This project started with a question: how might we make movie recommendations emotionally accurate? Current recommendation systems often focus on genres, ratings or casting, missing the emotional context that frequently drives people’s choices. The challenge was to create an app that could recommend movies based on the user's current mood.
With a target audience of Gen Z users, the main goal was to make navigation easy and fun. For the different moods, jolly illustrations by Aliaksandra were used to give a face to each emotion and make the experience feel lighthearted. A swipe-based flow similar to TikTok was adopted to bring familiarity while browsing through movie recommendations. The experience was designed to be fun, functional, and fast. As users explore, they see recommendations ordered by match percentage, and they can improve it by tagging movies with moods on each film's page.
The final prototype demonstrates a more playful and personalized way to connect users with films that resonate with their emotions. In addition, a landing page was also created using Webflow to present the concept in a clean format across desktop and mobile.
This project helped me deepen my skills in product design and no-code development, while exploring how digital products can foster better user experiences.
This project helped me deepen my skills in product design and no-code development, while exploring how digital products can foster better user experiences.