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Transitioning off Amazon Lookout for Metrics 

AWS Machine Learning

Amazon Lookout for Metrics is a fully managed service that uses machine learning (ML) to detect anomalies in virtually any time-series business or operational metrics—such as revenue performance, purchase transactions, and customer acquisition and retention rates—with no ML experience required.

Metrics 82
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Guest Blog: Live Chat Simplifies the Customer Journey

ShepHyken

The Royal Bank of Scotland uses the power of AI live chats to provide customers with real-time customer support. 4. Employs live chat analytics to better understand prospective buyers. To understand a website visitor’s behavior, live chat software is embedded with analytics tools. It improves the buying experience.

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Better Together (Blog#3)

Enghouse Interactive

Trends and Realities of Successful Organizations (Blog Series). Contact centers, using AI and UCaaS, drive better customer service perceptions, agent performance and improve overall outcomes . Blog #3 of 4: Customer-facing agents. AI – Finds What’s Been Overlooked. Agent Analytics (28.4% Back office support.

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Video-Enable Your Contact Center to Enhance CX (Blog #2)

Enghouse Interactive

Trends and Realities of Successful Organizations (Blog Series). In our first blog in this series, we explored how successful companies focus on implementing and optimizing the use of new technologies that help improve the customer experience. Blog #2 of 4: It’s NOT just another channel. Video is the new Face-to-Face.

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Super-Agents Are Real (Blog #4)

Enghouse Interactive

AI Makes It Possible (Blog Series). Blog #4 of 4 The MORE you know. How AI-Enabled Super-Agents Improve CX. Enable your Super-Agents with AI to Deliver Better CX. Adopt automation to make operations more efficient and agents more productive. Leverage AI to Transform the Customer Experience.

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How to Improve Call Center Customer Service

TechSee

In this blog post, we will explore these pain points, discuss best practices, and describe how AI and automation can not only improve call center customer service – they can revolutionize it. These two metrics are closely related, as longer handle times will naturally result in longer wait times for customers.

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Customized model monitoring for near real-time batch inference with Amazon SageMaker

AWS Machine Learning

Real-world applications vary in inference requirements for their artificial intelligence and machine learning (AI/ML) solutions to optimize performance and reduce costs. SageMaker Model Monitor monitors the quality of SageMaker ML models in production. Your client applications invoke this endpoint to get inferences from the model.

Scripts 89