Leveraging User Transition States: A Data-Driven Approach to Enhance User Retention in Digital Platforms

Abstract

In the digital ecosystem, user retention is a critical factor for the sustainable growth and success of platforms. This paper presents
a novel approach to improving user retention by analyzing and leveraging user transition states. By employing advanced data
science techniques, including Markov chain models, machine learning algorithms, and survival analysis, we propose a framework for identifying, predicting, and influencing key transition states in the user journey. Our findings suggest that certain transition states serve as critical junctures in user engagement, offering opportunities for targeted interventions. This research provides valuable insights for digital platforms to develop more effective retention strategies, ultimately enhancing user lifetime value and platform sustainability.