Omni-Channel Customer Engagement Article

While the telephone may be somewhat on the wane when it comes to customer support – most customers try out alternatives to picking up the phone before they call the toll-free number – this doesn’t mean it’s declining in importance. In fact, because customers can answer routine questions themselves with Web searches, FAQs, social media, mobile app and SMS, the calls that come into a contact center become even more important: they’re the most critical issues.

Human speech is a great way of communicating, but contact center agents don’t have eidetic memories, and they and they can get tired and miss verbal cues. Complex issues can become contentious issues if not handled properly, and managers and supervisors need to know when customer loyalty making (or breaking) calls happen. They also need to be able to evaluate recorded calls fairly so agents aren’t getting judged for their job performance on the worst call they had all month.

“Listening” is a human skill, but it’s also a contact center resource when it’s done by a computer. Speech analysis is gaining a lot of traction in the contact center, particularly for companies that record a lot of calls but don’t have the manpower (who does?) to listen to all of them. The earliest iterations of speech analytics were expensive and generally suited for only the largest companies. Today, the providers of speech analytics solutions have scaled their products for small to medium-sized companies (SMBs) looking for feature sets compelling enough for them to buy, and affordable enough to make it workable (otherwise known as “perceived value.”)

In a recent blog post, Aspect’s (News - Alert) Magdi Khalil noted that ensuring that the perceived value of a product aligns with Aspect’s customers’ requirements and expectations is crucial when deciding a pricing strategy. In this way, the company is able to make highly usable speech analytics solutions  for quality management available to companies that may not have been able to afford – or may not have needed most of the features – of earlier generations of speech technology.

“Using Aspect EQ Speech Analytics, a quality management analyst is able to be very targeted in selecting the right calls to evaluate based not only on the traditional metadata available with a call but also on the content of the conversation itself,” he wrote.

Most companies use speech analytics to improve their quality metrics in a way that doesn’t require thousands of hours of human listening to recorded calls. Speech analysis helps managers and supervisors understand those most critical calls to listen to and where they can make the fastest improvements to their customer experience.

“Applying this type of targeted approach allows an organization to align its quality program to exact business objectives and KPIs achieving greater value from the quality program,” wrote Khalil. “In addition to targeted word search, the business is able to track the trending of several categories to follow the health of the business, all within the Aspect web-based user interface.”

Today, most companies – like most consumers – are “value buyers” and aren’t willing to splash out money unless the value of a product exceeds the cost. Speech analytics is one of those technologies that can help a company make a relatively small purchase in order to gain great value.