How to Pick the Right Chart Type

Raw data can be overwhelming and difficult to interpret. We get it.

You need to extrapolate meaningful results from piles of data to achieve your goals and make data-informed decisions, but that isn't always easy. That's where data visualization comes in. It's a way to present data in a graphical format that makes it easier to understand, interpret, and share. But how do you choose the right chart type to effectively communicate your data? That's what Spontivly is here to help with.

Let's talk about the importance of data visualization, how to choose the right chart type based on your data, and some tips and tricks for using different types of charts effectively.

The Importance of Data Visualization 📊

Data visualization is a crucial part of any data analysis process. Why? Because our brains are wired to process visual information more efficiently than text. This visualization can be integral in every role at your organization, from community managers to social media managers to project managers and everyone in between. When implementing strategy or reporting results, you need to be able to monitor your progress. A good chart can help with that.

When we see a chart, we can quickly grasp complex data insights. The right chart can reveal patterns, trends, and correlations that might go unnoticed in text-based data. That's a lot of pressure, though… consider this post your one-stop-shop to understand when deciding between area chart vs. line chart or pie chart vs. bar chart.

Pie Charts: A Slice of the Data 🥧

Pie charts are a popular choice for presentations. They're visually appealing and can effectively show the proportions of different categories within a whole. However, they're not always the best choice.

The effectiveness of pie charts can be hindered if the slices are too small to communicate a point or if you're trying to showcase comparative results over different samples. In these cases, a pie chart can be confusing rather than clarifying. Another chart type might be more conducive to your storytelling.

When considering whether or not to use a pie chart, you can ask yourself a few questions, but the most important one is this: does the proportion matter more than the total?

For example, let's say you're looking at engagement demographics on your most recent post. The post received 10k likes and you notice that 6500 of those likes are from female accounts. In this case, it may be more valuable to present this as "65% of the post's likes were from female-identifying users" as opposed to just sharing the number of likes without comparative context.

🚀 TLDR: You might want to use a pie chart if you're comparing a single data point among a small selection of information.

Line Charts: Tracking Changes Over Time 📈

Line charts are great for showing changes over time. They can clearly illustrate trends and patterns in your data. However, they're less useful for storytelling if there are no gradual changes or observed spikes. Line charts are great for samples over longer periods than just a single moment in time.

Line charts can be really helpful for looking for patterns and outliers. For example, if your marketing team changed its marketing strategy, a line chart may help you notice something like an uptick in female engagement after the implementation of the new strategy. This can help you start analyzing what variables have changed over time, controlled or not, and how that correlates with results over time.

🚀 TLDR: You might want to use a line chart if you want to showcase change where the specific points matter across shorter intervals.

Bar Charts: Comparing Increments and Changes 📊

Bar charts are another versatile chart type. They're especially useful when you want to compare actual increments or larger changes. They can be more effective than line charts over a smaller sample, as they can clearly show differences between categories. If you're comparing data across different groups, a bar chart is the way to go.

Unlike the pie charts mentioned above, bar charts are a great comparative visual, especially if the raw number matters just as much as the proportion. Their axes help showcase the importance of the data points' values themselves as well as the comparison, whether it's between one data point's change over time or a specific snapshot of a data set.

🚀 TLDR: You might want to use a bar chart if you think both proportions of a total and the total number within those proportions matter.

Area Chart: Changes Within Datasets 📉

Area charts may look a lot like line charts, and you would be right in thinking that - they do have a lot of similarities. While both charts are great for monitoring changes over time, area charts are particularly great for changes over time among several variables in a dataset.

You might use an area chart over a line chart if you want to showcase drastic changes or discrepancies. Since area charts are more visual because of the heavy use of colored blocks, they might be easier to interpret and digest. They're also a more useful tool if the chart extends over a really long time.

🚀 TLDR: You might want to use an area chart if you're pulling from a big sample to showcase a trajectory.

Map View: Capitalize on Existing Visuals 📍

There's rarely a bad time to turn text or numbers into a visual. When the opportunity arises, why not use a familiar visual to help communicate your data? Our brains understand (and enjoy) looking at maps, so if your data can be sorted by geographic traits, using a map view chart is the way to go.

If geography is relevant, plotting data points on a map can help understand the spread and reach of your dataset. On the map, you can use a legend to identify between different symbols and colors, making this visual very versatile. Just be careful not to exhaust the viewer - if there's too much going on on the map, your point may be lost among the other noisy elements.

🚀 TLDR: You might want to use a map view to communicate a dataset with geographical relevance.

Choosing the Right Chart Type 🧐

Choosing the right chart type depends on what you want to communicate with your data. Here are some questions to ask yourself:

What story do I want to tell with my data?
What patterns or trends do I want to highlight?
What comparisons do I want to make?

Remember, the goal is to make your data easy to understand and interpret. You should always ask yourself, why am I presenting this in the first place? Why is this something that we measure? This will help keep you on track to make sure you're telling that valuable story.

Spontivly Workspace view with Marketing dashboards connected to TikTok, LinkedIn, Instagram, and Pinterest.

Next Steps 🚀

Now that you have a better understanding of how to choose the right chart type, it's time to put your knowledge into practice. With Spontivly, you can easily create data visualizations to tell a compelling story. Our tool is designed to be simple and user-friendly, so you can start building your data dashboards in no time. There's no complicated coding required to build these visualizations - we do that for you, so all you need to know how to do is drag and drop.

Remember, data is a powerful tool, but it's only as good as your ability to understand what it's telling you. By choosing the right chart type, you can make your data work for you and your team. So go ahead, start visualizing your data, and see the difference it can make.

How to Pick the Right Chart Type

The Importance of Data Visualization 📊

Pie Charts: A Slice of the Data 🥧

Line Charts: Tracking Changes Over Time 📈

Bar Charts: Comparing Increments and Changes 📊

Area Chart: Changes Within Datasets 📉

Map View: Capitalize on Existing Visuals 📍

Choosing the Right Chart Type 🧐

Next Steps 🚀

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