Billions of dollars worth of display advertising are sold via contracts and deals. This paper is the first formal study of preferred deals, a new generation of contracts for selling online advertisement that generalize the traditional reservation contracts; these contracts are suitable for advertisers with advanced targeting capabilities. We propose an approximation algorithm for maximizing the revenue that can be obtained from these deals. We evaluate our algorithm using data from Google's ad exchange platform. Our algorithm obtains about 90% of the optimal revenue. Furthermore, we show, both theoretically and via data analysis, that deals, with appropriately chosen minimum-purchase guarantees, can yield significantly higher revenue than auctions.