1. Credibility in visualizations
Trust is integral to data stories. Your message will be ignored if you can't build trust with your audience.
Therefore, credibility in your data story visual displays is key. How can you ensure that your visuals are trusted and not thought to be unreliable?
2. Strive to communicate
Since trust between the data storyteller and the audience is a key ingredient in success, you must strive not just to inform but communicate.
Consider how your data story differs markedly from simply informing someone.
When you inform someone, you merely report something in a clinical, passive manner. You expect the audience to comprehend and interpret data themselves, especially regarding the visualizations.
As a data storyteller, you are guiding your audience on a journey. They must be able to trust their guide! Your data story visuals demonstrate that you have conducted a logical data analysis. You don't want to merely convey what you have created, but communicate through honest thoughts and feelings on the results.
Proper communication means that a message is not only received but comprehended as you intend.
Describe your visuals in a way that affirms what your audience sees. Dual coding matches your written, audible or visual cues in a presentation or paper.
Dual coding leads to trust in your authority to tell the story.
3. Best practices
So what can make visuals as a whole credible?
Two ways to build and maintain credibility and integrity are through consistency and reputation.
If you have consistent design, it is inherently less jarring. Font, colors and design should all match from slide to slide or from page to page.
Remember that your numbers can be used to make important decisions and form strategic opinions, so it's important that they are calculated correctly and reliable.
If you have a teammate that worked on the story and is known as a quantitative expert, consider having her speak or write a section specifically about the visuals.
If time permits, a good way to start would be to introduce yourself, then provide your professional background. Then tell your data story and be sure to ask for questions after you conclude.
Finally, place citations on your slides or published document as needed, especially if your data was derived from sources trusted by your audience.
4. Truncation without causation
So what is important to avoid as you build your visuals?
Avoid a truncated Y-axis. Bar charts use length to display values and enable quick comparisons.
Truncating the y-axis of a bar chart breaks the convention that the difference in the height of the bars is proportional to the difference in values.
Look at these two charts. It is the same data but has two different effects. The chart on the right is honest and starts at zero.
5. At an appropriate interval
Ensure you avoid inconsistent data intervals on charts. Generally, the scale of the graph can differ between axes, such as the one on the left, but within an axis, each interval should represent the same value.
A good rule of thumb to follow when creating trustworthy visualizations is to making them as simple and straightforward as possible.
The three charts on the right show the same data, but only the top chart has consistent X-axis intervals.
6. Let's practice!
Finally, keep everything as simple as possible, so you don't distract the audience from your message. Avoid using too many colors or other design elements.
For now, trust me when I say that practicing these principles by doing the following exercises will improve your data storytelling skills.