What are the most effective data visualization design principles for email marketing?

1 Choose the right chart type

The first step is to select the type of chart that best suits your data and your message. There are many options, such as bar charts, pie charts, line charts, scatter plots, maps, and more. Each one has its own advantages and disadvantages, depending on the type and amount of data you have, the relationships you want to show, and the level of detail you need. For example, if you want to compare proportions, a pie chart might be a good choice. But if you want to show trends over time, a line chart might be more appropriate. The key is to choose the chart that makes your data clear and easy to interpret.

3 Use color strategically

Color is a powerful tool for data visualization, as it can draw attention, create contrast, convey emotion, or highlight patterns. However, it can also be a source of confusion, noise, or bias, if used incorrectly. Therefore, you need to use color strategically and sparingly in your email charts. Some of the best practices are to use a limited and consistent color palette, to avoid using too many colors or shades, to use color to emphasize the most important data points or categories, and to avoid using colors that are hard to see or distinguish, especially for people with color vision deficiencies.

4 Add context and narrative

Data visualization is not just about showing data, but also telling a story. You want your email recipients to understand not only what the data shows, but also why it matters, what it means, and what actions they should take. To do this, you need to add context and narrative to your charts, using elements such as titles, captions, annotations, or callouts. These elements can help you provide relevant background information, explain key findings or insights, highlight interesting or surprising facts, or suggest recommendations or next steps. They can also help you create a connection with your audience, by using a conversational tone, asking questions, or inviting feedback.

5 Test and optimize

Finally, before you send out your email campaign with data visualizations, you need to test and optimize them for different devices, platforms, and scenarios. You want to make sure that your charts look good and function well on various screen sizes, resolutions, browsers, and email clients. You also want to make sure that your charts load fast and don't affect the deliverability or performance of your email. To do this, you need to use tools and techniques such as responsive design, image optimization, alt text, or fallback options, that can help you adapt and improve your data visualizations for email.

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?