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PostHog Funnel Analyzer

Find where conversion drops before guessing why users leave

PostHog Funnel Analyzer gives product teams a bounded, aggregate view of funnel friction without exposing person-level data or turning correlation into a product diagnosis.

It queries exact event names through PostHog's read-only Query API, normalizes ordered-funnel steps, compares two explicit date windows, and returns daily event trends. The companion brief identifies the largest observed numeric drop-off but labels it as a measurement, not a reason. It never requests user profiles, session recordings, request properties, or write permissions.

What you can do

  • analyze_funnel — calculate aggregate counts, step conversion, and drop-off
  • compare_funnels — compare the same event sequence across two explicit windows
  • analyze_event_trends — read bounded daily totals for up to ten events
  • build_friction_brief — preserve observations and generate safe validation steps

Who it's for

Product managers, growth teams, founders, analysts, developers validating instrumentation, and agencies improving onboarding or checkout flows.

How to use it

  1. Connect a personal API key with Query Read permission only
  2. Supply two to ten exact event names in their intended order
  3. Choose a bounded date range and conversion window
  4. Compare equal windows before interpreting movement
  5. Validate the largest observed drop with instrumentation, qualitative research, and release context

Getting started

Start with a two-to-five-step funnel over 30 days. PostHog answers where aggregate drop-off was observed; the tool deliberately does not claim why a user left or which product change should ship.

Information

Price
From $0.01
Billing
The final price is shown before running. Failed paid calls do not charge.
Provider
PostHog
PostHog Personal API Key
Personal API key restricted to Query Read permission for the selected project. · Get key
PostHog Project ID
Numeric project identifier whose aggregate product analytics may be queried.
PostHog Host
HTTPS PostHog API origin, such as the US, EU, or an authorized self-hosted instance.

Example workflows

Find the largest observed onboarding drop-off

Measure an aggregate funnel and turn the largest numeric drop into validation steps rather than a guessed cause.

  1. Call `analyze_funnel` with two to ten exact ordered events.
  2. Use `compare_funnels` for an equal previous period and `analyze_event_trends` for daily context.
  3. Pass aggregate steps to `build_friction_brief` before planning instrumentation or user research.

Frequently Asked Questions

What does PostHog Funnel Analyzer measure?

It calculates aggregate counts, step conversion, and drop-off for two to ten exact ordered events over a date range no longer than 90 days.

Does funnel drop-off explain why users leave?

No. The largest numeric drop is an observation, and the tool keeps product cause unknown until instrumentation, qualitative, experiment, and release evidence supports it.

Does the PostHog tool read person profiles or session recordings?

No. It uses aggregate Query API funnels and trends and never requests persons, profiles, identities, session recordings, or person-property breakdowns.

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