Messaging Done Right Takes Teamwork Between Virtual and Live Agents


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Virtually every adult and most teenagers now own a mobile phone. That’s conditioned them to expect anytime, anywhere access to information, which is why they touch their smartphones an average of 2,617 times per day.

Here’s an even more surprising statistic: although 90 percent of consumers want to use messaging to communicate with businesses, less than half of those companies have the infrastructure necessary to interact that way.

Why? One reason is channel fragmentation. Some consumers prefer to use SMS/text messaging to contact customer service. Others prefer services such as Facebook Messenger. Still others are happy to use messaging services built into a business’ mobile app. And then there’s a host of emerging, non-mobile options, such as smart speakers, which are still bound by phone-oriented expectations of convenient, immediate interactions. The bottom line: Brands need to engage customers on their terms, and that means supporting as many channels as possible seamlessly while customers navigate between channels.

Another challenge is responding to all those messages. It’s expensive and sometimes impossible to hire and train enough contact center agents, especially when a major product launch sends messaging volumes through the roof. Some brands have turned to artificial intelligence automation for help but encountered shortcomings. For example, Facebook Messenger has proven capable of automating only about 30 percent of interactions.

Some vendors are touting asynchronous messaging as the be-all, end-all solution. Granted, it is an essential part of an effective messaging strategy, but it’s just that: a part. Some consumers still prefer to speak with a live agent, while others prefer a real-time chat with a virtual agent.

Go Virtual

Mobile phones come into play here, too: The proliferation of smartphone-based virtual agents such as Siri has made consumers comfortable using their voice to ask a computer for information. In fact, virtual agents also meet the overwhelming consumer preference for self-service over talking with a live agent. For example, in a 2016 AYTM survey of consumers worldwide, 89 percent said they want to use a virtual agent to get information.

But not just any virtual agent is up to the task. It must have the cognitive intelligence necessary to achieve first-contact resolution rates of at least 75 percent. Anything less means it won’t be shouldering enough of the workload for the brand to respond to many messages as immediately as today’s consumers demand.

The virtual agent platform also needs to be able to transfer interactions to live agents quickly when they involve requests that are beyond the virtual assistant’s capabilities. This also enables a human-in-the-loop machine learning process, which is key for training the virtual agent so that it becomes smarter over time—and thus capable of supporting even more interactions.

Above all, the virtual agent should support a wide variety of channels—and not just digital ones such as messaging, Twitter and web chat. Voice is equally important. According to a 2016 Forrester Research study, 63 percent of U.S. adult Internet users choose the voice channel for self-service, such as IVRs equipped with virtual agents.

But aren’t digital interactions growing exponentially? They are, just not at the expense of voice engagement. A virtual agent strikes the right balance by supporting both, such as by giving IVR callers the option to engage in an immediate SMS chat.
Virtual agents also provide an opportunity to eliminate one of the biggest customer annoyances: having to repeat themselves. Virtual agents can collect important information at the beginning of an interaction so that if it must be transitioned to a live agent, that person has all those details at her fingertips. This capability is key because today’s consumers prefer brands that know who they are, where they are, what they want, and what their customer journey has been.

No Channel—or Customer—Left Behind

To accommodate these customers’ preferences, brands should build their omnichannel messaging strategy around natural language understanding (NLU). An advanced form of speech-recognition technology, NLU can understand customers even when they use everyday language rather than just a limited set of industry-standard terms. (Think “cable box” rather than “set-top box.”) That sophistication reduces frustration right off the bat by providing the kind of conversational experience they’d get if they were interacting with a live agent.

Next, the NLU-enabled platform analyzes the customer’s input to decide whether to route her to a virtual agent or a live agent. This decision can be based on criteria that the business chooses. For example, the business might decide that certain types of questions are so complex that a live agent is best equipped to provide the right answers, right away.

With virtual agents handling the bulk of interactions, live agents now have more time to provide the remaining customers with white-glove service—the kind that builds brand loyalty. And when live agents don’t feel overloaded, they’re also better able to upsell customers, who are more receptive to those pitches because they haven’t wasted a lot of time and energy getting to that point.

The bottom line is that the longer consumers must wait to get what they need, the grumpier they become—and the more likely they are to churn or gripe on social media. Based on actual customer data, Nuance research shows that customer satisfaction (CSAT) scores plummet when it takes more than 36 seconds to respond on a mobile device or more than 30 seconds on the desktop. That’s one more reason why savvy brands are combining NLU, virtual agents and live assistance to deliver fast, convenient, seamless access to information.

Marina Kalika
Marina Kalika is director of marketing for the digital portfolio in the Enterprise Division of Nuance Communications. She has over 25 years of leadership experience in the hi-tech industry, managing every aspect of the product and customer life cycle: from industry research, and requirements gathering to product development and marketing, all the way through to sales and customer support.


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