A financial services company noticed on its Google Analytics account that within the last month, a loan sign-up form page was experiencing a much higher bounce rate than normal. They wanted to figure out why this was happening, but none of their analytics tools could tell them more than what was happening.
This is when the company found Mouseflow. They knew that seeing user recorded sessions first hand would be just the evidence they would need to diagnose the problem on this form page.
They still needed to determine how to drill down on the recorded sessions that were bouncing from this specific page so that they could watch visitor sessions that left this page.
After a quick demo with Mouseflow, the company found that using the ‘Waterfall View’ view on the recording list would allow them to break apart user sessions.
The next step was to indicate a page of interest (using the Funnels Feature) and select the appropriate page type (in this case “Exit Page”).
Using these two filters, the resulting recording list showed visitors who were leaving the page
within the last month.
Diagnosing a Problem
After watching a handful of sessions, they were able to identify a recurring pain point on the page: the text in the “Loan Amount” and “Monthly Revenue” fields was only allowing visitors to input numerical values (not commas). For example, for a visitor that was trying to record a $500,000 loan and a $300,000 monthly revenue, the form would fail validation and they would settle for $500 and $300 values. This glitch frustrated potential leads and lowered their priority because their revenue was being undervalued.
With this information, the company changed the field to a drop down menu to help to eliminate confusion and increase the conversion rate on loan inquiries.
By using Mouseflow’s filtering and user recorded session features, the company was able to identify a problem with their loan form page that would have otherwise remained unknown and unresolved while it sabotaged their revenue stream.