Today, we are announcing the general availability of Amazon Marketing Cloud (AMC) on AWS Clean Rooms to help advertisers use their first-party signals to collaborate with Amazon Ads unique signals. With this collaboration, advertisers can generate differentiated insights, discover new audiences, and enable advertising campaign planning, activation, and measurement use cases, all without having to move their underlying signals outside of their AWS account. With AMC on AWS Clean Rooms, customers can easily prepare their data, match and create audiences, use custom insights to activate more relevant advertising campaigns with Amazon Ads, and measure return on ad spend. All of this can be accomplished from the most secure cloud computing environment available today.

Advertisers continually strive to reach new audiences and deliver relevant, marketing campaigns to better engage their customers. Yet, the advertising and marketing landscape is undergoing a fundamental shift with signal loss and fragmentation. As such, advertisers and their partners need to collaborate together using signals that are stored across many applications to personalize their advertising campaigns. However, to work with one another to gather insights, companies typically need to share a copy of their signals with their partners, which is often not aligned with their data governance, security and privacy, IT, and legal teams’ policies. As a result, many businesses miss opportunities to fully maximize the value of their first-party signals and improve planning, activation, and measurement outcomes for their campaigns.

AMC on AWS Clean Rooms makes it easier and scalable for advertisers to use their first-party signals with Amazon Ads, including collaborating across event-level signals and modeling unique audiences to help improve media planning, activation, and outcomes without having to move underlying signals outside their cloud environment.

AMC on AWS Clean Rooms prerequisites (environment setup)
To get started with AMC on AWS Clean Rooms, the advertiser needs an AWS account and a dataset that contains user population and event-level data stored in open data formats (CSV, Parquet, or Iceberg) in an Amazon Simple Storage Service (Amazon S3) bucket. The next step is to send an email to the Amazon Ads team to request the creation of an AMC instance. Once an instance has been created, the Amazon Ads team will create an AWS Clean Rooms collaboration and invite the advertiser to join the collaboration.

How it works
1. Join an AWS Clean Rooms collaboration and create an ID namespace.
2. Configure and associate tables to an AMC collaboration.
3. Run an ID mapping workflow to create and populate the ID mapping table.
4. Run a query in AMC.

Walkthrough

1. Join an AWS Clean Rooms collaboration and create an ID namespace.
The advertiser will accept the collaboration invite by creating a membership in their AWS account. Once in the collaboration, the advertiser will access the AWS Clean Rooms console and then select the AWS Entity Resolution ID namespace generated when the collaboration was created to start the process of using their data for matching and collaboration in AWS Clean Rooms. Next, specify the AWS Glue table and the associated schema mapping and choose the S3 bucket in the same AWS Region as the collaboration for temporarily storing your data while it processes. Lastly, the advertiser will provide permissions to read your data input from AWS Glue and write to Amazon S3 on their behalf.

In the AirportLink collaboration shown in the following screenshot, the advertiser (member AirportLink2) accepts a collaboration invite sent by member AirportLink1.

2. Configure and associate tables to an AMC collaboration.
After joining the collaboration, the advertiser will create configured tables on their purchase data, add custom analysis rule, and associate the configured table to the collaboration.

Within the collaboration, the advertiser will set up a collaboration analysis rule to control which party can receive the result of a query run on the associated table.

3. Run an ID mapping workflow to create and populate the ID mapping table.
Now that the ID namespace is associated with the collaboration, the Amazon Ads team will create an ID mapping table in the AWS Clean Rooms console. This step requires both the advertiser (source) and the Amazon Ads team (target) to associate their ID namespace resources to the collaboration. Amazon Ads will provide the methods of mapping and configuration, add the details for querying to name the ID mapping table, and provide permission for AWS Clean Rooms to execute and track the ID mapping workflow job on their behalf. Finally, the Amazon Ads team will select Create and Populate to start the mapping workflow and generate an ID mapping table that captures a common user cohort, who were matched on the rules provided in Step 2.

4. Run a query in AMC.
Advertisers can either use templates or write a SQL query to run for analysis and get query results for further insights. They can run the SQL query in the following ways:

• Run a SQL query with AMC data and the advertiser’s data that return the results to the advertiser’s S3 bucket using aggregate analysis. An example query is “How many of the customers who are registered for my email list saw the ads I’m running on Amazon?”
• Run a SQL query to create an audience on the advertiser’s data or overlap with AMC signals that returns results to the S3 bucket of Amazon Ads. An example query is to generate an audience to target in an ad campaign.
• Run an AWS Clean Rooms ML lookalike modeling job where Amazon Ads contributes the configured model and the advertiser contributes a seed audience. The resulting segment (list of user ad IDs) is sent to Amazon Ads.

After running the query, the advertiser can create an audience using a rule-based audience or a similar audience by navigating to the Audience tab in AMC. The output of the audience query will be sent directly to Amazon Demand Side Platform (DSP). The following table shows the options available to you when creating the audience:

When creating a new query, the advertiser will configure various options such as name, description, and date adjustments. Additionally, the advertiser can choose from the two following audience types:

– Rule-based audience – Create audience-based on the audience query.
– Similar audience – Create machine learning (ML) based audiences based on the seed audience outputs from the audience query.

Now available
AMC on AWS Clean Rooms is available in in the US East (N. Virginia) Region. Be sure to check the full Region list for future updates. Learn more about AMC on AWS Clean Rooms in the AWS documentation.

Give it a try by emailing the Amazon Ads team to get started and send feedback to the AWS re:Post for AWS Clean Rooms or through your usual AWS Support contacts.

— Veliswa