If you are looking for a ranking function that optimizes consumption, an obvious baseline is item popularity. The reason is clear: on average, a member is most likely to watch what most others are watching. However, popularity is the opposite of personalization: it will produce the same ordering of items for every member. Thus, the goal becomes to find a personalized ranking function that is better than item popularity, so we can better satisfy members with varying tastes.
Netflix uses lot of variables to recommend movies for you and one interesting item (and close to home) is social relevancy.
Social data has become our latest source of personalization features; we can process what connected friends have watched or rated.