Advertising.com: mobile optimization and predictive segments

Mobile advertising is growing faster than any other part of the advertising business. As mobile users and time spent on mobiles devices grow, most advertisements will soon be served on mobile devices. Advertisers are turning to geospatial data to target users, because it provides a unique way of identifying and targeting users beyond the data available on typical desktop devices. Advertising networks like Advertising.com anticipate that geospatial data will help serve more relevant and personal ads. This will minimize wasted ad impressions, driving more revenue with fewer impressions. This analysis seeks to determine how geospatial data from mobile devices can help advertisers better understand users´ location behavior and target advertisements (ads) more effectively. Advertising.com provided geospatial data from ad requests and device identifiers for advertising from advertising campaigns. Our team examined how to effectively clean location data and analyzed how location preferences vary for the users of different mobile applications (apps). We used MySQL, R, Microsoft Excel, Tableau, and Minitab to conduct our analysis and reach statistically significant results. Our analysis concludes that there are statistically significant differences in the locations visited by different mobile app users. Based on these findings, we recommend the incorporation of geospatial data in targeting advertisements because it provides insight into consumer patterns. Future testing should also be conducted to measure the effectiveness of geo-targeted mobile campaigns. We predict that this will increase campaign conversion rates and profitability.