  We study the optimal mechanism design problem faced by a market intermediary
who makes revenue by connecting buyers and sellers. We first show that the
optimal intermediation protocol has substantial structure: it is the solution
to an algorithmic pricing problem in which seller's costs are replaced with
virtual costs, and the sellers' payments need only depend on the buyer's
behavior and not the buyer's actual valuation function.
  Since the underlying algorithmic pricing problem may be difficult to solve
optimally, we study specific models of buyer behavior and give mechanisms with
provable approximation guarantees. We show that offering only the single most
profitable item for sale guarantees an $\Omega(\frac1{\log n})$ fraction of the
optimal revenue when item value distributions are independent and have monotone
hazard rates. We also give constant factor approximations when the buyer
considers all items at once, $k$ items at once, or items in sequence.
