What is Average Wait Time (AWT)?

AWT measures total duration customers spend waiting before being served. Formula: Total Wait Time / Number of Customers Served. It tells you how long customers sit in queue.

Should I include abandoned contacts in AWT?

Most calculations exclude them, which flatters performance. Calculate both AWT (Answered) and AWT (All Contacts). The gap tells you how much the metric is flattering you.

What's the difference between AWT and ASA?

Often used interchangeably but can mean different things. ASA typically measures time-to-answer for answered calls only. AWT may include pre-queue time. Define your terms explicitly.

What should I pair with AWT?

Customer Effort Score, CSAT, first contact resolution, and abandonment rate. AWT tells you wait duration but not whether the wait was worth it or if problems got solved.

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Average Wait Time (AWT): A Practitioner's Guide

Q: Why should I segment AWT by cohort?

Blended averages hide problems. Company-wide AWT might hide that billing runs at 30 seconds while technical runs at 8 minutes. Segment by channel, time, segment, and issue type.

Michelle Wen

Apr 8, 2026

Customers who waited longest and gave up don't count against your average. A contact center with 30% abandonment at the 5-minute mark will report better AWT than one with 5% abandonment, even if the latter serves customers faster overall.

The formula: AWT = Total Wait Time / Number of Customers Served
Critical decision: Do you include abandoned contacts? Most calculations exclude them, which flatters performance
Calculate two versions: AWT (Answered) and AWT (All Contacts) - the gap tells you how much the metric is flattering you
Segment by cohort: Blended averages hide queue-specific problems
Staffing is core: AWT is fundamentally a supply-demand problem

Last updated: April 2026

Average Wait Time measures the total duration customers spend waiting before being served by an agent or system. It answers: how long do customers sit in queue before someone helps them?

Lorikeet is an AI customer support platform that reduces queue pressure by resolving issues without human intervention, improving AWT for the contacts that do need human help.

How to Calculate It

The core formula:

AWT = Total Wait Time / Number of Customers Served

Numerator: Cumulative time all customers spent waiting, typically from queue entry until agent connection.

Denominator: Number of customers who actually received service. This is where measurement gets tricky.

Critical decision - abandoned contacts:

Most AWT calculations only count answered contacts. This creates a perverse incentive: customers who waited longest and gave up don't count.

Calculate two versions:

AWT (Answered): Wait time for customers who reached an agent
AWT (All Contacts): Includes abandoned contacts, using their abandon time as their wait time

Data Collection and Measurement

Data sources:

For voice: ACD systems log queue entry and answer timestamps
For chat: Your chat platform records conversation start and first agent response
For email: Less meaningful since email is asynchronous

Segment by: Channel, time of day, customer segment, issue type, and region. A blended average hides problems in specific queues.

Want to reduce wait times with AI that actually resolves issues? See how Lorikeet handles contacts without queueing.

Worked Example

A B2B SaaS company tracks chat AWT for a Tuesday afternoon:

Customer A: 3 min wait, answered
Customer B: 3 min wait, answered
Customer C: 12 min wait, answered
Customer D: 3 min wait, answered
Customer E: 8 min wait, abandoned

AWT (Answered only): (3+3+12+3) / 4 = 5.25 minutes

AWT (All contacts): (3+3+12+3+8) / 5 = 5.8 minutes

The 10% gap is relatively small here. If abandonment were higher with longer waits, the gap would be dramatic.

Common Pitfalls

Excluding abandoned contacts from the calculation. The most common form of unintentional metric gaming.

Fix: Track both answered and all-contacts AWT. Report the gap as a quality signal.

Ignoring IVR and pre-queue time. Your metric says 45 seconds; your customer experienced 3+ minutes.

Fix: Measure total elapsed time from first contact attempt.

Treating blended averages as meaningful. Company-wide AWT might hide that billing runs at 30 seconds while technical runs at 8 minutes.

Fix: Segment by queue, channel, and customer tier.

Optimizing AWT at the expense of resolution quality. Rushing customers off hold to hit targets, only to transfer them multiple times.

Fix: Pair AWT with FCR and CSAT.

Lorikeet's Take

At Lorikeet, we've learned that AWT is a supply-demand problem at its core. Staffing model improvements and contact volume reduction through effective self-service are higher-leverage than incremental process optimizations.

The most honest way to measure AWT includes abandoned contacts. The gap between answered-only and all-contacts AWT tells you how much your headline metric is flattering you. We recommend reporting both.

Finally, AWT doesn't tell you whether the wait was worth it. A customer who waited 5 minutes and got their problem solved is happier than one who waited 30 seconds and got transferred three times. Pair AWT with resolution quality metrics.

Key Takeaways

The denominator decision (answered only vs. all contacts) dramatically affects what AWT means.
Cross-platform comparisons are unreliable because wait time starts and stops at different points.
Blended averages hide queue-specific problems. Segment by cohort.
AWT is a supply-demand problem. Staffing and volume reduction are highest-leverage fixes.
Pair with resolution quality metrics. Fast answers that lead to poor outcomes create worse experiences.