As the touchpoints customers use to engage with brands move to an increasingly complex mixture of digital and real-life interactions, you’re faced with the daunting task of delighting your customers with personalized experiences that hit the mark across these channels. Customer expectations are evolving as well. Today’s customers quickly lose patience with brands that can’t seamlessly support transitioning experiences between mobile, web, email, SMS, call centers, and in-person engagements.
Amazon Personalize applies machine learning (ML) algorithms to produce personalized recommenders, also known as campaigns, that understand a user’s preferences over time while also adapting to a user’s evolving interests in real time. This powerful tool helps you deliver truly personalized customer experiences. However, putting Amazon Personalize to work across channels requires a thoughtful approach to the architecture and tools you use to power these experiences.
This post shows you how to integrate Amazon Personalize into a sample full-stack eCommerce application

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