What are custom audience and lookalike audience

Facebook and Google have these powerful features called custom audience and lookalike audience. The features allow you to use a list of customers that you currently have. Consider that you have a list of your 100 best customers, complete with their email address and phone number. You can upload the list to Facebook and Google. Based on the email address and phone number, Facebook and Google will match those individuals to the email address and phone number that they use to register for their Facebook or Gmail account, and find out their characteristics, for example, their demographics (age, gender, location) and psychographics (interests, values).

Based on the characteristics of the list of customers you have uploaded called the “custom audience”, Facebook will find in their database other people who match the profile of your custom audience.

Facebook grades similarity of audience from a scale of 0 to 20, with 0 being very similar, and 20 being not so similar. However, if you try to create a lookalike audience on Facebook on your own, the similarity scale is only from 0 to 10. But as Peasy uses API, we can create a lookalike audience up to the scale of 20. The advantage of this is we can create a bigger size of audience that matches your seed or custom audience. For example, on your own, you can perhaps find a population size of 1,000,000, but Peasy can find 2,000,000 people who match the profile of your custom audience.

For your information, previously, Facebook did a lot of targeting based on third-party cookie data. Whenever you key in “interests” targeting profile e.g. people who like online shopping, the data is derived from Facebook which observes what people watch and consume on Facebook and outside of Facebook. However, since late 2020, Google Chrome and Apple iOS have blocked third-party cookie data. This means that Google and Facebook’s ability to learn about customers’ profiles from their behaviours outside of Facebook, YouTube or Google, is now limited. Hence, targeting based on interests is not as powerful as before. To compensate for the lack of interests-based targeting, it is useful to upload a custom audience, then create a lookalike audience from the seed audience.

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