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User Path Analysis

User Path Analysis (also known as Journey Analysis) helps you understand how users navigate through your product. You pick one anchor event and walk outward from it - either Forward to see what users did next, or Backward to see what led them there. The result is a flow diagram plus supporting tables that reveal common journeys, unexpected detours, and opportunities for optimization.

Accessing Path Analysis​

Navigate to Analytics → User Paths from the sidebar. The page header reads User path analysis.

Analysis Direction​

Direction is the first choice you make, and it changes the rest of the page - the event field label and its hint follow the direction you pick.

Forward​

Start from an anchor event and see where users went afterwards. The event field is labelled Starting event.

Use cases:

  • After signup, what do users do next?
  • After viewing pricing, what happens?
  • What paths lead out of a key action?

Backward​

Start from a target event and trace back how users got there. The event field is labelled Ending event.

Use cases:

  • How do users reach the purchase page?
  • What leads to support ticket creation?
  • What paths precede churn?

The Config Bar​

All controls live in a single config bar at the top of the page.

ControlWhat it does
DirectionForward or Backward (see above).
Starting / Ending eventThe anchor event. The label follows the direction.
Max stepsHow far to walk from the anchor: 4, 6, 8, or 10 steps.
Hide paths belowA single percentage threshold - the minimum % of users a path must represent to be shown.
Collapse repeated eventsView toggle - collapses runs of the same event into one segment.
Show where users exitView toggle - draws where users' paths ended.

Hide paths below (percentage threshold)​

Rare paths add noise. Instead of an absolute count, you set a single percentage floor - for example, hide any path taken by fewer than 1% of users. Because it is relative, the same setting stays sensible whether you are looking at hundreds of users or millions - it scales with your traffic instead of needing to be re-tuned every time volume changes.

What re-runs vs. what is instant​

Most controls change which data is analysed, so they re-run the query when you click Analyze paths: Direction, the anchor event, Max steps, and Hide paths below.

Two options are pure view toggles and apply instantly, with no re-run: Collapse repeated events and Show where users exit. Flip them freely to reshape what you are already looking at.

KPI Row​

Once an analysis runs, a row of key numbers sits above the diagram:

  • Users in analysis - how many users are included.
  • Unique paths - how many distinct paths were found, with a note reading "N above X% shown" so you know how many cleared the visibility threshold.
  • Avg path length - the average number of steps per path.
  • Repeat events % - the share of steps that simply repeat the previous event. This is often the most revealing number on the page: a high value means users are looping on the same action rather than progressing.

The Flow Diagram​

The flow diagram is the heart of the page. It reads left to right (Forward) or right to left (Backward), one column per step.

Colour follows the event, not the step​

Every event keeps one colour everywhere it appears. If add_to_cart is teal at step 2, it is teal at step 5 too. This lets you follow a single event across the whole diagram at a glance, and a colour legend below the diagram maps each colour to its event name.

Nodes​

Each node is a bar whose length is proportional to the number of users at that point, with the full event name and the user count shown beside it. Wider bar, more users.

Exit bands​

When Show where users exit is on, each node emits a dashed grey exit band for the users whose path ended right there. This makes drop-off visible directly in the flow - you can see how many people left at each node instead of continuing.

Hover to trace​

Hovering a node - or a legend item - traces its flow through the diagram and dims everything else, so you can isolate one event's journey. The diagram scrolls horizontally when a wide analysis runs past the edge of the screen.

Where Users Stop​

Below the diagram, the Where users stop strip gives you a step-by-step retention read. There is one bar per step showing how many users are still on a path at that step and, in coral, the share who left there. It answers "at which step are we losing people?" in a single glance, without having to read the full diagram.

Most Common Path​

The Most common path card highlights the single top path as a row of event chips, followed by a short, data-derived insight sentence describing what that path tells you (for example, how large a share of users it represents).

Top Paths Table​

The full Top paths table lists the most common complete paths, one per row:

ElementMeaning
PathThe sequence of events as chips.
xN badgeWhen Collapse repeated events is on, consecutive duplicate events collapse into a single chip with an "xN" badge.
+N moreVery long paths truncate to their first 5 segments with a "+N more" expander you can click to see the rest.
CONVERTED tagPaths that end in a click or conversion event get a CONVERTED tag.
Share barA bar per row shows that path's share of users.

Use Show all N paths at the bottom to expand from the top handful to the complete list.

Analysis Examples​

Finding Paths to Purchase​

Configuration:

  • Direction: Backward
  • Ending event: purchase_completed
  • Max steps: 6

Insights:

  • What events typically precede purchase?
  • Do users compare products before buying?
  • How many touchpoints before conversion?

Understanding Onboarding Flow​

Configuration:

  • Direction: Forward
  • Starting event: signup_completed
  • Max steps: 8

Insights:

  • What is the most common first action after signup?
  • Where do users get stuck or loop (check Repeat events %)?
  • Where do most users exit (turn on Show where users exit)?

Identifying Drop-off Points​

Configuration:

  • Direction: Forward
  • Starting event: checkout_started
  • Max steps: 6

Insights:

  • At which step do most users abandon checkout (read the Where users stop strip)?
  • What events happen before abandonment?
  • What is the happy path to completion?

Best Practices​

Start Focused​

Begin with a lower Max steps (4 or 6) and increase only if you need more depth. Long diagrams are harder to interpret.

Let the threshold do the filtering​

Rather than eyeballing a busy diagram, raise Hide paths below until only meaningful paths remain. Because it is a percentage, it keeps working as your traffic grows.

Watch Repeat events %​

A high Repeat events % often points to users looping on one action - a sign of friction or a place where a single step is being retried. It is frequently the key finding.

Combine with Funnels​

Use path analysis to:

  1. Discover the most common paths.
  2. Then create funnels to measure those specific flows.
  3. Monitor funnel conversion over time.

Look for Unexpected Patterns​

Surprising findings are often the most valuable:

  • Users skipping expected steps
  • Unexpected events before conversion
  • Circular paths (users going back and forth)

Limitations​

  • Path analysis shows correlation, not causation.
  • Very long paths may have small sample sizes.
  • Users with many events can skew results.