Funnel Analysis
Measuring progression through a sequence, where the largest drop is rarely the biggest opportunity.
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.
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.
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
Principles behind this
The reasoning this solution is an application of.
- Survivorship BiasCognitive bias
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.
- One Long Form or Several Short StepsCase study
- Whether to Require an Account at CheckoutCase study
Short definition
The one-paragraph version, for when that is all you need.
- CohortTerm
- Conversion RateTerm
Related concept
Connected closely enough to change how you apply this.
- OnboardingPattern
- A/B TestingResearch method
- Product AnalyticsResearch method
- Measuring UXWorkflow