Balancing Automation and Human Service
It is essential to leverage technology solutions to ensure quality customer experiences. With the evolution of artificial intelligence (AI) and machine learning (ML), organizations can take a more comprehensive approach to analyzing customer interactions and streamlining contact centre operations.
While AI is a reliable means to address mundane, repetitive tasks such as checking an account balance or pausing a subscription, not all customer interactions are that simple.
When it comes to more complex problems, customers continue to seek out human assistance. In a recent report, 82% of respondents claimed to want the reassurance only a live agent could offer when asked why they escalated their issue.
That’s why a fully automated approach to CX won’t be successful. When it comes to empathy and resolution of complex issues, live agents are irreplaceable.
Machine-learned results must be considered within the context of the customer’s perspective, as well as agent resources, technology, training, and empowerment to truly bridge the insight-to-action gap.
When that perfect balance is found, AI and ML are powerful tools that make customer interactions more humane.
The H.U.M.A.N.E Approach to CX
ML makes it possible to intelligently cluster the intent, action, and emotion of customer interactions to uncover conversational meaning more effectively than humans can.
From there, AI can help prioritize where to place customer service and CX attention, empowering customer service and call centre agents with actionable guidance derived from behavioral data and insights.
Leverage AI to uncover the critical customer and employee insights management needs to transform, improve, and change business strategy.
Routinely correlating conversational context with machine-learned insights reveals unanticipated challenges, and, in turn, opportunities for agents to better support customers.
Organizations must continue to invest in their workforce and use AI to help agents master their jobs. The more you coach and enable employees with data-supported guidance, the better they will perform, leading to stronger customer and employee satisfaction, better agent scores, and higher compensation.
Deploy AI and conversation analytics to analyze the context of a situation and provide both real-time and post-engagement coaching, guidance, and insights.
In situations where customers call or send messages that do not have an applicable script or answer, AI can suggest the best option based on historical and situational analyses, helping customer service teams navigate complex requests, quickly solve problems, and offer solutions that meet customer needs.
By providing a data-fueled customer perspective, agents can be empowered to offer appropriate empathy, guide conversations with issue-resolution ownership, and intelligently react to emotional expressions with techniques that reinforce brand perception.This blog post has been re-published by kind permission of CallMiner – View the Original Article
For more information about CallMiner - visit the CallMiner Website
Call Centre Helper is not responsible for the content of these guest blog posts. The opinions expressed in this article are those of the author, and do not necessarily reflect those of Call Centre Helper.