Average Speed of Answer (ASA) is a call center key performance indicator (KPI) typically referenced by managers when assessing their team’s efficiency, performance and degree of accessibility to their callers. It is one of the most popular KPIs but can also be difficult to interpret. In order to be successful, call center managers must have a comprehensive understanding of exactly what ASA is, how to measure it and the impact that high ASA can have on customers, agents and the call center as a whole.
ASA is a call center metric for the average amount of time it takes for calls to be answered in a call center during a specific time period. This includes the amount of time callers wait in a waiting queue and while the agent’s phone rings however does not include the time it takes for callers to navigate through the IVR.
Before discussing how ASA impacts the call center, it is first important to understand how ASA is calculated. A common formula for ASA is:
Average Speed of Answer = Total Waiting Time for Answered Calls/Total Number of Answered Calls
Many managers use ASA as an estimate of customer satisfaction. Although ASA can influence customer satisfaction, it doesn’t paint a complete picture. In order to have a better understanding of the impact ASA has on customer satisfaction, call center managers should also:
1. Conduct an outlier analysis
It is important to note that because ASA is calculated as a mean, it may or may not be easily skewed by outliers depending on the sample size. Thus, managers must augment their analysis of ASA by analyzing data from outliers in order to gain a more comprehensive understanding of wait time and how it impacts customer satisfaction.
For example, when the sample size is large (i.e., when measuring ASA over a long time span) a few outliers may not skew ASA very much. In these instances, call center managers can very easily be falsely reassured that everything is fine as long as the ASA falls within their target range. However, the ASA can still be within the target range and include callers that waited an unacceptable amount of time in the waiting queue. Conversely, outlier callers who wait a very long time before being connected to an agent will skew ASA when measuring it over a short time span.
Thus, when calculating ASA, it is important to conduct an outlier analysis as well. Knowing that a few callers waited 30 minutes before their call was answered may be more meaningful than knowing the ASA was or was not within an acceptable range.
2. Analyze abandonment rates
When analyzing ASA it is also important to note that ASA only takes into consideration calls that were answered. Thus, managers should also assess caller abandonment rates for the same time frame in order to better understand how ASA impacts customer satisfaction in the call center. For example, if callers wait for 30 minutes in a queue and then give up, this is meaningful information as it will have a negative impact on customer satisfaction, however will not negatively impact the ASA.
In sum, when analyzing ASA, managers must be sure to also conduct an outlier analysis and measure abandonment rates for that time frame as that will provide a more holistic picture of how ASA impacts customer satisfaction in the call center.
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Once a comprehensive understanding of how to calculate ASA has been developed, it is important to understand the impact of high ASA in the call center. High ASA can have a profound impact on the customer, agent, team and call center as a whole. Specifically, high a ASA is related to:
Poor customer satisfaction
The longer a customer has to wait to speak with an agent, the less satisfied they will be with their experience. Thus, ASA is negatively related to customer satisfaction.
Reduced agent satisfaction
Customers who wait a long time to speak with an agent are often unhappy. This negatively impacts the agent’s degree of satisfaction with their work as it increases agent stress and emotional exhaustion.
High abandonment rates
The longer it takes for calls to be answered, the more likely callers will be to leave the queue. Thus, ASA is positively associated with abandonment rates.
Increased handle time
Callers who are frustrated from waiting in long queues will be more likely to vent to agents once they are connected. This time spent venting increases handle time as the agent must first apologize for the inconvenience before asking the customer the reason for their call.
Decreased call center agent efficiency
Every second a call center agent spends apologizing to callers for long wait times decreases their efficiency. Thus, ASA is negatively related to call center agent efficiency.
Increase in escalated calls
Callers who are unhappy with long wait times are more likely to ask to speak with a manager about this issue. Thus, the number of escalated calls to management significantly increases as ASA increases.
Worse first call resolution rates
Callers who are frustrated are less likely to effectively communicate their needs once they are connected with an agent. They are therefore less likely to have their issue resolved on first contact. Thus, first call resolution is negatively impacted when ASA increases.
Increased call center costs
All of the aforementioned factors associated with high ASA as well as telephony costs associated with callers waiting for long periods of time in the queue increase costs for the call center as a whole. Thus, when ASA increases, so do call center costs.
Average speed of answer is a common call center KPI that provides a quick overview of a team’s efficiency, performance and accessibility to their callers. It is a go-to call center KPI for most managers, however many are not exactly sure how it is measured and how it impacts the call center. In order to be effective, managers must develop a comprehensive understanding of ASA and how high ASA can negatively affect the call center. Doing so will help to build a solid foundation from which they can apply that knowledge and work to reduce ASA in their call center.