DYNAMIC METRIC OPTIMIZATION IN PREDICTIVE BEHAVIORAL ROUTING

Methods for optimizing the routing of customer communications include receiving a customer communication; identifying a customer associated with the customer communication; accessing a profile of the identified customer to determine customer data; receiving normalized customer metric scores for a plurality of customer metrics; identifying available agents; accessing a profile of each available agent to determine agent data; predicting interaction outcome metric values for a plurality of customer metrics based on the customer data and the agent data; normalizing the predicted interaction outcome metric values; calculating, in real-time, an aggregate agent-customer pairing score for each available agent; selecting a responding agent from the available agents with the highest aggregate agent-customer pairing score; and providing a routing recommendation to a communication distributor to route the customer communication to the responding agent with the highest aggregate agent-customer pairing score.