Average Handle Time (AHT)
Average handle time (AHT) is the average total time an agent spends resolving a customer interaction, including talk time, holds, and after-contact work like logging notes. It is a core efficiency metric in support operations.
Key takeaways
- AHT is the average total time to handle an interaction: talk time plus holds plus after-contact work.
- It is calculated as total handle time divided by number of interactions.
- Lower AHT increases capacity per agent, but optimizing it alone can hurt resolution and satisfaction.
- Reduce it safely by cutting after-call work, surfacing answers faster, and automating routine contacts, not by rushing agents.
Average handle time, or AHT, is the average total time an agent spends resolving a customer interaction, including talk time, any holds, and the after-contact work like logging notes. It is one of the most-watched efficiency metrics in support and contact-center operations.
What AHT includes
AHT is calculated as total handle time divided by the number of interactions. Handle time covers the full effort per contact: the conversation itself, hold or wait time, and the wrap-up work afterward. Measuring all three matters, because a short call followed by ten minutes of manual logging is not actually efficient.
Why AHT matters, and its trap
Lower AHT means more interactions handled per agent, so it is a direct lever on cost and capacity. The trap is optimizing it in isolation: an agent who rushes to cut AHT may leave issues unresolved, hurting first-contact resolution and satisfaction. AHT is only meaningful read alongside quality metrics like CSAT and resolution rate.
How teams reduce AHT the right way
- Cut the after-work, not the conversation, often the biggest, safest win.
- Surface answers faster with agent assist and a clean knowledge base.
- Automate routine contacts so agents handle the complex ones.
Reducing AHT without harming quality is about removing friction, not pressuring agents to go faster.
Frequently asked questions
What is average handle time?
Average handle time (AHT) is the average amount of time an agent takes to fully handle a customer interaction, from start to finish. It includes the actual conversation (talk time), any time the customer spends on hold, and the after-contact work such as logging notes and updating records. It is calculated by dividing total handle time across all interactions by the number of interactions.
Why can focusing on AHT be risky?
Because AHT measures speed, not quality. An agent pressured to lower their AHT may cut conversations short or skip steps, leaving the customer's issue unresolved. That hurts first-contact resolution and customer satisfaction and often creates repeat contacts, which raises total cost. AHT is only meaningful when read alongside quality metrics like CSAT and resolution rate, so the two are balanced rather than traded off.
How do you reduce average handle time?
The safest gains come from removing friction rather than rushing agents. Cutting after-contact work (for example by automating note-taking and CRM updates) is often the biggest win. Surfacing answers faster with agent assist and a clean knowledge base shortens the conversation without sacrificing quality. Automating routine, repetitive contacts lets human agents focus on the complex ones, lowering the average without harming outcomes.
Related terms
ACV vs ARR
ACV vs ARR is the distinction between two subscription-revenue metrics: ACV (annual contract value) measures the average yearly value of a single customer contract, while ARR (annual recurring revenue) measures the total recurring revenue across the entire customer base, annualized.
ARR vs MRR
ARR vs MRR is the distinction between two recurring-revenue metrics that measure the same thing at different time scales: MRR (monthly recurring revenue) is the predictable revenue earned each month, and ARR (annual recurring revenue) is that figure annualized, so ARR equals MRR times twelve.
Annual Contract Value (ACV)
Annual contract value (ACV) is the average annualized revenue from a single customer contract, the total value of a contract normalized to a one-year figure, so deals of different lengths can be compared on equal footing.
CRM Analytics
CRM analytics is the analysis of customer and deal data stored in a CRM to reveal patterns in pipeline, conversion, and forecasting, turning raw records into decisions about where to focus and what to fix.
Closing Ratio
Closing ratio, also called close rate or win rate, is the percentage of opportunities a salesperson or team wins out of the total they pursue.
Cloud CRM
A cloud CRM is a customer relationship management system hosted by the vendor and accessed over the internet, where the provider handles infrastructure, updates, and security and you pay a recurring subscription instead of running it on your own servers.