公开(公告)号：US20240214493A1

公开(公告)日：2024-06-27

申请号：US18121237

申请日：2023-03-14

Applicant: GENESYS CLOUD SERVICES, INC.

Inventor： TALEB JOHN MOUSLMANI ,  THERESE M. FERRIS ,  TRAVIS DALE COLEMAN ,  MATHEW SCOTT DANISH

IPC: H04M3/523 ,  G06Q10/0631 ,  H04M3/493 ,  H04M3/51

CPC classification number: H04M3/5238 ,  G06Q10/06311 ,  H04M3/493 ,  H04M3/5175 ,  H04M3/5231 ,  H04M2203/402 ,  H04M2203/551 ,  H04M2203/558

Abstract: A method for synchronizing agent staffing and customer call volume within a contact center estimates the number of agents to staff the contact center during a future time and uses historical data to estimate the number of customer calls anticipated during the future time. The method performs a first comparison of the number of agents with the anticipated customer calls volume for the future time and then determines at least one preferred contact-center callback window. The method communicates with the customer to request at least one preferred customer-selected callback time and performs a second comparison to provide the customer with a suggested callback time that is selected to synchronize the customer call volume with the number of agents, the preferred contact-center callback window, and the preferred customer-selected callback time to improve the customer's experience and efficiency of the contact center.

公开(公告)号：US20240283868A1

公开(公告)日：2024-08-22

申请号：US18129192

申请日：2023-03-31

Applicant: GENESYS CLOUD SERVICES, INC.

Inventor： THERESE M. FERRIS ,  TRAVIS DALE COLEMAN ,  MATHEW SCOTT DANISH ,  TALEB JOHN MOUSLMANI

IPC: H04M3/51 ,  G06F40/211 ,  G06F40/253 ,  G06F40/284 ,  G06F40/35 ,  G10L13/02 ,  G10L15/18 ,  G10L15/22 ,  H04L51/02 ,  H04L51/216

CPC classification number: H04M3/5175 ,  G06F40/211 ,  G06F40/253 ,  G06F40/284 ,  G06F40/35 ,  G10L13/02 ,  G10L15/1815 ,  G10L15/1822 ,  G10L15/22 ,  H04L51/02 ,  H04L51/216 ,  H04M3/5191 ,  G10L2015/088 ,  H04M2201/39 ,  H04M2201/40 ,  H04M2203/403

Abstract: A method for generating a customer bot and using the customer bot to train agents, where a first process generates the customer bot and a second process uses the customer bot to train the agents. The first process includes: gathering conversation data; mining intents from the conversation data; constructing, from the mined intents, a dialog engine simulating an interaction type; uploading the customer bot to an automated training module for use thereby; and periodically repeating the previous steps so to update the customer bot with recent conversation data. The second process includes: monitoring for triggering events; initiating the training by initiating a virtual communication to a user device of a first agent; connecting the virtual communication to the customer bot; conducting a simulated interaction; and analyzing one or more statements received from the first agent to derive a performance assessment.