Files

Abstract

In the era of digital music streaming, understanding user behavior and preferences is cru- cial for platforms like Spotify to optimize their services and drive growth. This study aims to investigate the factors influencing premium membership conversion and develop user personas to inform targeted strategies for enhancing user satisfaction and engagement on Spotify. Through a survey of 600 Spotify users, three distinct user segments are identified: free members (59%), free members willing to upgrade to premium (24%), and premium members (17%). Logistic regression analysis reveals key factors influencing premium con- version, including current Spotify plan, premium plan price, and age. To gain a deeper understanding of each user segment, three personas are developed: Nia (free member), Aria (free member with willingness to upgrade), and Sienna (premium member). These personas encapsulate the characteristics, preferences, and pain points of each user segment, providing insights into their needs and expectations from the platform. By leveraging these insights, Spotify can improve user satisfaction, increase premium conversion rates, and maintain a competitive edge in the music streaming industry. This research contributes to the growing body of knowledge on user experience and premium conversion in music streaming services by synthesizing insights from various data sources and methodologies. It bridges the gap between academic research and industry application, providing actionable recommendations for Spotify and other streaming platforms to drive growth and user engagement.

Details

Actions

from
to
Export
Download Full History