Customer Experience: A Multifaceted Metric
August 17, 2018
By Paula Bernier, Executive Editor, TMC
Customer experience is moving center stage in call centers and contact centers. Some studies even suggest it’s now the top strategic imperative in such environments.
But how do you measure contact center CX?
The answer is by using a combination of data gathered from real-time and recorded interactions with customers, and asking customers straight up for their opinions on how your organization and your staff members are doing in meeting their needs.
For the former, call center managers can listen in on select agent-customer conversations. They can also use automated systems to prompt them to join a call when certain sentiment is detected to see how agents handle such situations. Call center managers and quality assurance experts may also use systems and processes to record and analyze calls, and rate calls based on CX metrics.
That said, organizations should remember that customer experience is about more than just a person’s interaction with a call center agent. It’s also about the quality of the product itself, the extent to which the organization has already built a relationship with the caller, the experience the company provided (via the call center IVR, other agents, a website, or whatever other touch points) before the caller talked to the agent. So, to be fair, it’s important to consider all that. And it’s good to review process and not just people to seek CX improvement.
All of the above can help call centers improve their agent hiring efforts, coaching, internal toolsets, processes and scripts, training, and more.
So can voice of the customer efforts.
Keep your survey requests to customers to limited, and make the surveys themselves short. You don’t want them to suffer from survey exhaust. You can do that by carefully formulating your questions and only asking the ones you think will provide real insights in what you’re doing right and wrong.
Aggregating data from all of the above initiatives – as well as CRM-type data that looks at what customers are buying and discontinuing when and how – and then analyzing that aggregated data, can go a long way in better understanding customers and delivering truly strong customer experiences.
Edited by Maurice Nagle