Customer service has proven to be one of the most popular applications of generative AI. But how exactly can generative AI help customer service teams (without alienating customers)? And which companies are already taking full advantage of generative AI? Read more Read on and find out.
Generative AI capabilities
One obvious use for generative AI is customer-facing chatbots. If you've ever been frustrated by dealing with a particularly unhelpful chatbot, rest assured. Tools like ChatGPT allow organizations to create chatbots that better understand customer questions and respond with more precision and nuance. It can also efficiently process large numbers of queries and provide more personalized responses over time.
Traditional AI products (such as less intelligent chatbots with which you might interact) rely on rule-based systems to provide predetermined responses to questions. And when you encounter a query that you don't recognize or that doesn't follow the defined rules, you get stuck. And even if they do give a helpful answer, their words are usually pretty stiff. However, tools like ChatGPT can understand even complex questions and answer them in a more natural conversational manner.
In fact, ChatGPT is so good that British energy supplier Octopus Energy says it is incorporating conversational AI into its customer service channels to handle inquiries. The bot reportedly did the work of 250 people for him and received higher customer satisfaction ratings than human customers and his service agents. This is a great example of how contact centers can incorporate generative AI chat and voice tools to address simple and easily repeatable tasks. And of course, these tools allow customers to access her 24/7 support via multiple channels (phone, online chat, social media messaging, etc.).
But answering customer questions isn't the only way generative AI can add value to customer service. Other tasks that generative AI can perform or assist with include:
・Give to customers Personalized recommendations based on customer data and previous interactions It also helps improve the customer experience.
· Data optimization To support customer service operations. Generative AI can process vast amounts of data and turn that information into actionable insights, such as “What are the most common complaints?” You can also track and categorize customer trends.
· Human customer service agent support. Generative AI helps human agents become more productive. For example, you can automatically generate responses to common queries, provide a summary of previous complaints and resolutions that agents can use in their conversations, or generate product recommendations.
In this way, generative AI supports the work that human agents do, freeing them up to focus on more complex customer interactions where they can add the most value.
How John Hancock enhanced customer service with conversational AI tools
We've already seen how one company used generative AI to improve its customer service capabilities. Now let's move on to another example. John Hancock, the U.S. division of global financial services provider Manulife, has been supporting customers for more than 160 years. But that doesn't stop life insurance companies from adopting the latest technology.
The company has partnered with Microsoft to implement conversational AI tools, such as Azure Bot Service, to provide support for common customer questions and issues. Like many businesses, John Hancock Contact's center saw a surge in inquiries at the beginning of the COVID-19 pandemic. This meant the company needed a new way to help customers access the answers they needed. So they turned to Microsoft to help them set up a chatbot assistant that could answer common inquiries. This reduced the total number of message center and phone calls and freed up contact center employees.
In other words, this allows contact center agents to focus on more complex cases, calls that really require expertise, rather than common questions like “How do I reset my password?” It will look like this. As a result, team members enjoy a better work experience and more manageable workloads, while customers enjoy shorter wait times and a better service experience. As Tracy Kelly, AVP of Contact Center and His LTC Operations, put it down“The reduction in calls resulting from chatbot innovation represents significant cost savings that could be reinvested into customer contact centers…”
And, as an added bonus, our customer service teams are upskilling in valuable AI skills, which will help future-proof them.
It’s no wonder that customer service has become a top generative AI priority for CEOs, according to the IBM Institute for Business Value. 85% of executives It says generative AI will be interacting directly with customers within the next two years. Companies that ignore the generative AI trend clearly risk being left behind.