How generative AI is revolutionizing customer service
Customer service is proving 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 making extensive use of generative AI? Keep reading to find out.
The capabilities of generative AI
One obvious use for generative AI is in customer-facing chatbots. If you’ve ever had a frustrating interaction with a chatbot that wasn’t particularly helpful, take heart because with tools like ChatGPT, organizations can create chatbots that better understand customer queries and respond with much more precision and nuances. They can also efficiently handle a high volume of queries and provide more personalized responses over time.
Traditional AI offerings (like some low-intelligent chatbots you may have interacted with) rely on rule-based systems to provide predetermined answers to questions. And when they encounter a query that they don’t recognize or don’t follow the defined rules, they get stuck. And even when they give a helpful answer, the language is usually quite stiff. But a tool like ChatGPT, on the other hand, can understand even complex questions and answer them in a more natural and conversational way.
In fact, ChatGPT is so effective that UK energy provider Octopus Energy has integrated conversational AI into its customer service channels and says it is now responsible for handling inquiries. The robot would do the work of 250 people and receive higher customer satisfaction rates than human customer service agents. This is a great example of how contact centers will increasingly integrate generative chat and AI voice tools to handle simple, easily repeatable tasks. And of course, these tools provide customers with access to support 24/7, 365 days a year, through multiple channels (such as phone, online chat, and social media messaging).
But answering customer questions isn’t the only way generative AI can add value to customer service. Some of the other tasks that generative AI can perform or help with include:
· Give to customers personalized recommendations based on customer data and previous interactions further helps to improve the customer experience.
· Provide conversational search functions for, say, online FAQs. Generative AI can respond to natural language prompts such as “Where is my package?” and either direct the customer to the correct answer to the FAQ or provide a personalized response. Plus, it can be done in multiple languages.
· Data Optimization to support customer service operations. Generative AI can handle large amounts of data and turn that information into actionable insights – insights like “What are our most common complaints?” » It can also track and categorize customer trends.
· Support human customer service agents. Generative AI can help human agents be more productive. For example, it can automatically generate responses to common queries, provide summaries of previous complaints and resolutions that agents can use in conversations, and generate product recommendations.
In this way, generative AI can support the work done by human agents and allow them to focus on more complex customer interactions where they can add the most value.
How John Hancock Improved Customer Service with Conversational AI Tools
We’ve already seen how one company improved its customer service function using generative AI. Now let’s move on to another example. John Hancock, the US arm of global financial services provider Manulife, has been supporting customers for more than 160 years. But that doesn’t stop the life insurance company from adopting the latest technology.
The company has partnered with Microsoft to implement conversational AI tools, including Azure Bot Service, to provide support for common customer queries and issues. Like many businesses, at the start of the COVID-19 pandemic, John Hancock contact centers saw an increase in calls, meaning the company needed new ways to help customers to access the answers they needed. So they turned to Microsoft to help them implement chatbot assistants that could handle general inquiries, reducing the total number of inquiries in the message center and over the phone and freeing up contact center employees.
In other words, it allows human contact center employees to focus their efforts on more complex cases, i.e. calls that actually require their expertise, as opposed to generic queries such as “How Reset my password ? » As a result, team members benefit from a better work experience and more manageable workloads, while customers benefit from reduced wait times and a better service experience. Like Tracy Kelly, assistant vice president of contact center and LTC operations, the dish“The reduction in calls thanks to chatbot innovation equates to impressive savings that we have been able to reinvest in our customer contact centers…”
Plus, as a bonus, the customer service team upskills in valuable AI skills, helping to future-proof their work.
It’s no wonder that customer service has become the number one priority for CEOs when it comes to generative AI, according to the IBM Institute for Business Value, with 85 percent of executives claiming that generative AI will interact directly with their customers in the next two years. Companies that ignore the generative AI trend clearly risk being left behind.