AI is still a new and emerging technology. But with its ability to reduce operational costs, customize the customer experience, provide actionable analytics, and increase agent productivity, it is changing the way customer service organizations operate today. You can automate calls using artificial intelligence for call center operations as it enables you to manage repetitive and simple calls. This saves customer support agents a significant amount of workload, giving them time to focus on more complex issues.
The purpose of using artificial intelligence for call center operations is primarily to improve the customer experience. But it also frees agents from the time and energy spent on simple requests. AI can help customer support agents be more productive and have engaging and personally satisfying conversations. As a result, AI can automate simple tasks, provide in-depth analysis and help agents achieve efficient uptime. Here are a few scenarios that you can benefit from implementing artificial intelligence for call center operations of your business:
Predictive Call Routing
One of the most important contributions that artificial intelligence can make to the call center is the predictive call forwarding system to detect the problems of the customers and match them with the customer service agent who can best solve the problem. This technology examines customers' natural predispositions and communication habits, matching each query with the best-equipped agents to deal with specific types of customers and inquiries. This saves time for both customers and agents and allows tickets to be closed quickly and effectively.
Interactive Voice Response (IVR)
Interactive voice response (IVR) is a system where you respond to recorded questions, usually simple questions like name, account number. IVR service saves time and customer representative density especially for companies where routine questions such as hours, availability, payment or bank statement information that do not require a real call center representative take up a lot of time. Customers calling the call center today can complete their first inquiry in less than two minutes without having to wait to speak to a live representative, thanks to IVR.
Conversational Artificial Intelligence
Conversational AI, commonly known today as chatbots, allows a call center to have an AI-powered online chat option. Chatbots are one of the most popular channels for customer service inquiries. With chatbots, customers can quickly interact with website content live and use self-service support options. So they can solve their problems quickly without having to meet with a service representative face to face, and the burden on service teams is reduced.
Emotional Intelligence AI
Another form of artificial intelligence in call centers is emotional intelligence AI that can track customer sentiment during a phone call. This type of artificial intelligence can be used in countries with different language and cultural styles thanks to its trainable structure. Emotional AI can detect the caller's mood by analyzing the caller's tone of voice and the structure of the language. Thus, he can let the agent know how the customer is feeling during the call.
Artificial Intelligence Powered Suggestions
This technology also uses sentiment analysis to understand what a customer is trying to achieve and makes recommendations to the support agent for the best solutions. It is one of the key supports of artificial intelligence for call center operations to help reduce call times by providing a personalized, positive customer experience. The technology can analyze how many times a customer calls or talks about canceling their account, and then notifies the agent by giving that customer a customer risk score.
One of the scenarios where AI is most used in call centers is to provide in-depth analysis on call times, first resolution, and more. These technologies can spot trends and access customer data to have insight into whether customers had a positive or negative experience. AI can provide more comprehensive analytics, measuring customer sentiment, tone, and personality better than a human agent.