B2B Tech Company Reduces Customer Support Team’s Average Handling Time (AHT) by 50%

Author:

Level AI Team

Last updated:

February 8 2023

Blog /Contact Centers / B2B Tech Company Reduces Customer Support Team’s Average Handling Time (AHT) by 50%

We all know the importance of ensuring customers’ inquiries and complaints are handled quickly, efficiently, and with top-notch service. After all, a great customer experience is essential for building loyalty—and ultimately driving profits. But how can you increase your speed without compromising quality? One B2B tech company has reduced their average handling time by 50% while maintaining—and improving—their customers’ satisfaction levels. Here’s a look at exactly how they did it and the hidden business insights they uncovered along the way.

The Challenge

The client noticed in the performance reports that some agents showed higher than usual average AHT and leveraged Level AI to search for agent conversations with high AHT and reviewed several to identify a possible cause.

The Analysis

In these calls, they noticed that agents were putting customers on hold and transferring them, which increased the wait times and contributed to the high AHT. However, while there seemed to be a correlation between call transfers and AHT, the client needed to verify this with data to be certain before taking action.

The client configured the AI to listen and look for conversations with indications that the calls were transferred by entering sample phrases, such as “please hold while we transfer your call” and “let me transfer you to a dedicated team” into the system. This analysis showed a clear pattern: Agents with the highest percentage of call transfers also had the highest AHT average.

Taking the analysis a step further, the client wanted to know if there was any logic behind the high volume of calls transferred. Level AI’s ability to automatically categorize conversations into topics revealed that payment-related inquiries were the most transferred calls.

The Result

The cause of the high AHT and the issue’s impact on agent behavior confirmed that there may have been a lack of knowledge or insufficient training on effectively handling payment inquiries. With this insight, the client rolled out additional coaching on handling payment inquiries while continuing to monitor agent performance. As the agents completed the sessions and began applying the new training, the call transfer rate significantly decreased, and the overall AHT improved.

For more details about this use case and how four other companies use Level AI to uncover hidden insights with contact center analytics, download the e-book, From Insights to Action: Uncover Hidden Insights and Transform Contact Center Operations.