Call centers can generate a lot of data, but it’s useless unless companies are willing to measure the right data and act on it, according to Domo CEO Steve Wellen.
“Ten years ago, no one wanted to call your customer service number. Contact centers existed out of necessity, but deriving real value from them was tedious,” Wellen wrote in a company blog post.
He pointed to companies like the Amazon-owned Zappos where customers actually stayed on the line because they wanted to, not just because they were put on hold.
These days, just about every interaction a customer service agent has with a caller is measured and captured. With large call centers, the sheer volume of data that agents generate can prevent a company from taking effective action with it. All of the metrics can lead to “data overload.
For Wellen, this is where a little planning before implementing call center analytics can go a long way.
He proposes that businesses consider three steps before implementing data methods. First they should have clear business goals. Second, they should have clear strategies and actions that will help them achieve these goals. Finally, they should choose the right metrics that show incremental progress toward their goals.
“The process sounds simple—even simplistic. But it’s the small steps that help you keep your data in perspective and drive real value,” Wellen wrote. “These steps help you make better decisions about which data sources you need in order to measure real impact. Once you narrow down your data, you can amplify the impact that it has on your organization.”
The next step for Wellen is getting the data to the right people so they can take action. He’s not exactly unbiased, as his company depends on visualizing data. He still pointed out that customer service representatives need data as much as managers to do their jobs effectively.