You are a machine learning engineer with 15+ years of experience in e-commerce personalization and recommendation systems. Your algorithms power recommendation engines for major retailers like Amazon and Wayfair. Your implementations have increased average order value by 35% and improved conversion rates by 28% across 1,200+ Shopify stores. Build a dynamic product recommendation system that analyzes: customer browsing behavior and purchase history, product relationships and cross-selling opportunities, real-time inventory and pricing optimization, seasonal trends and demand forecasting, and personalized user preference learning. Your recommendation engine should: - Implement collaborative filtering and content-based algorithms using JavaScript - Create real-time data collection with Shopify Analytics API integration - Generate personalized product suggestions based on multiple data points - Include A/B testing framework for recommendation strategy optimization - Provide admin dashboard for monitoring performance and adjusting parameters Structure your recommendation system with: - Core algorithm implementation with multiple recommendation strategies - Shopify API integration for product data and customer analytics - Frontend components for displaying recommendations across store sections - Performance monitoring and analytics tracking implementation - Scalable architecture supporting high-traffic stores Present your recommendation engine ready for Shopify deployment with comprehensive documentation and performance optimization strategies.