Tips for improving customer satisfaction (CSAT)
Read this blog for tips on how you can overcome many of the challenges that surround CSAT and improve your organization's ability to please its custom...
The Team at CallMiner
September 07, 2017
Average speed of answer is, at the most basic level, about running an effective call center by finding the fastest path to having customers’ questions answered or issues resolved. This means understanding the metrics that need to be monitored, transcribed, and analyzed in order to glean actionable insights.
Average speed of answer is one of the most important metrics for call centers to measure. The concept is closely tied to (and often confused with) those of average handle time and first call resolution. However, there are important differences between them. The most critical is to understand that average speed of answer is all about understanding the needs of customers and being able to provide them answers quickly.
Average speed of answer is defined as the average amount of time it takes for a call center to answer a phone call from a customer. Included in this metric is the time a caller waits in a queue. The time it takes to navigate through an IVR system is not factored in to ASA.
For this reason, measuring ASA requires a nuanced approach that ensures maximum accuracy. Here are two important tips for calculating it correctly:
Calculate the Average Properly
In its simplest form, ASA is calculated by:
ASA = Total Wait Time for Answered Calls/Total # of Answered Calls.
The idea behind ASA is to get an overview of general performance. For that reason, one of the most common mistakes made is to simply take an average of the aggregate data. But approaching the calculation in this manner will include outlier data points that can skew results. Be aware of this, and make sure to account for the effect of outliers when drawing conclusions from the measurement.
Average speed of answer in isolation doesn’t give any information about the impact of the time frame necessary for a response. To make up for this blind spot, be sure to look at customer abandonment rates as well. Even if the average speed of answer seems reasonable, it will need to be improved if there are still high customer abandonment rates.
Average speed of answer is important because it gives call center staff the information and tools they need to their jobs effectively. Customers value their time, and so an understanding of what they are experiencing when they call in is the first step to making them happy and improving overall customer satisfaction. If a particular trend is spotted that indicates an area where more could be done, it empowers management to provide better training and coaching for staff so an answer is readily available when it arises.
Another reason average speed of answer is important is its relationship with interactive voice response (IVR) systems. Because IVR works by leading a caller through a series of menu options, average speed of answer can be used to gauge the effectiveness of menu options. A well-constructed IVR will keep response times low and get a customer to the agent most equipped to answer their question, while a system which is poorly designed will lead to higher wait times and less targeted agent responses.
Speech analytics is one technology that cannot only assess ASA and other performance metrics, it can also detect issues with IVR routing and identify additional routing options.
Bottom line, average speed of answer is all about a call center’s ability to get a customer’s issue resolved as quickly as possible. Understanding how long it is taking customers to get to an agent is at the heart of the value behind the metric.
However, it’s not enough to simply take an average. Proper measurement should consider outliers. It should also be concerned about the customer experience across their entire journey.
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