It\u2019s fair to say COVID-19 has changed the way businesses operate. Compare everyday life today with your daily concerns from three months ago. The difference is\u00a0pretty stark.\u00a0\u00a0<\/p>\n
Like everyone else,\u00a0call\u00a0centers have been reeling from the aftermath of the coronavirus. Paul Stockford, National Association of Call Centers Research Director, raised concerns about what he called a\u00a0\u201cpretty\u00a0high\u201d risk of exposure<\/a>\u00a0in those working environments. It\u2019s not difficult to see why experts like Stockford are so worried:\u00a0contact\u00a0centers manage a large workforce sitting in close quarters. Not to mention, agents often share their work surfaces with employees from different shifts.\u00a0<\/p>\n Where does that leave companies? They want to meet customer expectations, follow public health guidelines, and protect their employees. Some businesses have embraced a remote workforce. Meanwhile, others have resorted to shutting down their\u00a0call centers completely.<\/p>\n One avenue to explore is artificial intelligence. The latest\u00a0AI-based call\u00a0center\u00a0RPA\u00a0tools<\/a>\u00a0support better customer experience from start to finish. At the same time, they reduce the amount of work assigned to call center agents. With cutting-edge AI solutions, customer service and support teams can do more with less.\u00a0<\/p>\n Here are five ways artificial intelligence can become the hero during this recent pandemic.<\/p>\n No 1. Build Smarter Chatbots With\u00a0Intent\u00a0Recognition<\/strong>\u00a0<\/p>\n Chatbots and virtual agents reduce the burden placed on call-center representatives. They answer basic questions and guide site visitors to extra support materials. They\u2019re also good at addressing simple problems and collecting information, but often, too simple. Most of us have tried to describe a problem to a chatbot, only to get a response that didn\u2019t come close to solving it.\u00a0<\/p>\n What if chatbot software could understand exactly what you said? What if they could understand\u00a0nuance.\u00a0Then, they might achieve some level\u00a0of accuracy without redirecting to an agent. If\u00a0nothing else, they could gather more relevant details upfront and share that information with a\u00a0call center\u00a0employee.\u00a0\u00a0<\/p>\n Intent\u00a0recognition is a component of AI that addresses this issue head-on. Using natural language processing (NLP) tools, virtual agents can analyze communications to determine what customers are trying to say. More importantly,\u00a0NLP and AI platforms help chatbots recognize the user\u2019s\u00a0intent<\/a>\u00a0– that is, what they\u2019re trying to do.\u00a0\u00a0<\/p>\n You can phrase a specific question in any number of different ways, but the\u00a0intent\u00a0will be the same every time. Let\u2019s say you\u2019re trying to check the status of an upcoming flight. You might say:\u00a0<\/p>\n NLP and AI\u00a0help virtual agents understand the shared\u00a0intent<\/a>\u00a0behind all these prompts. Intelligent chatbots provide better customer experience without involving a\u00a0call center\u00a0agent.<\/p>\n No. 2. Guide Conversations\u00a0With\u00a0Dialogue\u00a0Management<\/strong>\u00a0<\/p>\n Part of what makes designing an effective chatbot so difficult is that the conversation could go in any number of directions. How do you plan for every prompt that a customer might give? The longer a conversation goes on, the more likely a chatbot is to run into dialogue it doesn\u2019t recognize or understand.\u00a0<\/p>\n\n