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In this paper, we focus on the users' aggregate data demand dynamics in a wireless communications market served by a monopolistic wireless service provider (WSP). Based on the equilibrium data demand, we optimize the WSP's data plans and long-term network capacity decisions to maximize its profit. First, by considering a market where only one data plan is offered, we show that there exists a unique equilibrium in the data demand dynamics regardless of the data plans, and that the convergence of data demand dynamics is subject to the network congestion cost, which is closely related to the WSP's long-term capacity decision. A sufficient condition on the network congestion cost indicates that the WSP needs to provide a sufficiently large network capacity to guarantee the convergence of data demand dynamics. We also propose a heuristic algorithm that progressively optimizes the WSP's data plan to maximize its equilibrium revenue. Next, we turn to a market where two different data plans are offered. It is shown that the existence of a unique equilibrium data demand depends on the data plans, and the convergence of data demand dynamics is still subject to the network congestion cost (and hence, the WSP's network capacity, too). We formalize the problem of optimizing the WSP's data plans and network capacities to maximize its profit. Finally, we discuss the scenario in which the data plans are offered by two competing WSPs and conduct extensive simulations to validate our analysis.