In a world where businesses offer hundreds of products, and customers have limited time for exploration, recommendation systems make the difference between providers of similar products. While early studies into product recommendation target systems based on explicit feedback, with the expanse of big data, the usage of implicit feedback becomes vital. In this talk I will focus on different methods for data representation, algorithmic approaches for building product recommendations, as well as model evaluation.