Average Handle Time (AHT) is a critical metric that measures the average time an agent spends handling a customer interaction. AHT is a key performance indicator for contact centers since it can directly impact both customer satisfaction (CSAT) and overall operational costs.
Reducing AHT can help businesses manage costs, improve their agent performance, and provide high-quality customer service. But, it can be challenging to reduce AHT without negatively impacting the customer experience in some way.
This article will explain the significance of AHT from a business perspective and how to calculate it. And, we’ll also offer tips to optimize AHT performance and reduce associated costs—all while maintaining customer service quality.
AHT is the average duration of the entire customer call transaction, from when the customer initiates a call or contact to when it ends.
It measures more than just conversation time: it also covers hold times, transfer times, talk times, wrap-up activities, and any other activities related to resolving a customer's issue.
AHT gives insights into the efficiency of call center representatives in managing calls or interactions. It also identifies areas where agents may need additional training or support to improve their performance and optimize workflows for a higher CSAT.
If AHT is too high, it can indicate that agents may not be able to handle calls or interactions quickly and efficiently. This can result in higher costs, decreased productivity, and lower customer satisfaction.
If AHT is unnaturally low, it could suggest agents are rushing calls or interactions, which can also lead to poor service quality, frustrated customers, and decreased customer retention.
AHT can be calculated by adding up all of the talk, hold, and follow-up times for a given period and then dividing it by the total number of calls or interactions.
The formula for calculating AHT is:
AHT = (Total Talk Time + Total Hold Time + Follow up Time) ÷ Total Number of Interactions
For example, let's say you want to calculate the AHT for a call center that handled 50 calls. Let’s assume that the total talk time for all calls was 500 minutes, the total hold time was 100 minutes, and the related task time (follow-up time) was 50 minutes.
Using the formula above, you can calculate the AHT as follows:
AHT = (500 + 100 + 50) ÷ 50
AHT = 650 ÷ 50
AHT = 13 minutes
AHT industry benchmarks vary depending on the industry and the nature of customer interactions. However, some sources suggest that a typical AHT for a call center is about 6 minutes.
It's important to note that while benchmarks can be helpful for setting goals and tracking progress, they should not be the sole focus.
Each business should set its own targets based on specific service needs and customer expectations. Therefore, there isn't necessarily a "good" AHT.
Having a low AHT can indicate that agents are handling calls quickly and efficiently, which can lead to higher customer satisfaction and retention rates. However, it's important to balance a low AHT with other metrics such as first call resolution and customer satisfaction to ensure that agents are not rushing through calls at the expense of providing quality service.
It's also important to recognize that certain types of calls or inquiries may naturally have a longer AHT than others, such as complex technical support calls or product demos. In these cases, a longer AHT can actually indicate that the agent is taking the necessary time to provide thorough and accurate assistance to the customer.
While contact centers want to reduce the amount of time agents and customers spend handling a problem, it can be hard to do that without negatively impacting the customer experience.
With the current call center software and technology available, contact center leaders can face challenges in:
Call centers aim to provide efficient and effective service to their customers. One way to achieve this is by evaluating the performance of agents and determining which ones need coaching. Evaluations usually involve identifying which agents are performing poorly for specific inquiries, which agents have the lowest overall performance, and which are doing the best.
In a contact center where agents handle hundreds of inquiry types, it can be difficult to identify which specific areas agents need training on. Therefore, coaching agents with the highest AHT may not be effective since it doesn't necessarily address the actual issues that agents are facing.
Certain call or contact types may also impact an agent’s AHT more than others. Sometimes, an agent's AHT may be within the normal range for a more complex inquiry, but they may struggle with other types of inquiries even if their AHT is in a normal range.
Therefore, it's not enough to simply look at AHT when determining which agents need coaching. Unfortunately, existing systems don't provide this level of insight, making it difficult for support leaders to determine which areas to focus on.
As a result, leaders are left with the task of listening to calls to identify opportunities for improvement. This approach is not scalable and may not be able to identify all the areas for improvement. Leaders must have a deeper understanding of the issues that agents are facing when handling different inquiries to provide more effective coaching.
Call center managers can sample and listen in on the conversations between agents and customers in real-time or review recordings later. By doing so, they can identify other areas where agents need improvements such as call handling techniques or adherence to company policies and procedures.
They can also use this information to provide targeted training to individual agents or groups of agents, obtain insights, and identify trends and patterns in customer behavior.
A low sample size, where only a few interactions are taken into account, can result in an inaccurate representation of the AHT, since a few bad calls with longer handling times can skew the results.
Alternatively, when there are hundreds of calls, it becomes less likely that a few outliers will significantly impact an agent's overall AHT. The impact of a few bad calls will be diluted and the AHT will be more reflective of the agent's overall performance.
AHT alone doesn’t provide a complete picture of an agent's performance, as it does not indicate whether the agent effectively resolves customer calls or ensures customer satisfaction. Contact centers use corresponding metrics like First Contact Resolution (FCR) and CSAT to get a more comprehensive view of the quality of service being provided.
Modern contact center analytic tools can help contact centers analyze multiple metrics such as AHT, CSAT, and FCR together. However, even with these tools, it can still be challenging to analyze and interpret the data.
The data analysis process can be cumbersome because it involves processing large amounts of data and identifying correlations between different metrics. It usually also requires skilled analysts who can make sense of the data and provide actionable insights to improve the customer experience.
Contact centers can identify the activities that will have the highest impact on AHT by measuring and understanding all the different types of customer inquiries, including the workload and AHT for each inquiry.
The inquiries with the highest workload and AHT are the ones where the center can make the largest impact in reducing AHT. By identifying these activities, contact centers can prioritize their efforts to improve efficiency, ultimately leading to better customer satisfaction and increased agent productivity.
This type of information is not always readily available through existing systems–it requires being able to automatically pull AHT, CSAT, FCR, (and more) from 100% of all interactions. Contact center managers may need to rely on call listening and deep analysis to gain insights into which inquiries are driving the AHT which can be time consuming and resource intensive.
We already know that reducing AHT enables companies to improve customer retention rates, increase team productivity, and lower operating costs.
To achieve these benefits, we provide practical ways to help enhance AHT without overwhelming call center agents or compromising the quality of your customer service.
The first step in setting an AHT target is to identify a specific goal that can be measured either in seconds or as a percentage. After establishing the target, it’s essential to align everyone in the organization on the desired outcome and why it’s important.
For example, if a contact center wants to reduce AHT by 20 seconds, they should consider how this will help them achieve a specific goal, whether it’s faster response times, lowering service costs, or reducing customer effort scores.
Customer contact drivers are inquiries or issues that make customers reach out to a contact center for assistance or resolution. Companies can revolutionize the overall customer experience by uncovering the precise drivers of customer contact.
Customer contact drivers provide contact center leaders with actionable opportunities to improve customer experience and boost agent efficiency.
Knowing the AHT for each customer contact driver, and their workload and volume allows contact centers to understand why certain inquiries take longer to resolve and how to optimize the process. By mapping each driver to AHT, contact centers can determine the ideal AHT for different inquiries and create specific plans to correct deviations.
After identifying the root cause of contact drivers, along with their AHT, workload, and volume; businesses can shortlist the ones with the biggest impact for customers and agents, and focus on optimizing those areas. This approach can help contact centers reduce customer churn, improve customer satisfaction, and reduce costs associated with longer handle times
Once the prioritized AHTs have been determined, the next step is mapping the performance of agents for each prioritized driver, and measuring it across the board. This means determining the AHT for each driver and for each agent and then analyzing the data to identify which agents have the highest and lowest AHT for each driver. It's important to ensure a statistically significant sample size by collecting enough data to make reliable conclusions.
By mapping agent performance in this way, contact center leaders can identify which agents are performing well for each driver and which agents may need additional training or support to improve their AHT. It also helps leaders to identify any patterns or trends in performance across the team, and to develop strategies for improving overall performance for each driver.
Connecting agent performance or inquiry level to FCR and CSAT will enable you to identify what the ideal performance looks like each customer contact, (e.g. high FCR, high CSAT, and low AHT for simple inquiries or a high FCR, high CSAT, and medium AHT for more complex queries). Then you can focus coaching efforts on agents who fall below that standard.
These steps can all help reduce AHT without compromising customer experience–but they require a lot of time, effort, and investment.
Fortunately, Operative Intelligence automates the entire process.
Operative Intelligence can unlock the reality of your customer’s needs with AI-powered
customer insights. The platform helps you analyze the different customer contact drivers and inquiries and shows each agent's performance in terms of their corresponding AHT, FCR, and CSAT.
Pulling data from various channels including voice, email, chat, web, messaging, social media, and customer reviews, Operative Intelligence can:
Average Handle Time is an important metric for measuring customer service efficiency in contact centers. However, the current methods of reducing it have several limitations due to a lack of insights into its biggest drivers.
Operative Intelligence empowers contact centers to shift their focus from listening to calls and evaluating interactions to developing their agents and teams. The platform automates the FCR and CSAT for 100% of agent interactions, and identifies the root cause of AHT and its associated costs.
Leveraging this data, contact center management teams can easily identify performance disparities across teams and enable team leaders to coach with precision and drive measurable improvements in their AHT without negatively impacting the customer experience.
Modernize your business with automated and actionable insights today.
When considering the future of customer service, the industry is largely evaluating new call center technology and the growth of artificial intelligence.