Leveraging Sentiment Analysis to Optimize Customer Experience in Digital Wallets: A Case of Opay Wallet
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Abstract
With the growing adoption of digital financial services, customer experience has become a key differentiator for fintech companies. Sentiment analysis offers a data-driven approach to understanding user opinions, enabling companies to improve service quality and address customer concerns proactively. This study leverages sentiment analysis to assess user feedback on the Opay Wallet, a leading mobile payment platform. Using a dataset of user reviews collected from the Google Play Store between September 2018 and December 2024, TextBlob was employed to classify sentiments as positive, neutral, or negative. The results indicate that 82.2% of reviews were positive, 13.5% were neutral, and 5.5% were negative, suggesting an overall favorable perception of Opay Wallet. Furthermore, Latent Dirichlet Allocation (LDA) topic modeling was applied to identify key themes in user feedback. The analysis revealed that users frequently praised transaction speed, ease of use, and reliability, while negative reviews highlighted concerns about customer support and occasional transaction failures. These insights underscore the importance of optimizing fintech services based on real-time user sentiment. The study recommends continuous sentiment monitoring and AI-driven customer support enhancements to maintain user satisfaction and competitive advantage in the digital payments industry.
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