Highly valued Information technology (IT) service contracts involve the delivery of complex IT services, such as migrating the client's IT infrastructure to the Cloud, Mainframes, among others. IT service providers usually compete to win these IT service contracts. In order to bid on such deals, IT service providers need to price/quote the solution that they propose to the client, trying to convince him to use their services. A few analytical methods in the literature have been provided for pricing these deals. However, these methods ignore an important characteristic of these services; that is they are typically characterized by a decreasing cost profile in subsequent years to the first year. Typically, these methods require solutioners to manually input these annual cost reductions. In this paper, we present an analytical way for calculating this cost reduction, if applicable, via mining historical data. We show that using our methodology could achieve significant increase in the accuracy of estimating the costs and prices of IT service deals.