See how many people enter a flow — and where they drop off.
Fix (and find) drop-offs
Identify where users fall out of a funnel, so you can make improvements where it really matters.
Powerful filtering
Filter by user cohorts, specify a strict sequence of steps, or allow events to be tracked in any order.
Correlation analysis
Understand the properties and previous behaviors that successful or unsuccessful users have in common.
How do PostHog Funnels compare?
Swipe right to compare.
Amplitude | Mixpanel | Heap | Pendo | PostHog | |
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Product analytics | |||||
Funnels | |||||
Conversion funnels | |||||
Historical trends | |||||
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Sequential step order | |||||
Strict step order | |||||
Any step order | |||||
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Reveal user paths between steps | |||||
Anomaly detection | |||||
Filter internal and test users | |||||
Filter by cohort | |||||
Filter by user property | |||||
Breakdown by user property | |||||
Correlation analysis |
“We observed drop-offs at very particular stages of our onboarding flows, as a result, we took several actions such as moving these steps further down the funnel. These changes helped us deliver a 10-20% improvement in our conversion rate.”
Instant realtime GraphQL APIs
Rikin KachhiaSoftware Engineer, Hasura
Funnels documentation
- Why do funnels matter?
- What can you learn from funnels?
- Getting started
- Setting up a funnel
- Saving a funnel
- Modifying a funnel
- Analyzing Funnels
- Understand where people are getting stuck during your flow
- Find out who is successful and who is not
- Identify the steps which have the highest friction and time to convert
- Identify possible causes of failure and success
- Understand how your changes are improving your flow
- Choosing breakdown property behaviour
- First touchpoint
- Last touchpoint
- Specific step
- All steps
- Understand seasonality in your conversion rates
- Refining your funnel to filter out noise
- Correlation analysis
- Further reading