Systems and methods for routing callers to an agent in a contact center
First Claim
1. A computer-implemented method for improving performance in a contact center system, the method comprising:
- collecting, via at least one computer processor configured to operate in the contact center system, a plurality items of agent data for each agent in a set of agents comprising demographic data and/or psychographic data and agent grades;
collecting, via the at least one computer processor, at least one caller data for a caller comprising demographic data and/or psychographic data;
generating, via the at least one computer processor, a computer model reflecting predicted chances of an optimal interaction occurring between the caller and each of the agents in the set of agents using the agent data and the caller data;
matching and connecting, via the at least one computer processor, the caller to one of the agents based at least in part on the predicted chances of the optimal interaction from the computer model to increase the chance of an optimal interaction;
cycling, via the at least one computer processor, between using the computer model and a different algorithm to match and connect the caller to one of the agents;
generating, via the at least one computer processor, data for display on a visual computer interface screen measuring results of the matching and connecting using the computer model and results of the matching and connecting using the different algorithm; and
setting, via the at least one computer processor, times when the matching and connecting using the computer model is cycled on and when it is cycled off to provide a degree of randomness to achieve improved contact center system performance via agent learning.
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Abstract
Methods are disclosed for routing callers to agents in a contact center, along with an intelligent routing system. One or more agents are graded on achieving an optimal interaction, such as increasing revenue, decreasing cost, or increasing customer satisfaction. Callers are then preferentially routed to a graded agent to obtain an increased chance at obtaining a chosen optimal interaction. In a more advanced embodiment, caller and agent demographic and psychographic characteristics can also be determined and used in a pattern matching algorithm to preferentially route a caller with certain characteristics to an agent with certain characteristics to increase the chance of an optimal interaction.
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Citations
34 Claims
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1. A computer-implemented method for improving performance in a contact center system, the method comprising:
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collecting, via at least one computer processor configured to operate in the contact center system, a plurality items of agent data for each agent in a set of agents comprising demographic data and/or psychographic data and agent grades; collecting, via the at least one computer processor, at least one caller data for a caller comprising demographic data and/or psychographic data; generating, via the at least one computer processor, a computer model reflecting predicted chances of an optimal interaction occurring between the caller and each of the agents in the set of agents using the agent data and the caller data; matching and connecting, via the at least one computer processor, the caller to one of the agents based at least in part on the predicted chances of the optimal interaction from the computer model to increase the chance of an optimal interaction; cycling, via the at least one computer processor, between using the computer model and a different algorithm to match and connect the caller to one of the agents; generating, via the at least one computer processor, data for display on a visual computer interface screen measuring results of the matching and connecting using the computer model and results of the matching and connecting using the different algorithm; and setting, via the at least one computer processor, times when the matching and connecting using the computer model is cycled on and when it is cycled off to provide a degree of randomness to achieve improved contact center system performance via agent learning. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18)
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19. An intelligent routing contact center system, the system comprising:
at least one computer processor configured to operate in the contact center system, wherein the at least one computer processor is further configured to; collect a plurality items of agent data for each agent in a set of agents comprising demographic data and/or psychographic data and agent grades; collect at least one caller data for a caller comprising demographic data and/or psychographic data; generate a computer model reflecting predicted chances of an optimal interaction occurring between the caller and each of the agents in the set of agents using the agent data and the caller data; match and connect the caller to one of the agents based at least in part on the predicted chances of the optimal interaction from the computer model to increase the chance of an optimal interaction; cycle between using the computer model and a different algorithm to match and connect the caller to one of the agents; generate data for display on a visual computer interface screen measuring results of the matching and connecting using the computer model and results of the matching and connecting using the different algorithm; and set times when the matching and connecting using the computer model is cycled on and when it is cycled off to provide a degree of randomness to achieve improved contact center system performance via agent learning. - View Dependent Claims (20, 21, 22, 23, 24, 25, 26, 27, 28)
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29. An article of manufacture for improving performance in a contact center system comprising:
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a non-transitory computer processor readable medium; and instructions stored on the medium; wherein the instructions are configured to be readable from the medium by at least one computer processor configured to operate in the contact center system and thereby cause the at least one computer processor to operate so as to; collect a plurality items of agent data for each agent in a set of agents comprising demographic data and/or psychographic data and agent grades; collect at least one caller data for a caller comprising demographic data and/or psychographic data; generate a computer model reflecting predicted chances of an optimal interaction occurring between the caller and each of the agents in the set of agents using the agent data and the caller data; match and connect the caller to one of the agents based at least in part on the predicted chances of the optimal interaction from the computer model to increase the chance of an optimal interaction; cycle between using the computer model and a different algorithm to match and connect the caller to one of the agents; generate data for display on a visual computer interface screen measuring results of the matching and connecting using the computer model and results of the matching and connecting using the different algorithm; and set times when the matching and connecting using the computer model is cycled on and when it is cycled off to provide a degree of randomness to achieve improved contact center system performance via agent learning. - View Dependent Claims (30, 31, 32, 33, 34)
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Specification