App User Segmentation

In today’s highly competitive digital landscape, retaining users is as crucial as acquiring them, prompting the need for effective strategies to identify and engage users at risk of disengagement. This paper presents a machine learning–based approach utilizing KMeans clustering to segment mobile app users into three categories—Retained, Churn, and Needs Attention—based on key behavioral metrics such as average screen time, spending patterns, ratings, review activity, password reset frequency, and last activity timestamp. By analyzing these multidimensional indicators, the system provides actionable insights that enable businesses to proactively tailor retention strategies and enhance user experience. The proposed solution is implemented as a Flask-based web application featuring role-based access control, where administrators can manage users and maintain a Frequently Asked Questions (FAQ) section, while users can register, log in, and submit behavioral data to receive segmentation results.