Try to book a train ticket on Amtrak’s home page and you might just swear off train travel. For sure, you’ll swear. A recent attempt to book a journey from New York to Boston, for example, required toggling between windows, looking up obscure station codes, and waiting for slow page repaints. When the order was finally submitted, an error message came up noting that, due to technical difficulties, the request could not be processed.
If only Amtrak’s Web designers were as attentive as the makers of the railroad’s telephone self-service system. That system, which features the digitized voice of an operator named Julie, is a primer on good customer service. Rather than requiring Amtrak’s 20 million or so yearly callers to punch in numbers, the system allows them to voice responses to questions like “What city are you departing from?” And unlike many Web-based self-service setups, Amtrak’s voice-activated operator does most of the legwork for the customer.
Expect to bump into more Julies out there. A new technology, called natural language speech recognition, is markedly improving voice-activated self-service. Powered by artificial intelligence, these speech-recognition systems are altering consumer perceptions about phone self-service, as calls for help no longer elicit calls for help. That, in turn, is spurring renewed corporate interest in the concept of phone self-service. In 2004, sales of voice self-service systems topped $1.2 billion. “We’ve seen voice systems move from emerging technology to applied technology over the last few years,” says Steve Cramoysan, principal analyst at Stamford, Connecticut-based research firm Gartner. “It’s still fairly immature. But it’s proven and moving toward the mainstream.”
We Call It Maze
Users of first-generation telephone self-service systems probably would have bet against such a development. Those early programs required customers to punch in an endless series of numbers or symbols when responding to questions. The advent of cell phones, and their Lilliputian keyboards, only amplified the ire of customers who used Touch-Tone customer-service systems. First-generation voice-activated self-service systems weren’t much better. Customers who responded to prompts with complete sentences, rather than monosyllabic grunts, often found themselves backtracking through a labyrinth of menus. “Things still weren’t quicker, because of the number of [menu] trees the person had to get through,” says Maureen Govern, chief technology officer with call-center technology provider Convergys Corp., based in Cincinnati.
Software based on natural language speech recognition, however, has eliminated many of the hang-ups of phone self-service. Instead of matching user responses to predefined lists of isolated words, the software uses a statistical model to connect those words and better understand their intent. The result? “Customers are frustrated less often,” says Govern.
The average estimated cost of customer service, per customer, per interaction.