Bluegreen Vacations: Using Speech Analytics to Improve Customer Experience
To analyze the texts of calls, McCord builds searches and categories. The category piece of it groups past calls by type based on keywords. “So we build a category for reservations and all those calls can be pushed out to end users—like managers—who can look at Joe Smith’s calls, for example, and notice that 40% were about reservations and 20% of those were about reservations in Orlando, 15% about reservations in Branson, and 5% somewhere else,” McCord says. With that information in hand, managers might choose to offer Smith further training on setting up reservations at those sites, he adds.
McCord considers Bluegreen vacations an early adopter of speech analytics technologies, having purchased CallMiner software in 2010 “right when programs like this were starting to come on the market.”
“One great thing about CallMiner is it grew along with us; it’s a very valuable resource,” he says.
Soon after implementation, the speech analytics software was able to pinpoint the reason for spikes in call volume. “We found out our website was very important,” McCord says. “Its usage directly impacts our call volume.”
With that in mind, McCord’s team began focusing on gaining more insight into how people use its website. One tool he built using CallMiner determines what part of the website an owner is looking at while he or she is speaking with an agent. “Getting the reasons for those calls shows us where the website [isn’t meeting the needs of viewers]. We can see…why people are calling and we’re able to make web enhancements,” McCord says.
While the company now knows to expect increased call numbers during those infrequent times when it, like all websites, experiences issues, the information about the website has guided Bluegreen toward other changes. For example, it now pushes out timely information via the website. “In our industry the fall is kind of the time when Mother Nature calls,” McCord says. “We could get flooded with call volume if we’re not proactively getting messaging out ahead of tropical storms, hurricanes, and wildfires.
“As soon as we start hearing through speech analytics that people are concerned, we post on the website and send emails about the proactive steps we’re taking to ensure their vacations aren’t affected,” he says. If a natural disaster means an area in which Bluegreen operates becomes closed to tourists or is dangerous, the company also immediately pushes out that information.
Those messages help preempt calls about the issues, which allows its customer service agents to concentrate on others types of calls, McCord says. “The calls we do handle now are for more complex procedures,” McCord says.
Call analytics have helped Bluegreen gain insight into its owners in other ways. For instance, when owners wanted to change the ownership title for their vacation ownership, they called to ask for a form to be sent to them. “Then we’d mail them something and they’d mail it back,” McCord says. “We determined through speech analytics that we were getting a number of calls each month about that.”
The company now posts that document on its website. To change their titles, owners need only print it, fill it out, and mail it to the processing center. That move alone saved an estimated 2,000 processing hours annually.
While it could be said that saving many hours spent processing paperwork isn’t exactly a little thing, Bluegreen Vacations continues to use its speech analytics software to find other areas where seemingly small enhancements and new ways of doing business can add up to a better experience for everyone involved.
The NWEA sought a way to streamline oral evaluations to save school districts time and money while still ensuring students are on track.
One of the biggest challenges of call-centers is making sure customers have a good user experience—and more of than not, that comes down to the interaction they have with your agents. If there is a language barrier—or even if the agent has a heavy accent that your majority of callers have trouble understanding—that can cause user satisfaction problems. Allianz wanted to find a way to solve that problem.