How do you justify your data visualizations to clients and managers?

1 Know your audience

Before you create or present any data visualization, you need to understand who your audience is, what they care about, and what they expect from you. Different audiences may have different levels of familiarity with data, different preferences for visual styles, and different goals and questions. To justify your data visualizations, you need to tailor them to your audience's needs and interests, and explain how they address their challenges and opportunities.

2 Choose the right chart type

One of the most important decisions you have to make as a data visualizer is what type of chart to use for your data. There are many factors to consider, such as the number and type of variables, the relationship and distribution of data, and the message and purpose of the visualization. To justify your data visualizations, you need to choose the chart type that best suits your data and your story, and avoid misleading or confusing charts that may distort or obscure the data.

3 Apply design principles

Data visualization is not only about data, but also about design. How you design your visualizations can have a significant impact on how your audience perceives and interprets them. To justify your data visualizations, you need to apply some basic design principles, such as contrast, alignment, hierarchy, balance, and consistency. These principles can help you create visualizations that are clear, attractive, and easy to understand.

4 Add context and annotations

Data visualization is not enough by itself, it also needs context and annotations to provide meaning and guidance to your audience. Context and annotations can include titles, labels, legends, scales, sources, notes, and explanations that help your audience understand what the data is, where it comes from, how it was collected and analyzed, and what it implies. To justify your data visualizations, you need to add context and annotations that are relevant, accurate, and concise.

5 Tell a story

Data visualization is not only about showing data, but also about telling a story. A story can help you engage your audience, convey your message, and persuade your audience to take action. To justify your data visualizations, you need to tell a story that is relevant, compelling, and credible. A story can have a structure, such as a beginning, a middle, and an end, or a problem, a solution, and a call to action. A story can also have elements, such as characters, conflicts, emotions, and surprises.

6 Get feedback and iterate

Data visualization is not a one-time process, but a continuous one. You can always improve your visualizations by getting feedback and iterating on them. Feedback can come from your audience, your peers, your mentors, or yourself. Feedback can help you identify strengths and weaknesses, opportunities and threats, and gaps and errors in your visualizations. To justify your data visualizations, you need to get feedback and iterate on them until you achieve your desired results.

7 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?