Scheduling of Dynamic In-Game Advertising

• 成果类型: Article
• 署名作者: Turner, John; Scheller-Wolf, Alan; Tayur, Sridhar
• 署名单位: University of California System; University of California Irvine; Carnegie Mellon University
• 刊物名称: OPERATIONS RESEARCH
• ISSN/ISSBN: 0030-364X
• DOI: 10.1287/opre.1100.0852
• 发表日期: 2011
• 页码: 1-16
• 关键词: broadcast television

摘要

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.