Storytelling with Data

1. Understand your audience and context before visualizing data

There is a story in your data. But your tools don't know what that story is. That's where it takes you—the analyst or communicator of the information—to bring that story visually and contextually to life.

Know your audience. Before diving into data visualization, clearly identify who your audience is and what they need to know or do. This understanding shapes every decision you'll make in crafting your message. Consider:

• Who is your specific audience? (e.g., decision-makers, team members, clients)
• What is their level of familiarity with the subject?
• What action do you want them to take after seeing your data?

Clarify your purpose. Determine the key message you want to convey and how your data supports it. Use tools like:

• The "Big Idea": A concise, one-sentence summary of your main point
• The "3-minute story": A brief overview that captures the essence of your message
• Storyboarding: A visual outline of your content to establish structure

By investing time in understanding context upfront, you'll create more focused, impactful data visualizations that resonate with your audience and drive action.

2. Choose the right visual display for your data and message

The answer is always the same: whatever will be easiest for your audience to read.

Match form to function. The type of data you have and the story you want to tell should guide your choice of visual display. Consider these common options:

• Tables: Best for precise, lookup values or mixed units of measure
• Line graphs: Ideal for showing trends over time
• Bar charts: Excellent for comparing categories
• Scatterplots: Useful for showing relationships between variables

Avoid unnecessary complexity. Simpler charts are often more effective:

• Limit the use of pie charts, as they can be difficult to interpret accurately
• Avoid 3D effects, which can distort data perception
• Be cautious with dual-axis charts, as they can be confusing

Remember that your choice of visual should make it easier for your audience to grasp the key information quickly. If you're unsure, test different options with colleagues to see which one communicates most clearly.

3. Eliminate clutter to enhance clarity and focus

Because it makes our visuals appear more complicated than necessary.

Simplify ruthlessly. Every element in your visualization should serve a purpose. Identify and remove anything that doesn't directly contribute to understanding:

• Gridlines (or make them very light)
• Redundant labels
• Excessive decimal places
• Ornamental graphics or borders

Use white space strategically. Don't feel compelled to fill every inch of your canvas. White space:

• Helps direct attention to important elements
• Makes your visualization feel less overwhelming
• Improves overall readability

Emphasize through de-emphasis. Instead of making important elements stand out, try muting everything else. This can be a more subtle and effective way to guide your audience's focus.

By decluttering, you reduce the cognitive load on your audience, allowing them to more quickly and easily grasp the key insights from your data visualization.

4. Use preattentive attributes to guide attention effectively

If we use preattentive attributes strategically, they can help us enable our audience to see what we want them to see before they even know they're seeing it!

Leverage visual cues. Preattentive attributes are visual properties that our brains process almost instantaneously, before conscious attention. Use them to highlight key information:

• Color: Use sparingly to draw attention to important data points
• Size: Make critical elements larger
• Position: Place important information where the eye naturally looks first (often top-left)
• Shape: Use distinct shapes to differentiate categories

Create visual hierarchy. Combine preattentive attributes to guide your audience through the information in a specific order:

1. Primary focus: Use the strongest visual cues
2. Secondary information: Apply more subtle differentiation
3. Context: Keep supporting details visible but de-emphasized

Be intentional with color. Color is a powerful tool, but overuse diminishes its impact:

• Choose a single accent color for emphasis
• Use color consistently throughout your visualization
• Consider colorblind-friendly palettes

By strategically applying preattentive attributes, you can direct your audience's attention and create a clear visual path through your data story.

5. Apply design principles for accessible and aesthetic visuals

Form follows function.

Prioritize accessibility. Ensure your visualizations are easily understood by a wide audience:

• Use clear, legible fonts
• Provide sufficient contrast between text and background
• Include descriptive titles and labels
• Avoid relying solely on color to convey information

Create visual appeal. Aesthetically pleasing designs are perceived as easier to use and more credible:

• Align elements to create a sense of order
• Use consistent styling (fonts, colors, spacing) throughout
• Balance white space and content

Consider your medium. Adapt your design for different formats:

• Presentations: Simpler visuals with less text
• Reports: More detailed visualizations with supporting explanations
• Interactive dashboards: Allow for exploration while guiding key insights

Remember that good design should feel effortless to the viewer. If your audience is focusing on the design itself rather than the content, you may need to simplify further.

6. Craft a compelling narrative to bring your data to life

Stories resonate and stick with us in ways that data alone cannot.

Structure your story. Use classic storytelling elements to engage your audience:

1. Beginning: Set the context and introduce the problem
2. Middle: Present your data and analysis
3. End: Conclude with insights and call to action

Create tension. Highlight the gap between the current situation and a desired outcome to maintain interest:

• What problem does your data address?
• Why should your audience care?
• What could be improved or changed?

Use narrative techniques:

• Repetition: Reinforce key points
• Analogies: Make complex concepts relatable
• Specific examples: Bring data to life with real-world applications

Remember, your data should support your story, not be the story itself. Focus on the "so what" – why the information matters and what actions it should drive.

7. Iterate and seek feedback to refine your data story

There is incredible value in getting a fresh perspective when it comes to communicating with data in general.

Embrace iteration. Your first attempt is rarely your best. Plan time for multiple revisions:

• Create quick drafts to explore different approaches
• Step away and return with fresh eyes
• Be willing to start over if a new idea proves more effective

Seek diverse feedback. Different perspectives can uncover blind spots and improve clarity:

• Colleagues familiar with the subject matter
• People outside your field (to test general understanding)
• If possible, members of your target audience

Test comprehension. Ask reviewers specific questions:

• What do you think the main message is?
• What questions do you have after seeing this?
• What would you do differently based on this information?

Use the insights gained from feedback to refine your visualization and narrative. Remember that the goal is effective communication, not perfection. Continuous improvement through iteration will help you develop stronger data storytelling skills over time.

Last updated: July 21, 2024