We live in a world surrounded by, aided in, or made possible because of technological advances. These advances, both in business to business and consumer environments are made possible by the tech breeze that wafts from Palo Alto to New York City, catching products like ours from Chicago smelling the sweet smell of better, more efficient customer support.
Text is king
2016 proved to be the year where customer support and artificial intelligence intersected to create solutions to some of the biggest gaps in service. The immense growth of platforms like Facebook Messenger, Snapchat, WhatsApp, and others show that adopting a text-based support platform is a natural means of communication for billions of people around the world.
The idea of artificial intelligence being baked into a text environment isn’t new, though. Remember AOL Instant Messenger’s SmarterChild? Chances are you or someone you know grew up chatting with SmarterChild about the weather, movie show times, or some other random tidbit of potentially useful information.
What do we call the artificial intelligence that we’ll use every day to help us with support issues, service concerns, and to play with when we’re bored? A bot, of course.
Bots take over social media
Facebook, having already announced and begun using artificial intelligence, has released developers notes on how to build bots for their Facebook Messenger platform.
Twitter, still looking to claim their right to the future, recently introduced quick replies and DM bots to help aid in customer support woes. Vivian Rosenthal, founder of Snaps, a mobile messaging platform connecting brands and millennials, wrote in Forbes, “for many users, [Twitter’s] purpose is a channel to express dissatisfaction in a product or service and use it as a mechanism to get help. Twitter is finally accepting and embracing its value as a customer support platform.”.
Save time, energy, and frustration
Can we take bots further from just the point-of-sale and move to a support system? The adoption of bots and other artificial intelligence software is beginning to take shape, especially since there is significantly faster response times and a dramatic decrease in cost.
What do customers feel about bots? Shep Hyken, New York Times bestselling author and customer service and experience expert, writes in Man vs Machine, “customers are becoming comfortable with new technologies. Even with a slight learning curve, the payoff can save time, energy and frustration.”.
Humans still wanted
While technology has evolved to a place where you can order airline tickets, ask the support team (read as “bot”) for help, and have automated responses in chat boxes across platforms, we are not yet in a place where bots can solve every problem, and most humans don’t want that to become true.
A study focusing on technology-based self-service, like bots, and human interaction services in the tourism industry showed that while a desire for speed and easy service is the main reason for preferring a bot-like support experience, the desire for receiving human interaction at higher, more in-depth levels of support was paramount.
Humans like talking to humans about complicated and nuanced support concerns. While we are not yet at the point where everyday technology is moving from artificial intelligence to an intelligent assistant, capable of processing sentiment and nuance, there’s a foundation that you can build into your platform right now to help carry you into the future.
What you can do right now
- Define a primary use. Your bot serves a specific purpose. Identify the behavior patterns you want your bot to attain to by outlining what your bot is for, how your customer can use it, and when a human is needed to take over.
- Build a knowledge base. Think like your customer, and list all of the potential questions, concerns, and notes your customers would bring to your bot. Pair these with predetermined answers to help with what would normally be FAQ’s, easy to answer questions, and other areas of concern.
- Structure it all. Put all of this information into categories, subcategories, and even deeper organization as a way for your bot to answer easy questions first and then dive into the specifics of a topic if your customer needs that level of support.
Now that you’re brought up to speed on the bot space and how to start, get going! Have you already built a customer support bot for your business? Tell us about it. Thinking about building one now? Keep us in the loop on Twitter.