Research on Digital Platform User Retention Strategies and Marketing Model Optimization from a Data-Driven Perspective

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Published: 2026-01-20
Keywords:
digital platforms, user retention, data-driven marketing, marketing model optimization, personalization, behavioral targeting, algorithmic bias

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Robert L. Chen
Department of Marketing, Monte Ahuja College of Business, Cleveland State University, Cleveland, OH, USA
Simon J. Richards
School of Business and Management, University of Central Lancashire, Preston, UK

Abstract

This review paper synthesizes existing research on digital platform user retention strategies and marketing model optimization from a data-driven perspective. It examines various approaches employed by platforms to enhance user engagement and loyalty, leveraging data analytics to personalize experiences and improve marketing effectiveness. The review encompasses an historical overview of user retention techniques, delving into the evolution of marketing models in the digital age. Core themes explored include data-driven personalization, behavioral targeting, and dynamic pricing strategies. A comparative analysis of different retention models is presented, highlighting their strengths and weaknesses, and addressing the challenges associated with data privacy and algorithmic bias. Furthermore, the paper explores future research directions, anticipating the impact of emerging technologies such as AI and blockchain on user retention and marketing practices. This review aims to provide a comprehensive understanding of the data-driven landscape of user retention, offering insights for both academics and practitioners.

Article Details

Issue

Vol. 1 No. 1 (2025): 2025 International Conference on Intelligent Computing and Automated Systems (ICAS 2025)

Section

Articles

How to Cite

Research on Digital Platform User Retention Strategies and Marketing Model Optimization from a Data-Driven Perspective. (2026). Journal of Science, Innovation & Social Impact, 1(1), 463-470. https://sagespress.com/index.php/JSISI/article/view/67

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