Case Study: SoFi prevents $9M in potential revenue loss with Glassbox
Key results
The challenge
SoFi was unaware of a technical website issue that was causing an increase in incomplete loan applications, with no visibility into how many users were affected or the financial impact.
The solution
Glassbox's cloud-native, tag-less platform captured 100% of sessions and used machine-learning anomaly detection to flag the affected sessions, then session replays let the production support team identify the root cause.
“With insights into our users behavior, we improved customer experience, engagement and ultimately drove more revenue.”
The results, in context
Glassbox's anomaly detection engine alerted SoFi to 546 sessions in a one-week period where users hit an error and never completed their application, and the root cause was identified and fixed within the same day. Glassbox estimates the fix prevented a potential annual loss of over $9 million.