Measure multi-step funnels inside experiments
Funnel metrics measure a multi-step journey inside an experiment, such as viewing a product, adding it to a cart, and purchasing. One metric gives you the end-to-end completion rate for each variation. You can expand it to see where units drop off at each step.
Define the journey once
Before this, a funnel in an experiment relied on legacy metrics, where a binomial denominator metric acted as a filter on the numerator. Funnel metrics replace that approach. A funnel metric is a Fact Table metric with an ordered list of steps instead of a numerator:
- Define each step with a Fact Table, row filters, and an optional conversion window.
- Point steps at different Fact Tables in the same Data Source, such as product views in an events table and purchases in an orders table.
- Mark a step optional when skipping it should not block later steps.
Read it in your results
In the results table, the funnel is one row you can expand into a row per step, with each step's conversion rate and lift. Each step uses all exposed units as its denominator, not only units who reached the previous step. The metric's own value is the share of units who reach the last step.
This makes funnel metrics a fit for testing marketing funnels, onboarding flows, and other multi-step experiences. For ad-hoc funnel analysis outside an experiment, use the Funnel Explorer in Product Analytics.
Getting started
Funnel metrics are available on Pro and Enterprise Cloud plans, and on Enterprise when self-hosted. They need a supported data source, and each step's Fact Table must share an identifier with your experiment's assignment data. Funnel metrics don't yet work with Incremental Refresh, and CUPED is off for a funnel and its steps.
- In Metrics, click Add Metric, choose your Data Source, then select Funnel.
- Add at least 2 steps, save the metric, and add it to an experiment.
Follow the funnel metric setup guide for step settings, optional steps, and the API.
