User Journeys
Visualize the most common navigation paths visitors take through your website and identify drop-off points with interactive Sankey diagrams.
Overview
User Journeys shows you the actual paths visitors follow as they navigate your website. Rather than looking at individual page views, you see complete multi-step flows — from landing page through to conversion or exit. The data is presented as an interactive Sankey diagram where each band represents a group of visitors flowing from one page to the next.
Getting Started
Navigate to Audience → User Journeys in the dashboard sidebar. The page loads with default settings covering the last 30 days.
Filters
Use the controls at the top of the page to refine the data:
| Filter | Purpose |
|---|---|
| Date range | The period to analyse. It defaults to the last 30 days, can span up to 120 days, and cannot start more than 119 days ago — older start dates are not offered. |
| Widget | Which chat widget's site to analyse. Journeys are always viewed one widget at a time — the first widget is selected automatically. |
| Steps | How many navigation steps to display, from 2 to 6 (3 steps shows landing → page 2 → page 3). |
| Step filters | Pin a specific address at any step to see only journeys that pass through that page. |
The reason you cannot look further back is that Yaplet keeps website activity records for 125 days and deletes the older ones; the picker stops a few days short of that, at 119. If you pick a range that reaches past the limit, the picker adjusts it and says "Report data is only kept for the last 119 days."
Step Filters
Step filters let you answer questions like "Where do visitors go after visiting /pricing?". Open the Refine popover, type or pick a path for any step position, and hit Apply — the diagram updates to show only matching journeys. Each field suggests the pages with the most traffic at that step, and active filters appear as chips under the toolbar where you can remove them individually.
Filters also support two wildcards: * stands for one or more characters inside a single path segment, and ** stands for any run of characters across segments — so /docs/* covers every first-level docs page and /docs/** covers the whole docs tree. Matching ignores capitalisation, and the pattern must match the whole path.
/ and step 3 to /signup to see every path from the homepage that ends at the signup page.Addresses are grouped by their path only — the domain, query string and anchor are stripped, and numeric or ID-like segments are collapsed (so /order/1042 and /order/2087 both count as /order/:id). This keeps high-traffic pages from being split into thousands of one-off variations.
Key Metrics
Four cards above the diagram summarize the selected range:
- Sessions — every visitor session in range, with the average per day
- Multi-page sessions — sessions that viewed more than one page, with their share of all sessions. These are what the diagram and the journey table are built from — bounces count toward the totals but don't appear as flows
- Bounce rate — the share of sessions that left after a single page
- Top entry page — the most common starting page among multi-page journeys
An Updated badge in the toolbar shows when the data was last refreshed.
Reading the Sankey Diagram
The Sankey diagram is the main visualization on the page. Here is how to read it:
- Columns represent navigation steps (step 1, step 2, step 3, etc.)
- Nodes (blocks) within each column represent individual pages, sized by the number of sessions that visited that page at that step
- Bands (connecting flows) show how visitors moved between pages, with wider bands indicating more traffic
- Hover over any node or band to see exact session counts, including how many visitors continued to a next page and how many exited there
- Click any page node to pin it as a step filter — the whole view narrows to journeys passing through that page (click it again or remove the filter chip to undo)
Pages that appear at multiple steps will have a node in each column, so you can see how traffic redistributes across steps. The gap between a node's height and its outgoing ribbons is the drop-off — visitors who ended their session on that page.
Journey Table
Below the diagram, a table lists the top journey paths with exact numbers:
| Column | Description |
|---|---|
| Path | The full sequence of pages the visitor navigated (e.g. / → /features → /pricing) |
| Sessions | How many visitor sessions followed this exact path |
| Share | What percentage of total sessions this path represents |
The table is sorted by session count, so the most popular journeys appear first.
Practical Use Cases
- Conversion analysis — Point a step filter at your signup or checkout page to see which entry paths lead to the most conversions
- Content discovery — See which pages visitors naturally explore after reading a blog post or landing page
- Drop-off identification — Look for steps where the majority of visitors exit rather than continuing deeper
- Campaign evaluation — Select a date range around a marketing campaign to see how campaign traffic behaved differently