Abstract: Techniques for behavioral pairing in a task assignment system are disclosed. In one particular embodiment, the techniques may be realized as a method for behavioral pairing in a task assignment system comprising: determining, by at least one computer processor communicatively coupled to and configured to operate in the task assignment system, a priority for each of a plurality of tasks; determining, by the at least one computer processor, an agent available for assignment to any of the plurality of tasks; and assigning, by the at least one computer processor, a first task of the plurality of tasks to the agent using a task assignment strategy, wherein the first task has a lower-priority than a second task of the plurality of tasks.
Type:
Application
Filed:
January 15, 2021
Publication date:
May 6, 2021
Applicant:
Afiniti, Ltd.
Inventors:
Ittai KAN, Zia CHISHTI, Vikash KHATRI, James Edward ELMORE
Abstract: Techniques for behavioral pairing in a task assignment system are disclosed. In one particular embodiment, the techniques may be realized as a method for behavioral pairing in a task assignment system comprising: determining, by at least one computer processor communicatively coupled to and configured to operate in the task assignment system, a priority for each of a plurality of tasks; determining, by the at least one computer processor, an agent available for assignment to any of the plurality of tasks; and assigning, by the at least one computer processor, a first task of the plurality of tasks to the agent using a task assignment strategy, wherein the first task has a lower-priority than a second task of the plurality of tasks.
Type:
Application
Filed:
January 15, 2021
Publication date:
May 6, 2021
Applicant:
Afiniti, Ltd.
Inventors:
Ittai KAN, Zia CHISHTI, Vikash KHATRI, James Edward ELMORE
Abstract: Techniques for estimating expected performance of a task assignment strategy in a task assignment system are disclosed. In one particular embodiment, the techniques may be realized as a method comprising receiving, by at least one computer processor communicatively coupled to a task assignment system, a plurality of historical agent task assignments; determining, by the at least one computer processor, a sample of the plurality based on a strategy for pairing agents with tasks; determining, by the at least one computer processor, an expected performance of the strategy based on the sample; outputting, by the at least one computer processor, the expected performance; and optimizing, by the at least one computer processor, the performance of the task assignment system based on the expected performance.
Abstract: Method, system and program product, comprising obtaining agent performance data; ranking, agents based the agent performance data; dividing agents into agent performance ranges; partitioning callers based on criteria into a set of partitions; determining for each partition an outcome value for a first agent performance range and a second agent performance range; calculating for the partitions a respective outcome value difference indicator based on the outcome value for the first agent performance range and the outcome value for the second agent performance range for the partition; matching a respective agent to a respective caller in one of the partitions, based on the outcome value difference indicators for the partitions.
Abstract: Methods, systems, and articles of manufacture for ranking individuals in a contact center system including ranking a first individual in a set of individuals based on relative amounts of data for the first individual and one or more other individuals in the set of individuals.
Abstract: Techniques for estimating expected performance of a task assignment strategy in a task assignment system are disclosed. In one particular embodiment, the techniques may be realized as a method comprising receiving, by at least one computer processor communicatively coupled to a task assignment system, a plurality of historical agent task assignments; determining, by the at least one computer processor, a sample of the plurality based on a strategy for pairing agents with tasks; determining, by the at least one computer processor, an expected performance of the strategy based on the sample; outputting, by the at least one computer processor, the expected performance; and optimizing, by the at least one computer processor, the performance of the task assignment system based on the expected performance.
Abstract: Techniques for behavioral pairing in a dispatch center system are disclosed. In one particular embodiment, the techniques may be realized as a method for behavioral pairing in a dispatch center system comprising determining, by at least one computer processor communicatively coupled to and configured to operate in the dispatch center system, a dispatch request for a customer; determining, by the at least one computer processor, a plurality of field agents available to service the customer's dispatch request; determining, by the at least one computer processor, a model of preferred field agent-customer pairings based at least in part on historical field agent-customer interaction outcome data; selecting, by the at least one computer processor, one of the plurality of field agents based on the model; and outputting, by the at least one computer processor, the selection to facilitate dispatching the selected field agent to the customer.
Abstract: Techniques for workforce management in a contact center system are disclosed. In one particular embodiment, the techniques may be realized as a method for workforce management in a contact center system comprising generating historical workforce data regarding an agent workforce capacity of the contact center system, and initiating an increase or decrease to an agent workforce of the contact center system based at least in part on the historical workforce data to increase an amount of choice among available agents or waiting contacts.
Abstract: Techniques for adapting behavioral pairing to runtime conditions in a task assignment system are disclosed. In one particular embodiment, the techniques may be realized as a method for adapting behavioral pairing to runtime conditions in a task assignment system comprising: determining, by at least one computer processor communicatively coupled to and configured to operate in the task assignment system, at least two pairing models for assigning tasks in the task assignment system; monitoring, by the at least one computer processor, at least one parameter of the task assignment system; and selecting, by the at least one computer processor, one of the at least two pairing models based on a value of the at least one parameter.
Abstract: Techniques for case allocation are disclosed. In one particular embodiment, the techniques may be realized as a method for case allocation comprising receiving, by at least one computer processor, at least one case allocation allocated using a first pairing strategy, and then reassigning, by the at least one computer processor, the at least one case allocation using behavioral pairing.
Abstract: Techniques for behavioral pairing in a task assignment system are disclosed. In one particular embodiment, the techniques may be realized as a method for behavioral pairing in a task assignment system comprising: determining, by at least one computer processor communicatively coupled to and configured to operate in the task assignment system, information about a task waiting for assignment in the task assignment system; and selecting, by the at least one computer processor, a hold activity from a plurality of hold activities for the task based on the information about the task, wherein the selected hold activity is expected to improve performance of the task assignment system.
Abstract: Techniques for behavioral pairing in a multistage task assignment system are disclosed. In one particular embodiment, the techniques may be realized as a method for behavioral pairing in a multistage task assignment system comprising: determining, by at least one computer processor communicatively coupled to and configured to operate in the multistage task assignment system, one or more characteristics of a task; determining, by the at least one computer processor and based at least on the one or more characteristics of the task, a sequence of agents; and pairing, by the at least one computer processor, the task with the sequence of agents.
Abstract: Techniques for benchmarking performance in a contact center system are disclosed. In one particular embodiment, the techniques may be realized as a method for benchmarking contact center system performance comprising cycling, by at least one computer processor configured to perform contact center operations, between a first contact-agent pairing strategy and a second contact-agent pairing strategy for pairing contacts with agents in the contact center system; determining an agent-utilization bias in the first contact-agent pairing strategy comprising a difference between a first agent utilization of the first contact-agent pairing strategy and a balanced agent utilization; and determining a relative performance of the second contact-agent pairing strategy compared to the first contact-agent pairing strategy based on the agent-utilization bias in the first contact-agent pairing strategy.
Abstract: Techniques for behavioral pairing in a contact center system are disclosed. In one particular embodiment, the techniques may be realized as a method for behavioral pairing in a contact center system comprising: determining, by at least one computer processor communicatively coupled to and configured to operate in the contact center system, a plurality of contacts available for connection to an agent; determining, by the at least one computer processor, a plurality of preferred contact-agent pairings among possible pairings between the agent and the plurality of contacts; selecting, by the at least one computer processor, one of the plurality of preferred contact-agent pairings according to a probabilistic network flow model; and outputting, by the at least one computer processor, the selected one of the plurality of preferred contact-agent pairings for connection in the contact center system.
Type:
Application
Filed:
November 9, 2020
Publication date:
February 25, 2021
Applicant:
Afiniti, Ltd.
Inventors:
Ittai KAN, Michael Richard KLUGERMAN, Blake Jay RILEY