Although the data monetization market continues to grow with a Compound Annual Growth Rate of 19.5% between 2022 and 2027 (MarketsAndMarkets, 2022), many data marketplaces have failed and withdrawn from the market (Carnelley et al., 2016; Spiekermann, 2019). Particularly the pricing of data remains a key challenge for practitioners (Muschalle et al., 2013; Balazinska et al., 2011). Fricker and Maksimov (2017) come to the conclusion that “research on pricing for data products is still in its infancy” and cannot provide satisfactory recommendations for practioners. The objective of this paper is to contribute in closing this gap based on semi-structured expert interviews which address two research questions: (1) Which price setting mechanisms are chosen in practice? (2) Which value drivers contribute to the value of a dataset? Our results show that data marketplaces dominantly choose cost-based pricing approaches or hand over pricing responsibilities to data providers and buyers. At the same time, they prioritize value drivers outside the cost category. One explanation is that data marketplace are striving for a value-based pricing approach, but currently fail to implement it. We suggest a pragmatic pricing approach that calculates the base price based on the costs and considers performance on value drivers for margin calculation.