Applications of Statistical Experimental Design to Improve the Performance of Google AdWords Campaigns

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2012-03

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The Ohio State University

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Abstract

Google AdWords are a set of self-advertising tools which are provided by Google Company. Due to the complexity of the methods, the methods provide limited information to users related to the many decisions associated with setting up an ad campaign including: daily budget, cost per click, the contents of the advertisement, and the key words selected. This thesis focuses on how to improve advertisement click numbers with lowest cost using data to support decision-making. A case study application of experimental design is included together with recommendations for future applications. The case study was based on a 12-run Plackett-Burman array. In the case study, we planned 12 individual varying 10 factors, and developed associated statistical data analysis. Results from the case study focus on so-called "covariates" and results indicate that the "day" affected the experiment result significantly as well as both daily budget and cost per click had positive effects. Another issue that was considered was the possible importance of "keywords". The preliminary findings suggest that "keywords" and the "day" or seasonality should be considered in future experiments and should be considered in future applications of statistical design of experiments.

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DOE, Google AdWords, Case Study of Google AdWords, Plackett-Burman Array

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