a few gatekeepers. This allows them to potentially influence and steer individuals’ purchase choices, as well as to charge – in case they are e-commerce platforms – different prices to different customers [pp. 445, @Acquisti2016; @CouncilofEconomicAdvisers-CEA2015; @kshetri2014big], who are clustered via different techniques.

As a matter of fact, the more data platforms manage to gather, the more effective their attempt will be to shift from a third price discrimination degree (different prices are charged to different socio-demographic groups) to a perfect discrimination, that is the condition in which it is possible to set different prices for different individuals or to nudge the same consumers towards the purchase of a certain good o service based on their price sensitivity [@shiller2014first; @kramer2017digital; @regner2017privacy]. It happen indeed to be addressed by product recommendations based on one’s past online purchases, to be targeted by real-time advertisements reflecting past browsing behaviour, or to be the recipient of tailored search results stemming from individual queries [@Levin2011]. As a matter of fact, platforms collect data, the more they can move towards perfect discrimination. The proof of the progressively enhanced platforms’ capacity to implement discriminatory practices lies with their increased ability to estimate individuals’ preferences [@lu2012recommender; @lu2015recommender].

The 