Machine Learning-Driven Gamification: Boosting User Engagement in Business
DOI:
https://doi.org/10.18034/gdeb.v12i1.774Keywords:
Machine Learning, Gamification, User Engagement, Behavior Prediction, Data Privacy, Reward Optimization, Algorithmic Bias, Adaptive Systems, Business StrategyAbstract
This research shows personalized, adaptive, and data-driven machine learning-driven gamification may improve corporate user engagement. The goal is to study how machine learning (ML) may improve classic gamified systems by providing personalized challenges, improved reward structures, and predictive insights to maintain interest. This study synthesizes existing machine learning and gamification literature using secondary data to identify critical trends, difficulties, and future directions. ML allows deep customization and behavior prediction, which is crucial for user pleasure and engagement. Data privacy and algorithmic bias pose ethical and practical issues, highlighting the need for solid legislative frameworks. Transparent data methods, user control, and algorithmic fairness principles promote equal user experiences. As real-time adaptation, emotion detection, and immersive technologies emerge, machine learning-driven gamification will help contemporary businesses retain user engagement, loyalty, and satisfaction. This research allows companies to balance engagement innovation with data management to build ethical and successful gamification methods.
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Copyright (c) 2023 Kazi Ahmed Farhan; A B M Asadullah; Hari Priya Kommineni; Pavan Kumar Gade; Satya Surya MKLG Gudimetla Naga Venkata
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