What is ASA (Average Speed of Answer)
Average Speed of Answer, often called ASA, is a Key Performance Indicator used in call centres and contact centres to measure the average time it takes for incoming calls to be answered. It excludes time spent navigating interactive voice response menus and focuses instead on queue time.
ASA reflects how efficiently a support team manages call traffic, handles call volume, and routes calls to available agents. It plays a major role in Customer service and overall customer experience because long wait times often lead to call abandonment, frustration, and reduced customer satisfaction.
ASA is used widely across traditional call centres, live chat channels, and omnichannel environments supported by platforms such as an AI-enabled contact centre.
How ASA works
ASA is calculated by dividing the total length of customer wait time by the total number of calls answered. It is a clear indicator of how quickly conversations move from the queue to an agent.
Several factors influence ASA:
- call volume peaks
- staffing levels and workforce scheduling
- automatic call distribution
- call routing strategy
- IVR system menus
- availability of self-service options
- agent efficiency and workload
ASA also interacts heavily with related performance metrics such as average handling time, first call resolution, agent satisfaction, call abandon rate, response times, longest waits, escalated calls, and customer satisfaction scores.
In centres using tools like CRM and interaction analytics, ASA becomes more accurate because customer history, previous channel usage, and behavioural patterns help predict queue conditions more reliably.
How ASA is used in the contact centre and customer service industries
ASA is central to workforce planning, service desk operations, and real-time monitoring. Contact centres rely on ASA to:
- Understand if staffing levels match call volume
- Monitor queue time throughout the day
- Adjust routing options or skill-based routing
- Reduce abandonment rates during high-traffic periods
- Improve contact centre operations through predictive analytics
- Track agent availability and utilisation
- Optimise Interaction Orchestration across channels
High ASA values often indicate operational bottlenecks, inefficient call handling, or understaffed teams. Low ASA values usually reflect strong workforce management, effective call routing, and well-designed menu options.
Retail environments, such as retail, rely on ASA to manage large enquiry volumes. Sectors like government, healthcare, and housing often experience complex queries where queue times must be carefully controlled.
In education environments such as higher education, ASA helps manage peak periods like admissions and fee-related calls.
Why ASA matters
ASA directly affects customer abandonment, waiting frustration, and customer satisfaction. When wait times exceed expectations, customers tend to abandon calls, leading to higher abandonment rates and reduced first call resolution across support channels.
ASA also influences:
- Support team workload
- Quality monitoring tools
- Staff turnover levels
- Ticket backlog
- Service desk efficiency
- Net Promoter Score
- Routing efficiency
- Operational costs
Lower ASA values generally lead to smoother customer journeys because callers get connected faster, reducing escalations and repeat contacts.
How to calculate ASA
ASA calculation is straightforward. The formula is:
(Total customer wait time) / (Total answered calls)
For example, if customers collectively spend 5,000 seconds waiting and 200 calls are answered, the ASA is 25 seconds.
Contact centres often refine the formula using calculated fields within reporting tools to separate queue time from IVR navigation or call transfer periods.
ASA is also supported by predictive tools like Erlang C calculations, which estimate agent demand and help forecast future queue loads.
Improving ASA in a contact centre
Organisations can reduce ASA by improving staffing levels, refining routing strategies, and using modern technology. Common improvements include:
1. Workforce planning
Accurate workforce scheduling supported by workforce optimisation ensures that agent availability matches call patterns. Tools like Customer Queue Calculators, Erlang calculators, and simulation and optimisation methods help support teams prepare for peak demand.
2. Faster routing
Contact centres use automated call distribution, skill-based routing, and Omnichannel interaction routing to connect customers to the right agent faster. Systems integrated with omni-channel support consistent queue handling across phone, live chat, email, and social media.
3. Strong knowledge access
Agents reduce call handling time when they can quickly access knowledge base articles, customer history, and call data. Integrating CRM helps minimise delays and improve personalised support.
4. Self-service
Providing IVR system improvements, interactive voice response menus, and self-service options reduces inbound call load, allowing agents to answer calls more quickly.
5. Real-time support tools
Using AI-powered agent support provides agents with real-time recommendations that reduce hesitation and improve answer times.
6. Collaboration
For complex issues requiring escalation, tools such as Microsoft Teams integration allow quick collaboration and reduce long queue times caused by delayed decision-making.
Additional ASA resources
ASA becomes more powerful when combined with other tools in the contact centre ecosystem.
- Features supporting accessibility ensure callers with varying communication needs receive timely service.
- Secure payment activities during calls or digital interactions are supported through secure payments.
- For organisations with high conversation volumes, such as business process outsourcers (BPOs), ASA helps measure analyst utilisation and queue performance.
- In the nonprofit sector, not-for-proft organisations use ASA to monitor support capacity despite limited staffing.
Across industries, ASA works well alongside AI-powered analytics, conversation insights, and routing optimisation to create a predictable and stable customer experience.
Limitations of ASA
ASA is a useful metric, but should not be evaluated in isolation. A low ASA does not always mean better service quality. It may simply indicate rushed conversations or misrouted calls. A high ASA might reflect complex issues that require time, especially in healthcare or government services.
ASA does not measure:
- Accuracy of solutions
- Empathy or communication quality
- Context of customer issues
- Agent performance beyond answering speed
- Customer Satisfaction throughout the journey
This is why ASA must be paired with other indicators, such as first call resolution, customer satisfaction scores, and handle time for a full performance view.
Final thoughts
ASA helps organisations understand how long customers wait before speaking to an agent. When monitored correctly, it supports staffing efficiency, improves queue management, and enhances the overall customer experience across channels.
To explore how ASA fits into your performance measurement strategy, request a demo.
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