Q. How are the models created?

A.The goal of lookalike (LAL) segments is to expand a segment (the "seed segment") by finding similar users. 

In order to create a lookalike segment, Permutive uses machine learning to generate a lookalike model. The model learns the common features (in this case, what segments a user is in) and their relative importance.

For example, if we want to expand a segment of "Tennis Lovers", our lookalike model may learn that many users in the segment are also in a "Sports Lover" segment. This means that if we see a user that is in "Sports Lover", within some given probability, they are "almost" a "Tennis Lover" as well. Conversely, the model may learn that users who are "Tennis Lovers" are not "Basketball Lovers", and a negative importance can be given to the "Basketball Lovers" segment.

 

Was this article helpful?
0 out of 0 found this helpful
Have more questions? Submit a request