Amazon Marketing Cloud on AWS Clean Rooms now generally available

NewsAmazon Marketing Cloud on AWS Clean Rooms now generally available

Amazon Marketing Cloud Now Available on AWS Clean Rooms: A Game Changer for Advertisers

Today, Amazon has announced the general availability of the Amazon Marketing Cloud (AMC) on AWS Clean Rooms. This new offering aims to help advertisers leverage their first-party data in collaboration with Amazon Ads’ unique signals. By doing so, advertisers can gain differentiated insights, discover new audiences, and enable more effective advertising campaign planning, activation, and measurement—all while keeping their data securely within their AWS account.

The Challenge: Signal Loss and Fragmentation

In the rapidly evolving advertising landscape, signal loss and fragmentation have become significant challenges. Advertisers strive to reach new audiences and create relevant marketing campaigns to engage their customers better. However, the data required for these efforts is often scattered across various applications, leading to inefficiencies and missed opportunities.

Traditionally, companies need to share copies of their data with partners to gather insights, which often conflicts with data governance, security, privacy, IT, and legal policies. This has made it difficult for businesses to fully maximize the value of their first-party data, thereby impacting their campaign outcomes.

The Solution: AMC on AWS Clean Rooms

AMC on AWS Clean Rooms addresses these challenges by providing a scalable and secure environment for advertisers to use their first-party data alongside Amazon Ads’ data. This collaboration allows advertisers to work with event-level signals, model unique audiences, and improve media planning and activation without transferring data outside their cloud environment.

Getting Started with AMC on AWS Clean Rooms

To begin using AMC on AWS Clean Rooms, advertisers need an AWS account and a dataset containing user population and event-level data stored in open data formats such as CSV, Parquet, or Iceberg in an Amazon Simple Storage Service (Amazon S3) bucket. Here’s a step-by-step guide to setting up and using the service:

  1. Join an AWS Clean Rooms Collaboration and Create an ID Namespace:
    • Advertisers accept a collaboration invite by creating a membership in their AWS account.
    • Access the AWS Clean Rooms console and select the AWS Entity Resolution ID namespace generated during the collaboration setup.
    • Specify the AWS Glue table and associated schema mapping, and choose the S3 bucket in the same AWS Region for temporary data storage.
    • Provide permissions to read data input from AWS Glue and write to Amazon S3.
  2. Configure and Associate Tables to an AMC Collaboration:
    • Create configured tables on purchase data, add custom analysis rules, and associate the tables with the collaboration.
    • Set up a collaboration analysis rule to control which party can receive query results.
  3. Run an ID Mapping Workflow:
    • The Amazon Ads team creates an ID mapping table in the AWS Clean Rooms console.
    • Both the advertiser and Amazon Ads team associate their ID namespace resources with the collaboration.
    • Start the mapping workflow to generate an ID mapping table that captures a common user cohort based on predefined rules.
  4. Run a Query in AMC:
    • Advertisers can use templates or write SQL queries to run analyses and obtain query results for further insights.
    • Queries can return results to the advertiser’s S3 bucket using aggregate analysis, create an audience on the advertiser’s data or overlap with AMC signals, or run an AWS Clean Rooms ML lookalike modeling job.

      Detailed Walkthrough

  5. Joining a Collaboration and Creating an ID Namespace:
    • After accepting the collaboration invite, the advertiser accesses the AWS Clean Rooms console and selects the ID namespace.
    • Specify the AWS Glue table and the associated schema mapping, and choose the S3 bucket in the same AWS Region.
    • Provide permissions to read data from AWS Glue and write to Amazon S3.
  6. Configuring and Associating Tables:
    • Create configured tables on purchase data, add custom analysis rules, and associate the tables with the collaboration.
    • Set up a collaboration analysis rule to control the distribution of query results.
  7. Running an ID Mapping Workflow:
    • The Amazon Ads team creates an ID mapping table, and both parties associate their ID namespace resources with the collaboration.
    • Start the mapping workflow to generate an ID mapping table that captures a common user cohort.
  8. Running a Query in AMC:
    • Use templates or write SQL queries to run analyses and obtain query results.
    • Queries can return results to the advertiser’s S3 bucket, create an audience on the advertiser’s data, or run an AWS Clean Rooms ML lookalike modeling job.

      Creating Audiences in AMC

      After running a query, advertisers can create audiences using rule-based or similar audience options. The output of the audience query is sent directly to the Amazon Demand Side Platform (DSP). Advertisers can choose from pre-built audience templates or create custom audience queries.

    • Rule-based Audience: Create an audience based on the audience query.
    • Similar Audience: Use machine learning (ML) to create audiences based on seed audience outputs from the audience query.

      Availability and Getting Started

      AMC on AWS Clean Rooms is now available in the US East (N. Virginia) Region. For future updates, check the full Region list in the AWS documentation. To get started, email the Amazon Ads team and provide feedback through AWS re:Post for AWS Clean Rooms or your usual AWS Support contacts.

      Conclusion

      The general availability of AMC on AWS Clean Rooms represents a significant advancement for advertisers. By enabling the secure and scalable use of first-party data in collaboration with Amazon Ads’ unique signals, advertisers can gain deeper insights, discover new audiences, and optimize their advertising campaigns. This new offering addresses the challenges of signal loss and fragmentation, providing a robust solution for the modern advertising landscape.

      For more information, visit the Amazon Marketing Cloud and AWS Clean Rooms pages.

For more Information, Refer to this article.

Neil S
Neil S
Neil is a highly qualified Technical Writer with an M.Sc(IT) degree and an impressive range of IT and Support certifications including MCSE, CCNA, ACA(Adobe Certified Associates), and PG Dip (IT). With over 10 years of hands-on experience as an IT support engineer across Windows, Mac, iOS, and Linux Server platforms, Neil possesses the expertise to create comprehensive and user-friendly documentation that simplifies complex technical concepts for a wide audience.
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