公开(公告)号：US20200213447A1

公开(公告)日：2020-07-02

申请号：US16233516

申请日：2018-12-27

Applicant: Avaya Inc.

Inventor： Eyal Serero ,  Gal Netanel ,  Ronen Bar-Yoav ,  Roman Nekrashevich ,  Tamar Barzuza

IPC: H04M3/523 ,  H04M3/51 ,  G06Q10/06

Abstract: Contact centers often seek to provide the most effective agents for a particular communication. A communication may comprise a customer node and an agent node. In addition to selecting the particular agent node based on a skill of the agent or other static information, dynamic information may be received and processed to make a routing decision. For example, one agent may be presently located in a noisy area and a communication may be impeded by routing a call to a node associated with an agent in a noisy environment and a different agent node selected. Other dynamic inputs may include determining an agent's proximity to a resource likely required in order to successfully satisfy a purpose of the communication. Additionally, self-learning may be utilized in order to predict when a particular environmental factor is about to change and make routing decisions accordingly.

公开(公告)号：US10681214B1

公开(公告)日：2020-06-09

申请号：US16233516

申请日：2018-12-27

Applicant: Avaya Inc.

Inventor： Eyal Serero ,  Gal Netanel ,  Ronen Bar-Yoav ,  Roman Nekrashevich ,  Tamar Barzuza

IPC: H04M3/523 ,  G06Q10/06 ,  H04M3/51

Abstract: Contact centers often seek to provide the most effective agents for a particular communication. A communication may comprise a customer node and an agent node. In addition to selecting the particular agent node based on a skill of the agent or other static information, dynamic information may be received and processed to make a routing decision. For example, one agent may be presently located in a noisy area and a communication may be impeded by routing a call to a node associated with an agent in a noisy environment and a different agent node selected. Other dynamic inputs may include determining an agent's proximity to a resource likely required in order to successfully satisfy a purpose of the communication. Additionally, self-learning may be utilized in order to predict when a particular environmental factor is about to change and make routing decisions accordingly.