How AI and Digital Self-Service Will Revolutionize Customer Service
Make life easier on your customers: Automate simple processes by using artificial intelligence (AI).
To keep customers happy, organizations need to build the right digital customer-service infrastructure. This includes things such as customer relationship management (CRM) and helpdesk software. It also involves training customer support staff on how to use these tools to deliver immediate and rewarding customer experiences.
Unfortunately, just plugging in new software and training staffers isn’t going to be enough to bring your company to the highest level of customer satisfaction. Cutting-edge support teams are using artificial intelligence (AI) and digital self-support to make it easier for their staffers and customers to find the information they need to experience your products or services the way they were intended to be experienced. I spoke with JC Ramey, CEO of DeviceBits, about digital self-service and how it’s revolutionizing the customer service industry.
Before we discuss how AI and self-service work as it relates to your customer service operation, it’s important to define AI and self-service in the context of support. Companies that utilize AI give autonomy to software to carry out tasks and make decisions without human oversight.
Think of AI as a car driving you to work while you take a nap in the backseat. Now, what if you trusted that software to make recommendations and solve customer problems without your oversight? Digital self-service comes into play by ensuring that AI delivers the right educational materials to customers at the point of interaction. This includes things such as how-to blog posts, whitepapers, ebooks, videos, and whatever else your company might want to create. These educational materials will let customers solve problems themselves, without the help of a customer service agent or an account manager.
AI and Customer Support
You’ve probably used a chatbot to try to get an answer to a customer service query. Typically, chatbot responses are built on a scripted set of branches created by the brand, based off historical questions their agents have received from customers. If you ask about A, then the script knows to take you to B. However, chatbots that don’t leverage AI won’t be able to help you if you run off of the script. As the chatbots learn from the questions customers ask, the gulf between branches goes away and the conversation becomes more natural in its give and take.
“Where we see the real benefit of AI is in the knowledge engineering that’s happening,” said Ramey. “Everybody thinks chatbots are the golden ticket for implementing AI but you have to build intelligence into that chatbot experience.”
More intelligent chatbots means more complex calls can be handled by agents. Whereas 10 years ago agents might have fielded very basic service queries, they’re now free to handle issues that can’t be resolved by two or three message volleys with a chatbot.
“Agents can contribute to what’s being put into the knowledge and engineering,” said Ramey. “That’s a paradigm shift from having you sit at your desk and put on your headset and answer the phone when you see the blinking light.”
Perhaps most important to business owners, AI can help generate revenue. Ramey said DeviceBits helped one of its clients, a wireless service provider, take advantage of customer searches and queries to sell more products. DeviceBits software flagged a pattern in the wireless service provider’s customers’ queries and on-site searches during the holiday season. Customers were coming to the website looking for information on international roaming charges ahead of vacations they’d planned for the holiday break. DeviceBits recommended the wireless service provider connect a commerce platform to the customer service platform so that, via AI, anyone who searched the website or asked a chatbot about international roaming would receive an offer to purchase an international roaming package.
When asked about how his company defines digital self-service, Ramey replied, “I used to work at IBM; I call it my two-year prison sentence. The joke was, you had to use Google to find anything on IBM.” Ramey’s IBM slight is probably true for most organizations. Companies do an excellent job creating materials that help customers solve problems. Unfortunately, those materials often live in many different places, they’re disconnected, and they don’t convert well to mobile platforms.
Ramey said it’s important to build out a digital self-service experience that is able to predict what customers are trying to accomplish and then guide them through that process. This requires companies to connect knowledge across platforms, gather intelligence to make sure that on-site search engines are making the smartest recommendations possible, and then building out the experience across all device types.
But what happens when self-service doesn’t work? Ramey said technology should be able to guide the user to the agent in a seamless way that doesn’t require a restart. Rather than forcing the user to repeat his or her issue, the technology the company uses should be able to automatically decipher that information based off of how the customer was navigating the self-service knowledge base.
Just remember: More information is not always better. You might think that building out more articles will ultimately direct your customers to what they need without the help of an agent. But, in reality, an abundance of information might drive customers away from the website entirely. Instead, AI should be able to disable and enable the articles within your knowledge base, depending on the topic for which your customer is searching. Think of it like this: Instead of having 10,000 articles with no AI built in, you could leverage 500 incredible articles. And your customer never sees 499 of them because your digital self-service ecosystem is so intelligent, it knows exactly which one article to surface based off of how the customer navigated the website and what the customer typed in as his or her search query.
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Originally published at www.pcmag.com.