Launch announcement

Advertisers can now use Amazon Marketing Cloud (AMC) to create lookalike audiences composed of people sharing similar characteristics with their high-value customers. Specifically, advertisers can define a “seed audience”, usually a group of high-value customers, using cross-source signals in AMC. The AWS machine learning model embedded in this feature processes the “seed,” locates more prospects that share similar traits as the “seed,” and generates lookalike audience ready for use in Amazon DSP campaigns. This feature allows advertisers to discover more high-potential prospects in an easy and streamlined manner, helping advertisers extend their reach while maintaining relevancy.

Audiences tab in AMC UI

Many advertisers have been using the rule-based audiences feature in AMC to create custom audiences based on their past ads engagement, shopping activities, and other attributes. With the introduction of AMC lookalike audiences, advertisers can continue to take advantage of the rich signals and flexible query capabilities that rule-based audiences provides, while creating more sizable audiences composed of individuals from the broader Amazon Ads audience pool. These lookalike audiences are suitable for prospecting campaigns, and complementing the rule-based audiences options commonly used for remarketing and exclusion purposes.

While Amazon DSP today supports advertisers to build lookalike audiences basing off their own first-party signals, AMC lookalikes allows advertisers to use cross-source signals to build “seeds,” helping advertisers to utilize engagement and conversion patterns on Amazon media and stores to define high-value customers and uncover high-potential prospects.

• Amazon Marketing Cloud users

• AMC UI Audiences tab
• Advanced tool centers AMC Audiences section