Event and exhibit solutions provider Freeman deals with thousands of such inquiries each week. As these conversations became longer and more complex, the company needed a more reliable and scalable way to evaluate those interactions and generate insights to support coaching and improve agent performance.
This set-up made it difficult to consistently evaluate agents, provide them with targeted coaching, and identify trends or recurring issues.
“We knew we needed a better approach to QA,” adds Riel. “We needed more data to improve our performance and make informed decisions.”
A smarter way to coach
After participating in demos from several conversation intelligence platforms, Riel’s team chose Observe.AI for its pricing, product roadmap, and support. They implemented Post-Interaction AI to get a full view of every customer interaction.
“We use the QA tool in our Observe.AI platform to manage coaching sessions,” says Riel. “We can track agents’ progress, connect the dots, and show them actual data and examples. That kind of visibility just wasn’t possible before.”
Instead of relying on just a handful of calls, the team now uses insights from 100% of conversations to guide coaching and decision-making. This has improved first-call resolution and contributed to a 4% year-over-year drop in call volume, even as the business continues to grow.
Improvements across quality and efficiency
Two years into using Observe.AI, Freeman has made impressive improvements in terms of quality, speed, and customer experience. Most notably, its net promoter score has gone up by almost four points.
“That’s huge for us,” says Riel. “Our QA scores also rose about 6%, and at the same time, we saw a 22-second decrease in average handle time as well as a 10% reduction in not-ready time.”
Uncovering trends and supporting other business units
Other departments are also benefiting. They turn to the customer support team to better understand what exhibitors are saying and why. With features such as keyword search, and access to transcripts, the team can quickly pull out the conversations others need.
“They want us to basically help do some forensics,” explains Denise Brown, Vice President of Customer Experience. “Like, go look at those calls and help us understand. How many times did people call and actually say, “My driver was refused,” or “My shipment couldn’t get picked up”? Whatever it is, we go in and look for those keywords.”
Instead of speculating, the team can validate trends in customer calls using actual data. For example, when issues cropped up after the rollout of a new invoicing platform, the customer support team was able to confirm that calls about duplicate charges had indeed spiked during that period.
The team previously used a manually updated system for tracking customer inquiries. Now, they cross-reference that with data from Observe.AI to verify issues and identify themes.
This capability is helping improve the customer experience. For example, when exhibitors frequently ask the same questions, such as how to handle freight, that often suggests a gap in communication.
“Those little things we’re doing help reduce friction and improve the overall experience for our customers,” says Brown.“Our average agent takes about 100 to 120 calls a week. But at the time, we were only evaluating one of those,” says John Riel, Director of Exhibitor Support at Freeman.
With Observe.AI now part of its daily operations, Freeman is exploring new capabilities. It is particularly interested in generative AI.
“If we’re looking for company-wide impact, we’re really hoping that we can partner with Observe.AI,” says Brown. “I really do feel that can be a game changer for us, and not just for the call center.”
Since many teams at Freeman use the same telephony platform as customer support, there’s an opportunity to identify insights that map the full customer journey. The company is also evaluating real-time assistance tools to help agents respond more quickly.
“We think that’s where the value is, giving our agents faster answers to help customers,” says Riel. “We can see a reduced handle time, which of course, for us and the company overall, could potentially lead to a reduced full-time equivalent and cost savings by us investing more with Observe.AI and with AI in general.”
