Glossary · AHT

What is AHT?

AHT (Average Handle Time) is a contact center metric measuring the total average time agents spend on each customer interaction from initial contact through post-call wrap-up. AHT is calculated as: (Total Talk Time + Total Hold Time + Total After-Call Work) ÷ Number of Calls. Lower AHT generally indicates higher efficiency, but reducing AHT at the expense of First Call Resolution or CSAT is counterproductive — customers who have to call back drive costs up and satisfaction down.

AHT formula

AHT = (Total Talk Time + Total Hold Time + Total ACW) / Total Calls

All times are typically measured in seconds or minutes.

AHT component breakdown

Talk time — time the agent spends actively conversing with the customer. Usually the largest component.

Hold time — time the customer spends on hold while the agent researches, transfers, or consults with a supervisor.

After-call work (ACW) — time the agent spends on post-call tasks: notes, CRM updates, disposition codes, follow-up tasks.

Typical breakdown in a well-run contact center:

Talk: 60–75% of AHT
Hold: 5–15% of AHT
ACW: 15–25% of AHT

AHT benchmarks by industry

AHT varies dramatically by contact center type:

Industry	Typical AHT
Retail / ecommerce	4–6 min
Financial services	6–8 min
Healthcare patient access	5–10 min
Telecom / ISP	8–12 min
Utilities	6–9 min
Technical support	10–20 min
Government	8–15 min
Insurance	8–12 min

Complex industries (tech support, insurance claims, healthcare) legitimately have higher AHT because the calls are more complicated.

Why AHT matters

AHT directly drives contact center economics:

Capacity — lower AHT means each agent handles more calls per day
Staffing cost — a 10% AHT reduction is roughly equivalent to 10% headcount reduction
Service level — faster handling means shorter queue waits for other customers
Customer satisfaction — customers generally prefer shorter interactions (up to a point)

AHT can be misleading

Focusing exclusively on AHT creates bad behavior:

Agents rush customers — quality drops
FCR falls — customers call back, increasing total cost
CSAT drops — people feel unheard
Cold transfers increase — agents pass calls off to end them faster
Wrap-up gets sloppy — worse CRM data downstream

Better metric: total contact cost per resolved issue. Lower AHT is only good if the issue actually gets resolved on the first contact.

How to reduce AHT — real ways

Reduce talk time (carefully)

Better knowledge base — agents find answers faster
Real-time Agent Assist — AI surfaces relevant information during the call
Pre-authenticated callers — verify identity in IVR, not again with the agent
Better IVR self-service — deflect simple questions so only complex ones hit agents

Reduce hold time

Cross-trained agents — fewer cold transfers
Embedded tools — agents don’t leave the call to look up information
Integrated CRM — customer history one click away
Eliminate unnecessary authentication steps

Reduce ACW

AI-generated call summaries — no manual note-writing
Auto-CRM logging — DialPhone automatically posts transcripts and summaries
Templated follow-ups — AI-drafted messages for common scenarios
Streamlined disposition — fewer wrap-up codes, simpler forms

Reduce rework (biggest lever)

Improve First Call Resolution — a 5% FCR increase often cuts call volume more than AHT reduction
Fix root causes surfacing in interaction analytics — reducing call drivers
Proactive notifications — head off calls before they happen

AHT and AI

AI has the biggest impact on AHT since the invention of the call queue. Specific improvements:

Real-time transcription — eliminates the need for agents to type notes during calls
AI Agent Assist — real-time knowledge suggestions cut research time
Auto call summaries — the biggest ACW time-sink vanishes
Auto CRM logging — data entry time zeroes out
Predictive intent — AI flags likely callback topics so agents can proactively address them

DialPhone customers deploying AI Agent Assist + AI QM report 50 percent AHT reduction on average. See results →

AHT by channel

Different channels have different AHT profiles:

Voice — traditional AHT measurement
Chat — similar to voice but agents often handle multiple concurrent chats
SMS — low per-interaction handling time but often spans hours
Email — handled in batches, different measurement model
Social DMs — async, different metrics

Omnichannel platforms should measure “channel-adjusted AHT” that accounts for concurrent handling and async timelines.

Look at AHT over time:

Weekly trend — catches rapid changes from product issues, policy changes, training
Monthly trend — overall performance direction
By agent — identify outliers for coaching
By call type — differentiate complex calls from simple ones
By time of day — catch shift performance variance

A sudden AHT spike often signals something outside the contact center — product bug, policy change, new-customer influx. Good supervisors investigate quickly.

AHT and coaching

Individual agent AHT drives coaching decisions:

High AHT with high CSAT — rapport-heavy agents; coach on efficiency without losing warmth
High AHT with low CSAT — unclear communication; coach on clarity
Low AHT with high CSAT — model agents; have them mentor others
Low AHT with low CSAT — rushing; coach on empathy and thorough resolution

DialPhone’s AI Quality Management scores 100% of calls automatically and generates personalized coaching modules per agent.

Example

A 200-agent B2C customer support operation averaged 7-minute AHT with 68% FCR. They deployed DialPhone Professional ($95/user):

AI Agent Assist surfaced answers in real time → talk time down 18%
AI Call Summary eliminated note-writing → ACW down 55%
New AHT: 5.1 minutes
Same team capacity went from 17,000 to 23,400 interactions per day
FCR simultaneously rose to 76% because agents were better-informed
Total result: handled 38% more volume at same headcount, CSAT rose 12 points