Online consignment company ThredUP sells secondhand women’s and children’s clothing to a wide range of customers. Along with “like new” secondhand finds, it touts a crackerjack support team and strives to make excellent customer service a top priority.
Yet, ThredUP was encumbered by its tedious manual ticket classification process, which required some of its most senior agents to look at, classify, and sort up to 1,200 tickets a day. To solve these issues, the ThredUP team turned to AnswerIQ.io to implement the AnswerIQ Triage Application.
In this case study eBook, you will learn:
How the AnswerIQ machine learning tools use intelligent automation to classify and route tickets.
How machine learning assimilates the patterns and past actions of human service agents.
How intelligent automation tools can improve agent satisfaction by redirecting them toward more complex and creative problem-solving tasks.
Why improved classification can reduce agent response times, and why that matters to the customer experience.
Download this eBook now to learn how the AnswerIQ Triage Application impacted ThredUP’s support processes, consistency, and customer experience.