Online repeated posted price auctions with a demand side platform

TL;DR

This paper analyzes online posted price auctions in ad networks with intermediaries, focusing on optimal reserve pricing, advertiser scheduling, and revenue optimization under various constraints and item types.

Contribution

It introduces dynamic reserve pricing for heterogeneous items and algorithms for scheduling advertisers with budget and impression constraints.

Findings

Optimal reserve price is dynamic for heterogeneous items.

Algorithms effectively schedule advertisers under budget and impression constraints.

Numerical results demonstrate the approach's effectiveness across valuation distributions.

Abstract

We consider an online ad network problem in which an ad exchange auctions ad slots and intermediaries called demand side platforms (DSPs) buy these ad slots for their clients (advertisers). An intermediary represents multiple advertisers. Different types of ad slots are auctioned by the ad exchange, e.g., video ad, banner ad etc. We study repeated posted price auctions for homogeneous and heterogeneous items when there is an intermediary. In a posted price auction, the auctioneer sets a fixed reserve price. The buyer can accept the price and win the ad slot or reject the price. We analyze the system from the auctioneer's perspective and show that the optimal reserve price is dynamic for heterogeneous items. We also investigate system from intermediary's perspective and devise algorithms for scheduling advertisers. Often the advertisers have budget constraints and impression constraints. We formulate a revenue optimization problem at the intermediary and also consider the problem of scheduling advertisers with budget and impression constraints. Finally, we present a numerical study for the single seller and advertiser model which considers various valuation distributions such as uniform, exponential and lognormal.