Amazon Pinpoint added template personalization using Machine Learning
Today, Amazon Pinpoint launched a new feature that helps customers to personalize their email, SMS and push messaging templates using dynamic message variables. Customers can add dynamic message variables as placeholders within their templates and then populate them with content specific to each user. Content can come from either user attributes stored in Pinpoint or a machine learning model created with Amazon Personalize. Customers wanting to deliver relevant product recommendations or targeted marketing promotions can now use machine learning to select the right content for each of their users.
Today, Amazon Pinpoint launched a new feature that helps customers to personalize their email, SMS and push messaging templates using dynamic message variables. Customers can add dynamic message variables as placeholders within their templates and then populate them with content specific to each user. Content can come from either user attributes stored in Pinpoint or a machine learning model created with Amazon Personalize. Customers wanting to deliver relevant product recommendations or targeted marketing promotions can now use machine learning to select the right content for each of their users.
Using either the Amazon Pinpoint console or API, customers can integrate their Amazon Personalize campaign with their Amazon Pinpoint account. Once the customer has connected a model, it only takes a few clicks to select the model and copy relevant variables to the customer’s templates using the Pinpoint Attribute Finder. The more messages the customer sends using a model, the better the recommendations will get.
This feature is now available in the following AWS Regions: US East (N. Virginia), US West (Oregon), Europe (Dublin), Asia-Pacific (Mumbai), and Asia-Pacific (Sydney). You can learn more in the Amazon Pinpoint User Guide.