SYSTEM AND METHOD FOR AN OPTIMIZED, SELF-LEARNING AND SELF-ORGANIZING CONTACT CENTER

摘要

A system and method for an optimized, self-learning and self-organizing contact center has been developed. This system and method uses principles and tools of information theory, including the latent Dirichlet allocation which reduces information to specific predetermined topics and a distribution of topic related words to infer its hidden, generative underpinnings so to self-organize a contact center, infer its desired electronic versus human make up, and optimally route all customer requests to an electronic resource or a specific human agent best suited to respond to the request for maximal business value per interaction. The system can also infer and respond to changes in customer call center usage.

主权项

1. A system for an optimized, self-learning and self-organizing contact center comprising:
a topic based routing module stored in a memory of and operating on a processor of a computing device; an interaction information optimization module stored in a memory of and operating on a processor of a computing device; and wherein the topic based routing module:
(a) receives requests for information or assistance by a plurality of means;(b) infers the topic distribution of the request based upon information theory based algorithms;(c) routes the request to the contact center resource best suited to respond to the request; and wherein the interaction information optimization module:
(d) monitors all communication in to and out of the contact center;(e) analyzes communication streams for all topics and topic related identifiers;(f) creates optimized relationships between identifiers present in analyzed communications and business value related topics attached to contact center resources using information theory algorithms and machine learning.