The rise of data analytics has spawned the data broker industry that has played an increasingly important role in data-driven advertising. In this study, we build an analytical model to analyze the strategic interactions between the data broker, publishers, and advertisers. Specifically, we investigate the data broker’s data selling strategies, publishers’ data analytics strategies, as well as the advertisers’ choice between competing publishers. We find that the data broker’s data selling strategies depending on the intensity of information externality and competition between downstream publishers. Interestingly, under some circumstances, the data broker chooses to sell only one publisher with low externality his competitor’s data, which leads to selling fewer data. This result highlights that the conventional wisdom that the data broker always attempts to sell more data may not always hold. We discuss the managerial implications of our findings and provide future research directions.