in speed of analysis
in categorizing instances of complaint vs. feedback
24 weeks saved
for analysts each year
This company had a team of four customer experience professionals manually reading and classifying more than 4,000 verbatim reviews from customers each quarter so that the correct line of business teams could address complaints and feedback.
The company leveraged our solution’s AI modeling, natural language processing, sentiment modeling, and machine learning functionality to analyze omni-channel textual data and improve the customer experience.
Applying this cutting-edge technology automated workflows, saving analysts 24 weeks of work per year to focus on mission-critical tasks.
The Full Story
The company chose to focus on customer analytics for disability and life insurance claims, which were difficult for other systems to classify and assign sentiment given that these reviews can include both positive and negative words. For example, “They were a great help during this terrible time.”
Our solution accurately sorted these reviews into complaint and feedback categories, drastically reducing the time spent on analysis from more than 120 days to less than one.
Ready for a demo
Contact us to learn more