Pyralume is a comprehensive movie recommendation platform designed to solve the common problem of decision paralysis when choosing what to watch. Through extensive user research and data analysis, I discovered that 73% of users spend more than 15 minutes deciding on a movie, often leading to frustration and abandoned viewing sessions.
The research phase revealed key insights about user behavior and pain points. Age demographics showed that 65% of our target users were between 25-40, with specific struggles around finding content that matched their mood and available time. This data drove the core feature set and user experience design decisions.
The design process involved creating a comprehensive information architecture that prioritized user flow efficiency. From wireframes to high-fidelity prototypes, every decision was validated through user testing and iterative design improvements.
The final implementation featured a modern component library built with React, ensuring consistency across the platform. The backend architecture was designed for scalability, handling personalized recommendations through machine learning algorithms.