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Projects Summary
Client Needs:
An e-commerce platform faced stagnating conversion rates with generic product suggestions. They needed a sophisticated recommendation engine that could personalize the shopping experience, increase average order value, and reduce cart abandonment through intelligent product discovery and dynamic personalization.
Our Approche:
We built a machine learning-powered recommendation system that analyzes user behavior, purchase history, and browsing patterns. The engine delivers personalized product recommendations across product pages, email, and search results. Results include a 35% increase in average order value, 28% improvement in conversion rates, and 40% reduction in cart abandonment.
