Help find user pain points and opportunities for improvement by filtering recordings of sessions that resulted in a drop-off.
Identify two steps of the user flow that you want to analyze.
For example, these could be two of the steps involved in a checkout flow:
- The cart page
- Billing/delivery details
- Order purchase page
- Confirmation page
Add a Viewed page filter for the URL of the step before the drop-off you're targeting.
Depending on the structure of your URL, select either "contains", "starts with", "ends with", or "is" to specify the URL to filter by for this step. In this example, I'm interested in drop-offs before the confirmation page, so the first filter applies to the Order purchase page.
Add another Viewed page filter, this time for the drop-off step.
We suggest using one of the negative options for this filter: "does not contain", "does not start with", "does not end with", "is not". The option you choose for the filter will depend on the structure of your URL.
With these two filters applied, in plain English, we're saying: Show me recordings of users who viewed one page but didn't view the following page in the flow. We can then watch recordings of users matching these filters to:
- Compare the behavior of users who drop-off against users who don't.
- Add other filters to reveal further insights about the drop-off. For example, device used, country, rage clicks, a custom Event or User Attributes, etc.
You can also apply this same filtering pattern in Heatmaps or Dashboards to view an aggregated view of drop-off data. Saving the filter set as a Segment will enable you to revisit it again in the future more quickly.
Check Survey responses to learn the reasons behind the drop-offs
Check any Survey responses left on the page before the drop-off. To understand why they're leaving, we also recommend creating an abandonment Survey that will trigger when users leave your site from that page.