OR PRACTICE---Scheduling of Dynamic In-Game Advertising
John Turner (),
Alan Scheller-Wolf () and
Sridhar Tayur ()
Additional contact information
John Turner: The Paul Merage School of Business, University of California, Irvine, Irvine, California 92697
Alan Scheller-Wolf: Tepper School of Business, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213
Sridhar Tayur: Tepper School of Business, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213
Operations Research, 2011, vol. 59, issue 1, 1-16
Abstract:
Dynamic in-game advertising is a new form of advertising in which ads are served to video game consoles in real time over the Internet. We present a model for the in-game ad-scheduling problem faced by Massive Inc., a wholly owned subsidiary of Microsoft, and a leading global network provider of in-game ad space. Our model has two components: (1) a linear program (solved periodically) establishes target service rates, and (2) a real-time packing heuristic (run whenever a player enters a new level) tracks these service rates. We benchmark our model against Massive's legacy algorithm: When tested on historical data, we observe (1) an 80%--87% reduction in make-good costs (depending on forecast accuracy), and (2) a shift in the age distribution of served ad space, leaving more premium inventory open for future sales. As a result of our work, Massive has increased the number of unique individuals that see each campaign by, on average, 26% per week and achieved 33% smoother campaign delivery as measured by standard deviation of hourly impressions served.
Keywords: dynamic in-game advertising; video game advertising; display advertising; revenue management; linear programming; goal programming (search for similar items in EconPapers)
Date: 2011
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)
Downloads: (external link)
http://dx.doi.org/10.1287/opre.1100.0852 (application/pdf)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:inm:oropre:v:59:y:2011:i:1:p:1-16
Access Statistics for this article
More articles in Operations Research from INFORMS Contact information at EDIRC.
Bibliographic data for series maintained by Chris Asher ().