Mining for Meaning

For Larry Mark, speech analytics is a lot like a Dremel tool. Initially created for simple hands-on projects, the Dremel has spawned thousands of other uses around the house—often for projects totally unrelated to its initial purpose. Mark, who is chief technology officer at SER Solutions, says speech analytics has evolved the same way. Once viewed as a spin-off of speech recognition used for just word spotting, speech analytics today is seen as a means to spot deep-seated business problems, many of which had previously gone unnoticed.

For example, broadband cable systems provider Comcast purchased CallMiner’s Speech Analytics Suite in hopes that the technology could help contact center agents better adhere to standards and policies. By recording and monitoring call content, the company sought to use the data extracted with speech analytics to develop better agent performance. But when the company looked at the actual data, it found that agent performance wasn’t really a problem; the real issue was a mix-up in the company’s billing procedures. Comcast subscribers were calling customer service at higher volumes because they appeared to have been billed twice. Though they were not, the mix-up generated an increase in call traffic. Comcast was able to address the problem and is now focusing on using the technology to pinpoint areas in which agents can promote service upgrades during customer calls.

How does a company use speech analytics to not only address initial concerns, but also to effect change within the enterprise? Therein lies the challenge. For speech analytics to work, a company has to put in a significant amount of work to analyze the data. And for the technology to produce a return on investment, an organization must make that data actionable; changes must be made enterprisewide. Most analysts and vendors agree that for speech analytics to take off, companies must begin to see the technology’s effectiveness outside the contact center.

According to Paul Stockford, president and chief analyst at Saddletree Research, companies must think outside the contact center box.

"For all the talk you hear in the market about how important the contact center is—and it’s true—the majority of companies still look at the call center as those people who answer phones and we pay $8 an hour," Stockford says. "There are a handful of companies that use the call center to their advantage, and they will immediately recognize the benefit of speech analytics."

Missionary Work and Rocket Fuel
In 2007, DMG Consulting published a 270-page report on the state of the speech analytics marketplace. "The 2007 Speech Analytics Market Report" made a strong prediction: that the speech analytics market would grow by 100 percent in 2007 and 2008, making it the fastest-growing contact center technology market segment.

At a time when products like workforce optimization (WFO) and unified communications (UC) attempt to stake their claims in improving contact center operations, speech analytics vendors are making the sell that their products can also change the way a business operates. But companies faced with IT budget cutbacks have perhaps been hesitant to invest a substantial sum of money in a still relatively new technology. It’s a big gamble, and some vendors realize this.

"Speech analytics is a great technology, but right now it has niche applications, and I think that what’s lacking is executive understanding and buy-in," notes John Benchoff, senior director of product marketing at SER. "It has the potential, but I don’t see it having the kind of rocket fuel right now to get there."

When it comes to software for the contact center market, speech analytics vendors and analysts are some of the most adamant and charismatic. And rightly so—while able to whip up impressive stats and technical terms, the market’s players have to be cheerleaders. Until speech analytics gets what Benchoff calls "rocket fuel," the stand-alone application means nil. And that is the biggest letdown.

While many organizations have purchased call recorders, few have utilized data gleaned from their customer interactions effectively. With millions of hours of conversations floating in contact centers worldwide, speech analytics vendors can see their software’s potential to extract actionable information. If only more companies would listen.

"There’s still a lot of missionary work to be done," Saddletree’s Stockford says. "We’re just starting to see some real traction for business analytics, and speech analytics is something that seems way out there to a lot of people still."

The laws of technology adoption cycles play a significant role in speech analytics’ growth. Most ideas operate along years-long curves before being accepted as an essential part of everyday business operations. That’s how Greg Borton, vice president of analytics at Nuance Communications, views speech analytics.

"No one knew what CRM meant in 1990, and look how it’s totally transformed our industry in 10 or 12 years," Borton states. "IP telephony was not heard of until 1996, and look how it’s transforming our worlds. These were real trends independent of the invention. Speech analytics is in year three or five of that pretty typical, 12-year curve of technologies."

What sparked CRM’s and IP telephony’s successes were not only more adoptions and established best practices, but also innovation and integration. Just because speech analytics is emerging in the marketplace, it doesn’t mean the vendors’ work is through. In a multimodal landscape, companies must find new ways to integrate their technology into existing applications, form partnerships with other contact center technology vendors, and work out the kinks between two very different speech analytics models: Large Vocabulary Conversational Speech Recognition (LVCSR) and phonetics (see the sidebar).