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2020 Call Center Metrics: 6 Key Metrics for Your Call Center Dashboard

Callminer

At the heart of most technological optimizations implemented within a successful call center are fine-tuned metrics. Keeping tabs on the right metrics can make consistent improvement notably simpler over the long term. However, not all metrics make sense for a growing call center to monitor. Peak Hour Traffic.

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Introducing the Amazon SageMaker Serverless Inference Benchmarking Toolkit

AWS Machine Learning

To help determine whether a serverless endpoint is the right deployment option from a cost and performance perspective, we have developed the SageMaker Serverless Inference Benchmarking Toolkit , which tests different endpoint configurations and compares the most optimal one against a comparable real-time hosting instance.

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Ground truth curation and metric interpretation best practices for evaluating generative AI question answering using FMEval

AWS Machine Learning

This post focuses on evaluating and interpreting metrics using FMEval for question answering in a generative AI application. FMEval is a comprehensive evaluation suite from Amazon SageMaker Clarify , providing standardized implementations of metrics to assess quality and responsibility. Question Answer Fact Who is Andrew R.

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How to Establish a Net Promoter Score Benchmark for Your Call Center

Fonolo

The best strategy is to use a combination of data reports and benchmarking to ensure your findings reflect “the big picture” Creating a Customer Service Strategy That Drives Business Growth. NPS is one of the strongest customer service metrics available to a call center. How to Establish a Net Promoter Score Benchmark.

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Study: The Health of the Contact Center

What does it take to engage agents in this customer-centric era? Download our study of 1,000 contact center agents in the US and UK to find out what major challenges are facing contact center agents today – and what your company can do about it.

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Fine-tune multimodal models for vision and text use cases on Amazon SageMaker JumpStart

AWS Machine Learning

Vision Instruct models demonstrated impressive performance on the challenging DocVQA benchmark for visual question answering. ANLS is a metric used to evaluate the performance of models on visual question answering tasks, which measures the similarity between the model’s predicted answer and the ground truth answer. The Meta Llama 3.2

Benchmark 108
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Get started with Amazon Titan Text Embeddings V2: A new state-of-the-art embeddings model on Amazon Bedrock

AWS Machine Learning

As new embedding models are released with incremental quality improvements, organizations must weigh the potential benefits against the associated costs of upgrading, considering factors like computational resources, data reprocessing, integration efforts, and projected performance gains impacting business metrics.

Benchmark 128
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The Health of the Contact Center: Are You Ready for 2019?

A survey of 1,000 contact center professionals reveals what it takes to improve agent well-being in a customer-centric era. This report is a must-read for contact center leaders preparing to engage agents and improve customer experience in 2019.