Posted On: Nov 18, 2022
Today, Amazon Personalize launches the ability for customers to measure the business impact of their Personalize recommendations. Amazon Personalize is a fully managed machine learning service that allows customers to deliver personalized experiences to their users, no ML experience required. Customers can now evaluate the sum or count of any user interaction with a Personalize recommendation such as click, view, purchase, video start, add to cart, or download. Prior to this launch, customers could not evaluate the results of Personalize recommendations unless they built their own pipelines or workflows. Personalize has removed the need for this operational overhead by allowing customers to define the metrics they want to track, and automatically sending event data to the customer’s Amazon CloudWatch account for visualization and monitoring. The data can also be sent to an S3 bucket for download and integration into another business intelligence tool.
Defining and measuring the business metrics that you want to track is easy. From either the Amazon Personalize console or API, you can define a “metric attribution,” which is a list of interactions (i.e. event types) that you want to report on. For example, an online shopping application may want to track two metrics: the click through rate (CTR) for recommendations and total number of purchases. A streaming video platform may want to track the number of video starts and completions. For each event type, you simply define the metric and function to calculate (sum or count), and Personalize performs the calculation and sends reports to your CloudWatch or S3 account.
Amazon Personalize enables you to personalize your website, app, ads, emails, and more, using the same machine learning technology used by Amazon, without requiring any prior machine learning experience. To get started with Amazon Personalize, visit our documentation.