1. A method, comprising: at a vehicle data system running on one or more server machines coupled to one or more computing devices over a network: obtaining, from one or more data sources at a time interval by the vehicle data system running on the one or more server machines, data on a set of dealers, wherein the data comprises information on a payout program, a number of vehicles sold, and historical values associated with at least one dealer cost component, wherein the at least one dealer cost component comprises a Customer Satisfaction Index (CSI), and wherein the historical values comprise historical dealer CSI scores; constructing, by the vehicle data system running on the one or more server machines, a predictive model to determine an expected CSI score at a particular level, wherein the predictive model comprises a regression analysis on the data including the historical dealer CSI scores; determining, by the vehicle data system running on the one or more server machines utilizing the expected CSI score at the particular level, an expected average of the expected CSI score for a time period; generating a market-share probability density function utilizing the historical dealer CSI scores; determining, by the vehicle data system running on the one or more server machines utilizing the market-share probability density function and the expected average of the expected CSI score predicted for the time period, a probability of a transaction having a given CSI score; determining, by the vehicle data system running on the one or more server machines utilizing the probability of the transaction having the given CSI score, an average CSI bonus payout per vehicle for the time period; and producing, by the vehicle data system running on the one or more server machines, an actual dealer cost by adjusting a base dealer cost with the average CSI bonus payout per vehicle for the time period.