Remove Entertainment Remove Personalization Remove Scripts
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Unlocking insights and enhancing customer service: Intact’s transformative AI journey with AWS

AWS Machine Learning

The goal was to refine customer service scripts, provide coaching opportunities for agents, and improve call handling processes. This efficiency has allowed for more effective use of auditors’ time in devising coaching strategies, improving scripts, and agent training.

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5 Things Pro Wrestling Teach Us About Customer Service

Steve DiGioia

I used to take the train from my home in Brooklyn, NY to Madison Square Garden in Manhattan each month to watch the matches in person. The fans need to be entertained and the wrestler won’t let them down. They are here to not just satisfy but to exceed their fan’s need for entertainment. And we watch it every week.

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Drive hyper-personalized customer experiences with Amazon Personalize and generative AI

AWS Machine Learning

Today, we are excited to announce three launches that will help you enhance personalized customer experiences using Amazon Personalize and generative AI. Amazon Personalize is a fully managed machine learning (ML) service that makes it easy for developers to deliver personalized experiences to their users.

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5 Keys to Writing a Successful B2B Telemarketing Script

Quality Contact Solutions

Recently I was asked what the key was to create a robust B2B Telemarketing Script. It’s a good question, and after having helped develop and implement thousands of successful scripts over the years, I don’t have that 30-second elevator pitch answer to that question. What is the goal of the script?

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

Callminer

Bill Dettering is the CEO and Founder of Zingtree , a SaaS solution for building interactive decision trees and agent scripts for contact centers (and many other industries). Interactive agent scripts from Zingtree solve this problem. Agents can also send feedback directly to script authors to further improve processes.

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Power recommendation and search using an IMDb knowledge graph – Part 1

AWS Machine Learning

The IMDb and Box Office Mojo Movies/TV/OTT licensable data package provides a wide range of entertainment metadata, including over 1 billion user ratings; credits for more than 11 million cast and crew members; 9 million movie, TV, and entertainment titles; and global box office reporting data from more than 60 countries.

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Centralize model governance with SageMaker Model Registry Resource Access Manager sharing

AWS Machine Learning

from time import gmtime, strftime experiment_suffix = strftime('%d-%H-%M-%S', gmtime()) experiment_name = f"credit-risk-model-experiment-{experiment_suffix}" The processing script creates a new MLflow active experiment by calling the mlflow.set_experiment() method with the experiment name above. fit_transform(y).