Abstract: The rise of hyperlocal e-commerce presents a transformative opportunity for local businesses to compete in the digital marketplace. This research explores the development and implementation of a hyperlocal e-commerce platform that bridges the gap between local vendors and consumers by leveraging geolocation technology. The platform uses the Haversine algorithm to calculate the proximity between users and nearby businesses, enabling faster and more efficient deliveries. Additionally, it incorporates collaborative filtering to personalize user experiences by recommending relevant products based on browsing history. To ensure seamless order management and secure transactions, the system integrates Twilio for real-time messaging and PayPal as the payment gateway. Unlike traditional e-commerce models, which often overlook local needs, this platform fosters community-driven commerce, supports small businesses, and provides users with a personalized and efficient shopping experience. The paper outlines the challenges of building such a system, evaluates its performance, and suggests future improvements for scalability and enhanced functionality.

Keywords: Hyperlocal E-commerce, Local Businesses, Geolocation Technology, Haversine Algorithm, Deliveries, Collaborative Filtering, Personalization, Order Management, Secure Transactions, Twilio, PayPal, Community-Driven Commerce, Small Businesses, Personalized Shopping Experience, Scalability, Enhanced Functionality.

| DOI: 10.17148/IARJSET.2022.91121