  Price differentiation describes a marketing strategy to determine the price
of goods on the basis of a potential customer's attributes like location,
financial status, possessions, or behavior. Several cases of online price
differentiation have been revealed in recent years. For example, different
pricing based on a user's location was discovered for online office supply
chain stores and there were indications that offers for hotel rooms are priced
higher for Apple users compared to Windows users at certain online booking
websites. One potential source for relevant distinctive features are
\emph{system fingerprints}, i.\,e., a technique to recognize users' systems by
identifying unique attributes such as the source IP address or system
configuration. In this paper, we shed light on the ecosystem of pricing at
online platforms and aim to detect if and how such platform providers make use
of price differentiation based on digital system fingerprints. We designed and
implemented an automated price scanner capable of disguising itself as an
arbitrary system, leveraging real-world system fingerprints, and searched for
price differences related to different features (e.\,g., user location,
language setting, or operating system). This system allows us to explore price
differentiation cases and expose those characteristic features of a system that
may influence a product's price.
