von Tobias-Benedikt Blask (2014), 11th International Joint Conference on e-Business and Telecommunications (ICE-B).
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.
Keywords: Bayesian Statistics, Bayesian Analysis of Variance, Search Engine Advertising, Sponsored Search, Paid Search Advertising, Multivariate Testing.