Platforms can obtain sizable returns by operationally managing their market thickness, i.e., the availability of supply-side inventory. Using data from a natural experiment on a major B2B auction platform specializing in the $424 billion secondary market for liquidating retail merchandise, we find that thickening the platform’s market by consolidating the ending times of auctions to certain weekdays substantially increases its revenue by roughly 6.5%, due primarily to the bidders’ participation frictions. We study two complementary design levers to calibrate and control the platform’s market thickness in the face of complex demand-side decision making: (i) its listing policy, which determines the ending times of auctions, and (ii) a recommendation system. To optimize these design decisions, we first develop a structural model to characterize how bidders form expectations and respond to the imminent availability of auctions in equilibrium, including how frequently they visit the platform, in which auctions they choose to participate, and their bidding strategies. In calibrating its market thickness, the platform trades off increasing bidder participation in each auction by appropriately thickening the market (demand-side competition) against limiting the extent to which auctions for substitutable goods ultimately cannibalize one another under thicker market conditions (supply-side competition). Using our structural estimates, we illustrate how the platform can optimize its listing policy as a function of the incoming liquidation inventory and its bidder pool so as to achieve a supply-demand sweet spot, thereby increasing its revenue significantly relative to having auctions end after a fixed time. Furthermore, we find that real-time recommendations sent on the market’s thickest days would add 3% revenue on such days (on top of the benefits obtained by optimizing the platform’s listing policy) by reducing supply-side cannibalization and altering the composition of participating bidders.