Auction Design for ROI-Constrained Buyers

35 Pages Posted: 5 Mar 2018 Last revised: 10 Sep 2020

See all articles by Negin Golrezaei

Negin Golrezaei

Massachusetts Institute of Technology (MIT) - Sloan School of Management

Ilan Lobel

New York University (NYU)

Renato Paes Leme

Google Inc.

Date Written: February 15, 2018

Abstract

We combine theory and empirics to (i) show that some buyers in online advertising markets are financially constrained and (ii) demonstrate how to design auctions that take into account such financial constraints. We use data from a field experiment where reserve prices were randomized on Google’s advertising exchange (AdX). We find that, contrary to the predictions of classical auction theory, a significant set of buyers lowers their bids when reserve prices go up. We show that this behavior can be explained if we assume buyers have constraints on their minimum return on investment (ROI). We proceed to design auctions for ROI-constrained buyers. We show that optimal auctions for symmetric ROI-constrained buyers are either second-price auctions with reduced reserve prices or subsidized second-price auctions. For asymmetric buyers, the optimal auction involves a modification of virtual values. Going back to the data, we show that using
ROI-aware optimal auctions can lead to large revenue gains and large welfare gains for buyers.

Keywords: Return on Investment, Performance Buyers, Mechanism Design, Online Advertising.

Suggested Citation

Golrezaei, Negin and Lobel, Ilan and Paes Leme, Renato, Auction Design for ROI-Constrained Buyers (February 15, 2018). Available at SSRN: https://ssrn.com/abstract=3124929 or http://dx.doi.org/10.2139/ssrn.3124929

Negin Golrezaei

Massachusetts Institute of Technology (MIT) - Sloan School of Management ( email )

100 Main Street
E62-416
Cambridge, MA 02142
United States
02141 (Fax)

Ilan Lobel (Contact Author)

New York University (NYU) ( email )

Bobst Library, E-resource Acquisitions
20 Cooper Square 3rd Floor
New York, NY 10003-711
United States

Renato Paes Leme

Google Inc. ( email )

1600 Amphitheatre Parkway
Second Floor
Mountain View, CA 94043
United States

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