Leveraging Speech Applications In The Contact Center, Part One

Customer Inter@ction Solutions, Nov 2007 by Barnard, Patrick

Betsy, an inbound contact center agent, handles about 100 calls a day. She is always polite and courteous, except for perhaps late in the day when she gets tired of reading the same script repeatedly. She gets two weeks' paid vacation, 10 paid holidays, and a half hour for lunch every day. On average, she calls in sick five days a year, is late to work 30 times, takes a 15 minute break every four hours and goes to the rest room two times per shift. She gets paid $15 an hour and requires health insurance for herself and her family. She asks for a raise about every six months.

Gladys, on the other hand, can handle thousands of calls a day - hundreds simultaneously. She is polite and courteous and never gets tired of reading the same script. She never takes a vacation, doesn't celebrate holidays, never eats lunch and never calls in sick. She works 24 hour shifts and never takes a break. She costs about 20 cents per transaction and requires no health insurance.

So is Betsy jealous of Gladys? Of course not ...Gladys is a machine. She is an automated agent - a software solution that uses speech recognition to carry out "natural" interactions with people over the phone. If anydiing, Betsy likes Gladys because she makes her job easier.

Gladys can help customers with basic information and transactions. She can tell a customer when his order was shipped, what items he ordered and how much his credit card was charged. She can help the customer find a particular product in the catalog or on the Web site, tell him what sizes and colors it comes in, arrange for shipping, take the customer's credit card information and complete the transaction. Betsy and her fellow human agents are no longer bogged down with routine transactions and can instead concentrate on handling more complex interactions which have a higher transactional value. Thus, a contact center can blend automated agents with live agents to whatever degree of efficacy it desires, automating those interactions which are suitable for automation, while leaving more important transactions for the live agents.

When a customer needs something that Gladys can't deliver, or says something that she doesn't understand, she automatically transfers the call to Betsy. And when Betsy gets the call, she has all of the customer's call history right on her desktop, including information on their past transactions, plus everything Gladys told the customer and what offers she has already made. With this detailed information, Betsy can quickly pick up where Gladys left off and help the customer get what he needs. And if at the end of the call there's a need to complete another transaction, Betsy can hand the call back to Gladys, who is happy to finish the sale, achieving the much soughtafter first-call resolution.

Welcome to the world of contact center automation, where human and machine work in harmony to provide superior customer experience. Playing an increasingly important role in this automated world is speech recognition and analytics. Speech recognition is what Gladys uses to interpret what customers are saying so she can carry out their commands and give them the proper information. Meanwhile, speech analytics is what contact centers use to "mine" recorded calls to detect problems with agent/customer interactions and to gain insight into customer behavior which the enterprise can then use to drive key business decisions. Speech recognition and speech analytics are two distinct yet similar disciplines, each yielding benefits for the contact center in the form of operational efficiencies, higher customer satisfaction and increased profits. Let's take a closer look at the ways speech technology is being leveraged in the contact center today.

Speech recognition has advanced in recent years to the point where today's automated agents are able to ask callers open-ended questions, accurately interpret their responses and determine why they're calling. This achievement springs not only from significant advancements in the core technology, but also from innovations in application design, user interface design and die speech science capabilities used to optimize the software for specific user demographics. Speech technology vendors have also made strides in recent years in terms of technical optimizations, and through experience, speech software vendors and their customers have gained a better understanding of where it makes sense to use speech applications and where it doesn't.

Natural Language Capabilities

Their ability to carry out more natural conversations with callers is perhaps the most impressive aspect of today's speech recognition solutions. Thanks to the advances in large vocabulary continuous speech recognition (LVCSR) systems, automated agents can now ask open ended questions such as "How may I help you today?" and either provide the appropriate response or, in the event the system doesn't understand the caller or can't help, steer the call toward the appropriate agent. When implemented properly, these speech self-service solutions can lead to higher customer satisfaction, as the customer is no longer limited to a static set of options, one of which must be selected using the telephone keypad in order to proceed through the call.