WebToolArcHow to read this chart
A funnel is meaningful when rows are ordered stages of the same process.
Before publishing
The publication review flags stage increases and missing values so decreasing area is not mistaken for a precise conversion model.
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Funnel Chart Maker
Use a funnel when stages have a meaningful order and drop-off; do not use area alone to imply precision when a bar chart would compare values more honestly.
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—Rows / flows
—Structure
—Data check
Data readiness & publication review
Reviewing…Check the data before you export
Review the source structure, chart-specific interpretation risks and a copyable accessible summary. The chart itself remains the primary workspace above.
Findings
Accessible chart summary
Reviewing the current data…
This review checks structure and common interpretation risks; it does not prove that the source data, measurement method, denominator, units or conclusion are valid.
Core data-to-chart workflows
Start with Graph Maker or CSV Chart Maker, then use a focused chart type when the visual question changes. Keep source data and export evidence connected instead of treating a rendered picture as the only record.
Graph MakerGeneral pasted-data chart workspaceLine Graph MakerOrdered change and multi-series trendsBar Graph MakerCategory comparison and sortingPie Chart MakerParts of one meaningful totalScatter Plot MakerX/Y relationships and trendlineGantt Chart MakerTask schedules across datesRadar Chart MakerMulti-axis profile comparisonCSV Chart MakerCSV/TSV import and chart switching
Practical guide and verification
Keep stages in the real process order
A funnel implies progression through an ordered sequence. Sort stages according to the actual workflow rather than largest-to-smallest value unless those happen to be the same, otherwise the visual can invent a progression that the underlying data never had.
Interpret conversion rates with the denominator visible
Stage-to-stage conversion uses the previous stage as its denominator, while overall conversion uses the first stage. Keep those definitions separate so a 50% stage conversion is not mistaken for 50% of the original population.
Investigate increases instead of forcing a funnel shape
Later stages can legitimately exceed earlier stages when records re-enter, cohorts differ or the measurements are not one closed pipeline. Treat an increase as a data-model signal and explain it rather than hiding it by sorting or clipping values.
Keep source counts beside percentages
Percentages make stages comparable, but absolute values reveal scale. A dramatic-looking percentage drop from a tiny cohort may be less important than a modest percentage drop from a much larger stage, so preserve both in reports when possible.
Use the exported chart with a text summary
SVG and PNG are useful presentation formats, but an accessible report should also describe the important stage values and drop-offs in text. Keep the source data or generated summary available so the chart is not the only record of the numbers.