It’s safe to argue that FCR (First Contact Resolution/First Call Resolution) is the single most important metric in a call center. Not only does an improved FCR rate help reduce costs (fewer callbacks means less overhead), when a call center focuses on improving FCR their customer satisfaction score also tends to improve alongside it. Think about it—when an agent resolves a caller’s service or sales issue the first time around (bonus points if they don’t have to transfer the call to another agent!) that customer walks away from the exchange with no more issue and a more positive opinion of your brand. A 1% increase in FCR means a 1% decrease in call volume and 1% increase in CSAT! Depending on how large your enterprise’s contact center is, 1% could mean hundreds or even thousands of calls and customers.
But if FCR is so important why do so many contact centers have such a hard time measuring it accurately? There are a number of technologies out there designed to track, measure, and improve FCR and almost every call center has implemented an FCR initiative at some point or another. So why has no one figured it out yet?
Accurate FCR has to account for every time that customer called.
Keep in mind that a customer can call from their mobile phone, home phone, someone else’s phone, the phone from their computer, or any other phone that isn’t associated with their account in your call center. In order to accurately track FCR your system needs to be able to string all those call sequences together and understand that they came from one customer, not five different customers. If your system doesn’t string them together suddenly your FCR is trying to account for 5 unique interactions and their outcomes. In reality, a customer might have started the call on their mobile phone and then switched to the home phone after they accidentally hung up while on hold. Or maybe they have to use the calling feature on their computer because they are overseas, even though their first call two days came from their home line.
Accurate FCR relies on accurate contact reasoning to separate repeat calls from new issues.
According to an Enkata survey, fewer than 10% of call center managers said they were able to answer the question “why do your customers call?” with any certainty. Over 70% of call centers capture call reasons at some level, but only 7% of those companies actually trust their findings! If you cannot accurately define why a customer is calling how you effectively measure FCR? Are they calling because the exact same problem wasn’t resolved the first time? Did a secondary issue (that maybe the agent should have foreseen) pop up? Or is this customer calling for a completely different reason?
For instance, in the contact center for a cable provider is the customer calling because they are still getting charged for a package they unsubscribed from last month? Are they calling because the agent accidentally unsubscribed them from the wrong package? Or are they calling because they want to add a second box in their house? If you don’t know why a customer is calling you can’t accurately determine FCR.
The only way to know for certain why a customer called is to track and label every single call automatically with a automated, algorithmic contact reasoning methodology that takes the guess work and human error out of the process.