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Advertising.com: Mobile optimization and predictive segments

机译:Advertising.com:移动优化和预测性细分

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Today the advertising industry is becoming increasingly dependent on the Internet to deliver advertisements to viewers. Third party advertising networks such as Advertising.com, a division of AOL Inc., are utilizing targeted advertising strategies to make Internet advertising more profitable. Targeted advertising utilizes cookies to track users and target them with advertisements based on attributes such as site history and past advertisements viewed. Chad Gallagher, the Mobile Team lead for Advertising.com, projects that mobile Internet usage will surpass computer Internet usage by 2015. This major shift will render the traditional cookie based targeting model obsolete, as the majority of mobile devices do not store cookies. Consequently, the development of new mobile targeting strategies has become a top priority for companies such as Advertising.com in order to increase the profitability of online advertising. Predictive segments power the Internet advertising targeting strategy, but with cookies no longer available new variables need to be used for the predictive segments aimed at mobile users. This analysis seeks to determine the predictive power of the information unique to mobile users, in particular cellular provider and model of phone. This analysis was conducted utilizing data from two telecom companies' advertising campaigns. The findings indicate that for telecom advertising, service provider and model of phone are statistically significant predictors of a consumer's likelihood to convert. From these findings, the authors of this paper recommend the incorporation of mobile variables into predictive segments as they provide significant insight into consumer patterns. With the addition of the team's work, Advertising.com will be able to boost their revenue per thousand impressions (RPM) from their mobile Internet traffic, which is currently their least valuable but most rapidly growing business segment. Future researchers should analyze the significanc- of these variables on advertising for nontelecom products, but as telecom companies are a major driver of mobile advertising, their campaigns proved to be a logical starting point.
机译:如今,广告行业越来越依赖于Internet向观众传递广告。诸如AOL Inc.旗下子公司Advertising.com之类的第三方广告网络正在利用有针对性的广告策略来使互联网广告更加有利可图。定向广告利用cookie来跟踪用户,并基于诸如站点历史和浏览过的先前广告之类的属性以广告为目标。 Advertising.com的移动团队负责人Chad Gallagher预测,到2015年,移动Internet的使用量将超过计算机Internet的使用量。这一重大转变将使基于传统cookie的定位模型过时,因为大多数移动设备都不存储cookie。因此,开发新的移动定位策略已成为广告公司(例如Advertising.com)的头等大事,以提高在线广告的盈利能力。预测细分为Internet广告定位策略提供了动力,但是由于Cookie不再可用,因此需要针对面向移动用户的预测细分使用新的变量。该分析旨在确定移动用户(尤其是蜂窝电话提供商和电话型号)特有的信息的预测能力。这项分析是利用两家电信公司的广告活动中的数据进行的。研究结果表明,对于电信广告而言,服务提供商和电话型号是消费者转换可能性的统计显着预测因子。根据这些发现,本文的作者建议将移动变量并入预测性细分中,因为它们可提供对消费者模式的重要洞察力。通过增加团队的工作量,Advertising.com将能够通过其移动互联网流量来提高每千次展示收入(RPM),而移动互联网流量目前是其价值最低,但发展最快的业务领域。未来的研究人员应该分析这些变量在非电信产品广告中的意义,但是由于电信公司是移动广告的主要驱动力,因此他们的竞选活动被证明是合乎逻辑的起点。

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