Category: Amazon Personalize

With personalized content more likely to drive customer engagement, businesses continuously seek to provide tailored content based on their customer’s profile and behavior. Recommendation systems in particular seek to predict the preference an end-user would give to an item. Some common use cases include product recommendations on online retail stores, personalizing newsletters, generating music playlist […]

We are excited to announce that Amazon Personalize now supports incremental bulk dataset imports; a new option for updating your data and improving the quality of your recommendations. Keeping your datasets current is an important part of maintaining the relevance of your recommendations. Prior to this new feature launch, Amazon Personalize offered two mechanisms for […]

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. For instance, you can have marketing partnerships that require you to promote certain brands, in-house content, or categories that you want to improve the […]

August 30, 2023: Amazon Kinesis Data Analytics has been renamed to Amazon Managed Service for Apache Flink. Read the announcement in the AWS News Blog and learn more. Many companies must tackle the difficult use case of building a highly optimized recommender system. The challenge comes from processing large volumes of data to train and […]

Today, customers interact with brands over an increasingly large digital and offline footprint, generating a wealth of interaction data known as behavioral data. As a result, marketers and customer experience teams must work with multiple overlapping tools to engage and target those customers across touchpoints. This increases complexity, creates multiple views of each customer, and […]

Today, we’re excited to announce intelligent user segmentation powered by machine learning (ML) in Amazon Personalize, a new way to deliver personalized experiences to your users and run more effective campaigns through your marketing channels. Traditionally, user segmentation depends on demographic or psychographic information to sort users into predefined audiences. More advanced techniques look to […]

Today, we’re excited to announce the launch of personalized recommenders in Amazon Personalize that are optimized for retail and media and entertainment, making it even easier to personalize your websites, apps, and marketing campaigns. With this launch, we have drawn on Amazon’s rich experience creating unique personalized user experiences using machine learning (ML) to build […]

It’s almost here! Only 9 days until AWS re:Invent 2021, and we’re very excited to share some highlights you might enjoy this year. The AI/ML team has been working hard to serve up some amazing content and this year, we have more session types for you to enjoy. Back in person, we now have chalk […]

Today, we’re excited to announce a new similar items recommendation recipe (aws-similar-items) in Amazon Personalize that helps you leverage your users’ interaction histories and what you know about the items in your catalog to deliver relevant recommendations. Across Amazon, we provide personalized experiences for each of our users, and based on a user’s interests, we […]

This is a guest post by Shae Selix (Staff Data Scientist at Calm) and Luis Lopez Soria (Sr. AI/ML Specialist SA at AWS). Today, content is proliferating. It’s being produced in many different forms by a host of content providers, both large and small. Whether it’s on-demand video, music, podcasts, or other forms of rich […]