Advertising.com mobile optimization

Abstract

The number of mobile-connected devices has been growing at a tremendous rate in recent years. These increasingly powerful tablets and smartphones are portable and personal, giving advertisers the potential to reach consumers on a one-on-one basis with personalized advertisements based on location, recent behaviors, and much more. A substantial difference between mobile media usage and mobile advertising spending suggests a significant growth opportunity in the mobile advertising market. Our work involves improving the decision-making technology used by Advertising.com, a large online advertising network, as it attempts to increase its presence in the mobile advertising market. We examined the factors that differentiate mobile consumers in order to target them more effectively, and drive the direction of Advertising.com's future mobile optimization technology development. Data was available to us from Advertising.com's back-end database, as well as in its front-end campaign reporting system. To investigate this data and determine the most valuable mobile variables, we performed data analysis utilizing tools including Microsoft Excel, R, SQL, and Minitab. We also leveraged Advertising.com's existing decision algorithm, AdLearn, as well as looked to existing mobile advertising studies. Our analyses indicate several factors are influential in the effectiveness of mobile advertisements including hour of day, day of week and device type. We found that mobile campaigns perform best during the morning hours and late at night in terms of both impressions and conversions. Also, we found that weekends have statistically superior conversion rates.