Abstract
A novel system and techniques are presented herein for intelligent contact center call routing that leverages a multi-factor, real-time predictive model using live transcript analysis, call complexity, agent historic performance, and scheduling data. When a customer is waiting and their preferred agent is predicted to become available imminently, the system dynamically calculates and applies an optimal wait extension to enable a more meaningful and efficient connection. This approach optimizes routing by combining agent availability forecasting with customer preference and contextual data, resulting in improved call resolution, reduced average handling time, and enhanced customer satisfaction.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
Chidambaram, Rajarathinam; George, Jibin; B T, Gururaj; Ottayil, Riyad; and M L, Anil Kumar, "REAL-TIME PREFERRED AGENT AVAILABILITY PREDICTIONS FOR ENHANCED CONTACT CENTER ROUTING", Technical Disclosure Commons, (December 02, 2025)
https://www.tdcommons.org/dpubs_series/8974