Amazon Personalize

Contributor(s): Sarah Lewis

Amazon Personalize is a machine learning (ML) service that can be used to develop application functionality that creates tailored recommendations for customers. The service allows software developers without technical ML experience to introduce personalization capabilities into their existing platforms. Personalize can be implemented across multiple devices and channels and deployed within a few clicks.

The goal of Amazon Personalize is to deliver customized recommendations and combat issues that may arise surrounding customer engagement. For example, the algorithms used in the service evolve over time, remove bias and can handle new users without data. Additionally, the service adjusts recommendations in real time to ensure customers are not missing opportunities or moving to competitors.

Amazon Personalize is based on the same technology Amazon Web Services (AWS) has been using for over twenty years. The service is based on a pay–as-you-go model and is accessed with an AWS console.

How Amazon Personalize works

The following steps must be carried out in order to implement personalized customer recommendations:

  1. Data must be formatted and input into the service. Inventory and user demographic information can be taken from an Amazon S3 bucket or an Amazon Personalize API can be set up to stream event or activity data, such as clicks, page views and purchases.
  2. Recommendation data should also be provided to the service. This includes any contextual information that might be relevant and an inventory of items that can be recommended, from articles to products to media.
  3. Amazon Personalize processes and examines the data in order to identify what is important. An algorithm is then chosen to train and optimize a personalization solution that is tailored to an organization’s data.
  4. The solution, or trained model, is deployed and implemented into applications through an API call. Potential integrations include websites, mobile apps, social media platforms, content management systems (CMS) and email marketing software.

Applications for Amazon Personalize

Relevant and real-time personalization can be implemented in a variety of use cases, including:

  • Personalized recommendations- The main function of Amazon Personalize is to act as a recommendation engine based on customer profile information, buying history and preferences. Personalization can range from content to next steps to product recommendations.
  • Custom search- In order to improve customer experience (CX), Amazon Personalize can be used to design search functions that rank results based on each user’s behavioral data and preferences.
  • Relevant notifications- Customers that only receive the most relevant marketing materials are more likely to convert. Amazon Personalize can ensure only appropriate, adapted notifications reach users.
This was last updated in September 2019

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