Working in the customer service field isn’t easy. It requires strong communication and persuasion skills, patience, empathy, the ability to work under pressure and recommend innovative solutions, and numerous other skills. Customer satisfaction is the goal many service industries, such as retail, hospitality and food service, strive to reach.
Contact center agents face additional obstacles in the pursuit of this goal, including high call volumes, a lack of knowledge and/or access to knowledge, poor workforce management, stressful work environments, and more. Some innovative contact centers have started to use artificial intelligence (AI)-enabled solutions to solve some of these challenges and improve organizational performance.
Let’s evaluate how automation can give contact center agents the on-the-job support they need to ensure every customer interaction is a positive one.
Salesforce research has found that 64% of consumers and 80% of business buyers expect a real-time response to their inquiries. To give customers the on-demand support they’re looking for, contact centers must first support their employees. When agents don’t have the knowledge they need to quickly respond to customer inquiries, they often end up spending more time looking for answers than connecting with the customer. In fact, according to IBM, in a six-minute customer service call, 75% of agents’ time is spent doing manual research, and only 25% is spent on “valuable customer interaction.” AI gives agents knowledge at their fingertips so that they can focus on providing a positive customer experience.
On-demand support not only helps new agents feel more comfortable responding to customers, but it also helps the business feel more comfortable letting them do so, says Jeff Gallino, chief technology officer at CallMiner, a speech analytics solutions provider. In addition to instant knowledge transfer, CallMiner’s Eureka, an AI- and machine learning (ML)-powered speech analytics solution, gives agents instant feedback on everything from their tone of voice and pacing to their soft skills, like empathy.
Also providing on-demand support, Cresta, an AI platform born out of the Stanford Artificial Intelligence Lab, gives agents “guided selling recommendations” based on the language and behaviors of high-performing talent, says Zayd Enam, Cresta’s chief executive officer. The platform also uses automation to coach agents in real time. Enam explains, “Automatic personalized coaching makes coaching continuous by identifying each agent’s strengths and weaknesses based on industry best practices and existing quality assurance guidelines.”
On-demand knowledge transfer and coaching give agents the tools they need to satisfy customers and, consequently, the business.
Eliminating the Mundane
From sending follow-up emails to answering frequently asked questions, automation can “shoulder the burden of the menial, repetitive inquiries” that take up so much of a call center agent’s time, says Henry Iversen, chief commercial officer and co-founder of Boost.ai, a conversational AI platform for customer service in enterprise-level companies. Technology can automate inquires like address or account changes, bill payments, and balance inquiries, as well as other everyday tasks, including inputting data, locating information, sending emails and even following up with leads.
While all customer inquiries are important, “human resources don’t always have to be expended” to satisfy them. For example, Boost.ai uses conversational AI to recognize and respond to various customer queries, whether that means completing an automated process on a customer’s behalf, providing information or transferring the customer to a human agent.
Automation “greatly improves” the customer experience, says Iversen, because “not only does their interaction feel like they are talking with an intelligent machine that truly understands their needs, but they also get the answers they’re looking for with a minimum of friction, regardless [of whether] it comes from a virtual agent, a human or some combination of the two.”
When customer service agents have more time to focus on the customer experience, learning leaders should train them on soft skills such as empathy, patience and active listening. Ideally, this training should happen live or in an immersive environment, like virtual reality (VR) or augmented reality (AR), to simulate the various scenarios agents may encounter on the job, such as helping a frustrated customer.
Not only do AI-enabled tools support agents in their roles, but they can support the bottom line as well: In a field prone to turnover, AI can reduce onboarding costs. By giving agents “tools at their disposal,” Enam says, contact centers can avoid “time-consuming and inefficient training attempts.”
What the Future Holds
Automating certain contact center processes enables agents to use their expertise to help the customers who need it most. As conversational AI continues to advance, Iversen sees contact center roles transforming into more advisory roles. Gallino agrees, noting that automation is elevating agents “out of the mundane” and transforming them into skilled “knowledge workers.”
While automation will continue to transform contact center operations in the future of work, the customer experience will still rely largely on something that won’t be automated any time soon: human connection.