Teacher-Student Learning on Complexity in Intelligent Routing

arXiv:2402.15665v1 Announce Type: new
Abstract: Customer service is often the most time-consuming aspect for e-commerce websites, with each contact typically taking 10-15 minutes. Effectively routing customers to appropriate agents without transfers is therefore crucial for e-commerce success. To this end, we have developed a machine learning framework that predicts the complexity of customer contacts and routes them to appropriate agents accordingly. The framework consists of two parts. First, we train a teacher model to score the complexity of a contact …

abstract agents arxiv commerce complexity cs.ai cs.lg customer customers customer service e-commerce framework intelligent machine machine learning routing service success type websites