Describe your data and get a clean pareto chart in seconds, with descending bars, a cumulative percentage line, and the 80% threshold marked. Perfect for quality analysis, root-cause work, and business reporting.
Browse pareto charts made with Figviz, or generate your own above
A textbook-style pareto chart with sorted bars, a dual-axis cumulative line, and the vital few causes highlighted.
A quality-control pareto chart identifying the vital few defect types that account for 80% of failures.
A pareto chart pinpointing the top complaint categories driving 80% of customer dissatisfaction.
A sales pareto chart revealing which product categories generate 80% of total revenue.
A detailed pareto chart with both y-axes labeled and cumulative percentage values annotated on the line.
A Six Sigma DMAIC pareto chart used to prioritize process improvement efforts by defect frequency.
Start with one of these examples, then adapt the subject, labels, data, or layout for your own use.
A textbook-style pareto chart with sorted bars, a dual-axis cumulative line, and the vital few causes highlighted.
Create a classic labeled pareto chart for general defect data. Show 6 descending bars (tallest to shortest), a cumulative percentage line on a right y-axis from 0% to 100%, a dashed horizontal 80% threshold line, and labeled category names on the x-axis. Classic black-on-white textbook style, readable fonts. White background.
A quality-control pareto chart identifying the vital few defect types that account for 80% of failures.
Create a pareto chart for manufacturing defect root causes: Surface scratch (120), Dimension error (85), Weld defect (60), Missing component (35), Labeling error (20), Other (10). Descending bars, cumulative percentage line, 80% threshold dashed, axes labeled "Defect Count" and "Cumulative %". Classic style. White background.
A pareto chart pinpointing the top complaint categories driving 80% of customer dissatisfaction.
Create a colorful pareto chart for customer complaint categories: Late delivery (45), Wrong item (30), Damaged packaging (15), Poor quality (8), Billing error (5), Other (3). Show descending colored bars, a cumulative percentage line on the right y-axis, an 80% threshold dashed line, and labeled axes. White background.
A sales pareto chart revealing which product categories generate 80% of total revenue.
Create a pareto chart for annual sales by product category: Electronics ($420K), Furniture ($280K), Apparel ($150K), Sporting Goods ($90K), Toys ($55K), Books ($30K). Descending bars in a gradient blue palette, cumulative revenue percentage line on the right axis, 80% threshold marked, all axes labeled. White background.
A pareto chart maker is a tool that builds a combined bar-and-line chart that ranks your categories from most to least frequent, then overlays a cumulative percentage line so you can see at a glance which few causes account for 80% of the problem. The chart is named after economist Vilfredo Pareto and the 80/20 rule he observed. With Figviz you describe your data in plain language and get a fully labeled pareto chart in seconds, without touching a spreadsheet or charting library.
The core insight behind a pareto chart is the 80/20 rule: roughly 80% of effects come from 20% of causes. The cumulative percentage line makes this visible. As bars are plotted left to right in descending order, the line climbs steeply at first (the vital few) and then flattens as smaller contributors are added (the trivial many). The point where the line crosses the 80% mark divides the categories you should focus on from those with diminishing returns. This makes pareto charts a standard tool in quality control, Six Sigma, and business analysis.
Include numeric counts for each category in your prompt so the bars are sized accurately. Give the chart a descriptive title (for example "Customer Complaint Types, Q1 2026") to make it self-explanatory when shared. If you have an "Other" category, keep it last even if it is large, because it bundles unrelated items and would distort the analysis if placed first. For quality-engineering contexts, mention that you want the left y-axis labeled with frequencies and the right y-axis with cumulative percentages, so reviewers can read both scales.
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