US 12,425,519 B2
Systems and methods for relative gain in predictive routing
Emir Muñoz, Galway (IE); Apostolos Galanpoulos, Galway (IE); Greg Toth, Galway (IE); David Farrell, Galway (IE); and Maciej Dabrowski, Galway (IE)
Assigned to Genesys Cloud Services, Inc., Menlo Park, CA (US)
Filed by Genesys Cloud Services, Inc., Menlo Park, CA (US)
Filed on Aug. 4, 2023, as Appl. No. 18/365,577.
Claims priority of provisional application 63/433,538, filed on Dec. 19, 2022.
Prior Publication US 2024/0205336 A1, Jun. 20, 2024
Int. Cl. H04M 3/00 (2024.01); H04M 3/51 (2006.01); H04M 3/523 (2006.01)
CPC H04M 3/5233 (2013.01) [H04M 3/5175 (2013.01); H04M 3/5238 (2013.01); H04M 2203/402 (2013.01)] 16 Claims
OG exemplary drawing
 
1. A method of leveraging relative gain in predictive routing of interactions to contact center agents, the method comprising:
identifying an interaction to be routed to a contact center agent;
determining a predictive routing score for each prospective contact center agent of a plurality of prospective contact center agents to which the interaction can be routed based on a historical performance of each prospective contact center agent;
determining a relative gain for each prospective contact center agent based on an interaction class of the interaction, an agent class performance of the prospective contact center agent, and an agent value of the prospective contact center agent, wherein the relative gain of a respective contact center agent is indicative of a relative optimization improvement of routing the interaction to the respective contact center agent relative to another of the prospective contact center agents;
ranking the prospective contact center agents based on the associated predictive routing score and the associated relative gain for each prospective contact center agent;
selecting the contact center agent of the prospective contact center agents based on the ranking of the prospective contact center agents;
routing the interaction to the selected contact center agent;
determining the interaction class of the interaction in response to identifying the interaction to be routed to the contact center agent;
identifying a prospective interaction class;
determining an average handle time and an agent performance rank of each contact center agent for the identified prospective interaction class based on historical performance data of each contact center agent;
determining whether relative gain criteria are satisfied based on the average handle time and the agent performance rank of each contact center agent for the identified prospective interaction class; and
defining the prospective interaction class as an interaction class for relative gain analysis in response to determining that the relative gain criteria are satisfied.