Abstract
In 2016, Madera et al. tested the performance of a fuzzy inference system against the Google Ads algorithms for optimizing the number of clicks, the click through rate (CTR) and the average cost per clicks to lower the cost of an advertising campaign [7]. The results of their experiments suggested that the implementation of their fuzzy inference system outperformed the Google Ads algorithms in terms of the obtained number of clicks and cost per clicks. While the research idea is with no doubts an interesting and valuable contribution to the fields of digital marketing research, in the opinion of the authors, their experimental setup was flawed. However, applying a few adjustments can lead to valid findings. This paper reflects on the flaws and suggests enhancements to correct them.
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