Remove Construction Remove Metrics Remove Scripts
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What is Call Center Quality Assurance?

OctopusTech

In the case of a call center, you will mark the performance of the agents against key performance indicators like script compliance and customer service. The goal of QA in any call center is to maintain high levels of service quality, ensure agents adhere to company policies and scripts, and identify areas of improvement.

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The Customer Success Maturity Model Part 2: “Operationalize” Capabilities (Constructing Your CS System)

Education Services Group

Constructing and evolving these processes is the second category of capabilities on the ESG Customer Success Maturity Model. Metrics that track your customers’ experience are crucial to the stability and longevity of your CS organization. Let’s break that down a bit. CX (NPS, CSAT, etc.).

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International Contact Centre Operations Tips & Best Practices

Callminer

Encourage agents to cheer up callers with more flexible scripting. “A 2014 survey suggested that 69% of customers feel that their call center experience improves when the customer service agent doesn’t sound as though they are reading from a script. They are an easy way to track metrics and discover trends within your agents.

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Enhancing LLM Capabilities with NeMo Guardrails on Amazon SageMaker JumpStart

AWS Machine Learning

Colang is purpose-built for simplicity and flexibility, featuring fewer constructs than typical programming languages, yet offering remarkable versatility. It leverages natural language constructs to describe dialogue interactions, making it intuitive for developers and simple to maintain. define bot express greeting "Hey there!"

Chatbots 118
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Create a document lake using large-scale text extraction from documents with Amazon Textract

AWS Machine Learning

The first allows you to run a Python script from any server or instance including a Jupyter notebook; this is the quickest way to get started. The second approach is a turnkey deployment of various infrastructure components using AWS Cloud Development Kit (AWS CDK) constructs. We have packaged this solution in a.ipynb script and.py

Scripts 131
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Build an air quality anomaly detector using Amazon Lookout for Metrics

AWS Machine Learning

This post shows you how to use an integrated solution with Amazon Lookout for Metrics and Amazon Kinesis Data Firehose to break these barriers by quickly and easily ingesting streaming data, and subsequently detecting anomalies in the key performance indicators of your interest. You don’t need ML experience to use Lookout for Metrics.

Metrics 98
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Build an end-to-end MLOps pipeline for visual quality inspection at the edge – Part 2

AWS Machine Learning

With this format, we can easily query the feature store and work with familiar tools like Pandas to construct a dataset to be used for training later. We can follow a simple three-step process to convert an experiment to a fully automated MLOps pipeline: Convert existing preprocessing, training, and evaluation code to command line scripts.

Scripts 124