How to create clear, useful data visualizations

What is data visualization?

Data visualization is the process of turning numbers, patterns, and trends into visual formats like charts, graphs, and infographics to increase comprehension. It’s not just about an aesthetically pleasing visual representation of data; it’s about making information easier to understand, compare, and act on.

Visualizing your data helps your audience quickly grasp the point. A study by MIT found that visualization “speeds up decision‑making…our brains can process images we’ve seen for as few as 13 milliseconds.” It also allows you to spot insights that may otherwise be buried in a spreadsheet or report.

Why do small businesses need data visualization?

Large companies aren’t the only ones to enjoy the benefits of data visualization. Small teams can also use visualization to save time, build trust, and make faster decisions. In fact, 77 percent of organizations reported improved decision-making thanks to data visualization methods.

Here’s why a visual representation of data matters:

• Clarity: Visuals simplify complex ideas
• Focus: Highlights what matters most
• Engagement: Keeps your team or audience interested
• Efficiency: Speeds up meetings and presentations
• Alignment: Helps everyone get on the same page faster

You probably already have ways to visualize data without realizing it, like when you add a chart to a pitch deck or track performance in a dashboard.

How do you make a data visualization plan?

Here is a breakdown of the seven essential steps that shape an effective data visualization plan.

Step 1: Know your goal

Start by defining why you’re creating the visual. What do you want people to learn or do after seeing it?

Some data visualization examples:

• Compare performance over time
• Show progress toward a goal
• Explain a process or customer journey
• Highlight areas of improvement
• Make a case for change or investment

Being clear about the purpose helps you choose the right format and layout.

Step 2: Know your audience

Think about who you’re showing the data to. A report for your internal team may look different than one for an investor, customer, or partner.

Ask:

• What does this group already know?
• What do they care about most?
• How much detail is helpful vs. distracting?

Your audience determines how you visual the data. A busy owner may only need a headline and one simple graph. A technical advisor might want to see the raw data behind the chart.

Step 3: Choose the right chart type

Different types of data visualization are designed for different types of stories and audiences. Use the format that best supports your message.

Common data visualization chart types:

• Bar chart: Best for comparisons across categories
• Line chart: Useful for showing trends over time
• Pie chart: Shows proportions or parts of a whole (use sparingly)
• Scatter plot: Great for showing correlation between two variables
• Map: Good for showing location-based patterns
• Table: When you need precise values

If you’re not sure which chart type fits, think about what question your chart should help answer.

Step 4: Keep it simple and focused

The most common mistake in data visualization is overcomplicating it. You don’t need to show everything at once. A clear visual makes a single point well.

Tips:

• Limit the number of variables per chart
• Use color to highlight — not to decorate
• Avoid unnecessary 3D effects, shadows, or animations
• Label clearly but keep text minimal

If someone can’t understand your visual in five seconds, it may be too busy.

Step 5: Use consistent formatting

Your charts should be easy to scan and compare. Use a consistent layout across slides or reports to avoid confusion.

Consider using:

• Same font and size throughout
• Aligned chart titles and legends
• Matching color scales or themes
• Consistent axis labels and units

If you're building a dashboard or report with multiple visuals, use the same structure throughout.

Step 6: Add context and interpretation

A chart is only helpful if people know what to do with it. Don’t just show the data; help people understand what it means.

Include:

• A brief explanation above or below the chart
• Clear headings or subheadings
• Highlights or annotations to call out patterns
• Arrows, lines, or bold text for key takeaways

Example: “Sales increased 22 percent in Q2, driven by new product line.”

You can also include a short conclusion or next step below the visual to guide action.

Step 7: Test and improve

Before sharing your visual widely, test it. Show it to one or two people who weren’t involved in making it.

Ask:

• What do you think this is showing?
• Is anything confusing or missing?
• Would you change anything?

Use that feedback to make small adjustments. Over time, your visuals will get sharper and more effective.

Data visualization best practices

A strong visual helps your audience grasp the message quickly and makes it stick. In fact, studies show that individuals retain 80 percent of visual information, compared to just 20 percent of written text.

For best results:

• Focus on one message per visual
• Use simple and familiar chart types
• Highlight trends or changes, not just raw values
• Avoid clutter — less is more
• Always label your axes, units, and key data points
• Match the chart to the purpose (e.g., show a trend, make a comparison, or highlight a risk)
• Stay consistent with branding if visuals are external

Quick data visualization checklist

Use this checklist when preparing visuals for reports, presentations, or updates:

✅ Identify the purpose of the visual
✅ Select the right chart type
✅ Keep the design clean and focused
✅ Use clear, readable labels
✅ Highlight key insights
✅ Add context or next steps
✅ Test the visual with a fresh set of eyes