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International Contact Centre Operations Tips & Best Practices

Callminer

Use of recorded calls where similar issues were handled adeptly are particularly effective here.” – 5 Call Center Training Best Practices , CallMiner; Twitter: @CallMiner. ” – 15 Best Practices For Effective Call Center Management , Sling. Offer rewards for great performance.

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Customer Success in SaaS: A Complete Guide & Best Practices

Totango

SaaS success outcomes can be defined in terms of measurable digital benchmarks. SaaS technology and supporting apps should be used to implement a data-driven approach to customer success, automate best practices, monitor results, and manage performance. This makes success quantifiable for objective, data-driven CS management.

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

Callminer

Average Handle Time (AHT) gives an accurate, real-time measurement of the usual amount of time it takes to handle an interaction from start to finish, from the initiation of the call to the time your organization’s call center agents are spending on the phone with individual callers and handling any follow-up tasks, such as documentation.

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Best practices to build generative AI applications on AWS

AWS Machine Learning

Their research indicates that zero-shot CoT, using the same single-prompt template, significantly outperforms zero-shot FM performances on diverse benchmark reasoning tasks. Writing assistance – RAG can suggest relevant content, facts, and talking points to help you write documents such as articles, reports, and emails more efficiently.

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Best practices for building robust generative AI applications with Amazon Bedrock Agents – Part 1

AWS Machine Learning

This two-part series explores best practices for building generative AI applications using Amazon Bedrock Agents. This data provides a benchmark for expected agent behavior, including the interaction with existing APIs, knowledge bases, and guardrails connected with the agent.

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

AWS Machine Learning

In this post, we discuss best practices for working with FMEval in ground truth curation and metric interpretation for evaluating question answering applications for factual knowledge and quality. We used Amazon’s Q2 2023 10Q report as the source document from the SEC’s public EDGAR dataset to create 10 question-answer-fact triplets.

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Best practices and lessons for fine-tuning Anthropic’s Claude 3 Haiku on Amazon Bedrock

AWS Machine Learning

In this post, we explore the best practices and lessons learned for fine-tuning Anthropic’s Claude 3 Haiku on Amazon Bedrock. However, achieving optimal performance with fine-tuning requires effort and adherence to best practices.