Zendesk Average Handle Time: How to Measure and Optimize AHT
Average handle time (AHT) is one of the most practical metrics for understanding how your team spends its time. It tells you how long agents actually work on each ticket — from reading and research to writing responses and after-contact work. In Zendesk, AHT isn’t a built-in metric, so you need the right setup to track it. This guide covers how to measure AHT, how to report on it in Explore, and how to optimize it without sacrificing quality.
What average handle time means in Zendesk
AHT measures the total active time an agent spends on a ticket across its entire lifecycle. Unlike resolution time, which counts wall-clock time from creation to solve, AHT captures only the time someone is actively working on the issue.
In Zendesk, there’s no native AHT metric out of the box. To get it, you need the Time Tracking app (free from the Zendesk Marketplace). Once installed, it automatically records two custom fields on every ticket:
- Time spent last update — seconds spent during the most recent agent session.
- Total time spent — cumulative seconds across all sessions.
These fields flow into Explore, where you can build AHT reports. For a fuller definition and the calculation formula, see average handle time in the glossary.
How to set up AHT reporting in Zendesk Explore
Step 1: Install the Time Tracking app
Go to the Zendesk Marketplace, search for “Time Tracking,” and install it. It’s free and starts recording immediately on all new tickets. Existing tickets won’t have historical data, so plan for a ramp-up period (typically 2–4 weeks before you have enough data to report on).
Step 2: Create a calculated metric in Explore
In Zendesk Explore, create a calculated metric to convert the raw seconds into a usable average:
- Name: Average Handle Time (minutes)
- Formula:
VALUE(Total time spent (sec)) / 60 - Aggregation: AVG (or use MEDIAN for a more representative number)
Step 3: Build the report
- Dataset — Use the Support: Tickets dataset.
- Metric — Add your calculated AHT metric.
- Time dimension — Add Ticket Solved date by week (or day) so you see trend over time.
- Breakdowns — Add Group, Assignee, or Tags to identify which segments have the longest handle times.
Step 4: Add to a dashboard
Pin the report to your support metrics dashboard alongside resolution time and tickets per agent. That gives you efficiency, speed, and workload in one view.
Business hours vs calendar hours for AHT
Unlike first reply time or resolution time, AHT usually doesn’t need a business hours adjustment. The Time Tracking app records actual agent work time — if an agent isn’t working on the ticket, the clock isn’t running. That said, if you’re comparing AHT across shifts or time zones, normalize by shift length so you’re comparing apples to apples.
What’s a good AHT benchmark?
AHT varies widely by product complexity and channel:
| Context | Typical AHT |
|---|---|
| Simple email/chat (SaaS) | 4–8 minutes |
| Standard email support | 8–15 minutes |
| Complex B2B support | 15–30 minutes |
| Technical/engineering escalations | 30–60+ minutes |
Don’t chase a universal target. Instead, track AHT by ticket type (use tags or categories) and look for outliers within each type. A “how do I reset my password” ticket and a “my integration is broken” ticket shouldn’t have the same benchmark.
Common mistakes
- Optimizing AHT in isolation — Pushing agents to be faster can increase reopen rate and hurt CSAT. Always track AHT alongside quality metrics.
- Not segmenting by complexity — A blended AHT that mixes simple and complex tickets tells you very little. Break down by tag, category, or group.
- Forgetting the ramp-up period — The Time Tracking app only records data going forward. Don’t try to report on AHT for tickets created before installation.
- Ignoring after-contact work — If agents do categorization, notes, or follow-up after closing the ticket tab, the Time Tracking app may not capture that time. Document what’s included in your AHT definition.
How to optimize AHT
Reducing AHT is about removing friction, not rushing agents:
- Macros and templates — Pre-written responses for common questions cut writing time significantly. Review your top 20 ticket types and build macros for each.
- Internal knowledge base — Give agents fast access to troubleshooting steps, decision trees, and escalation criteria. If agents spend time searching Slack or asking colleagues, that’s a process problem.
- Skill-based routing — Match tickets to agents who know the topic. An agent with context resolves faster than one learning on the fly. See support capacity planning for routing strategies.
- Reduce back-and-forth — Ask for all relevant information upfront (ticket forms, required fields). Each unnecessary reply adds minutes to AHT.
- Spot training opportunities — If certain agents have consistently higher AHT on the same ticket types, pair them with faster peers. Use the Assignee breakdown in your report to identify this.
FAQ
Does AHT include wait time? No. AHT measures active agent work time. Wait time (customer waiting for a reply) is captured by requester wait time and first response time, not AHT.
What if agents forget to keep the ticket tab open? The Time Tracking app records time based on ticket tab focus. If an agent switches away, the clock pauses. This is mostly accurate but not perfect — agents who research in a separate tab may under-report. Communicate the importance of keeping the ticket tab active during work.
Should I use average or median for AHT? Median is usually more useful. A few very long tickets (escalations, complex bugs) can skew the average dramatically. Median gives you a better sense of what a “typical” ticket looks like. See why median beats average for more context.
How does AHT relate to cost per ticket?
Directly. Agent time is the largest component of cost per ticket. If you know your fully-loaded hourly cost per agent and your AHT, you can estimate the labor cost per ticket: (AHT in hours) × (hourly cost).