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Know How You Measure Up and See all the Difference: How your Team can Beat the Industry Standards of these Three Popular Call Center Metrics

SharpenCX

According to Gallup’s Re-Engineering Performance Management research, measurement is a positive pillar for developing employees. Getting benchmark data for your own contact center, then working to improve against those metrics, is crucial to better serving customers. Industry Standards: How do you Stack Up Against Your Peers?

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Establishing an AI/ML center of excellence

AWS Machine Learning

Examples of such standards include: Development framework – Establishing standardized frameworks for AI development, deployment, and governance provides consistency across projects, making it easier to adopt and share best practices. It helps manage and scale central policies and standards.

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Best practices to build generative AI applications on AWS

AWS Machine Learning

We provide an overview of key generative AI approaches, including prompt engineering, Retrieval Augmented Generation (RAG), and model customization. Building large language models (LLMs) from scratch or customizing pre-trained models requires substantial compute resources, expert data scientists, and months of engineering work.

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25 Call Center Leaders Share the Most Effective Ways to Boost Contact Center Efficiency

Callminer

Going from 50% first time resolution to 100% first time resolution might sound like a great target, but getting to 60% is already a 20% improvement over the benchmark. Since time is money in a contact center, first contact resolution is a primary goal, regardless of the industry. Scott Nazareth.

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Deploy large models at high performance using FasterTransformer on Amazon SageMaker

AWS Machine Learning

There is no industry standard for distillation, and many techniques are experimental. Prompt engineering Prompt engineering refers to efforts to extract accurate, consistent, and fair outputs from large models, such text-to-image synthesizers or large language models.

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Why the world’s leading brands are prioritizing in-country number testing?

Spearline

The test calls are recorded, and the audio quality is measured using the industry-standard Perceptual Evaluation of Speech Quality (ITU P.862 Monitor the performance of your entire telecommunications infrastructure and benchmark your performance against others in your industry using our advanced reporting features.

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Improving your LLMs with RLHF on Amazon SageMaker

AWS Machine Learning

Reinforcement Learning from Human Feedback (RLHF) is recognized as the industry standard technique for ensuring large language models (LLMs) produce content that is truthful, harmless, and helpful. Gone are the days when you need unnatural prompt engineering to get base models, such as GPT-3, to solve your tasks.