Price discrimination, setting the price of a given product
for each customer individually according to his valuation
for it, can beneﬁt from extensive information collected
online on the customers and thus contribute to the
proﬁtability of e-commerce services. Another way to
discriminate among customers with different willingness to
pay is to steer them towards different sets of products
when they search within a product category (i.e., search
discrimination). Our main contribution in this paper is to
empirically demonstrate the existence of signs of both
price and search discrimination on the Internet, and to
uncover the information vectors used to facilitate them.
Supported by our ﬁndings, we outline the design of a
large-scale, distributed watchdog system that allows users
to detect discriminatory practices.
If there is a very price sensitive shopping behavior this will lead to a strong increase of data noise by people trying to play the algorithms, e.g. fake accounts, deletion of accounts, groomed accounts towards specific deals, etc.