An “anomaly” is a deviation from what is standard, normal, or expected. Tealeaf Anomaly Detection automatically identifies atypical patterns in data and alerts users about the said anomalies. We have delivered a number of benefits to our customers based on Anomaly Detection. Some examples are as follows:
The insurance company uses this feature to track the rate of occurrence of errors across all sections of their website and take remedial action as necessary.
A deep dive into the technical errors revealed that it was predominantly an Internet Explorer issue that was inhibiting conversion.
These issues were detected in the month of July 2019 and as the customer worked on repairing these technical issues, the rate of occurrence of errors dropped significantly. As on Oct 2019, lost revenue due to errors during purchase process averaged around $250,000/month which is 70% less.
In Summary
Our customer’s investment in Tealeaf allows them to easily track and investigate any issues users have with their platform, making fixing bugs and spotting usability issues a far easier process and taking the pains of tracking down a problem out of the equation.
Additionally, the Tealeaf implementation spots fraudulent purchases from the get-go and allows their fraud prevention teams to step in as soon as possible – smoothly reducing the amount of insurance fraud enabled online.
