7 tips to avoid common pitfalls with AI in customer service

Research is clear: customer service is one of the biggest drivers of customer loyalty. In fact, 78 percent of U.S. consumers say customer service is important to loyalty, according to Netomi’s State of Customer Service 2020 report.

Increasingly, customers expect support that is fast, personal, and effective. To deliver the experience that customers expect, companies are adopting AI to provide immediate resolutions that bring customer delight and business value. But in the race to automation, there are seven common pitfalls that companies should avoid to ensure higher customer satisfaction and a successful AI program.

While over 60 percent of U.S. consumers say speed is critical to a great customer service experience and nearly half expect convenience, these expectations are not being met. In fact, more than 50 percent report not seeing any improvement in customer service over the last year, and 23 percent even claim that customer service has grown slightly or significantly worse. With customer service being more influential than ever before, companies are turning to AI to deliver against rising expectations.

Over the last few years, AI capabilities have matured. AI-powered solutions are no longer limited to chatbots with rigid decision trees that limit the user to interacting solely with keywords or buttons. Modern conversational AI leverages natural language understanding and deep reinforcement learning to enable users to engage as if they were interacting with a human.

Virtual agents can now respond within seconds to a variety of customer needs without human intervention. AI is also helping agents work more efficiently and enabling them to focus on high-touch and advanced work. As a result, we’re seeing rapid adoption: according to Gartner, enterprise use of AI tripled in 2019.

While the benefits of AI in customer service aren’t under question, there are strategies companies can implement to help to ensure that AI improves CSAT, agent satisfaction, and overall business value.

Here are seven tips for avoiding common pitfalls when using AI in customer service:

Prioritize the user experience over delegating more use cases to AI. It’s about the quality of the customer experience, over the quantity of use cases an AI is tasked to manage.

Not every customer query should be automated, especially those that are critical or high-risk. Instead, leverage AI to automatically respond to queries that are high-volume, have low-medium business risk, and have low-to-medium exception management. Examples include order status and refund policies for a retailer, order modifications and cancellation requests for a subscription company, and baggage policies and upgrade requests for an airline.

Companies should determine the ideal use cases based on an analysis of historical tickets. In fact, most companies find that the same 5-7 scenarios account for over 50 percent of all tickets.

In addition to automating the right use cases, companies should also dictate if specific customers should immediately be routed to a human agent. For instance, some companies want to ensure their most loyal and valuable customers always have VIP support from human agents.

Most customers prefer self-service for low-risk issues. This requires companies to give AI the authority to help solve these customer concerns.

For instance, virtual assistants can help customers help themselves by directing them to relevant knowledge base articles. Or, they can solve issues within the conversational interface by integrating with business systems like CRM and E-commerce platforms. This allows a company, for instance, to provide the exact status of an individual’s order within the thread.