It depends on the volume of data that we have. Assuming there is a lot of data on hand, it is best to use a Collaborative filtering. This involves finding similar users/items for whom we are recommending products and implement a weighted average of their likeliness to the product to help make a decision on recommending the product. This could be implemented as a user-user collaborative filtering where we find similar users or an item-item collaborative filtering. If we have fewer data to work with, it is a better idea to implement a Content-based filtering approach where we create profiles for the users and try to recommend products based on the features of the user profiles.