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Implement real-time personalized recommendations using Amazon Personalize

AWS Machine Learning

Businesses use their data with an ML-powered personalization service to elevate their customer experience. Amazon Personalize accelerates your digital transformation with ML, making it easier to integrate personalized recommendations into existing websites, applications, email marketing systems, and more.

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How Does Mental Accounting Influence Customer Experience

Beyond Philosophy

The answer is found in the concept of mental accounting, and it might have significant implications for your Customer Experience. We discussed how our mental accounting affects our behavior as customers in our recent podcast. How Mental Accounting Works. We have written about Mental Accounting before.

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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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Build your multilingual personal calendar assistant with Amazon Bedrock and AWS Step Functions

AWS Machine Learning

They often find themselves struggling with language barriers when it comes to setting up reminders for events like business gatherings and customer meetings. Extract events information such as subject, location, and time from the original message. Generate an action plan list for events.

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Amazon Personalize launches new recipes supporting larger item catalogs with lower latency

AWS Machine Learning

Personalized customer experiences are essential for engaging today’s users. However, delivering truly personalized experiences that adapt to changes in user behavior can be both challenging and time-consuming. A higher coverage means Amazon Personalize recommends more of your catalog. compared to previous versions.

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Prepare your data for Amazon Personalize with Amazon SageMaker Data Wrangler

AWS Machine Learning

Transforming raw data into a format that is suitable for a model is key to getting better personalized recommendations for end-users. To be able to develop this understanding of users, Amazon Personalize needs to train on the historical user behavior so that it can find patterns that are generalizable towards the future.

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How Thomson Reuters delivers personalized content subscription plans at scale using Amazon Personalize

AWS Machine Learning

TR’s customers span across the financial, risk, legal, tax, accounting, and media markets. The key requirement for TR’s new machine learning (ML)-based personalization engine was centered around an accurate recommendation system that takes into account recent customer trends. Solution architecture.