Don’t Let Big Data Bog Down Your Contact Center

big data tunnel

Big Data: Helpful or Overwhelming?

U.S. call centers receive 45.4 billion calls per year. The average call costs $5.90, according to Zendesk, a customer service software company. Call centers collect all sorts of data on the customers who call, recording customers’ experiences from agent helpfulness to the online or in-store experience. Call center data systems often record call time, average wait for a call, pre-call survey responses, post-call survey responses, as well as the number of times a customer has called, the reasons they called, whether or not they were satisfied at the end of a call…the list goes on. However, having so much data can actually make it harder to see the relevant variables. And it’s easy to get hung up trying to fix problems that only affect a small number of calls.


Setting Priorities at Call Centers

The first step to streamlining the process of sorting through big data is deciding how managers will measure success of call center agents. Is it selling the most products? Is it selling the customer a product they will love and will use for a long time? Is it fixing every customer issue? Is it pleasing the customer? Is it fulfilling legal obligations? Each of these goals will lead to a different optimization strategy. Knowing how managers are going to measure agent success, having specific goals in mind, like saves rates and complaints-to-conversions, is the first step. One metric that a number of call center managers are paying close attention to when developing agent training materials and strategies to improve customer experience is the Net Promoter Score, which I’ve written about before.


Balancing First Call Resolution Rate and Average Handle Time

When I develop a custom training program for a call center, I always aim to balance the FCR and AHT. FCR is the percentage of time the issue is resolved in the first call. Obviously if a customer continues to call multiple times for the same issue, it will hurt the efficiency of the center. This can also lead to negative user experience. Managing the AHT is very important as well. The shorter average call time, the more calls a single agent can take. However, adequately addressing the customers’ issues will take a certain amount of time. So how can you speed up the call while still addressing customer concern adequately?

Call center agents need a process, or a set of tools, that allows them to quickly establish rapport with customers, while discovering primary and hidden concerns, so that they can efficiently offer solutions and close the call.

Managing Customer Satisfaction with the Quality Conversation

I provide a customizable training program for call center agents and their managers based on a technique I developed, the Quality Conversation. With the Quality Conversation, agents have a reliable technique that lowers AHT and increases FCR. The Quality Conversation is not just a call script—it’s a technique that helps agents discover crucial information and effectively solve problems.


Big data is certainly a boon to the modern call center since we now have quicker access to real-time data on agent performance and customer satisfaction. But it can often become overwhelming and unhelpful without the right analysis and strategies in place to make the most of that data. I can help you sift through the numbers and create a customized strategy to help your agent team win more sales and increase loyalty.

Do your agents have a Quality Conversation with every customer they talk to? Let’s discuss your organization’s challenges in a Quality Conversation of our own today! Please email me at or call 678-548-1775 to set up the first free strategy session.