Personalizing E-Commerce Experiences: A Machine Learning Framework for Dynamic Gamification and Customer Engagement
DOI:
https://doi.org/10.5614/itbj.ict.res.appl.2026.19.3.5Keywords:
adaptive gamification, customer engagement, e-commerce, machine learning, real-time analyticsAbstract
E-commerce platforms are increasingly challenged to sustain customer engagement amidst intensifying competition. Traditional gamification approaches, characterized by static, uniform mechanics, often fail to adapt to individual user preferences, leading to diminishing returns and decreased engagement over time. These conventional methods typically employ fixed reward structures that do not account for individual user behavior, resulting in a lack of sustained engagement. This paper introduces a comprehensive machine learning (ML) framework for dynamic gamification, designed to personalize game elements in real-time based on individual user behavior patterns. The framework integrates clustering algorithms, reinforcement learning (RL), and collaborative filtering techniques to analyze user interactions and generate adaptive gamified experiences. Simulated testing, conducted using a publicly available e-commerce customer behavior dataset from Kaggle, provided insights into diverse user preferences and behaviors. Simulated results demonstrated significant improvements, including a 32% increase in daily active users, a 24% higher conversion rate, and a 30.8% improvement in 30-day customer retention. The framework addresses critical technical challenges, such as scalability, real-time processing, and ethical data usage. This research contributes to the advancement of personalized digital experiences in e-commerce, offering practical guidelines for enhancing customer engagement through AI-driven gamification.
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References
Statista, Retail e-commerce sales worldwide from 2014 to 2027, Statista, https://www.statista.com/statistics/379046/worldwide-retail-e-commerce-sales/, (2024).
Google, Temasek & Bain, e-Conomy SEA 2023: Indonesia Chapter, Google, (2023).
Nwanna, M., Offiong, E., Ogidan, T., Fagbohun, O., Ifaturoti, A. & Fasogbon, O., AI-Driven Personalisation: Transforming User Experience Across Mobile Applications, Journal of Artificial Intelligence, Machine Learning and Data Science, 3(1), pp. 1920-1929, 2025.
Hassan, D.O. & Hassan, B.A., A Comprehensive Systematic Review of Machine Learning in the Retail Industry: Classifications, Limitations, Opportunities, and Challenges, Neural Computing and Applications, 37(1), pp. 2035?2070, 2024.
Chen, L., Wu, Y. & Gsoy, G., Contextual Personalization in E-Commerce: An Ai-Driven Approach to Dynamic Gamification, Electronic Commerce Research and Applications, 51, pp. 101089, 2022.
Kim, M. & Park, J., Reinforcement Learning for Adaptive Reward Systems in E-Commerce Gamification, Artificial Intelligence Review, 56(2), pp. 541-559, 2023.
Bitri, P., Buil, I. & Catal, S., Enhancing User Engagement: The Role of Gamification in Mobile Apps, Journal of Business Research, 132, pp. 170-185, 2021.
McKinsey & Company, The Future of E-Commerce: How Gamification Is Reshaping Customer Engagement, McKinsey Digital, 2023.
Xu, X. & Walton, J., Customer Segmentation Using Machine Learning: A Systematic Literature Review, Journal of Business Research, 129, pp. 641-659, 2021.
Liang, H., Xu, Y., Li, Y. & Nayak, R., Collaborative Filtering Meets Deep Learning: A Hybrid Approach for Personalized Recommendations, Information Sciences, 623, pp. 128-144, 2023.
Wang, C. & Liu, X., Real-Time Personalization of Gamification Elements in E-Commerce: A Machine Learning Approach, Information Sciences, 629, pp. 408-425, 2023.
Deloitte, Digital Consumer Trends 2023: Gamification in Retail, Deloitte Insights, 2023.
Xi, N. & Hamari, J., Does Gamification Affect Brand Engagement and Equity? A Study In Online Brand Communities, Journal of Business Research, 109, pp. 449-460, 2020.
Smith, M., Johnson, T. & Lee, S., Ethical Considerations in AI-Driven E-Commerce Gamification: A Reinforcement Learning Perspective, Journal of Business Ethics, 175(3), pp. 213-229, 2023.
Koivisto, J. & Hamari, J., The Rise of Motivational Information Systems: A Review of Gamification Research, International Journal of Information Management, 45, pp. 191-210, 2019.
Hensen, B., Koren, I. & Klamma, R., Gamification Support for Learning in Spatial Computing Environments, Journal of Universal Computer Science, 14(12), pp. 1644-1665, 2019.
Herranz, E., Colomo-Palacios, R., de Amescua Seco, A. & Schez-Gord, M.-L., Towards a Gamification Framework for Software Process Improvement Initiatives: Construction and Validation, Journal of Universal Computer Science, 22(12), pp. 1509-1532, 2016.
Andrias, R. M., Sunar, M. S. & Sondoh Jr, S. L., Adaptive Gamification: User/Player Type and Game Elements Mapping, Intelligent Technologies for Interactive Entertainment, Springer, pp. 242-256, 2022.
Lin, C. W., Chien, C. Y., Yang, C. P. & Mao, T. Y., Encouraging Sustainable Consumption through Gamification in a Branded App: A Study on Consumers? Behavioral Perspective, Sustainability, 15(1), pp. 389, 2023.
Koren, Y., Bell, R. & Volinsky, C., Matrix factorization techniques for recommender systems, IEEE Computer, 42(8), pp. 30-37, 2009.
Lee, M. & Park, J., Scalability Challenges in Real-Time Gamification for E-Commerce Platforms, Journal of Network and Computer Applications, 207, pp. 103552, 2023.
Johnson, E., Smith, J. & Brown, M., Technical Challenges in Implementing Real-Time Gamification Systems, Journal of Systems and Software, 194, pp. 111458, 2022.
Tharmalingam, L., E-Commerce Customer Behavior Dataset, Kaggle, https://www.kaggle.com/datasets/uom190346a/e-commerce-customer-behavior-dataset, 2022.
Nor, N. N., Sunar, M. S. & Kapi, A. Y., User Experience of Gamified Virtual Reality (VR) in Sport: A Review, Science and Technologies for Smart Cities, Springer, pp. 440-449, 2020.
