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Journey analytics

Every published journey tracks detailed performance metrics. Access them from Engage → Journeys → [journey name].

Dashboard overview

The analytics dashboard shows four KPI cards at the top:

MetricWhat it measures
EnrolledTotal contacts who entered the journey
ActiveContacts currently in-flight (at some step)
CompletedContacts who reached an exit node
ConvertedContacts who hit the journey’s goal event (if configured)

Below the KPIs, a funnel visualization shows the full journey graph with per-step metrics overlaid — how many contacts passed through each node, and where they dropped off.

Step-level metrics

Click any node on the journey canvas to see its metrics:

Trigger node

  • Total entries (over time)
  • Entry rate (entries per day/hour)
  • Re-entry attempts (if re-entry is set to “Ignore”, these are counted but not enrolled)

Send node

  • Messages queued, delivered, bounced, failed
  • Open rate, click rate, reply rate (where applicable)
  • Per-channel breakdown (if the journey has multiple send nodes on different channels)

Wait node

  • Contacts currently waiting
  • Average wait duration
  • For event waits: event-received vs timed-out split

Branch node

  • Distribution across paths (what % went yes vs no)
  • Per-path conversion rate (if a goal is set)

Split (A/B) node

  • Variant distribution (actual vs configured)
  • Winner metric per variant (if winner declaration is enabled)
  • Statistical significance indicator

Exit node

  • Total exits
  • Exit reason breakdown (if labeled)

Conversion tracking

If you defined a conversion goal on the journey:

  • Conversion rate = contacts who hit the goal event / total enrolled
  • Time to convert = median duration from entry to conversion event
  • Revenue attributed = sum of amount property on conversion events

Export

Export journey analytics as CSV from the dashboard. The export includes per-contact data: entry time, current step, exit step, exit reason, conversion status, and revenue attributed.

Tips

  • Compare A/B split variants weekly, not daily — small sample sizes produce noisy results in the first few days
  • Look at exit-reason distribution to identify where contacts are falling off — “Timed out” exits suggest your wait durations are too long
  • Use step-level send metrics to identify underperforming channels — if WhatsApp sends have 90% open rate but email has 20%, consider channel-switching in the branch logic