irregular intervals will distort the data.
• Use color wisely: choose distinct but complementary colors for different categories and avoid colors that are too similar to each other. Use a gradient for related categories and contrasting colors for unrelated ones.
• Provide context with clear labels: label the y-axis and x-axis clearly.
• Focus on proportions, not exact numbers: don’t try to show precise values. The proportions between values are more important for the reader.
• Highlight key trends: use annotations, tooltips, or callouts to label the most important trends in the data clearly.
• Use transparent or light shading: this ensures all the data remains distinguishable and does not overwhelm the reader.
• Ensure that data adds up to 100%: all the categories should add up to the total value on the x-axis.
• Use with time series data: this chart type works best with continuous time data series, so do not use them for categorical data.

Visualize your data with Luzmo

Did you know that you can use stacked area charts, as well as many other chart types, in your software? Simply embed a dashboard in your software or tool with Luzmo. Connect to your data sources with our API and visualize data for your end-users right in your app.

‍Grab a free demo with our team to learn more about data visualization in your software!