Average Handle Time (AHT)

Average duration of a call from start to finish. This metric is measured in milliseconds and directly correlates with user satisfaction scores. Industry benchmarks suggest keeping Average Handle Time (AHT) under specific thresholds for optimal caller experience.

Traditional metric being redefined for AI agents. Optimizing Average Handle Time (AHT) directly impacts caller experience, system performance, and operational costs. Even small improvements can significantly enhance user satisfaction.

Average Handle Time (AHT) is calculated by measuring the time between specific events in the voice agent pipeline. The measurement starts when the triggering event occurs and ends when the measured outcome is achieved. Platforms like Twilio, Bland AI, Hamming each implement Average Handle Time (AHT) with different approaches and optimizations.

Organizations implementing Average Handle Time (AHT) frequently encounter challenges with measurement accuracy, inconsistent performance across different network conditions, and difficulty achieving target benchmarks. High Average Handle Time (AHT) often results from inadequate infrastructure, unoptimized models, or poor network connectivity. Automated testing and monitoring can help identify these issues before they impact production callers.

Monitor AHT patterns: identify outliers with excessive duration, correlate AHT with task complexity, optimize conversation flow to reduce AHT, and balance efficiency with task completion.