What makes a data visualization story effective?

1 Define your goal and audience

Before you start designing your data visualization, you need to have a clear idea of what you want to achieve and who you want to reach. What is the main message or insight you want to convey? What is the context and background of your data? Who are your intended viewers and what are their needs and expectations? By answering these questions, you can tailor your data visualization to suit your purpose and audience.

2 Choose the right format and style

Depending on your goal and audience, you may need to choose different types of data visualization formats and styles. For example, if you want to show trends and patterns over time, you may use a line chart or a bar chart. If you want to compare proportions or categories, you may use a pie chart or a donut chart. If you want to show relationships or correlations, you may use a scatter plot or a bubble chart. You also need to consider the aesthetic aspects of your data visualization, such as colors, fonts, shapes, and icons. You want to use these elements to enhance your data visualization story, not to distract or confuse your audience.

3 Add context and narrative

A data visualization without context and narrative can be hard to understand or interpret. You need to provide some information and explanation that helps your audience to make sense of your data visualization. For example, you can add a title, a subtitle, a legend, a caption, or an annotation to your data visualization. You can also use text, images, audio, or video to create a narrative that guides your audience through your data visualization story. You want to use these elements to highlight your key points, provide evidence, and create emotion.

4 Simplify and focus

One of the common mistakes in data visualization storytelling is to overload your audience with too much or irrelevant data. You need to simplify and focus your data visualization by removing any noise or clutter that may distract or confuse your audience. For example, you can use filters, aggregations, or transformations to reduce the amount of data you show. You can also use contrast, emphasis, or hierarchy to draw attention to the most important or interesting data. You want to use these techniques to make your data visualization clear and concise.

6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?