Spend any time around a contact center and you’ll likely hear the acronym FCR.
What does FCR stand for? The definition has changed a bit over time as call centers transformed into contact centers that handle more than just calls.
Back in the call center days, FCR stood for first call resolution. Today FCR is commonly understood to mean first contact resolution.
The definition has changed, but the original concept of first call resolution still applies. It simply means that you take care of a customer’s issue or question the first time he or she contacts you. Such a simple concept can be frustratingly difficult to accurately measure though, and here’s why.
Suzie has a question about her bill and calls customer service. That contact center’s ACD system can capture the number Suzie calls from. That’s called her ANI, which stands for automatic number identification. So far, so good.
Suzie speaks with an agent and gets her question answered. This should be counted as a first call resolution. Tomorrow, Suzie remembers she forgot to ask about changing to a higher level service, so she calls again. The system, using ANI, identifies another call from Suzie. Things get complicated now.
All we know is that Suzie called twice in 24 hours. Is her second call a follow-up to the first one? If it is, then her first call should not be counted in FCR. If it’s about something totally different, then her first call should be counted in FCR.
Knowing the reason Suzie calls is critically important for accurate measurement of first call resolution. Lacking this information, most call centers pick some arbitrary time period, like 24 hours, and if a person calls multiple times within that period, he or she is not counted in FCR.
Following this logic, Suzie’s call would be counted incorrectly.
Because knowing the reason for a call is so important, how can we figure this out? In industry terminology, this is referred to as call reasoning, or contact reasoning.
Having different numbers for customers to call, say for billing versus support would help. Unfortunately, these are really broad categories and don’t help much. Plus customers like having a single number to call.
Another option we are all maddeningly familiar with is using an IVR system to ask why we’re calling. There are a limited number of buttons on a phone though, so again the categories tend to be fairly broad.
Plus it aggravates customers to listen to a bunch of selection options. A speech-enabled IVR system can help alleviate this if you have that option.
We could ask agents to identify call reasons. This is probably the most commonly used method when calculating first call resolution.
It’s reasonable to assume that an agent knows what they are talking to a customer about. If not, you’ve got bigger issues than how to measure FCR to tackle. There’s a problem with asking agents to identify reasons though.
Studies have shown that agents given a list of 20 call reasons tend to pick from the top 10, even if it’s not the right reason.
Explaining to agents why picking the correct reason is important helps. It also helps to give then a few extra seconds of AHT, or average handle time, to scroll through a long list and pick the right one.
Probably the best way of getting call reason is through the use of speech analytics, also called interaction analytics. Analytics can accurately determine the context, or meaning, of conversations between agents and customers, and then categorize these calls by what they were about.
If this is so hard, why don’t we just throw in the towel and give up? It may be hard, but it’s really important. FCR is a very good indicator of customer satisfaction, which has become increasingly important in today’s customer-centric environment.
The bottom line: Measuring first call resolution is better than doing nothing. Just be aware of some of the limitations.
