Systems and methods for routing callers to an agent in a contact center
View Patent ↗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.
1. A method for routing callers to agents in a call-center routing environment, the method comprising the acts of:
determining, by one or more computers, agent data comprising service skill data, demographic and psychographic data for an agent;
determining, by one or more computers, caller data comprising a service skill requirement, demographic and psychographic data for each one from a set of callers; and
matching, by one or more computers, by comparing via a pattern matching algorithm at least one caller from the set of callers to the agent based on the agent data and the caller data and based at least in part on increasing the chance of revenue generation; and
changing, by one or more computers, a connection priority of the one caller relative to the other callers in the set of callers to increase the chance of revenue generation.
2. The method of claim 1 , wherein the agent data comprises demographic data, and the demographic data comprises one of gender, race, age, education, accent, income, nationality, ethnicity, area code, zip code, marital status, job status, or credit score.
3. The method of claim 1 , wherein the caller data comprises demographic data, and the demographic data comprises one of gender, race, age, education, accent, income, nationality, ethnicity, area code, zip code, marital status, job status, or credit score.
4. The method of claim 1 , wherein the pattern matching algorithm comprises an adaptive correlation algorithm.
5. The method of claim 1 , further comprising training the pattern matching algorithm by correlating the chance of an optimal interaction against the agent data and the caller data, wherein the agent data and the caller data is determined from at least one historical contact between a caller and an agent.
6. The method of claim 1 , wherein the set of callers comprises a queue of callers.
7. A system for routing callers to agents in a call-center environment, the system comprising one or more computers configured with logic to:
determine, by the one or more computers, agent data comprising service skill data, demographic and psychographic data for an agent;
determine, by the one or more computers, caller data comprising a service skill requirement, demographic and psychographic data for each one from a set of callers; and
match, by one or more computers, by comparing via a pattern matching algorithm at least one caller from the set of callers to the agent based on the agent data and the caller data and based at least in part on increasing the chance of revenue generation; and
changing, by one or more computers, a connection priority of the one caller relative to the other callers in the set of callers to increase the chance of revenue generation.
8. The system of claim 7 , wherein the agent data comprises demographic data, and the demographic data comprises one of gender, race, age, education, accent, income, nationality, ethnicity, area code, zip code, marital status, job status, or credit score.
9. The system of claim 7 , wherein the caller data comprises demographic data, and the demographic data comprises one of gender, race, age, education, accent, income, nationality, ethnicity, area code, zip code, marital status, job status, or credit score.
10. The system of claim 7 , wherein the pattern matching algorithm comprises an adaptive correlation algorithm.
11. The system of claim 7 , further comprising training the pattern matching algorithm by correlating the chance of an optimal interaction against the agent data and the caller data, wherein the agent data and the caller data is determined from at least one historical contact between a caller and an agent.
12. The system of claim 7 , wherein the set of callers comprises a queue of callers.
13. Computer readable storage medium comprising computer readable instructions for carrying out, when executed by one or more computers, a method comprising the acts of:
determining, by the one or more computers, agent data comprising service skill data, demographic and psychographic data for an agent;
determining, by one or more computers, caller data comprising a service skill requirement, demographic and psychographic data for each one from a set of callers; and
matching at least one caller from the set of callers to the agent based on the agent data and the caller data;
matching, by one or more computers, by comparing via a pattern matching algorithm at least one caller from the set of callers to the agent based on the agent data and the caller data and based at least in part on increasing the chance of revenue generation; and
changing, by one or more computers, a connection priority of the one caller relative to the other callers in the set of callers to increase the chance of revenue generation.
14. The computer readable storage medium of claim 13 , wherein the agent data comprises demographic data, and the demographic data comprises one of gender, race, age, education, accent, income, nationality, ethnicity, area code, zip code, marital status, job status, or credit score.
15. The computer readable storage medium of claim 13 , wherein the caller data comprises demographic data, and the demographic data comprises one of gender, race, age, education, accent, income, nationality, ethnicity, area code, zip code, marital status, job status, or credit score.
16. The computer readable storage medium of claim 13 , wherein the pattern matching algorithm comprises an adaptive correlation algorithm.
17. The computer readable storage medium of claim 13 , further comprising training the pattern matching algorithm by correlating the chance of an optimal interaction against the agent data and the caller data, wherein the agent data and the caller data is determined from at least one historical contact between a caller and an agent.
18. The computer readable storage medium of claim 13 , wherein the set of callers comprises a queue of callers.