Recommender systems are commonly used by Internet firms to improve consumers’ shopping experience and increase firm sales and profits. A large stream of work on recommender design has studied the problem of identifying the most relevant items to recommend to users. In parallel, recent empirical work has started to provide evidence that real-world recommenders contribute to increased sales and profitability for the firms. However, maximizing consumer welfare and firm profit are not the same. Given that recommenders impact sales and profits, a natural question is what is the impact of firm’s profit incentives on recommender design? This paper studies optimal recommender design in a profit-maximizing framework to answer the question and identifies the conditions under which a profit-maximizing recommender recommends the item with highest margins and those under which it recommends the most relevant item. We further elaborate on the social cost of the mismatch between consumer and firm incentives.