Lookalike Modeling explained

Marketers with growing sales targets are always looking to reach larger audiences.
Surely, advertising plays an important role in attracting new customers, but how to grow these audiences beyond the current database while keeping them relevant to the product and not waste ad spend?
This is where lookalike modeling comes in.
Lookalike modeling is a strategy that can be used to find and reach new customers that look and behave like marketer’s current best customers. Building lookalike audiences allow marketers to scale their campaigns to find new relevant consumers.
Lookalike modeling works by using data and algorithms, usually carried out by DMPs, Social platforms or DSPs.
As data comes in many forms, the most successful lookalike audiences are based on unique 1st-party data.
Today, traditional approaches, which rely heavily on the use of 3rd-party cookies, are facing growing challenges because of the new privacy-first era (data regulations, browsers and identity data, etc).
All media buyers should be aware on how their AdTech partners are responding or preparing to face these challenges, as “audience modeling” is an important part of every successful media buying strategy.
Other sources: see in the LinkedIn comments.
Previously posted by Luca Brighenti via LinkedIn. 

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