Self-Service Customers Are Choosing Speech Recognition

For businesses looking to give customers what they want, speech recognition has clearly become the self-service channel of choice. But new research shows that, when it comes to self-service, customers also prefer speech-recognition systems over other channels, including the traditional IVR system. And more than that, they're highly satisfied with the experience.

The research was conducted in 2007 by independent Australian research firm callcentres.net and used data collected from 262 Australian end users of speech recognition technology. The participants were asked to comment on a specific speech recognition application they had recently used and evaluate their experience versus other modes of customer service.

The results of the callcentres.net survey prove that sometimes there is a gulf between perception and reality when it comes to speech recognition. A common perception is that speech recognition technology can undermine customer satisfaction on some level. But the research found that more than 75 percent of customers are satisfied or highly satisfied with their customer experience using speech recognition. This was an 11 percent increase in satisfaction from replica research conducted by callcentres.net in 2005.

The results also validated the fact that speech recognition is customers' most preferred self-service channel over all, with 66 percent of respondents preferring speech over the Internet and 59 percent preferring speech to touch-tone IVR systems. Over time, there has also been a distinct reduction in the length of time that a customer is willing to wait on hold to talk to a customer service representative before the person's preference switches to using a speech recognition system. In 2005, on average, customers were willing to wait on hold for up to two minutes before their channel preference changed to speech recognition. The 2007 survey found that customers now prefer speech recognition after just 30 seconds on hold.

By age group
The callcentres.net research revealed a number of trends relating to customer use and interaction with speech recognition services between the generations. Confidence has emerged as a key factor influencing satisfaction with speech recognition. The research shows that frequent users of speech technology have a statistically significantly higher level of satisfaction with the experience than new or inexperienced users.

Another, perhaps surprising trend, is that Generation X (those people 30 to 40 years old) are more likely than Generation Y (those under 30) and Baby Boomers (41- to -62-year-olds) to use speech recognition to handle their entire transaction, without speaking to a customer service representative (CSR). That's an important factor for businesses to consider, given that Gen Y members are considered today's most powerful and influential age group. They want to interact with businesses in different ways to the older generations. Driven by convenience and speed, they are more than happy to use technology channels to access a company or service.

In today's environment, where consumers consider great customer service as an entitlement, rather than a nice surprise; there is no question that customers want interactions to be quick, convenient and positive. Speech recognition has proved itself as a tool with the means to meet these consumer demands and drive improved customer satisfaction. The important thing for businesses to remember is that part of the challenge is creating the optimal environment for speech recognition and assigning it to automate tasks that are appropriate to the needs of your individual customers. The environment is as important as the underlying technology in improving the customer experience.

Peter Chidiac, managing director, Nuance Communications, Australia and New Zealand, has worked in communications since 1984. His previous companies include ScanSoft and SpeechWorks. He has seen the evolution of communications systems from simple PABX, ACD, voice mail, paging and IVR systems to the adoption of sophisticated natural-language speech-recognition solutions.