Use a recommender model in Amazon Pinpoint with AWS Lambda

In Amazon Pinpoint, you can retrieve personalized recommendations from a recommender model and add them to messages that you send from campaigns and journeys. A recommender model is a type of machine learning (ML) model that finds patterns in data and generates predictions and recommendations based on the patterns that it finds. It predicts what a particular user will prefer from a given set of products or items, and it provides that information as a set of recommendations for the user.

By using recommender models with Amazon Pinpoint, you can send personalized recommendations to message recipients based on each recipient’s attributes and behavior. With AWS Lambda, you can also customize and enhance these recommendations. For example, you can dynamically transform a recommendation from a single text value (such as a product name or ID) to more sophisticated content (such as a product name, description, and image). And you can do it in real time, when Amazon Pinpoint sends the message.

This feature is available in the following AWS Regions: US East (N. Virginia); US West (Oregon); Asia Pacific (Mumbai); Asia Pacific (Sydney); and, Europe (Ireland).

Authorize Amazon Pinpoint to invoke a Lambda function using the AWS CLI and the Lambda add-permission command

After you assign a Lambda function policy to a function, you can add permissions that allow Amazon Pinpoint to invoke the function for a specific project, campaign, or journey. You can do this using the AWS Command Line Interface (AWS CLI) and the Lambda add-permission command. The following example shows how to do this for a specific project (projectId):

$ aws lambda add-permission \
--function-name function-name \
--statement-id sid \
--action lambda:InvokeFunction \
--principal pinpoint.us-east-1.amazonaws.com \
--source-arn arn:aws:mobiletargeting:us-east-1:accountId:recommenders/*

The preceding example is formatted for Unix, Linux, and macOS. For Microsoft Windows, replace the backslash (\) line-continuation character with a caret (^).

If the command runs successfully, you see output similar to the following:

{
  "Statement": "{\"Sid\":\"sid\",
    \"Effect\":\"Allow\",
    \"Principal\":{\"Service\":\"pinpoint.us-east-1.amazonaws.com\"},
    \"Action\":\"lambda:InvokeFunction\",
    \"Resource\":\"arn:aws:lambda:us-east-1:111122223333:function:function-name\",
    \"Condition\":
      {\"ArnLike\":
        {\"AWS:SourceArn\":
         \"arn:aws:mobiletargeting:us-east-1:111122223333:recommenders/*\"}}}"
}

The Statement value is a JSON string version of the statement that was added to the Lambda function policy.

Configure Amazon Pinpoint to invoke the Lambda function for a recommender model

To configure Amazon Pinpoint to invoke the Lambda function for a recommender model, specify the following Lambda-specific configuration settings for the model:

You can specify these settings by using the Recommender Models resource of the Amazon Pinpoint API (when you create the configuration for a model) or the Recommender Model resource of the Amazon Pinpoint API (if you update the configuration for a model). You can also define these settings by using the Amazon Pinpoint console.

For more information about using recommender models with Amazon Pinpoint, see Machine Learning Models in the Amazon Pinpoint User Guide.