# Funnel > People move through steps and the viewer needs to see where they leave. - Canonical: https://patterns.konigi.com/dashboards/funnel - Group: Visual representation - Level: implementation - Status: published - Updated: September 10, 2026 - Also called: conversion funnel, step drop-off --- ## Problem Ten thousand people started signing up and four hundred finished. The viewer needs to know which step lost the other nine thousand six hundred, because that step is the only thing worth working on. ## Solution One bar per step, ordered by sequence, each showing how many reached it. The shape falls away left to right and the biggest single drop is the finding. Two numbers per step do most of the work, and showing only one is the most common mistake. **Step conversion** is the percentage who moved from the previous step to this one. **Overall conversion** is the percentage of the original population still present. A step converting at 91% looks healthy until you notice it sits after four other steps and only 12% of the original cohort ever reached it. The definitional questions matter more than the chart, and they are the ones that get skipped. **Is the sequence real?** A funnel imposes an order. If people can skip a step, do them out of order, or arrive mid-sequence, the chart is describing a path that only some of them took while implying all of them did. **What is the window?** Somebody who started on Tuesday and converted on Friday either counts or doesn't. Fixed-window funnels understate conversion for anything with a long consideration period; unbounded ones overstate it and never settle. **Is it the same people?** Counting distinct users per step, independently, produces a chart where a later step can exceed an earlier one and nobody notices for a quarter. The traditional tapered-shape rendering is worth avoiding, incidentally. It encodes quantity as a trapezoid's area, which reads less accurately than length, for no gain but the metaphor. Plain horizontal bars are easier to compare and easier to label. ## Use when The sequence is genuinely ordered and mandatory, the population is large enough for percentages to mean something, and someone owns improving a step. ## Don't use when The path is a graph rather than a line. If people arrive from several entry points and take different routes, a funnel picks one story and hides the rest—that is what the Sankey pattern is for. ## Trade-offs Funnels flatten time, so a drop-off that appeared last Tuesday looks identical to one that has always been there. They flatten segments too: one funnel over all traffic averages a mobile disaster with a desktop success. The biggest bar-to-bar drop attracts all the attention, which is right when the steps are equally improvable and wrong when the big drop is an intentional qualifying step. And a funnel is a claim about intent—everyone who entered wanted to finish—which is frequently untrue at the top. ## Checklist - Is the step order real and mandatory, or imposed on a messier reality? - Is both step conversion and overall conversion shown? - What is the conversion window, and does it suit the decision cycle? - Is this the same set of people at each step, or independently counted? - Can someone enter mid-funnel, and where do they appear? - Is the funnel segmented, or is one number averaging incompatible populations? - Does anything show whether a drop-off is new or long-standing? - Is the biggest drop actually the most improvable one? - Are the counts shown, not only the percentages? - Is quantity encoded as length rather than as a tapered area? ## Compare **Amplitude** and **Mixpanel** made this the centrepiece of product analytics, with conversion windows, segmentation and step reordering as first-class controls, which is what turns a static chart into an analysis tool. **Google Analytics** ships a goal-funnel view built on session-scoped steps, which is why its numbers so often disagree with a product-analytics tool measuring the same flow on user scope. **Grafana** has no funnel panel and teams approximate it with a sorted bar chart, which works and loses the step-conversion arithmetic that makes the pattern useful. **Sentry** inverts the framing entirely, measuring where sessions fail rather than where they convert, which answers the same "where do we lose people" question from the error side. ## Related Sankey and path is what to use when the route branches rather than narrowing. Cohort grid answers the time question a funnel flattens. Ratio and rate covers the denominator problem, which is the funnel's central hazard. Stacked composition is the other way to show part-to-whole. Compare periods is how you tell a new drop-off from an old one. ## Examples ### Tableau Public (Salesforce) Thousands of dashboards made by people who are not designers, published without a review step. The best available sample of what the pattern language looks like in the wild. **User Funnel & Conversion Rates** — captured September 11, 2026, Tableau Public embed view; workbook published by Tetiana Berezhna. analytical, medium density, light theme, desktop-web. Another published workbook rather than anything Tableau designed, and it makes both of the mistakes the funnel entry names. It shows one number per step, not two. The labels down the right read CVR 100%, 74%, 55%, 37%, 23%, 7%, and every one of those is overall conversion—the share of the original 8,460 still present. Step conversion is missing, which matters because the worst step in this funnel is invisible: 1,948 people start a trial and 577 pay, so that step converts at 30%, and nothing on the chart says 30. You have to divide two numbers printed four inches apart. The second is the rendering. It is drawn as a taper, so quantity is encoded as the width of a trapezoid, and the eye compares areas rather than lengths. Plain horizontal bars would have been easier to read and easier to label. The panel on the left has a third problem: a 20% conversion rate sits above a bar of 10 registrations, next to a 26% rate over 3,673, at the same size and in the same grey. Hotspots in this capture: - [Funnel](https://patterns.konigi.com/dashboards/funnel) *(this pattern)* — Drawn as a taper, so the count is the width of a trapezoid. Length would have read more accurately for nothing. - [Funnel](https://patterns.konigi.com/dashboards/funnel) *(this pattern)* — Overall conversion only. The trial-to-payment step converts at 30% and no number on the chart says so. - [Ratio and rate](https://patterns.konigi.com/dashboards/ratio-and-rate) — A 20% rate over 10 registrations drawn the same size as a 26% rate over 3,673. - [Header KPI strip](https://patterns.konigi.com/dashboards/header-kpi-strip) — Three counts, boxed and centred, with no delta and no base. The first and last are the funnel's own endpoints. - [Tabs as genres](https://patterns.konigi.com/dashboards/tabs-as-genres) — Seven worksheet tabs across the top, named after the data rather than the question—Users : Registration, CVR to Start of Trial. ## Related patterns - [Sankey and path](https://patterns.konigi.com/dashboards/sankey-and-path) — Quantity flows from sources to destinations and the viewer needs to see the split. - [Cohort grid](https://patterns.konigi.com/dashboards/cohort-grid) — Retention differs by when people arrived; the viewer needs cohorts side by side over time. - [Ratio and rate](https://patterns.konigi.com/dashboards/ratio-and-rate) — A raw count misleads; the viewer needs it normalized by a denominator they understand. - [Stacked composition](https://patterns.konigi.com/dashboards/stacked-composition) — A total is made of parts, and the viewer needs both the total and the mix over time. - [Compare periods](https://patterns.konigi.com/dashboards/compare-periods) — Today's line means nothing without last week's line under it. ## Sources - [Funnel chart](https://en.wikipedia.org/wiki/Funnel_chart) - [Grafana, Bar chart panel](https://grafana.com/docs/grafana/latest/visualizations/panels-visualizations/visualizations/bar-chart/) - [Bach et al., Dashboard Design Patterns](https://dashboarddesignpatterns.github.io/patterns.html) --- Screenshots on patterns.konigi.com are reproduced for commentary and criticism. 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