Exploring 360-Degree View of Customers for Lookalike Modeling

• URL: http://arxiv.org/abs/2304.09105v1
• Date: Mon, 17 Apr 2023 14:01:12 GMT
• Title: Exploring 360-Degree View of Customers for Lookalike Modeling
• Authors: Md Mostafizur Rahman, Daisuke Kikuta, Satyen Abrol, Yu Hirate, Toyotaro Suzumura, Pablo Loyola, Takuma Ebisu, Manoj Kondapaka
• Abstract summary: 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.
• Score: 3.264007084815591
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: 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.

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