Dwell time at bus stops represents a significant portion of bus operating time and contributes to its variability. Although dwell time is highly correlated with the number of passengers boarding and alighting, there are also secondary factors such as crowding, fare type, and bus design that may affect it. These secondary factors may strongly influence the effectiveness of different strategies used to improve service. Automatic data collection systems provide a plethora of data, but they require preprocessing to combine records from different collection systems to control for measurement error and to determine the significant factors influencing dwell time. Using data from the automatic passenger counting, automatic fare counting, and automatic vehicle location systems installed on Chicago Transit Authority buses, the paper develops and implements preprocessing techniques, estimates a dwell time model, and analyzes the impact of the secondary factors. Smart media farecards are estimated to have a 1.5-s faster transaction time than magnetic strip tickets, but only in uncrowded situations. When the number of onboard passengers exceeds the seating capacity, there is no statistically significant difference between the fare media types.