Category: Amazon Personalize

This post was last reviewed and updated June, 2022. When this blog post was initially published, English was the only language supported for the textual field in the items dataset. Now Amazon Personalize supports textual field values in Chinese (simplified and traditional), French, German, Japanese, Portuguese, and Spanish; removes HTML and XML markup and whitespace […]

January 2022 – HiConversion is now Obviyo. We have updated this blog to reflect the new company name. You can read more about the name change on Obviyo’s blog. This is a guest post by Jeff McKelvey, Principal Development Lead at Obviyo. The team at Obviyo has collaborated closely with James Jory, Applied AI Services […]

Data can be used in a variety of ways to satisfy the needs of different business units, such as marketing, sales, or product. In this post, we focus on using data to create personalized recommendations to improve end-user engagement. Most ecommerce applications consume a huge amount of customer data that can be used to provide […]

Machine learning (ML)-based recommender systems aren’t a new concept across organizations such as retail, media and entertainment, and education, but developing such a system can be a resource-intensive task—from data labelling, training and inference, to scaling. You also need to apply continuous integration, continuous deployment, and continuous training to your ML model, or MLOps. The […]

This is a guest post by Jeff Finkelstein, founder of Customer Paradigm, a full-service interactive media firm and Magento solutions partner. Many small retailers use Magento, an open-source ecommerce platform, to create websites or mobile applications to sell their products online. Personalization is key to creating high-quality ecommerce experiences, but small businesses often lack access […]

This blog post was last reviewed or updated April, 2022 with database schema updates. We’re excited to announce dynamic filters in Amazon Personalize, which allow you to apply business rules to your recommendations on the fly, without any extra cost. Dynamic filters create better user experiences by allowing you to tailor your business rules for […]

Every day there is something new going on in the world of AWS Machine Learning—from launches to new to use cases to interactive trainings. We’re packaging some of the not-to-miss information from the ML Blog and beyond for easy perusing each month. Check back at the end of each month for the latest roundup. Launches […]

This blog post was last reviewed and updated April, 2022 with database schema updates. We’re excited to announce new efficiency improvements for Amazon Personalize. These improvements decrease the time required to train solutions (the machine learning models trained with your data) by up to 40% and reduce the latency for generating real-time recommendations by up […]

This blog post was last reviewed or updated April, 2022 with database schema updates. Amazon Personalize now makes it easier to manage your growing item and user catalogs with new APIs to incrementally add items and users in your datasets to create personalized recommendations. With the new putItems and putUsers APIs, you can simplify the […]

In this post, we show you how to select the right metadata for your use case when building a recommendation engine using Amazon Personalize. The aim is to help you optimize your models to generate more user-relevant recommendations. We look at which metadata is most relevant to include for different use cases, and where you […]