We develop and perform a non reactive A/B-test setting that enables us to evaluate the influence of green marketing signals on the customer's decision to take a specific online-shop into account in the process of buying a specific product by clicking on an ad on a search engine results page (SERP). We analyze campaign performance data generated by a European e-commerce retailer, apply a Bayesian parameter estimation to compare specific advertisements and discuss the implications of the results.

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.

No abstract