Toward an Integrated Framework for Automated Development and Optimization of Online Advertising Campaigns
This addresses the problem of reducing expertise and effort for advertising specialists, though it appears incremental as it builds on existing automation concepts in online advertising.
The paper tackles the resource-intensive task of creating and optimizing pay-per-click advertising campaigns by proposing a framework for semi- and fully-automated campaign management, which experimentally outperforms manually maintained campaigns on real-world Google AdWords data.
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.