Amazon Personalize

Create real-time personalized user experiences faster at scale

Amazon Personalize enables developers to build applications with the same machine learning (ML) technology used by for real-time personalized recommendations – no ML expertise required.

Amazon Personalize makes it easy for developers to build applications capable of delivering a wide array of personalization experiences, including specific product recommendations, personalized product re-ranking, and customized direct marketing. Amazon Personalize is a fully managed machine learning service that goes beyond rigid static based rules based recommendation systems and trains, tunes, and deploys custom ML models to deliver highly customized recommendations to customers across industries such as retail and media and entertainment.

Amazon Personalize provisions the necessary infrastructure and manages the entire ML pipeline, including processing the data, identifying features, using the best algorithms, and training, optimizing, and hosting the models. You will receive results via an Application Programming Interface (API) and only pay for what you use, with no minimum fees or upfront commitments. All data is encrypted to be private and secure, and is only used to create recommendations for your users.


Introducing Amazon Personalize (3:28)


Deliver high quality recommendations, in real-time

The ML algorithms used by Amazon Personalize create higher quality recommendations that respond to the specific needs, preferences, and changing behavior of your users, improving engagement and conversion. They are also designed to address complex problems such as creating recommendations for new users, products, and content with no historical data.  



Easily implement personalized recommendations in days, not months

With Amazon Personalize, you can implement a customized personalization recommendation system, powered by ML, in just a few clicks without the burden of building, training, and deploying a “do it yourself” ML solution.  


Personalize every touchpoint along the customer journey

Amazon Personalize easily integrates into your existing websites, apps, SMS, and email marketing systems to provide a unique customer experience for across all channels and devices eliminating high infrastructure or resource costs. Amazon Personalize provides flexibility for you to use real-time or batch recommendations based on what is most appropriate for your use case, enabling you to deliver a wide variety of personalized experiences to customers at scale.



How it works

How Amazon Personalize works

Amazon Personalize for Retail

Create unique homepages

Personalize your users homepage with product recommendations based on their shopping history.

Refine product recommendations

Recommend similar items on product detail pages to help users easily find what they are looking for.

Help customers discover products faster

Help users quickly find relevant new products, deals, and promotions.

Relevant product rankings

Easily re-rank relevant product recommendations to drive tangible business outcomes.


Enhance marketing communication

Personalize push notifications and marketing emails with individualized product recommendations.

Boost upsell and cross-sell

Combine Amazon Personalize with business logic to create high quality cart upsell and cross-sell recommendations.


Learn how StockX is using Amazon Personalize to create pioneering customized experiences for their customers, with no prior machine learning experience.

"We’re quickly learning the potency of integrating ML into all facets of the company. Our success led to key decision-makers requesting we integrate Amazon Personalize into more of the StockX experience and expand our ML endeavors. It’s safe to say that personalization is now a first-class citizen here."

Lotte Mart

Learn how Lotte Mart is using Amazon Personalize to enable over 600,000 users to save on their in store shopping experience.

“By using Amazon Personalize, we have seen a 5x increase in response to recommended products compared to our prior big data analytics solution resulting in increased revenue per month. In particular, Amazon Personalize has increased the number of products that the customer has never purchased before up to 40%. The new recommendation service powered by AWS is the first of a much broader roll-out of AI technologies across our organization“

Read blog »

Amazon Personalize for Media and Entertainment

Increase content consumption

Deliver highly relevant, individualized content recommendations for videos, music, e-books, and more.

Create personalized ad placements

Personalize pre-roll, mid-roll, and post-roll ad placements within audio and video content.

Highly curated content carousels

Create personalized content carousels for every user based on their content consumption history.

Improve marketing communication

Personalize push notifications and marketing emails with individualized content recommendations.

Highlight new content offerings

Help users find fresh, new content based on their unique tastes and preferences.

Enhance genre based recommendations

Add individualized recommendations to genre based on content carousels and lists.


Learn how Pulselive use Amazon Personalize to increase video views by 20%, highlight new content offerings, and build subscriber base.

"We were thrilled by our first foray into the world of ML with Amazon Personalize. We found the entire process of integrating a trained model into our workflow was incredibly simple"

Lotte Mart
"Using Amazon Personalize we have automated tailored recommendations starting on every user’s first day within the apps, resulting in a 15% increase in retention amongst these users. Furthermore, by reducing our dependency on our home grown personalization tool, we have reduced our development time by 53%, enabling our teams to focus on the next set of opportunities to further improve experiences for our customers."


Blog posts & articles >>

Amazon Personalize can now create up to 50% better recommendations for fast changing catalogs of new product and content

August, 2020
Hao Ding, Vaibhav Sethi, and Yen Su

Read blog »

Increasing the relevance of your Amazon Personalize recommendations by leveraging contextual information

August, 2020
Luis Lopez Soria

Read blog »

Introducing recommendation filters in Amazon Personalize


June 8, 2020
Vaibhav Sethi and Adam Ta

Read blog »

Tech Talk: Offer Your Customers Real-Time Personalized Recommendations


June, 2020
Vaibhav Sethi and Adam Ta

Watch Now »

Amazon Personalize features
Check out the product features

Easily build sophisticated personalization capabilities into your applications

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