How to Tell Engaging Stories with Data Visualization

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If a picture is worth a thousand words, data visualization is worth ten times that — at least.

No matter what kind of content you’re producing, the best way to prove a point is through data. On the other hand, looking at rows and tables packed with numbers can tax the brain and may be more confusing than illuminating.

Thankfully, data visualization, or data viz for short, can communicate the same essential information as those tables, just in a more understandable way.

We’ll show you why data visualization is important for publishers, our best tips and practices, and what kind of tools you can use to create your own — with examples, of course.

What is Data Viz?

Data visualization is the process of transforming information into a visual format such as a chart, graph, map, or even interactive content. They can be simple or creative, they are easily shareable and they help to tell the whole story.

To show the impact of wildfires, for example, Seagate’s Michael Mixon created this unique infographic:

Although it looks like a simple bar graph, it tells a captivating story. Each bar’s height shows the amount of burned area over the year. Every individual line represents a specific fire. The thickness of the lines depicts the number of acres consumed by fire.

Not only does the infographic provide all the important information at a glance, it’s also easy to grasp and keeps readers engaged.

Why Publishers (Should) Focus on Data Visualization

Data visualizations allow you to present detailed information and large data sets in a way that is natural for users to comprehend. It makes identifying patterns and trends easy, and it allows you to highlight certain relationships or areas that could be improved.

In fact, it’s an ideal way to relate your stories because our brains are primed for visual communication. Consider these statistics:

Fortunately, we live in a world where data visualization tools are abundant. You can design stunning visuals with free software.

Let’s start at the beginning with best practices.

Show Me the Data: 5 Best Practices

Your goal is to lower your audience’s burden when it comes to understanding information and key takeaways. Data visualizations do exactly that as long as you follow a few best practices.

Know Your Audience

Having a good understanding of your audience is marketing 101 and will help you create the right data visualizations. Ask yourself how familiar your readers are with the data you want to present and whether they are comfortable interpreting data.

Based on that answer, consider how much information to present in one visualization. Knowledgeable audiences can handle more detailed data presentations; others might benefit from multiple data visualizations that show more straightforward correlations.

Pick the Right Visual Format

From line graphs to heatmaps, there are many ways to present data visually, and no decision is more important than the format. The key here is to think about how the data points relate to each other and what you want to communicate.

The Financial Times created an incredibly helpful infographic (bookmark it now!) that categorizes 74 data visualization charts by purpose. 

Here’s a look at some of the most common data visualization formats:

Line Graphs

Use line graphs to show how trends change over time and display how two or more variables relate.

This line graph comes from a Taboola article that discusses traffic patterns for immunity-related content in India over a seven-month period. It allows readers to instantly identify when there were spikes or dibs in interest.

Bar Charts

Bar charts are a great way to display information when comparing quantities and to highlight rankings over absolute values.

This bar chart from another Taboola article shows how the COVID-19 news cycle impacted searches by comparing the average number of unique users each quarter to the number of unique users over one week.

Pie Charts and Donut Charts

With a pie chart or donut chart (a pie chart with a hole in the center), each segment or slice of the pie represents a subset of the data and shows how it compares to other segment sizes and the entire dataset.

This pie chart from The Washington Post clearly shows the religious breakdown of democrats and democrat-leaning voters.

Bubble Charts

Bubble charts are best for communicating three data points, with the X and Y axis used to depict two pieces of data and the size of the bubble showing the third. You can also use color to represent the fourth piece of data.

This data visualization comes from a World Bank article discussing different worldwide challenges. The agency used a bubble chart to show how prevalent stunting is (y-axis) in relation to the accessibility of sanitation services (x-axis). The third piece of data is the bubble’s size, which corresponds to each country’s population size. The color associates individual countries with their general regions.

Heatmaps

Choose a heatmap to display individual data values from a matrix through color intensity. It can be used to discover a website’s most used areas, for example, as well as weather phenoms, financial trends and population statistics.

The New York Times created a heatmap to visually communicate the areas in the US with the highest amounts of COVID cases. Darker colors represent higher amounts of cases.

Provide Context In Your Data Viz

Even the best-looking data visualizations need explanations to help guide the reader and to make sure the data won’t be misinterpreted. Here’s what you need to do:

  • Clearly label the image, the X and Y axes, and any incremental marks.
  • Add a few words directly into the graph to highlight interest points.
  • Include a caption to summarize the data or draw attention to a specific trend.

Here’s a well-labeled graph from a Taboola article showing traffic dips during the holiday season. The title is straightforward, the x- and y-axis are labeled, and extra information is pointed out visually with an arrow and a text label.

Use Colors Effectively

Colors are powerful and can help emphasize important information, but don’t forget to explain what the colors represent through a key. Optimize your use of color by:

  • Using a different color for each category
  • Showing lower values in lighter colors and higher values in darker ones
  • Having the same color to represent the same variable.
  • Selecting a color like gray to show a baseline
  • Picking brighter colors to depict important points

To explain why Sweden sends very little trash to landfills and what they do with it instead, Beautiful News Daily created this attractive infographic. All of the colors compliment each other but stand out on their own, making the data easy to interpret.

Design for Inclusivity

Following user experience and accessibility best practices should already be top of mind for your website and content pieces. Apply a similar mindset to data visualizations.

Worldwide, about 300 million people have a visual impairment, like color blindness or less than perfect eyesight. If you design with them in mind, you will produce data visualizations that serve them and every other visitor. Tips for doing this include:

  • Use contrasting colors
  • Avoid pairing red and green together
  • Add a pattern or texture on top of colors for an extra layer of distinguishability
  • Label elements with text or icons

Check out these accessible palettes from researcher David Nichols:

Get Visualizing: Your Data Viz Toolbox

There are hundreds of data viz tools on the market. Tools are designed with different user personas and industries in mind, so selecting the right one for your business will come down to usability, flexibility, price, and capabilities.

No matter which tool you use, product developers have included best visualization practices.

If your brand has specific design requirements or needs unique functionality, standard plans and free tools might not cut it. That said, it’s worth giving the ones you are considering a test drive and getting feedback from team members and stakeholders to determine if it fits your needs.

When evaluating data viz tools, ask these questions:

  • How will the tool or platform access my data?
  • What chart types are best, and how much variety do I need?
  • Do I want to create static visualizations or interactive ones?
  • How easy is it to export and embed my visualizations on my website?
  • What is the team’s coding ability?
  • What’s my budget?

User-friendly Data Visualization Platforms

Many times, your team will receive data in the form of an Excel file or Google Spreadsheet.

With a few clicks, you can quickly turn those rows of data into basic visualizations without ever opening another program.

However, if you want to create more branded visualizations or have more flexibility in visualization formats and interactivity, give one of the recommended tools below a shot.

Canva

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Canva is a fantastic site if you want to create simple, clean-looking charts. The free version offers nine different chart types.

Enter data manually or paste it from a spreadsheet, both of which are standard practices. You can choose from a pre-defined palate or add custom colors, and even implement some basic animations.

Infogram

With an intuitive interface, Infogram does a stellar job of turning data into interactive visual stories. It’s the tool of choice here at Taboola for that reason. The free version offers plenty of options, including 37 types of charts and 13 map types, and the ability to animate objects and import data.

Graphics are fully responsive, mobile-optimized, and social media-ready. Infogram offers a WordPress plugin to make publishing easier if that’s your website’s backbone.

Piktochart

Telling a compelling story through data visualizations is easy with Piktochart. With a free account, you can use all of the platform’s functionality, and for a small monthly fee, you’ll get access to lots of templates to help create visualizations and full infographics.

Tableau

Tableau is a more sophisticated tool and a great option if you want to create engaging, interactive graphics. The free version is somewhat limited, but if you are prepared to invest in data visualizations, this tool will pay off pretty quickly.

Tableau allows you to import data from the typical file types and includes built-in visual best practices by default, lightening the creation process. The only downside with Tableau is that visualizations aren’t as easy to share online as some of the other tools on this list.

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Google Charts

Google Charts provides 18 data visualization formats to choose from, including simple designs for pie charts and tree maps. The added benefit is that you can tap into more designs created by community members and customize them to fit your needs.

The only caveat with this free tool is that you need to know at least basic HTML to customize visualizations. The good news? Short online tutorials will help you get started. Interactive designs can easily be embedded into your site through HTML and JavaScript.

Visualize A Data-focused Future

With data becoming more important in all aspects of our lives, it is an essential element for modern storytellers. The way you present it can make the difference between highly appealing content and content that falls flat.

By converting data into visualizations, content creators have a fantastic opportunity to develop engaging stories that audiences will enjoy reading and sharing, which will lead to increased organic traffic and more monetization opportunities.

Want to know more? Get tips and insights with Taboola’s solutions for publishers.

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