Creating and monitoring competitive and cost-effective pay-per-click advertisement campaigns through the web-search channel is a resource demanding task in terms of expertise and effort. Assisting or even automating the work of an advertising specialist will have an unrivaled commercial value. In this paper we propose a methodology, an architecture, and a fully functional framework for semi- and fully- automated creation, monitoring, and optimization of cost-efficient pay-per-click campaigns with budget constraints. The campaign creation module generates automatically keywords based on the content of the web page to be advertised extended with corresponding ad-texts. These keywords are used to create automatically the campaigns fully equipped with the appropriate values set. The campaigns are uploaded to the auctioneer platform and start running. The optimization module focuses on the learning process from existing campaign statistics and also from applied strategies of previous periods in order to invest optimally in the next period. The objective is to maximize the performance (i.e. clicks, actions) under the current budget constraint. The fully functional prototype is experimentally evaluated on real world Google AdWords campaigns and presents a promising behavior with regards to campaign performance statistics as it outperforms systematically the competing manually maintained campaigns.
翻译:通过网络搜索渠道创建和监测竞争性和成本效益高的按职定薪广告运动是一项在专门知识和努力方面资源紧缺的任务。协助甚至使广告专家的工作自动化,将具有无可比拟的商业价值。在本文件中,我们提出了一种方法、一个架构和一个功能齐全的框架,用于半自动和完全自动化地创建、监测和优化具有预算限制的按职定薪酬运动。运动创建模块根据网页内容自动生成关键词,并随相应文本发布。这些关键词被用来自动创建配有适当价值的运动。这些关键词被用于自动创建具有适当价值的运动。这些运动被上传到拍卖商平台并开始运行。优化模块侧重于从现有运动统计中学习过程,以及从以往各期应用的战略中学习,以便在下一个时期进行最佳投资。目标是在目前预算限制下最大限度地提高业绩(即点击、行动)。完全功能化的原型在实际世界谷歌AdWord运动中进行实验性评估,并展示出在运动业绩统计方面有希望的行为,因为它系统地展示了竞合的手动运动。