This study presents an e-commerce platform with customer analysis using hybrid collaborative filtering, developed specifically for the EveryDay streetwear brand to enhance their online presence and improve their business operations. With the rise of online shopping and social commerce in the Philippines, the platform aims to enhance user experience by providing tailored product suggestions using hybrid collaborative filtering. It integrates features like order, payment, inventory management, and product customization, allowing users to personalize their shopping experience, while customer behavior analysis and monthly reporting help improve decision-making and operational efficiency. To guide the development of the platform, the team used the SCRUM methodology. The system's architecture emphasizes data security, user privacy, and reliability through the ISO 25010 Software Quality Model. Surveys were conducted with a total of 75 respondents to measure the system's performance based on the model's parameters. The system scored a weighted mean of 4.81 from customers, 5.00 from both staff and admin, and 4.88 from IT experts, resulting in an overall rating of “Excellent.”. This study highlights the potential of hybrid recommender systems in enhancing e-commerce platforms and driving customer engagement and sales.