Deregulation within the aviation market led to constant decreasing revenue of airfares while airlines across the market spectrum sharpen their focus on ancillaries. The objective of this thesis project is to utilize revealed preference data in a case-study of KLM Royal Dutch Airways to better understand the customer relation towards ancillaries. Therefore, the willingness to pay for bundled flight ancillaries, also called branded fares, is estimated. Discrete choice modelling offers the opportunity to estimate the willingness to pay of the customers from the given data. A multinomial logit model was chosen and designed to enable the estimation of the parameter. Therefore, revealed preference data has been extracted, combined and cleaned with Python. A total of 47.350 flights have been analysed from 10 medium-haul destinations within Europe. For a better model fit the travel motive of the customers has been used to split the dataset into multiple actor specific constants being used to calculate the willingness to pay from. The results indicate far less willingness to pay for the ancillaries as currently asked for, namely 8.06 EUR for the Standard fare for business customers and 2.95 EUR for leisure customers. The Flex fare is estimated for 26.33 EUR for business customers and 4.82 EUR for leisure customers. The estimation result leads to the conclusion that it might be useful to implement price discrimination for the ancillaries as it is already in place for the airfare. Beyond the application on the willingness to pay, the revealed preference data has been analysed to reflect on the propensity and the amount of customer wish to pay for C02 offsetting. It shows that compared to stated preference data of other research the customers in this case-study pay far less frequently (only 1.02 percent of the passengers) and offset a tremendously less amount (on avg. 0.63 EUR) compared to the research based on stated preference.