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How To Manage The Average Handling Time (AHT) For Contact Centers?

NobelBiz

However, it is obvious that insufficient training, incompatible interfaces and other factors might result in an increase of Average Handling Time. The AHT is a KPI that contact centers always strive to improve. But, how is the Average Handling Time (AHT) calculated?

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Unlocking insights and enhancing customer service: Intact’s transformative AI journey with AWS

AWS Machine Learning

Call processing and model serving Intact has on-premises contact centers and cloud contact centers, so they built a call acquisition process to ingest calls from both sources. Call Quality Trend Dashboard The following figure is an example of the Call Quality Trend Dashboard, showing the information available to agents.

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7 Essential Tips for Reducing Average Handling Time

VocalCom

For this reason, average handling time, or AHT, is often considered an important metric to measure in the contact center, as agents strive to offer great customer service while keeping their interactions as short as possible. Keeping agents well-informed is essential to reducing average handling time.

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Essentials of Cloud Contact Centers

Noble Systems

Ultimately, your unique business needs will determine what is included in your cloud contact center system. However, there are some technologies and capabilities that are must-haves for all cloud contact center deployments – here are the ten most essential. Speech analytics is another essential for cloud contact centers.

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Use generative AI to increase agent productivity through automated call summarization

AWS Machine Learning

Challenges with call summaries As contact centers collect more speech data, the need for efficient call summarization has grown significantly. However, most summaries are empty or inaccurate because manually creating them is time-consuming, impacting agents’ key metrics like average handle time (AHT).

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Principal Financial Group uses AWS Post Call Analytics solution to extract omnichannel customer insights

AWS Machine Learning

Each year, Principal handles millions of calls and digital interactions. As a first step, they wanted to transcribe voice calls and analyze those interactions to determine primary call drivers, including issues, topics, sentiment, average handle time (AHT) breakdowns, and develop additional natural language processing (NLP)-based analytics.

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Embracing AI in the contact centre starts with a top-down analysis

Connect

For example, automated chatbots can typically offload a large volume of common contact centre engagements by addressing repetitive issues with pre-programmed responses. A thematic analysis can easily identify the common phrases customers use most often when contacting the contact centre.