Applying Bayesian parameter estimation to A/B tests in e-business applications examining the impact of green marketing signals in sponsored search advertising

Author

Blask, Tobias

Author_Institution

Inst. of Electron. Bus. Processes, Leuphana Univ. of Lueneburg, Lueneburg, Germany

fYear

2013

fDate

29-31 July 2013

Firstpage

1

Lastpage

8

Abstract

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.

Keywords

Bayes methods; Internet; advertising data processing; electronic commerce; parameter estimation; retail data processing; search engines; Bayesian parameter estimation; European e-commerce retailer; SERP; campaign performance data; customer decision; e-business applications; green marketing signals; nonreactive A-B-test setting; online-shop; search engine results page; sponsored search advertising; Advertising; Bayes methods; Google; Green products; Parameter estimation; Predictive models; Search engines; A/B Testing; Bayesian Parameter Estimation; Bayesian Statistics; Paid Search Advertising; Sponsored Search;

fLanguage

English

Publisher

ieee

Conference_Titel

e-Business (ICE-B), 2013 International Conference on

Conference_Location

Reykjavik

Type

conf

Filename

7230666