Automating responses with zero-touch from agents is the ultimate goal for most businesses as there is no human cost attached to handling the ticket. After a period of studying tickets, AI can begin automatically responding to tickets and issues like refunds, password resets, package tracking, and other common tickets, prime for automation. Once the AI system has reached a predetermined confidence threshold (usually 70 percent or more) it can begin automating tickets, relieving agents from repetitive tasks, and enabling them to spend more time offering individualized customer care.
By sifting through or “mining” ticket history data, machine learning organizes and finds relationships between all of the seemingly disparate pieces of data—relationships that predictive analytics engines can then use to intelligently optimize your existing workflows. Future tickets can be routed automatically and with great precision to the agents with the ability to close them in the least amount of time.