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Plate RES·011 · Research methodGrid H1 · Rev. 2026-08-14

Funnel Analysis

Measuring progression through a sequence, where the largest drop is rarely the biggest opportunity.

Research methodCraft conventionIntermediate

Definition

A funnel measures how many users complete each step of a defined sequence. It localises where people leave, and it is systematically blind to the people who never entered.

Craft convention. True because the industry converged on it. Breaking it costs familiarity, not correctness.

On this plate
  1. 1Definition
  2. 2Reading a funnel properly
  3. 3Building one that answers something
  4. 4In practice
  5. 5Commonly confused with
  6. 6Local chart
  7. 7Continue from here

Reach for this when

  • Diagnosing conversion problems.
  • Prioritising work in checkout, signup or onboarding.
  • A conversion target has moved and nobody can say which stage is responsible.

Common mistakes

  • Ignoring the top of the funnel.
  • Optimising the largest percentage drop by default.
  • Aggregating across segments with different behaviour.
  • Ignoring the people who never entered the funnel, who are invisible to it by construction.

Reading a funnel properly

  • Measure the top of the funnel, not just the steps inside it. The biggest loss is often before step one.
  • Compare the drop at each step to a reasonable baseline. Some drop is expected and normal.
  • Segment by source, device and cohort. A funnel that looks healthy overall often hides one segment failing badly.
  • Look at where people go instead, not only that they left.
  • Distinguish abandonment from deferral. Someone who returns tomorrow is not lost.

Building one that answers something

  1. 1

    Define the steps from the user's goal

    Not from the page structure. Two screens that serve one intention are one step.

  2. 2

    Set the window

    A funnel over one session and a funnel over thirty days describe different products. State which one you built.

  3. 3

    Segment the funnel, not just the total

    New against returning, mobile against desktop, paid against organic. The aggregate usually hides two opposite stories.

  4. 4

    Weigh drop by volume, not by percentage

    A ten percent loss at the top can outweigh a sixty percent loss near the bottom. Convert every step to people before prioritising.

  5. 5

    Look outside the funnel for the cause

    The step where people leave is rarely the step that caused it. The damage is often done one screen earlier, by a price, a requirement or a promise.

In practice

  1. i.

    The step that was working correctly

    Misreading a drop

    A large drop at delivery options turned out to be people discovering the shipping cost. The step was doing its job. The problem was that the cost had not been mentioned anywhere earlier, and fixing the step would have changed nothing.

Commonly confused with

Close neighbours that get substituted for each other. The difference is stated first, then the condition that picks one over the other.

vs.

Product Analytics

Research method

Event data covering what people do across the product, aggregated.

Key difference

Analytics is the whole record of behaviour in the product. A funnel is one view of it: completion across a defined sequence. The funnel is the sharper tool and the blinder one, because it cannot see anyone who never entered it.

Use Funnel Analysis when

  • The steps are known, ordered and worth improving.
  • The question is where people drop out of a specific flow.
  • You will also account for the people who never started.

Use Product Analytics when

  • You do not yet know which sequence is the problem.
  • The question spans behaviour, retention or feature use.
  • You need to find where to look before measuring a path.

Learn about Product Analytics

Local chart

RES·011 · Region IV · Grid H1

This entry and the entries it is stated to connect with. Each line is labelled with what the connection means.

Survivorship BiasBIAS·010 · PRINCIPLES BEHIND THISJourney MapTPL·004 · OFTEN USED WITHAmplitudeTOOL·023 · OFTEN USED WITHFullStoryTOOL·027 · OFTEN USED WITHHotjarTOOL·026 · OFTEN USED WITHMixpanelTOOL·024 · OFTEN USED WITHPostHogTOOL·025 · OFTEN USED WITHProduct AnalyticsRES·010 · COMMONLY CONFUSED WITHOne Long Form or Several Short StepsCASE·009 · PRACTICAL EXAMPLEWhether to Require an Account at CheckoutCASE·001 · PRACTICAL EXAMPLEEcommerce ChecklistCHK·006 · CHECK YOUR WORKCohortTERM·101 · SHORT DEFINITION

Continue from here

Each link says what the connection is, so you can tell a principle from an alternative from a thing people mix this up with.

Applies when you are designing

A CheckoutA FormAn Ecommerce ExperienceAn Onboarding FlowAuthentication

Principles behind this

The reasoning this solution is an application of.

Often used with

These usually appear in the same screen or the same decision.

Practical example

A worked decision where this was the deciding factor.

Check your work

Review passes that test whether this was done properly.

Short definition

The one-paragraph version, for when that is all you need.

Related concept

Connected closely enough to change how you apply this.