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Putting Humanity in Contact Centers

Customer Relationship Metrics

The reasons behind millennials’ desire to enhance their skills and to further their careers is a great opportunity when a constructive process exists. Organizations must create performance management and employee development programs that use customer relationship metrics to drive their service delivery. In the Early Years.

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Call Center optimization: Tools and best practices to increase performance

NobelBiz

Performance Metrics and KPIs: Monitoring call center performance is essential. Metrics include First Call Resolution , Customer Satisfaction Score , and Call Handling Time 1. First Call Resolution (FCR) : This metric measures the ability of agents to resolve customer queries or issues on the first call.

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Call Center Quality Management: A Comprehensive Guide to Improving Customer Satisfaction and Agent Performance

NobelBiz

Using technology to record and analyze each and every customer encounter, developing and employing evaluation criteria, teaching and training agents, reporting and monitoring quality metrics are all part of call center quality management. Feedback should be specific, constructive, and actionable.

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Face-off Probability, part of NHL Edge IQ: Predicting face-off winners in real time during televised games

AWS Machine Learning

We also share the key technical challenges that were solved during construction of the Face-off Probability model. The decision tree provided the cut-offs for each metric, which we included as rules-based logic in the streaming application. At the end, we found that the LightGBM model worked best with well-calibrated accuracy metrics.

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Treating employees as customers

Connecting the Dots

Implementing learnings from a well-constructed survey results in employees incentivized to give great service, empowered with the tools, information (including clear, truthful and timely answers to common customer questions and concerns) and authority needed to perform their jobs. Metrics to enhance success and prevention.

Surveys 62
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Evaluate the text summarization capabilities of LLMs for enhanced decision-making on AWS

AWS Machine Learning

In this post, we explore leading approaches for evaluating summarization accuracy objectively, including ROUGE metrics, METEOR, and BERTScore. These metrics focus on assessing the overlap between the content of machine-generated and human-crafted summaries by analyzing n-grams, which are groups of words or tokens.

Metrics 74
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Treating employees as customers

Connecting the Dots

Implementing learnings from a well-constructed survey results in employees incentivized to give great service, empowered with the tools, information (including clear, truthful and timely answers to common customer questions and concerns) and authority needed to perform their jobs. Metrics to enhance success and prevention.

Surveys 48