Drive an Increase in Sales

Enhancing business discoverability and recommendation capabilities was achieved using cutting-edge machine learning models. For Fitting Room App Recommendations and Post Purchase Lifecycle Recommendations, collaborative filtering with the Surprise package was leveraged. Expertise extended to developing Product-to-Product Recommendation Engines using scikit-learn’s NearestNeighbors for efficient item similarity searches. Quick Nav Bubbles and User-to-Item Recommendations were optimized with TensorFlow and Keras, implementing deep learning models like Neural Collaborative Filtering (NCF). Seasonal promotions were supported by designing data models with NLTK for Holiday Support, featuring Best Selling Gifts Under $10, Stocking Stuffers, and Top Rated Gifts, maximizing seasonal revenue. Solutions also included Add to Bag Upselling and Buy Online, Pick Up In Store Upsell Recommendations using XGBoost to drive personalized experiences.