Third-Party Data Providers Ruin Simple Mechanisms

Yang Cai; Federico Echenique; Hu Fu; Katrina Ligett; Adam Wierman; Juba Ziani

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arXiv · 1802.07407

Third-Party Data Providers Ruin Simple Mechanisms

Yang Cai·Federico Echenique·Hu Fu·Katrina Ligett·Adam Wierman·Juba Ziani

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Abstract

Motivated by the growing prominence of third-party data providers in online marketplaces, this paper studies the impact of the presence of third-party data providers on mechanism design. When no data provider is present, it has been shown that simple mechanisms are "good enough" -- they can achieve a constant fraction of the revenue of optimal mechanisms. The results in this paper demonstrate that this is no longer true in the presence of a third-party data provider who can provide the bidder with a signal that is correlated with the item type. Specifically, even with a single seller, a single bidder, and a single item of uncertain type for sale, the strategies of pricing each item-type separately (the analog of item pricing for multi-item auctions) and bundling all item-types under a single price (the analog of grand bundling) can both simultaneously be a logarithmic factor worse than the optimal revenue. Further, in the presence of a data provider, item-type partitioning mechanisms---a more general class of mechanisms which divide item-types into disjoint groups and offer prices for each group---still cannot achieve within a $\log \log$ factor of the optimal revenue. Thus, our results highlight that the presence of a data-provider forces the use of more complicated mechanisms in order to achieve a constant fraction of the optimal revenue.

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BibTeX RIS

Yang Cai, Federico Echenique, Hu Fu, Katrina Ligett, Adam Wierman, Juba Ziani. 2018-02-21. Third-Party Data Providers Ruin Simple Mechanisms. https://arxiv.org/abs/1802.07407

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