Average Handle Time

Why It Matters

AHT is a primary driver of support operating costs and capacity planning. Lower AHT means agents can handle more interactions per shift, reducing cost per contact. However, AHT is a dangerous metric when optimized in isolation — pushing agents to reduce handle time without regard for resolution quality inflates repeat contacts and crushes customer satisfaction. The goal is the right AHT for the interaction type, not the lowest possible AHT. For AI chatbot deployments, AHT on escalated chats (where the bot passed context to the agent) should be significantly lower than cold contacts, reflecting the value of AI-provided context.

How It Works

AHT is tracked automatically by telephony systems, help desk platforms, and chat systems that timestamp interaction start, hold/pause periods, active time, and end. Wrap-up time is captured when agents use post-interaction work time in their system. Average is calculated across all interactions in a period. AHT analysis should be segmented by: issue type (simple vs. complex), channel (phone vs. chat), customer segment, and agent (for coaching purposes). Unusually high AHT interactions are reviewed for coaching opportunities or process improvements; unusually low AHT interactions may indicate inadequate resolution.

Real-World Example

Common Mistakes

• ✕Setting a universal AHT target — different interaction types have inherently different handle times; one target for all issue types is inappropriate
• ✕Rewarding agents for low AHT without also measuring resolution quality — this creates incentives to rush interactions and close tickets without solving the problem
• ✕Using AHT as a coaching metric for individuals without understanding their interaction mix — agents handling complex issues will naturally have higher AHT than those handling simple ones

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