As AI becomes a reality in our daily lives, Collab has developed an AI-suite applied to the Contact Center, through 3 major functionalities:
Predictive Quality Monitoring (PQM)
This technology provides structure to an interaction's data (voice and/or chat) and defines patterns for performance evaluation. This helps evaluators on their evaluation process because the system automatically suggests which recordings are good or should be analyzed. These patterns can continuously be reinforced based on the evaluator's feedback, so the system keeps getting more and more accurate in its predictions.
Predictive Routing (PR)
This technology aims to direct a customer to the most suitable agent based on past interactions and affinity patterns. Every interaction is a valuable input to route the next one.
Self-learning bots (SLB)
This technology is based on Natural Language
Understanding and Sentiment Analysis. It is possible to
implement a full bot experience, or the bot can be used
alongside with human agents, so that in case some
interaction starts escaping the bot's control, it can be
handed over to a human agent. The bot can still be kept in
the loop and, while the human agent interacts, the bot
learns for future interactions. In this situation, the bot can
still keep suggesting answers to the agent, and based on the
agent's feedback to those inputs, the bot also learns.
How it works?
Insights are gathered from the CRM, the interaction history and the analytics engine. Then, we use Machine Learning to suggest:
interactions should be evaluated first (PQM)
is the best possible affinity between inbound customers and agents (PR)