• October 1, 2015
  • By Leonard Klie, Editor, CRM magazine and SmartCustomerService.com

The Age of Speech Analytics Is Close at Hand

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It's not just the financial services industry that stands to gain from real-time analytics, though. Retailers and subscription-based service providers—businesses where customer churn is a real concern—could also benefit from real-time capabilities. Other key target verticals include utilities, government agencies, emergency responders, and healthcare—all businesses where the ability to respond to situations quickly is imperative. The size of the firm doesn't matter either, experts agree.

"If you know what's happening in real time, you can alter the outcome in real time," Fluss says.

Among other benefits, real-time analytics will allow companies to identify language indicative of a disgruntled customer and respond with relevant retention offers, all within the same call. That is something that could potentially have huge financial benefits for all businesses.

So, too, could the ability to identify caller intent and move frequent questions out of the contact center into automated self-service, says Nick Gyles, chief technology officer at WDS, a contact center outsourcing firm acquired by Xerox in 2012.

Real-time analytics can also improve call efficiency and efficacy by providing real-time guidance to only those agents who need the extra help resulting in less training overall. Errors or missing information that lead to costly repeat interactions can be flagged for immediate action.

"It's about being much more responsive to the customer and still having much more control over agents' behavior," Gyles says.

As an added benefit, "with real-time [analytics], you can take the appropriate actions for each individual caller," Fluss says. "You can customize each interaction, and when you can provide a more customized experience, it's better for everyone.

"It's not just about getting fancy, innovative new technology. It's about improving productivity, increasing agent satisfaction, and reducing operating costs," Fluss continues. "Real-time [analytics] is an important step in providing better customer service."


But for all its potential, real-time analytics in the contact center is still extremely rare. Of the 20 percent of contact centers that have deployed analytics, most (77 percent) use historical, post-call analytics; real-time or near-real-time speech analytics is used by just 38 percent, ContactBabel reported in its 2015 U.S. Contact Center Decision-Makers' Guide.

Post-call solutions that analyze recorded conversations are more mature by far than real-time applications, which only started to enter the market in 2011, according to Fluss.

Part of the reason for the slow uptick in real-time analytics, according to Jim Davies, an analyst at Gartner, has been a lack of organizational understanding and preparation.

And there's this: Achieving full real-time capabilities is not easy. Typically, a slight few-second delay is necessary for the application to collect and analyze a large enough snippet of the conversation to identify the triggers that require action.

Gyles says true real-time capabilities are still at least 12 to 18 months away—which does little to help the current situation. "The industry is not at the level we need right now," he says. "We can use the technology for keyword spotting, but we still have to drill down on our own. [Current solutions] do not give us the level of real-time insights we need."

That was the motivation for WDS to develop its own Agent IQ system. Agent IQ provides a real-time view of what is happening in the 175 contact centers WDS operates around the world. Agent IQ can interpret natural language, associate relevant root causes, and provide real-time guidance. Automated call logging captures data. Real-time, evidence-based self-learning draws on agent usage to optimize results against the latest call drivers. The self-learning system works with live chat, voice, and text interactions.

But even with Agent IQ, as with most other solutions, capabilities are limited. "We need to analyze calls with more detail," Gyles states. "There's a lot of work to do to get us there."

Gyles is certainly not alone in his frustration.

"In most cases, agents are receiving a very limited amount of real-time data, which is wrong," Fluss says. "The contact center is a real-time operation, yet, when it comes to information, a lot of it is not real time; it's historical."

That's not to say that post-call analytics should be phased out. Just the opposite: Post-call speech analytics is invaluable for identifying root causes and emerging trends from the recorded audio that most contact centers gather.

"You need post-call and real-time analytics together. Real-time is most effective when it's coupled with post-call, and vice versa," Skowronek explains.

Furthermore, experts explicitly warn against starting down the path toward real-time speech analytics without first collecting post-call information.

"Get a baseline understanding of what is happening [across the business] with post-call analytics first instead of starting with real-time analytics right away," Stephan suggests.

Skowronek agrees. "You can't do real-time analytics if you don't have post-call analytics to shape the types of things you need to look for and take action on," he says. "Post-call analytics are needed to point out the things that you should be focusing on in real time."

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