Average Speed of Answer - ASA: Definition, Formula and Australian Benchmarks
The average speed of answer (ASA) is the average time customers wait in a contact centre queue before their call is answered by an agent. It is one of the most widely used operational metrics in contact centre management — a direct, measurable indicator of how accessible and responsive a centre is from the customer's perspective.
ASA is closely related to — but distinct from — Grade of Service. Where Grade of Service measures the percentage of calls answered within a threshold, ASA measures the average wait time across all answered calls. Used together, they give a more complete picture of queue performance than either metric alone.
This guide covers the ASA definition, how to calculate it, Australian benchmarks from ACXPA's own research, the two critical limitations of the metric that most contact centres overlook, and practical tips to improve it.
What ASA measures
The average time customers wait in queue before an agent answers — from the moment they enter the queue to the moment the call connects.
Why it matters
Wait time is one of the top drivers of customer frustration, abandonment, and negative sentiment. ASA is the most direct measure of how long customers are actually waiting.
What this guide covers
Definition, formula, worked example, Australian benchmarks by call type and industry sector, two critical metric limitations, and tips to improve ASA.
What is Average Speed of Answer?
Average speed of answer (ASA) — sometimes called average wait time or average queue time — is the average amount of time that callers spend waiting in queue before their call is answered by a live agent. It is measured in seconds and calculated across all answered calls for a defined period.
The clock starts when a customer is placed into the queue and stops when an agent answers the call. Time spent in IVR menus before reaching the queue is typically not counted (more on this limitation below).
ASA is an average — which means it smooths out variation across all calls in the period. A contact centre with an ASA of 60 seconds may have some callers answered in 5 seconds and others waiting over 3 minutes. The average tells you the general trend, but not the distribution.
In plain English
ASA answers: on average, how long does a customer wait on hold before they speak to someone? The lower the number, the more accessible your contact centre is.
How to Calculate Average Speed of Answer
The ASA formula is straightforward — total queue waiting time across all answered calls, divided by the number of calls answered.
Simple example
5 calls answered with wait times of: 10, 15, 20, 25, and 30 seconds.
Total: 100 seconds ÷ 5 calls = ASA of 20 seconds.
Larger scale example
3,000 calls answered with a total queue wait time of 300,000 seconds.
300,000 ÷ 3,000 = ASA of 100 seconds.
Important: what is included
Only answered calls are included. Abandoned calls — where the customer hung up before being answered — are excluded from the calculation. This is one of the metric's key limitations (see below).
Australian Average Speed of Answer Benchmarks
ACXPA's research provides two complementary views of Australian ASA data: self-reported benchmarks by call type from the 2024 Australian Contact Centre Best Practice Report (Smaart Recruitment), and independently measured real wait times from the ACXPA Australian Call Centre Rankings.
Self-reported benchmarks by call type
The following figures from the 2024 Australian Contact Centre Best Practice Report show the average ASA across different call types — and reveal a significant spread depending on what type of call is being handled.
Source: 2024 Australian Contact Centre Best Practice Report, Smaart Recruitment. Presented at ACXPA Call Centre Roundtable, April 2026.
What these numbers tell us
The average Australian contact centre is taking between 97 and 130 seconds to answer calls — roughly 1.5 to 2 minutes. Inbound sales lines are fastest (commercial incentive to answer quickly) while tech support is slowest (more complex contacts, typically longer AHT driving higher staffing requirements). These are averages — well-run contact centres hit significantly lower figures, while poorly resourced ones run considerably higher.
Real Wait Times by Industry Sector — Australian Call Centre Rankings 2025
Unlike self-reported benchmarks, the ACXPA Australian Call Centre Rankings measures actual customer wait times through independent mystery shopping — callers contacting organisations as new customers and recording exactly how long they waited. This is one of the only independently measured sources of wait time data available in Australia.
Source: ACXPA Australian Call Centre Rankings 2025. Data reflects new/prospective customer calls via independent mystery shopping. Banks figure (3:48) is significantly higher than all other sectors measured.
The Banks outlier
Banks are a significant outlier — with an average wait time of 3 minutes 48 seconds in 2025, more than five times longer than the fastest sector (Internet at 45 seconds). The data suggests that for many Australian banks, customer wait time is simply not being prioritised — and customers calling to enquire about banking products are consistently experiencing some of the worst queue times of any sector measured.
Annual trend — national average wait times
ACXPA's Rankings data shows a positive trend in national average wait times, with consistent improvement from 2023 to 2025.
- 2023: 152 seconds national average
- 2024: 117 seconds — a significant improvement
- 2025: 109 seconds — continued improvement
Source: ACXPA Australian Call Centre Rankings.
Average Speed of Answer vs Grade of Service
ASA and Grade of Service (GOS) are the two most commonly used queue performance metrics in contact centres. They are complementary — not interchangeable — and each reveals something the other does not.
Average Speed of Answer
What it measures: The average wait time across all answered calls.
Strength: Shows the typical customer experience in absolute time — easy to understand and communicate to stakeholders.
Weakness: Hides the distribution of wait times. A good average can coexist with some customers waiting very long times.
Grade of Service
What it measures: The percentage of calls answered within a defined time threshold (e.g. 80% within 20 seconds).
Strength: Directly tied to staffing calculations via Erlang C. Gives a clear pass/fail against a defined standard.
Weakness: Tells you nothing about what happens to the calls that don't meet the threshold.
Use both together
A contact centre can have a good GOS (e.g. 80% of calls answered in 20 seconds) while still having a high ASA if the remaining 20% of callers are waiting a very long time. Using both metrics together gives a more complete picture: GOS tells you whether most customers are being answered quickly, and ASA tells you the average experience across all customers.
Two Critical Limitations of Average Speed of Answer
ASA is one of the most commonly reported metrics in contact centres — and one of the most misunderstood. Two specific limitations mean that ASA can significantly understate the true customer experience, yet many contact centres report it without flagging either caveat.
⚠️ Limitation 1 — Abandoned calls are excluded
ASA is calculated using only the calls that were answered. Calls where the customer gave up and hung up before being answered — abandoned calls — are excluded from the calculation entirely.
This creates a systematic bias. The customers who waited longest and abandoned are the very customers excluded from the average. If your busiest periods generate high abandonment, your ASA may look perfectly acceptable while your actual customer experience is significantly worse than the number suggests.
Always report ASA alongside abandonment rate. A low ASA with high abandonment is a warning sign, not a success.
⚠️ Limitation 2 — IVR time is excluded
The ASA clock starts when a caller enters the agent queue — not when they first call. If your contact centre uses an IVR system with multiple menus, prompts, or self-service steps before placing callers in queue, that time is not captured in ASA.
A customer might spend 3 minutes navigating IVR options before ever reaching the queue — and your ASA would still show a 30-second average. From the customer's perspective, they have been waiting for over 3 minutes. From the metric's perspective, they have been waiting 30 seconds.
The more complex your IVR, the more misleading ASA becomes as a measure of total customer waiting experience. If you want to understand the full journey, measure total time from call connection to agent answer — not just the queue component.
Pros and Cons of Using Average Speed of Answer
✓ Pros
- Easy to understand — a single number in seconds that any stakeholder can interpret
- Customer-centric — directly measures what customers experience in queue
- Benchmarkable — can be compared across periods, teams, and industry data
- Useful for staffing — supports workforce planning decisions alongside GOS
- Trend indicator — improving or worsening ASA over time signals staffing alignment or misalignment
✕ Cons
- Excludes abandoned calls — the worst wait experiences are not counted
- Excludes IVR time — understates total customer waiting time
- Hides distribution — a good average can mask very long waits for some customers
- Says nothing about quality — a fast answer doesn't mean a good interaction
- Daily averages hide intraday peaks — good overall ASA can mask very poor performance in specific intervals
How to Improve Your Average Speed of Answer
Improving ASA is fundamentally a workforce management and operational challenge. The levers available are predictable — but each requires genuine investment to implement effectively.
Optimise staffing levels with accurate forecasting
The most direct lever for reducing ASA is having the right number of agents available at the right times. Analyse historical call volume data to identify intraday and intraweek patterns, and schedule staffing to match demand. Peaks that consistently produce high ASA are a planning problem — not a random occurrence. Use Erlang C modelling to validate that your staffing plan will achieve your ASA targets before deploying it.
Reduce Average Handling Time
AHT directly determines how quickly agents become available for the next call. Reducing AHT — through better agent training, improved systems, reduced ACW, and smarter call flows — means agents cycle through calls faster and queue wait times fall. A 30-second AHT reduction across the team can have a significant impact on ASA without changing headcount.
Implement intelligent call routing
Skills-based routing directs calls to the most appropriate available agent — reducing transfers, reducing handle times, and improving first contact resolution. Fewer misdirected calls means less time wasted per call and agents available to answer the queue faster.
Improve self-service and digital deflection
Well-designed self-service — IVR containment, chatbots, online FAQs, and account portals — reduces the volume of calls reaching the agent queue. Fewer calls arriving means shorter queues and lower ASA for those who do need to speak to an agent. The key word is "well-designed" — self-service that frustrates customers generates more calls, not fewer.
Offer callback options
Virtual queue and callback technology allows customers to hold their position in queue without waiting on the phone. This doesn't reduce ASA in the traditional sense — but it dramatically reduces the negative experience of waiting and significantly reduces abandonment. From the customer's perspective, being called back within their expected window is substantially better than listening to hold music for the same duration.
Monitor and manage at the interval level
Daily ASA averages hide intraday variation. A contact centre with a strong daily ASA may be running very high during the morning peak and very low in the afternoon. Managing ASA at the half-hour interval level — and responding to real-time queue build-ups with appropriate actions — is essential for consistently delivering target performance throughout the day.
Frequently Asked Questions About Average Speed of Answer
What is average speed of answer in a call centre?
Average speed of answer (ASA) is the average time customers wait in queue before their call is answered by a live agent. It is calculated by dividing the total queue waiting time across all answered calls by the number of calls answered. It is measured in seconds and is one of the most widely used contact centre operational metrics.
What is a good average speed of answer?
There is no universal benchmark — it depends on your industry, call type, and customer expectations. Australian benchmarking data shows that the national average across contact centres is approximately 115 seconds for customer service calls, 97 seconds for inbound sales, and 130 seconds for tech support. Best-in-class contact centres typically run significantly lower. The right target for your centre should be based on customer tolerance data and commercial priorities, not just industry averages.
What is the ASA formula?
ASA = Total Waiting Time for All Answered Calls ÷ Total Number of Answered Calls. For example, if 500 calls were answered with a combined queue waiting time of 50,000 seconds, the ASA would be 100 seconds. Note that only answered calls are included — abandoned calls are excluded from the calculation.
Why are abandoned calls excluded from ASA?
ASA is calculated only on calls where the customer waited and was answered. Customers who gave up and abandoned before being answered are not included. This is one of ASA's most significant limitations — the customers who experienced the longest waits and chose to abandon are systematically excluded from the average. This means ASA can look perfectly acceptable even when significant numbers of customers are having a very poor experience. Always monitor ASA alongside abandonment rate.
Is ASA the same as wait time?
ASA and wait time are closely related but not identical in all contexts. ASA specifically measures the time from when a caller enters the agent queue to when the call is answered. "Wait time" is sometimes used more broadly to include IVR navigation time before the queue. Because IVR time is excluded from ASA, the total time a customer experiences waiting can be significantly longer than the ASA figure suggests.
What is the difference between ASA and Grade of Service?
ASA measures the average wait time across all answered calls (e.g. 90 seconds). Grade of Service measures what percentage of calls are answered within a defined threshold (e.g. 80% within 20 seconds). They measure the same underlying phenomenon — queue wait time — but from different angles. GOS is better for workforce planning calculations; ASA is better for communicating the typical customer experience. Use both together for a complete picture.
How does ASA relate to AHT and staffing?
Average Handling Time (AHT) is one of the primary drivers of ASA. Longer AHT means agents are occupied for longer on each call, reducing how quickly they become available for the next call in queue — which increases wait times. Reducing AHT through better training, systems, and ACW reduction directly improves ASA without adding headcount. Staffing levels are the other primary lever — more agents means shorter queues and lower ASA.
Which Australian industries have the worst wait times?
Based on ACXPA's Australian Call Centre Rankings independent mystery shopping data (measuring new customer contacts), Banks have significantly the longest average wait times — more than three times longer than most other sectors. Aged Care and Councils also run above average. Internet providers have the lowest average wait times among sectors measured. Note that this data reflects new/prospective customer calls, not existing customer service contacts.
Where to Next
Summary: Average Speed of Answer
Average speed of answer is the average time customers wait in queue before being answered — one of the most direct measures of contact centre accessibility available. Australian benchmarking data shows that most contact centres are answering calls in 97–130 seconds on average, with significant variation by sector. Banks are a notable outlier with wait times substantially higher than all other sectors measured by ACXPA's independent research.
ASA is a useful and important metric — but it comes with two critical limitations that every contact centre manager should understand. Abandoned calls are excluded, which means high-wait customers are systematically omitted from the average. And IVR time is excluded, which means the total customer waiting experience is typically longer than ASA suggests. Always report ASA alongside abandonment rate, and always caveat it with the IVR exclusion when communicating to stakeholders.
Improving ASA requires getting the fundamentals right: accurate forecasting, appropriate staffing, reduced AHT, and interval-level monitoring. The Erlang C Calculator is the right tool to model the staffing implications of any ASA target before committing to it.
