WEKA-BASED-DECISION-TREE-MODEL-FOR-USER-SUBSCRIPTION-PLAN-PREDICTION

In today’s competitive streaming landscape, understanding user preferences in subscription plan selection is essential for implementing data-driven strategies. This study explores the influence of key demographic and behavioral attributes—age, gender, country, device type, and subscription start month—on the selection of Basic, Standard, or Premium subscription plans. Using a dataset of 2,500 anonymized user records, we trained and validated a supervised classification model using the J48 decision-tree algorithm in WEKA. The model achieved a 72% overall accuracy, with country, age, and device type emerging as the most influential predictors. Results revealed interpretable decision rules, offering insights for subscription design and targeted user strategies. This highlights the value of interpretable machine learning models in supporting business intelligence for streaming platforms.