Your Chart Is Excluding People
About 300 million people worldwide have some form of color vision deficiency. Another 2.2 billion have a vision impairment. When you make a pie chart that relies entirely on red vs. green slices, or a bar chart with light gray labels on a white background, you're cutting a significant chunk of your audience out of the conversation.
Accessible data visualization isn't a nice-to-have checkbox. It's the difference between a chart that communicates to 100% of your audience and one that only works for 92%. The fixes are straightforward, they make your charts better for everyone, and most of them take under a minute.
This guide covers the practical steps: color contrast ratios, colorblind-safe palettes, text alternatives, and how to test your work before publishing.
Color Contrast: The Numbers That Matter
WCAG 2.1 requires a contrast ratio of at least 4.5:1 for normal text and 3:1 for large text (18px+ or 14px bold). For non-text elements like chart bars, lines, and pie slices, the requirement is 3:1 against adjacent colors. That means a light blue bar on a white background needs enough contrast to be distinguishable — and most default chart color schemes fail this test.
Check your numbers. White (#FFFFFF) against light gray (#D1D5DB) has a contrast ratio of 1.8:1 — that fails. White against medium gray (#6B7280) hits 4.6:1 — that passes. The difference between a readable chart and an inaccessible one is often just one shade darker.
Use the contrast checker to test your color combinations instantly. Paste in your background color and your data color, and it shows the exact ratio plus pass/fail for WCAG AA and AAA standards. Do this before you finalize any chart palette.
Colorblind-Safe Palettes
The most common color vision deficiency is deuteranomaly (red-green), affecting roughly 6% of men. A chart that distinguishes categories using red and green is unreadable for this group — both colors collapse into a muddy brownish-yellow.
Safe combinations that work for nearly everyone: blue and orange, blue and red, purple and yellow, dark blue and light blue. These pairs maintain distinct hues across all three types of color vision deficiency.
A useful rule: if your chart still makes sense when converted to grayscale, it works for colorblind users. If two categories become indistinguishable, you need more luminance contrast between them — not just different hues, but different lightness levels. For more on choosing palettes, see color psychology infographics.
Beyond Color: Redundant Encoding
The single most impactful accessibility practice is never using color as the only way to convey information. If a line chart uses a red line for "costs" and a blue line for "revenue," add a second encoding: make one solid and one dashed.
This principle is called redundant encoding, and it solves more accessibility problems than any other technique. It helps colorblind users, users with low-contrast displays, people viewing your chart on a grayscale printout, and anyone looking at a projected version in a bright conference room.
Direct labeling — putting the category name right next to the data element — is the simplest form of redundant encoding. Label each pie slice instead of relying on a color-coded legend. Put the value on top of each bar. See data visualization best practices for more on reducing chart clutter.
Text Alternatives and Screen Readers
A chart image without alt text is completely invisible to screen reader users. Every chart image needs alt text that conveys the same information a sighted user gets from looking at the chart.
Good alt text follows a pattern: chart type, what it shows, the key finding. Example: "Bar chart showing quarterly revenue for 2025. Q4 revenue was $4.2M, up 38% from Q3 and the highest quarter on record." That's 25 words and it communicates the takeaway.
For complex infographics with multiple charts, provide a structured text summary below the image. This serves both screen reader users and search engines — infographic text is invisible to crawlers, but a written summary is not.
Testing Your Visualization
Three tests catch 90% of accessibility issues. First: the grayscale test — convert your chart to grayscale and check that every data category is distinguishable. Second: the squint test — view at 50% zoom and squint. If labels disappear, increase font size and line weight.
Third: the screen reader test. For static infographic images, run your image through a screen reader (VoiceOver on Mac, NVDA on Windows) and confirm the alt text makes sense.
The contrast checker on GraphMake gives you instant pass/fail results for any color pair you're considering.
Make Your Next Chart Accessible
Accessible data visualization is not extra work — it is better design. Higher contrast, direct labels, text alternatives, and colorblind-safe palettes all make charts better for everyone.
Start with the contrast checker to audit your current palette. Then open the editor, apply a colorblind-safe palette, add direct labels, and export.
