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Who Is Today's Call Center Agent?

CCNG

then you know firsthand the diverse makeup of the agent population - from millennials to individuals near retirement age and career call center professionals to persons seeking short-term employment. Some are seeking longer tenure and career advancement into management, while others do not see themselves working in a call center long-term.

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Guest Post: Good Customer Service – How to Get It

ShepHyken

This week, we feature an article by Josh Centers, a Business Journalist at TextExpander , a platform that empowers teams and individuals to save time and eliminate repetitive typing with just a few keystrokes. He shares the challenges that customer service representatives face and how companies can overcome them. Toister has a theory.

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5 Things Online Casino Players Look for In Customer Service in 2022

CSM Magazine

Clear Policy Terms. The best online casinos make sure that terms and conditions are made clear to players. In an increasingly digital world, all industries and sectors face growing challenges to provide great customer service. Yes, technology offers solutions in many respects, but tech can also be part of the problem at times.

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Get a “Beautiful Morning Weather” alert with Zapier and Vonage

Nexmo

Common Terms: Learn to Speak Zapier. During the past couple of months, most people’s lives and routines took a turn for the unexpected, and mine was no exception. The rhythm I’d gotten into suddenly wasn’t there anymore, and I’ve found myself in desperate need of bringing some structure back into my day-to-day.

APIs 62
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Advanced RAG patterns on Amazon SageMaker

AWS Machine Learning

Solution overview In this post, we demonstrate the use of Mixtral-8x7B Instruct text generation combined with the BGE Large En embedding model to efficiently construct a RAG QnA system on an Amazon SageMaker notebook using the parent document retriever tool and contextual compression technique.

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Get better insight from reviews using Amazon Comprehend

AWS Machine Learning

“85% of buyers trust online reviews as much as a personal recommendation” – Gartner. Consumers are increasingly engaging with businesses through digital surfaces and multiple touchpoints. Statistics show that the majority of shoppers use reviews to determine what products to buy and which services to use.

APIs 68
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Fine-tune Llama 2 for text generation on Amazon SageMaker JumpStart

AWS Machine Learning

The Llama 2 family of large language models (LLMs) is a collection of pre-trained and fine-tuned generative text models ranging in scale from 7 billion to 70 billion parameters. Fine-tuned LLMs, called Llama-2-chat, are optimized for dialogue use cases. Llama 2 is intended for commercial and research use in English.