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Elevate your marketing solutions with Amazon Personalize and generative AI

AWS Machine Learning

Enterprises are using generative AI specifically to power their marketing efforts through emails, push notifications, and other outbound communication channels. Gartner predicts that “by 2025, 30% of outbound marketing messages from large organizations will be synthetically generated.”

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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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Unlock personalized experiences powered by AI using Amazon Personalize and Amazon OpenSearch Service

AWS Machine Learning

Amazon Personalize allows you to add sophisticated personalization capabilities to your applications by using the same machine learning (ML) technology used on Amazon.com for over 20 years. You can also add data incrementally by importing records using the Amazon Personalize console or API. No ML expertise is required.

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Customize your recommendations by promoting specific items using business rules with Amazon Personalize

AWS Machine Learning

Today, we are excited to announce Promotions feature in Amazon Personalize that allows you to explicitly recommend specific items to your users based on rules that align with your business goals. You can use promotions in domain dataset groups and custom dataset groups ( User-Personalization and Similar-Items recipes).

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How Amp on Amazon used data to increase customer engagement, Part 2: Building a personalized show recommendation platform using Amazon SageMaker

AWS Machine Learning

Amp uses machine learning (ML) to provide personalized recommendations for live and upcoming Amp shows on the app’s home page. This is Part 2 of a series on using data analytics and ML for Amp and creating a personalized show recommendation list platform. Measuring the outcome. Conclusion.

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The Rise of Machine Customers: How to Seamlessly Integrate Services

CSM Magazine

Understanding these implications is crucial, as the presence of machine customers is growing and will potentially reshape markets and how businesses approach customer service and experience. For example, they can autonomously purchase goods and services, reflecting an evolving understanding of customer preferences and market dynamics.

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How Amp on Amazon used data to increase customer engagement, Part 1: Building a data analytics platform

AWS Machine Learning

Amp wanted a scalable data and analytics platform to enable easy access to data and perform machine leaning (ML) experiments for live audio transcription, content moderation, feature engineering, and a personal show recommendation service, and to inspect or measure business KPIs and metrics. This post is the first in a two-part series.