What is Amazon Personalize? - Amazon Personalize
Pricing for Amazon PersonalizeRelated AWS services and solutionsThird-party servicesLearn more

What is Amazon Personalize?

Amazon Personalize is a fully managed machine learning service that uses your data to generate item recommendations for your users. It can also generate user segments based on the users' affinity for certain items or item metadata.

Common use case include the following:

  • Personalizing a video streaming app – You can use preconfigured or customizable Amazon Personalize resources to add multiple types of personalized video recommendations to your streaming app. For example, Top picks for you, More like X and Most popular video recommendations.

  • Adding product recommendations to an ecommerce app – You can use preconfigured or customizable Amazon Personalize resources to add multiple types of personalized product recommendations to your retail app. For example, Recommended for you, Frequently bought together and Customers who viewed X also viewed product recommendations.

  • Adding real-time next best action recommendations to your app – You can use customizable Amazon Personalize resources to recommend the actions that your users will most likely take based on their behavior. For example, you can add real-time recommendations for enrolling in your loyalty program, downloading your mobile app, or signing up for promotional emails.

  • Creating personalized emails – You can use customizable Amazon Personalize resources to generate batch recommendations for all users on an email list. Then you can use an AWS service or third party service to send users personalized emails recommending items in your catalog.

  • Creating a targeted marketing campaign – You can use Amazon Personalize to generate segments of users who will most likely interact with items in your catalog. Then you can use an AWS service or third party service to create a targeted marketing campaign that promotes different items to different user segments.

  • Personalizing search results – You can use customizable Amazon Personalize resources to personalize search results for your users. For example, Amazon Personalize can re-rank search results that you generate with OpenSearch.

For most use cases, Amazon Personalize generates recommendations primarily based on item interaction data. Item interaction data comes from your users interacting with items in your catalog. For example, users clicking different items. Your item interaction data can come from both your historical bulk interaction records in a CSV file, and real-time events from your users as they interact with your catalog. In some cases, Amazon Personalize also uses data from items and users such as genre, price, or gender. And for next best action scenarios, it uses actions and action interaction data.

When you import bulk data, you can use Amazon SageMaker Data Wrangler to import data from 40+ sources and prepare it for Amazon Personalize. For more information, see Preparing and importing bulk data using Amazon SageMaker Data Wrangler.

Amazon Personalize includes API operations for real-time personalization, and batch operations for bulk recommendations and user segments. You can get started quickly with use-case optimized recommenders for your business domain, or you can create your own configurable custom resources.

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Pricing for Amazon Personalize

With Amazon Personalize, there are no minimum fees and no upfront commitments. The AWS Free Tier provides a monthly quota of up to 20 GB of data processing per available AWS region, up to 100 hours of training time per eligible AWS region, and up to 180,000 recommendation requests. The free tier is valid for the first two months of usage.

For a complete list of charges and prices, see Amazon Personalize pricing.

Amazon Personalize integrates seamlessly with other AWS services and solutions. For example, you can:

  • Use Amazon SageMaker Data Wrangler (Data Wrangler) to import data from 40+ sources into an Amazon Personalize dataset. Data Wrangler is a feature of Amazon SageMaker Studio that provides an end-to-end solution to import, prepare, transform, and analyze data. For more information, see Preparing and importing bulk data using Amazon SageMaker Data Wrangler.

  • Use AWS Amplify to record item interaction events. Amplify includes a JavaScript library for recording events from web client applications. And it includes a library for recording events in server code. For more information, see Amplify Documentation.

  • Automate and schedule Amazon Personalize tasks with Maintaining Personalized Experiences with Machine Learning. This AWS Solutions Implementation automates the Amazon Personalize workflow, including data import, solution version training, and batch workflows.

  • Use Amazon CloudWatch Evidently to perform A/B testing with Amazon Personalize recommendations. For more information, see A/B testing with CloudWatch Evidently.

Third-party services

Amazon Personalize works well with various third-party services.

For a complete list of partners, see Amazon Personalize Partners.

Learn more

The following resources provide additional information about Amazon Personalize: