Humans are getting more comfortable with talking to machines today. While we’ve been doing it for a long time – think about routing via a IVR – we’re finally arriving at a time when machines can talk back in response to what we say, both via voice and via text.
While nobody’s offering technology that’s going to pass the Turing Test anytime soon, machines are getting smarter and better at understanding language, and the contact center, which is always seeking to lower costs through automation, is taking advantage of these technology improvements. Customers are long accustomed to seeking their own answers to questions, so using “chat bots,” or automated “smart” messaging solutions, should be a pretty easy adjustment.
If you’re embarking on a journey to get virtual assistants, or “bots,” working for your customers, it’s imperative that you start with the basics and work your way up, according to a recent blog post by Aspect’s (News - Alert) Ayesha Borker. It’s the best approach for customers, but it’s also the best approach for the technology, given that its artificial intelligence foundation “learns.”
“This basically means not offering too much at a time for the customer to experiment with,” she wrote. “And as a result, not confusing the bot with an array of human behavioral attack. It would be best to start with simple interactions, keeping the bot language crisp ‘n clear and a clear defined logic. Gradually, as better adoption sense is gauged, one can move onto adding more complex features and service offers.”
Borker also notes that that while performing an array of jobs may keep up the interest of human agents and raise their performance, it’s not the case with bots. Companies that adopt chat bots should ensure they are designed for one segment or category of frequently asked questions.
“It follows the rule of thumb of self-service – let the frequently asked questions be automated,” wrote Borker. “While, it’s fun to ask a banking bot,
‘What’s the weather today?’, it may actually not serve any business purpose. It is always a good idea to have a focused bot that wins a customer’s trust than attempt to set up a magician that may end up becoming a joke!”
When a bot is supported by predictive analytics, it can boost the channel’s effectiveness immensely. Bots that “learn” customer behavior and can tailor their answers and questions toward what they think the customer needs will keep transactions shorter and customers happier. It’s also a great way to be able to generate reports that help companies better understand what their customers want and how they want to be served, so they can build even better chat bots in the future.
Finally, it’s important that a chat bot never be a dead end. If the customer is floundering, the bot should be able to get him or her back on track by asking simpler questions. If this fails, ensure there is a path to a human agent who will be able to “keep” the context of the transaction.
“If nothing works, the customer should be able to reach out to an agent and have the context of the interaction kept intact,” wrote Borker. “This way a customer experience is never abrupt. It is a common practice for IVRs, why not have it for bots as well?”