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How to measure customer service skills

Toister Performance Solutions

Hiring, training, and giving feedback would all be easier if you could accurately measure customer service skills like rapport, listening, or empathy. There are the big three : Rapport Understanding Solving Rapport is most connected to friendliness, so let's go with that for this example. The analyst was stymied.

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Cutting Through the Buzzwords of AI in the Contact Center

CCNG

Generative AI is responsive and can generate high-quality text, images, responses, and content and utilize logic based on how it is trained. For example, you can take all your historical recorded conversations and current conversations from all channels, create a dashboard, and be able to organize that data by anything you imagine.

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How SaaS Unicorn Pipedrive Uses Klaus, Aircall & Intercom to Provide Excellent Customer Service

aircall

In combining these formats, Pipedrive is able to capitalize on their insights with better training. Maintaining fair and consistent grading with regular calibration sessions. To ensure this, Pipedrive conducts regular calibration sessions to ensure all the graders are on the same page. Managing agent appeals.

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Time to Fire your Training Department?

BetterXperience

So naturally, it’s time to find someone or something to blame so everyone else can feel better – you call it a post-mortem and almost every time you end up blaming training or “finding opportunities to improve training”. Is there really a bad customer interaction with your employees that isn’t the fault of training?

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The World Is Going Crazy

Beyond Philosophy

Then, on my return flight, we learned after taxiing through Heathrow that we were delayed because “the gate was not calibrated for the plane.” For example, Justin C. For example, many of the problems in the UK have to do with Brexit. Sure, it happens, I thought. However, that’s always been true.

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Accelerate Amazon SageMaker inference with C6i Intel-based Amazon EC2 instances

AWS Machine Learning

In the following example figure, we show INT8 inference performance in C6i for a BERT-base model. For more information, refer to Lower Numerical Precision Deep Learning Inference and Training. The following example is a question answering algorithm using a BERT-base model. The code snippets are derived from a SageMaker example.

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COPC Standards Committee Update: AI in Focus 

COPC

It is transforming key aspects such as employee recruitment, training, empowerment and team performance evaluation. While embracing the advancements brought by AI, it’s important to address concerns about its training, evaluation and impact on human staff.