HARMONIZING ALGORITHMS AND USER SATISFACTION: EVALUATING THE IMPACT OF SPOTIFYâS DISCOVER WEEKLY ON CUSTOMER LOYALTY - Janice, Natasha
The increasing integration of artificial intelligence (AI) in music streaming platforms has transformed user experiences, particularly through personalized features. This study investigates the impact of Spotify's "Discover Weekly" feature on user satisfaction and customer loyalty among Indonesian users. By examining the interplay between quality of service experience, perceived usefulness, and user engagement, this research aims to determine whether "Discover Weekly" effectively enhances the overall user experience and fosters loyalty to Spotify. The research employs mix methods, utilizing both qualitative and quantitative analysis. Qualitative data is analyzed using automated coding of NVivo software with a total of 18 respondents, while quantitative data is analyzed using the Partial Least Squares Structural Equation Modeling (PLS-SEM) method with a total of 397 respondents. The research found that the quality of service experience significantly influences user satisfaction through the "Discover Weekly" feature. Users who feel satisfied with the experience of the features have higher satisfaction and are more likely to remain loyal to Spotify. The research also discovered a strong positive relationship between satisfaction and word-of-mouth promotion, indicating that satisfied users are more likely to recommend Spotify’s “Discover Weekly” to others. Recommendations include enhancing the discoverability of the playlist, continuously refining algorithms, curating diverse and high-quality music content, and encouraging positive wordof-mouth promotion. Expanding research to other music streaming platforms, exploring additional personalized playlists offered by Spotify, and other demographic profiles will provide a broader understanding of their effectiveness in enhancing user experience and loyalty.