Abstract:
A method, system and program product, the method comprising: determining a distribution of real agent performance from previous real agent performance data; determining a set of hypothetical agents with respective hypothetical agent performances APi ranging from a worst performance to a best performance; calculating for each of the set of hypothetical agents a posterior distribution taking into account actual results of a respective actual agent in multiple skills, using the distribution of real agent performance and the set of hypothetical agents with respective hypothetical agent performances APi, to obtain a total probability for each hypothetical agent of the set of the hypothetical agents; repeating calculating the posterior distribution steps for multiple of the hypothetical agents to obtain the respective total probabilities for the respective hypothetical agents; determining one hypothetical agent with a better value of total probability as the actual agent's most probable global performance. This method may also be applied to obtain caller global propensity.
Abstract:
A method, system and program product, the method comprising: obtaining for calls in one set of calls a respective pattern representing one or multiple different respective data fields; obtaining performance data for the respective patterns of the calls; performance data for agents in a set of agents; determining pattern performance sensitivity to agent performance comprising the pattern performance data correlated to agent performance data; matching a respective one of the agents from the set of agents to one of the calls based at least in part on the performance data for the one agent and on the pattern performance sensitivity to agent performance for the respective call.
Abstract:
Method, system and program product, for operating a call center system, the method comprising: obtaining performance data for agents in a set of agents; obtaining a respective abstracted data stream for multiple calls, each respective data stream having multiple different locations along the abstracted data stream representing multiple different respective fields, the meaning for the field data in the respective different locations for the different respective fields not known by the system; determining respective patterns for the respective data streams; obtaining performance data for the respective patterns; matching using a selected matching algorithm one of the agents from the set of agents to one of the calls based at least in part on the performance data for the respective pattern of the call and on performance data for the respective agents of the set of agents.
Abstract:
Method, system and program product, comprising: obtaining agent parameter data; percentiling agents based on the agent parameter data, to obtain an agent distribution of agent percentiles; partitioning callers based on criteria into partitions; obtaining caller propensity data; percentiling the callers based on propensity for an outcome to obtain a caller distribution; performing distribution compensation using one algorithm selected from an edge compensation algorithm applied to the distribution of agent percentiles or the distribution of the caller percentiles, near at least one distribution edge to provide edge compensation, and a topology altering algorithm applied to either or both of the agent distribution and the caller distribution to change one or more of the distributions to a different topology; and matching an agent to a caller in one of the partitions with a closest respective percentile, where one of the caller percentile or the agent percentile has been distribution compensated.
Abstract:
A method, system and program product, the method comprising: obtaining for each call in one set of calls a respective pattern representing multiple different respective data fields; obtaining performance data for the respective patterns of the calls; obtaining performance data for the respective agents; determining agent performance sensitivity to call pattern performance for agents in a set of agents comprising the agent performance data correlated to call performance data for the calls the agent handles; and matching a respective one of the agents from the set of agents to one of the calls based at least in part on the performance data for the respective pattern of the one call and on the agent sensitivity to call performance for the respective one agent of the set of agents.
Abstract:
Method, system and program product, comprising: obtaining agent parameter data; percentiling agents based on the agent parameter data, to obtain an agent distribution of agent percentiles; partitioning callers based on criteria into partitions; obtaining caller propensity data; percentiling the callers based on propensity for an outcome to obtain a caller distribution; performing distribution compensation using one algorithm selected from an edge compensation algorithm applied to the distribution of agent percentiles or the distribution of the caller percentiles, near at least one distribution edge to provide edge compensation, and a topology altering algorithm applied to either or both of the agent distribution and the caller distribution to change one or more of the distributions to a different topology; and matching an agent to a caller in one of the partitions with a closest respective percentile, where one of the caller percentile or the agent percentile has been distribution compensated.
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.
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 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.