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How to Boost Efficiency and Customer Satisfaction with Contact Center Analytics

Global Response

Types of analytics: Performance metrics are measured using different approaches, including descriptive, predictive, prescriptive, interaction, speech and text, self-service, and cross-channel analytics. Tracking first-call resolution (FCR) and other metrics, for example, help you pinpoint where agents excel and where they can improve.

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Evaluate RAG responses with Amazon Bedrock, LlamaIndex and RAGAS

AWS Machine Learning

Current RAG pipelines frequently employ similarity-based metrics such as ROUGE , BLEU , and BERTScore to assess the quality of the generated responses, which is essential for refining and enhancing the models capabilities. More sophisticated metrics are needed to evaluate factual alignment and accuracy.

Metrics 102
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Optimizing AI responsiveness: A practical guide to Amazon Bedrock latency-optimized inference

AWS Machine Learning

To effectively optimize AI applications for responsiveness, we need to understand the key metrics that define latency and how they impact user experience. These metrics differ between streaming and nonstreaming modes and understanding them is crucial for building responsive AI applications.

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Live Chat Benchmark Data & Best Practices for Financial Services & Banking

Comm100

To help you on this journey, this blog reveals the key financial services and banking metrics from our 2021 Live Chat Benchmark Report , alongside top live chat best practices that will help you to gain your clients’ trust and loyalty. – Chatbots. Chatbots are the ultimate tool to manage high customer support volumes.

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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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9 Contact Center Quality Assurance Best Practices: Modernize Your Approach, Optimize Your Performance

Calabrio

Call center QA, or contact center QA, is a strategic, data-driven process that evaluates every facet and channel of customer interactionsfrom voice calls and live chats to emails and social media engagementsagainst established performance benchmarks. Ensure agents fully understand these standards, including the metrics used for evaluation.

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Comment l'IA peut vous aider à améliorer l'expérience de vos clients pendant les périodes de pointe. 

Inbenta

The benchmarks for customer service teams include customer satisfaction, NPS, churn, resolution rate, handle time and other metrics that measure customer service quality, effectiveness and efficiency.   Keeping KPIs high during peak periods can be difficult.

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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.