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Call Center Metrics: Examples, Tips & Best Practices

Callminer

These tips provide valuable insight into choosing and using call center metrics more effectively to condense performance data into actionable insights.

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Security best practices to consider while fine-tuning models in Amazon Bedrock

AWS Machine Learning

In this post, we delve into the essential security best practices that organizations should consider when fine-tuning generative AI models. Analyze results through metrics and evaluation. For Security group name , enter a name (for example, bedrock-kms-interface-sg ). Set up IAM permissions for data access.

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Best practices for Meta Llama 3.2 multimodal fine-tuning on Amazon Bedrock

AWS Machine Learning

In this post, we share comprehensive best practices and scientific insights for fine-tuning Meta Llama 3.2 One notable advantage of multimodal fine-tuning is its effectiveness with mixed datasets that contain both text-only and image and text examples. Amazon Bedrock now offers fine-tuning capabilities for Meta Llama 3.2

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What are QA Metrics? Examples of QA Metrics for Call Centers, Aligning Metrics with Your Goals, and Best Practices

Callminer

QA metrics refer to the data your company uses to measure performance. Interestingly, QA metrics can vary significantly by industry, since they reflect performance as defined by that industry.

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What is Average Handle Time? Challenges, Examples, and Best Practices for Improving AHT Copy

Callminer

Average handle time, or AHT, is an important call center metric. hurry customers off the phone, whether their problems are resolved or not – to reduce AHT, this would lead to dissatisfied customers and other declining metrics, for example first call resolution (due to repeat callers attempting to resolve their issues).

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20 Call Center Pros Share the Most Undervalued Call Center Metrics and How To Better Leverage Them

Callminer

From essentials like average handle time to broader metrics such as call center service levels , there are dozens of metrics that call center leaders and QA teams must stay on top of, and they all provide visibility into some aspect of performance. Kaye Chapman @kayejchapman. First contact resolution (FCR) measures might be…”.

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Best practices for Amazon SageMaker HyperPod task governance

AWS Machine Learning

In this post, we provide best practices to maximize the value of SageMaker HyperPod task governance and make the administration and data science experiences seamless. As a best practice, set the fair-share weight higher for teams that will require access to capacity sooner than other teams.