Real-Time Optimization Of Web Publisher RTB Revenues
- URL: http://arxiv.org/abs/2006.07083v1
- Date: Fri, 12 Jun 2020 11:14:56 GMT
- Title: Real-Time Optimization Of Web Publisher RTB Revenues
- Authors: Pedro Chahuara, Nicolas Grislain, Gr\'egoire Jauvion and Jean-Michel
Renders
- Abstract summary: This paper describes an engine to optimize web publisher revenues from second-price auctions.
The engine is able to predict, for each auction, an optimal reserve price in approximately one millisecond.
- Score: 10.908037452134302
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: This paper describes an engine to optimize web publisher revenues from
second-price auctions. These auctions are widely used to sell online ad spaces
in a mechanism called real-time bidding (RTB). Optimization within these
auctions is crucial for web publishers, because setting appropriate reserve
prices can significantly increase revenue. We consider a practical real-world
setting where the only available information before an auction occurs consists
of a user identifier and an ad placement identifier. The real-world challenges
we had to tackle consist mainly of tracking the dependencies on both the user
and placement in an highly non-stationary environment and of dealing with
censored bid observations. These challenges led us to make the following design
choices: (i) we adopted a relatively simple non-parametric regression model of
auction revenue based on an incremental time-weighted matrix factorization
which implicitly builds adaptive users' and placements' profiles; (ii) we
jointly used a non-parametric model to estimate the first and second bids'
distribution when they are censored, based on an on-line extension of the
Aalen's Additive model.
Our engine is a component of a deployed system handling hundreds of web
publishers across the world, serving billions of ads a day to hundreds of
millions of visitors. The engine is able to predict, for each auction, an
optimal reserve price in approximately one millisecond and yields a significant
revenue increase for the web publishers.
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