When creating a lookalike audience, an advertiser must choose between a more similar model (smaller audience) or less similar model (larger audience). Which scenario best justifies using a less similar lookalike model?

Question: When creating a lookalike audience, an advertiser must choose between a more similar model (smaller audience) or less similar model (larger audience). Which scenario best justifies using a less similar lookalike model?

• Retargeting customers who abandoned their shopping carts
• Running an an upper-funnel awareness campaign to discover new potential customers
• Running a conversion-focused campaign reaching high-intent shoppers

Explanation

Lookalike audiences in Amazon Marketing Cloud can balance similarity and scale. A less similar model broadens reach by expanding beyond users most closely matched to the seed audience. This supports awareness activity where the goal is to discover new potential customers. Greater scale is more useful in upper-funnel planning than in tightly focused conversion or retargeting efforts.

Why the other options are incorrect

Retargeting is incorrect because cart abandoners are known high-intent users, not a broad discovery audience.

Conversion-focused campaign is incorrect because high-intent acquisition usually benefits from stronger similarity rather than maximum scale.

Source for verification

https://advertising.amazon.com/API/docs/en-us/guides/amazon-marketing-cloud/audiences/rule-based-lookalike

The answer(s) to the question is highlighted in the BOLD text above. You can also find more questions and answers related to the exams on the "Amazon Marketing Cloud Certification" page.