The increasing reliance on mobile applications across various domains highlights the critical role of user reviews in shaping and guiding app development and improving user satisfaction. However, current app review systems, such as those used by the Apple App Store and Google Play, suffer from significant limitations, including the lack of structure and the proliferation of fake reviews. In this paper, we propose a structured review submission system that integrates predefined tags such as “Usability”, “User Experience” and “Features” and verification mechanisms such as “Verified Download” and “Verified Purchase” tags to enhance the authenticity and organisation of user feedback. We evaluate the system using a static prototype tested by 37 participants, gathering insights on usability and user satisfaction. Our findings demonstrate and highlight that the proposed structured system improves the clarity of reviews and enhances developer insights, while the verification tags increase trust in the authenticity of the feedback. Moreover, we integrate advanced Natural Language Processing (NLP) models like GPT-4 and RoBERTa further to further automate tag generation and sentiment analysis and to provide actionable insights for developers. Our study opens directions for improving mobile app review systems, with implications for user engagement, app quality, and developer responsiveness.