A lookalike audience is a marketing strategy[2] that utilizes existing customer[6] data to identify potential new customers who share similar characteristics. This approach is effective in reaching highly-qualified customers who may otherwise be hard to reach, reducing advertising[5] costs and time spent on acquiring a new audience. The success of this strategy heavily relies on the homogeneity of the initial customer data, or “seed”, which can be gathered from various sources such as customer relationship management[1] (CRM), user actions, site interactions, or specific behaviors and demographics. These seeds help to cater to different marketing goals. Companies, such as Facebook[7], create lookalike audiences through a three-step process: audience seed selection, location selection, and audience size customization. However, the use of lookalike audiences has sparked debates regarding privacidade[8], data usage, and issues of discriminatory targeting in digital marketing[3]. Despite these concerns, lookalike audiences are a significant trend in pay-per-click[4] marketing and have shown positive results in advertising.
A lookalike audience is a group of social network members who are determined as sharing characteristics with another group of members. In digital advertising, it refers to a targeting tool for digital marketing, first initiated by Facebook, which helps to reach potential customers online who are likely to share similar interests and behaviors with existing customers. Since Facebook debuted this feature in 2013, additional advertising platforms have followed suit, including Anúncios do Google, Outbrain, Taboola, LinkedIn Ads and others.