AWS Personalize

Step-by-step guide to set up AWS Personalize as a destination in RudderStack.

Amazon Personalize, also called as AWS Personalize, is a machine learning service by Amazon. It enables you to create high-quality content recommendations, personalized product and marketing promotions, and much more. With Personalize, you can boost your customer engagement and overall business revenue in no time at all.

RudderStack lets you configure AWS Personalize as a destination to which you can seamlessly send your event data for personalized recommendation and effective product marketing.

Find the open-source transformer code for this destination in our GitHub repo.

To use PutUsers and PutItems for Personalize, use the latest images for rudder-server and rudder-transformer images.

Getting started

To enable sending data to AWS Personalize, you will first need to add it as a destination in the RudderStack dashboard. Once the destination is enabled, events from RudderStack will start flowing to Personalize.

Before configuring your source and destination on the RudderStack app, check whether the source platform is supported by AWS Personalize by referring to the following table:

Connection Mode	Web	Mobile	Server
Device mode	-	-	-
Cloud mode	Supported	Supported	Supported

To know more about the difference between cloud mode and device mode in RudderStack, read the RudderStack connection modes guide.

Once you have confirmed that the source platform supports sending events to AWS Personalize, perform the steps below:

• Generate a Tracking ID by following the instructions here.

Keep this Tracking ID handy. It is required to configure AWS Personalize as a destination.

• Next, go to the RudderStack dashboard, and configure the source.

• From the list of destinations, select AWS Personalize. Assign a name to your destination and then click on Next. You should then see the following screen:

Destination Settings for AWS Personalize

• Next, in the Connection Settings page, fill all the fields with the relevant information and click on Next.

Connection Settings

This section details all the fields you need to configure to set up Personalize as a destination.

• Access Key ID: Enter the access key ID of your AWS account here.

The following actions need to be attached to the Access Key while setting up the AWS policy for it:

"Action": [
           "personalize:PutEvents",
           "personalize:PutUsers",
           "personalize:PutItems"
          ]

You can use these actions based on the type of Personalize events you want to send. For example, to send only putEvents type of events, you can attach only "personalize:PutEvents".

• Secret Access Key: Enter the secret access key of your AWS account.

• Region: Enter the region associated with your AWS account in this field.

• Information on Dataset Group:

  • TrackingId: Enter the Tracking ID that you generated in the first step.

  • Dataset ARN: Enter the dataset ARN of the dataset from the chosen dataset group.

For PutItems and PutEvents operations, it is mandatory to specify the Dataset ARN and Tracking ID in the RudderStack dashboard.

• Operational Choice:

  • Personalize Events: Choose the type of Personalize event you want to avail.

  • Map all the fields: In this section, enter the Schema Field you have used to create the schema in AWS Personalize (e.g. USER_ID, TIMESTAMP, ITEM_ID, etc.). Also, enter the corresponding Mapped Field from which the value will be taken from your event payload.

For more information on creating a schema in Personalize, refer to the Personalize documentation.

When using the PutItems operation, you need to provide the path to the corresponding Mapped Field corresponding to the ITEM_ID in your Personalize database schema.

Track

The track call lets you use PutEvents and PutItems operations of AWS Personalize.

For PutEvents, RudderStack sends the value of the event field in the payload as EVENT_TYPE. Also, the value of the timestamp or originalTimestamp field in the payload will be sent as sentAt.

For PutItems and PutEvents operations, it is mandatory to specify the Dataset ARN and Tracking ID in the RudderStack dashboard.

To use the PutUsers and PutItems operations, use the latest images for rudder-server and rudder-transformer images.

The following snippet shows a sample track event with the mapped field specified in the RudderStack dashboard:

rudderanalytics.track("PRODUCT ADDED", {
  typeOfSdk: "javascript",
  numberOfRatings: "12",
  X: "item 1",
});

When using the PutItems, the Schema Field ITEM_ID must be mapped to a specific key inside the payload and you need to mention the path to the chosen key as the corresponding Mapped Field.

In the above example, if you map ITEM_ID to the payload field X, the corresponding Mapped Field will be properties.X.

For any other Schema Field in your ITEMS dataset, it is not advised to specify the path - only the field name will be sufficient.

While using PutEvents, the Mapped Field for ITEM_ID should not contain the path to the field. Only the name of the field will be sufficient. The same rule is applicable for any other Schema Field mapping.

The following image shows an example of the dashboard configuration for PutItems:

Dashboard Configuration Based On The Above Example

The following image shows an example of the dashboard configuration for PutEvents:

Dashboard Configuration Based On The Above Example

Identify

The identify call lets you use PutUsers operation of AWS Personalize.

To use PutUsers and PutItems for Personalize, use the latest images for rudder-server and rudder-transformer images.

For the PutUsers operation, the value of the userId or anonymousId field in the payload will be sent as userId.

For PutUsers, the Dataset ARN field in the RudderStack dashboard is required.

The following snippet highlights a sample identify event with the Mapped Field specified in the RudderStack dashboard:

rudderanalytics.identify("userId", {
  name: "John",
  email: "[e-mail]"
  });

Contact Us

If you come across any issues while configuring AWS Personalize as a destination with RudderStack, please feel free to contact us. You can also start a conversation in our Slack community; we will be happy to talk to you!