Social Commerce Platform for Sellers
We built an innovative platform that allows sellers to create their personalized pages in various business domains like cosmetics, toys, apparel, home & living, and art. Inspired by social media, the platform simplifies product uploads and enables sellers to engage directly with their followers through live selling and seamless product purchases.
Discovery Phase
Objective: Simplify the online selling experience for small businesses and independent sellers. We identified the need for a user-friendly platform where sellers could showcase and sell their products without complex inventory systems. The focus was to create a familiar, social media-like experience for sellers and buyers. Outcome: A roadmap prioritizing simplicity, social engagement, and live selling functionality.
Planning Phase
Architecture and Technology Stack We selected Node.js for backend functionality, React.js for an engaging front-end interface, and AWS for scalable hosting. A MongoDB database was chosen for managing seller pages, posts, and transactions. Outcome: A clear architecture blueprint and a development plan focused on real-time interactions and ease of use.
Design Phase
Crafting a Social Media-Inspired Interface We designed the platform to look and feel like a social media app, making it instantly familiar to users. Key design features included: Post-Like Product Uploads — Sellers can upload products by simply adding photos, a description, and a price, similar to creating a post on Instagram. Follower Engagement — Sellers can build their follower base, interact with buyers, and schedule live selling events. Personalized Seller Pages — Each seller has a unique page where buyers can browse products and follow their updates. Outcome: A visually appealing, user-friendly design optimized for social engagement and seamless product browsing.
AI Integration
Personalized Gift Recommendations with AI Using TensorFlow, we built an AI-powered recommendation engine that analyzes user behavior, preferences, and past interactions to suggest the most relevant gifts. The AI continuously learns from user inputs, improving suggestions over time to deliver a more personalized experience for each visitor. Outcome: A recommendation system that adds value by helping users find the perfect gift effortlessly.
Development Phase
Building Core Features and Integrations In addition to the AI engine, we implemented backend systems with Node.js for efficient order processing and a React front-end for responsive, cross-device functionality. Outcome: A fully functional platform with AI recommendations, prepared for testing.
Testing Phase
Quality Assurance for Recommendations and Usability We conducted rigorous testing on recommendation accuracy, platform usability, and payment security. Cross-border testing ensured consistent delivery and payment functionality for global users. Outcome: A polished platform with reliable recommendations and seamless user experience.
Launch Phase
Deploying the AI-Powered Gifting Platform After final testing, the platform was launched, allowing users around the world to send gifts to India and Nepal, with AI-powered suggestions enhancing the experience. Outcome: A live, user-ready platform offering personalized gifting and global reach.
Post-Launch & Maintenance
Post-launch, we continue to monitor performance, gather user feedback, and optimize the AI recommendations. Planned updates include expanding gift categories and further refining the recommendation algorithm. Outcome: A proactive strategy for continuous improvement and user satisfaction.