Implementing machine learning in contact centers offers improved agent efficiencies and better customer experiences.
The role of machine learning in contact centers
Resolvable Pain Points Machine learning deployment How ML helps
The need to repeat information
or use specific phrases
Conversational IVRs/
bots/virtual agents
Enables bots and virtual agents to recognize customer
speech, understand intent, and create an experience where
questions can be resolved without a live agent. If questions
do need to transfer to a live agent, all information is passed
on, eliminating need for customers to repeat themselves
Multiple transfers between
agents while trying to get help
Smart routing
Understands customer needs and sentiment quickly while
predicting outcomes of specific customer-agent interactions,
helping customers connect to the most effective agents
Unhappy call experiences Live-call analytics
Becomes possible for agents and supervisors to be alerted
immediately to issues in order to help agents meet customer
needs quickly
Long call resolution times Agent assist
Suggests next-best actions via pre-determined rules, best
past responses, or hands-free live searches to help agents
identify applicable resources quickly
Repeated call frustrations Post-call analytics
Analyzes calls to identify patterns in customer feedback,
agent performance, and overall quality management
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