Amazon Personalize Documentation

Automated machine learning

Once you have provided your data via Amazon S3 or via real-time integrations, Amazon Personalize can load and inspect the data, enable you to select the right algorithms, train a model, provide metrics, and generate personalized recommendations. As your data set grows over time from new metadata and the consumption of real-time user event data, your models can be retrained to provide relevant and personalized recommendations. 

Batch recommendations

Compute recommendations for large numbers of users or items, store them, and feed them to batch-oriented workflows such as email systems. 

New user and new item recommendations

Generate recommendations even for new users and find new item recommendations for your users.

Contextual recommendations

Improve relevance of recommendations by generating them within a context. 

Similar item recommendations

Improve the discoverability of your catalog by surfacing similar items to your users.

Unlock Information in Unstructured Text

Unlock the information trapped in product descriptions, reviews, movie synopses or other unstructured text to help you generate highly relevant recommendations for users. Provide unstructured text as part of your catalog and Amazon Personalize extracts key information to use when generating recommendations.

Prioritizing your business goals and what is relevant for your users

Consider what’s relevant to your users and what is important for your business when generating recommendations. You can define an objective to influence recommendations. This can be used to help you maximize for metrics you define as important to your business.

Integrate with your existing tools

Amazon Personalize can be integrated into websites, mobile apps, or content management and email marketing systems, via an inference API call. The service lets you generate user recommendations, similar item recommendations and personalized re-ranking of items. You can call the Amazon Personalize APIs and the service will output item recommendations or a re-ranked item list, which you can use in your application.

GetRecommendations API - returns a list of relevant items when you provide a userID. The API can also be used to return a list of similar itemIDs given an input itemID. 

GetPersonalizedRanking – You can use an API to re-rank a list of itemIDs given a userID and a list of itemIDs to be re-ranked. 

Additional Information

For additional information about service controls, security features and functionalities, including, as applicable, information about storing, retrieving, modifying, restricting, and deleting data, please see This additional information does not form part of the Documentation for purposes of the AWS Customer Agreement available at, or other agreement between you and AWS governing your use of AWS’s services.