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Average speed of answer12/17/2022 ![]() That sweet spot appears to be when ASA is between 25% and 30% of average handle time. This suggests that there is a “sweet spot” where ASA can be optimized to minimize costs without sacrificing customer satisfaction. Moreover, driving down your ASA will do nothing to increase customer satisfaction, but it will almost certainly increase your costs. The 3-minute ASA represents 30% of the ticket handle time, but just 23% of the total transaction time (ASA + Handle Time). If your ASA is 3 minutes and your handle time is 10 minutes per ticket, the total transaction time is 13 minutes. This is a profound insight because it indicates customers know that ASA is almost always relatively small compared to the total transaction time. (Please note that the second figure our x-axis is not ASA in seconds, but rather ASA as a percent of average handle time.) Conversely, longer ASAs will not impact customer satisfaction until ASA exceeds 30% of your average handle time. However, the next figure clearly shows that as long as ASA remains less than 30% of ticket handle time, there is no customer satisfaction benefit to be gained by further reducing ASA. This is because low ASAs are most often the result of over-staffing on the service desk. It’s quite obvious that as ASA decreases, cost goes up. The first figure below illustrates the relationship between ASA and cost per ticket. Contrary to popular belief, low ASAs do not drive customer satisfaction. ![]() So, to continue with our example, if we spend $4 more per ticket to drive our ASA from 60 seconds to 30 seconds, but we see no improvement in customer satisfaction, why bother? We would be spending money and getting nothing in return. And here’s why.Ĭontrary to popular belief, low ASAs do not drive customer satisfaction. Is a 30 second reduction in ASA worth an increase of $4 per ticket? Probably not. However, with five additional FTEs their cost per ticket would increase to $24. Let’s further assume that they can forecast using their workforce scheduling tool that ASA can be reduced to just 30 seconds if they add five additional front-line analysts. Let’s say, for example, that a service desk has an ASA of 60 seconds, and they are spending $20 per ticket. ![]() But faster ASAs do come with a price, and that price can be quite high. This would be true if faster ASAs did not cost anything. There is a common perception in service and support that faster (lower) ASAs are better. Since most service desks have an ASA target, ASA is tracked to ensure service-level compliance. Almost everyone who works in service and support can tell you their ASA off the top of their head. It indicates how responsive a service desk is to incoming calls. Why It’s ImportantĪSA is one of the most widely tracked metrics in the technical support industry. But the principles that apply to ASA in the voice channel are equally applicable to average response time in the chat channel. The examples used in this article will refer to average speed of answer for the voice channel. ![]() Once again, abandoned chats are not included in the calculation for average response time. It measures the average wait time from when a chat customer initiates contact in the chat channel, until they receive a live response from an agent. The average response time in chat is calculated in the same way that ASA is calculated for the voice channel. However, for chat, the metric is generally referred to as the average response time (ART). Please note that abandoned calls are not included in the calls accepted number when calculating ASA.Īverage speed of answer applies to the live channels of voice and chat. For that particular month, the ASA was 50 seconds (250,000 seconds ÷ 5,000 calls accepted). Let’s say, for example, that in a particular month a service desk accepts 5,000 live voice calls, and the collective time in queue for all calls accepted was 250,000 seconds. Most automatic call distributor (ACD) systems capture this metric. This includes calls handled by an interactive voice response (IVR) system, as well as calls handled by live analysts. The purpose of the column is to familiarize you with the KPIs that really matter to your organization and to provide you with actionable insight on how to leverage these KPIs to improve your performance! This month, I look at Average Speed of Answer.Īverage Speed of Answer (ASA) is the total wait time that callers are in queue, divided by the number of voice calls handled. I define the KPI, provide recent benchmarking data for the metric, and discuss key correlations and cause-and-effect relationships for the metric. Each month, I highlight one Key Performance Indicator (KPI) for service and support.
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