This paper focuses on the sensitivity analysis for the calibration of an agent-based simulation that analyzes the brand-level diffusion dynamics of competing products in the domestic premium mid-sized car market. In this paper, we employ a consumer-agent model that imitates the purchasing characteristics and behaviors of the consumers. The group of consumer agents that are socially interconnected represents a virtual market. By spreading the product information from previous adopters to potential consumer agents in the virtual market, the word-of-mouth phenomenon emerges like in the real market. The phenomenon influences the product choice of potential consumer agents that causes the variation of the product diffusion dynamics. In this simulation model, it is important to calibrate the virtual market parameters(e.g., ratio of innovators, social network structure, purchase time decision method) so that the virtual market can simulate the real market. However, it is difficult to measure these parameters directly from the real market. In this paper, we analyze the diffusion dynamics of simulations under various conditions in comparison with real sales data to calibrate the parameters.