Avaya Technology LLC

Avaya Inc.

Liveops, Inc.

Keith R McFarlane

Andrew Derek Flockhart

Lucinda M Sanders

Darryl J Maxwell

Paul Lawrence Richman

Sanjay Mathur

Gary S King

David L Bauer

Wendy S Cook

Kieron Lawson

Steve R Russell

Robert Alan Stewart

An method of pivoting a customer among synchronous and asynchronous communications channels during a communication session.

Multi-channel pivoting

In a customer contact center ( ), a plurality of customers' communications are serviced simultaneously by one resource ( ) (agent or port). A conferencing function ( ) connects the plurality of customers ( ) to the one resource and/or to each other. When a resource becomes available, a batch service function ( ) determines ( ), for each skill of the resource, the value to the contact center of having the resource presently serve communications needing that skill, and uses the conferencing function to conference ( ) a plurality of communications needing the skill having the highest value with the resource. The conference connection may be listen-only, listen-and-talk, or listen-only/then listen-and-talk.

Customer service by batch

The system for integrating agent database access skills in call center agent assignment applications dynamically generates data indicative of an agent's effective skill level by mapping the agent's acquired skills into their augmented skills representative of their ability to use the various automated resources that are required to satisfy the customer's request. The determined effective skill level is automatically updated as changes in the agent's effective skills are measured. In order to distribute work among the agents based upon agent skill levels, there must be a measure of each agent's competence with a particular skill. The pool of agents is divided into categories of those who must use guided problem solving tools to service a customer request, those who can address issues beyond the scope of the guided problem solving tool, and those who exhibit various levels of efficacy in using the guided problem solving tool. The system for integrating agent database access skills in call center agent assignment applications automatically computes an agent's effective skill level, which is a term used herein to describe a metric indicative of the agent's overall knowledge management ability consisting of both acquired skills and augmented skills.

System for automatically assigning skill levels to multiple skilled agents in call center agent assignment applications

The present integrated work management engine for customer care orchestrates all forms of work relating to the servicing of customer requests across the entire business enterprise. This integrated work management engine brings together all types of disparate communication system components, applications and information storage systems so the business which provides the customer care via these systems can respond to their customer requests in a unified, efficient and effective manner. The integrated work management engine also integrates the real time operation of the front office customer communications and the batch data processing mode of the back office. The integrated work management engine accepts work through multiple access channels, where each work request is automatically mapped to a process flow that specifies the task associated with the handling of the particular work item. The integrated work management engine uses resource selection algorithms to select the customer agent who is best equipped to handle the next step of the work request where customer data is accessed, and customer case files are updated through the fulfillment process. The selected customer agent views the customer information, process information, forms, and performance statistics on their desktop terminal device through an API set that is tightly coupled to the integrated work management engine.

Integrated work management engine for customer care in a communication system

The flow of work items ( ) through a workflow process ( ) is optimized by repeatedly reordering (FIG. ) work items enqueued in inbox queues ( ) of workflow process tasks ( ) to maximize results according to a given business strategy expressed through target times. Each enqueued work item has an associated in-queue rating (IQR ) that represents the number of queue positions ( ) that the work item can be retarded or needs to be advanced to meet its target time. When a work item enters a queue and whenever a work item changes its queue position, its IQR is computed. An optimization function is then performed ( ) on the queue to determine an order of the enqueued work items that optimizes a metric of those work items that may fail to meet their target times. The work items in the queue are then reordered ( ) accordingly.

Workflow-scheduling optimization driven by target completion time

System for integrating agent database access skills in call center agent assignment applications

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Denver, CO, United States of America

Keith R McFarlane