Do specific text features influence click probabilities in Paid Search Advertising?

Paid Search Advertisers have only very few options to influence the user's decision to click on one of their ads. The textual content of the creatives seems to be one important influencing factor beneath its position on the Search Engine Results Page (SERP) and the perceived relevance of the given ad to the present search query. In this study we perform a non reactive multivariate test that enables us to evaluate the influence of specific textual signals in Paid Search creatives. A Bayesian Analysis of Variance (BANOVA) is applied to evaluate the influence of various text features on click probabilities. We conclude by finally showing that differences in the formulation of the textual content can have influence on the click probability of Paid Search ads.