Amazon Personalize

Real-time personalization and recommendation, based on the same technology used at

Amazon Personalize is a machine learning service that makes it easy for developers to create individualized recommendations for customers using their applications.

Machine learning is being increasingly used to improve customer engagement by powering personalized product and content recommendations, tailored search results, and targeted marketing promotions. However, developing the machine-learning capabilities necessary to produce these sophisticated recommendation systems has been beyond the reach of most organizations today due to the complexity of developing machine learning functionality. Amazon Personalize allows developers with no prior machine learning experience to easily build sophisticated personalization capabilities into their applications, using machine learning technology perfected from years of use on

With Amazon Personalize, you provide an activity stream from your application – page views, signups, purchases, and so forth – as well as an inventory of the items you want to recommend, such as articles, products, videos, or music. You can also choose to provide Amazon Personalize with additional demographic information from your users such as age, or geographic location. Amazon Personalize will process and examine the data, identify what is meaningful, select the right algorithms, and train and optimize a personalization model that is customized for your data.

All data analyzed by Amazon Personalize is kept private and secure, and only used for your customized recommendations. You can start serving your personalized predictions via a simple API call from inside the virtual private cloud that the service maintains. You pay only for what you use, and there are no minimum fees and no upfront commitments.

Amazon Personalize is like having your own machine learning personalization team at your disposal, 24 hours a day.


Create high-quality recommendations

Delivering personalization to individuals at scale requires a combination of the right data and the right technology. Few organizations have the knowledge, skills, and experience to overcome the challenges required to build an effective and scalable personalization engine. The algorithms used by Amazon Personalize are designed to overcome common problems when creating custom recommendations – such as new customers with no data, popularity biases, and evolving intent of customers – to deliver high-quality recommendations that respond to specific needs, preferences, and behavior of your users.

Own the moment for real-time customer engagement

Timing is everything. If a customer has spent time browsing products on your site, you need to understand what they're looking for and respond with the right offer before they move on to another site. Amazon Personalize can blend real-time user activity data with existing user profile and product information to identify the right offer for your customer at that moment. The service also enables companies to easily add contextual real-time personalization to their applications, to surface the most relevant video or article to a user.

Personalize every touchpoint along the customer journey

Amazon Personalize enables companies to provide a cohesive and unique experience for every customer across all channels and devices. Personalized recommendations from the model can be easily integrated into websites, mobile apps, or content management and email marketing systems, via a simple API call. Everything from on-site search, product sorting, recommendations and offers and can be tailored to develop personalized interactions that will drive deeper connections with customers.

Deliver personalization within days, not months

With Amazon Personalize, you can generate a custom personalization model in just a few clicks. Amazon Personalize automates and accelerates the complex machine learning required to build, train, tune, and deploy a personalization model – so you can start delivering timely and relevant experiences for your customers quickly.

How it works


Use cases

Personalized recommendations

Product and content recommendations tailored to a user’s profile and habits are more likely to result in a conversion. Rather than providing a single, uniform experience, Amazon Personalize can help applications and websites transform generic content delivery into highly relevant interactions based on individual behavior, history, and preferences. This helps companies provide visitors with the content they are looking for, better address their needs, and boost engagement. For example, a video streaming website can help users discover additional shows that they may be interested in by providing recommendations on the home screen based on past viewing habits and demographics. Once users begin to drill down into individual programs, similar content within the same genre that they may be interested in can be also be displayed. Throughout the user experience, Amazon Personalize is increasing the odds that users find a program they will watch and enjoy.

"With thousands of movies and TV shows selection, it is a challenge to surface the most relevant programs to our viewers. To enable faster and more efficient content discovery, we want to deliver the highest quality content recommendations that are tailored to individuals' interests and preferences. Amazon Personalize enables us to easily and quickly implement a recommendation engine. Despite having no prior experience in AI/ML, it only took us 3 days to understand the service, create a first data set, and generate a recommendation. With Amazon Personalize, we will be able to provide every consumer with an unique viewing experience."

Daniel Muller, Head of Cloud Infrastructure - Spuul

Personalized search

Many online users are frustrated by irrelevant search results and the inability to find the specific item they’re looking for. For an optimal user experience, search results should consider each person’s preferences and intent to surface products that are relevant to the individual, not just to the search term. Amazon Personalize can improve site search results for individual users by combining the query string with behavioral data from past application interactions. For example, an eCommerce retailer can personalize search results — leveraging a shopper’s recent views, purchase history, and preferences to boost product discovery and customer satisfaction. Additionally, Amazon Personalize can incorporate your back-end information to make the experience not just personal, but helpful. For instance, when a product’s more popular sizes go out of stock, Amazon Personalize will automatically lower the search ranking of a product until stock replenishes - all without the need of manual work.

"Wedding planning isn’t easy. We want to help couples to select gifts or services that that best match their situation, styles, interests and preferences. Until now, this has been done sparsely either via rule-based ranking, popularity, or more recently via a similarity model which are calculated offline. Amazon Personalize provides us with the state-of-the-art algorithms and an end-to-end personalization solution that that would enable us to respond to customer actions in real-time. Being a small team, using Amazon Personalize would allow us to get to a place that would have otherwise taken a much larger team, and likely 12-18 months development time if not more."

Stephane Bailliez, VP of Engineering -

Personalized notifications

Marketing promotions based on user behavior are more likely to convert because they align to with your customers’ interests and situational context. Amazon Personalize helps ensure that each user receives the most relevant marketing communication, so you can better reach your customers with the right message at the right time. For example, a retailer can use Amazon Personalize to select the most appropriate mobile app notification to send based on a customer’s location, buying habits, and discount amounts that have previously driven them to act rather than simply sending a generic promotion and hoping for the best.

"The customer is at the heart of everything we do at Domino's and we are working relentlessly to improve and enhance their experience. Using Amazon Personalize, we are able to achieve personalization at scale across our entire customer base, which was previously impossible. Amazon Personalize enables us to apply context about individual customers and their circumstances, and deliver customized communications such as special deals and offers through our digital channels.."

Mallika Krishnamurthy, Global Head, Strategy & Insights - Domino's Pizza Enterprises

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