Call Center Management Featured Article
A Strategy to Put Advanced Analytics Data to Use
The business world is mad for analytics and contact centers should be the foremost recipient of the knowledge. Once upon a time, performance metrics in the contact center were available only long after the fact, so managers were powerless to do much but hand out a stern lecture and a bit of remedial training. The customer who may have been affected by the bad service was probably long gone.
Analytics are everywhere today, and in the contact center, they can actually salvage customer relationships, sometimes in real time, according to a recent article by McKinsey & Co’s Guy Benjamin, Jeff Berg, Avinash Chandra Das, and Vinay Gupta.
“The good news is that basic data and analytics tools are becoming standard practice in call centers,” wrote the authors. “And while that is a solid first step, most organizations are likely not taking full advantage of the technology, meaning they are not applying advanced analytics in ways that truly put the customer first.”
Call center analytics can be used to do many things, including reduce average handle time, increase self-service containment rates, cut employee costs and boost the conversion rate on service-to-sales calls while at the same time improving customer satisfaction and employee engagement. So where do companies still go wrong despite the addition of analytics to their contact center solutions? There are a variety of missteps that can be made:
Poorly integrated data. To make the most out of analytics, companies need to ensure that the analytics solution has access to all the data necessary. When data is siloed and/or poorly integrated, the AI is working with an incomplete set of information, so it’s likely to come to incorrect conclusions.
No insight into action. Generating an analysis of call center data is one thing…but it’s useless unless it’s put into action.
“Most organizations, for instance, run voice-of-the-customer analytics to calculate first-call resolution (FCR) and customer satisfaction metrics, but they don’t use that customer feedback to redesign processes or take other steps to make a more transformative impact,” wrote the McKinsey analysts. “A common theme across these issues is that operations managers simply do not know what to do with analytics.”
To make the most of their analytics data, companies need to outline a clear vision for how the data is collected, analyzed and disseminated, who it’s shared with, and who has responsibility for making decisions and acting on it. Without this strategy, analytics solutions are just collecting numbers that won’t be of any use to anyone.