Lookalike models are based on the assumption that user similarity plays an
important role towards product selling and enhancing the existing advertising
campaigns from a very large user base. Challenges associated to these models
reside on the heterogeneity of the user base and its sparsity. In this work, we
propose a novel framework that unifies the customers different behaviors or
features such as demographics, buying behaviors on different platforms,
customer loyalty behaviors and build a lookalike model to improve customer
targeting for Rakuten Group, Inc. Extensive experiments on real e-commerce and
travel datasets demonstrate the effectiveness of our proposed lookalike model
for user targeting task