Do Specific Text Features Influence Click Probabilities in Paid Search Advertising?
Publikation: Beiträge in Sammelwerken › Abstracts in Konferenzbänden › Forschung › begutachtet
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ICE-B 2014 - Proceedings of the 11th International Conference on e-Business, Part of ICETE 2014 - 11th International Joint Conference on e-Business and Telecommunications. Hrsg. / Andreas Holzinger; Marten van Sinderen; Peter Dolog; Mohammad S. Obaidat. Science and Technology Publications, Lda (SciTePress), 2014. S. 55-62 (ICE-B 2014 - Proceedings of the 11th International Conference on e-Business, Part of ICETE 2014 - 11th International Joint Conference on e-Business and Telecommunications).
Publikation: Beiträge in Sammelwerken › Abstracts in Konferenzbänden › Forschung › begutachtet
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TY - CHAP
T1 - Do Specific Text Features Influence Click Probabilities in Paid Search Advertising?
AU - Blask, Tobias-Benedikt
N1 - Conference code: 11
PY - 2014/1/1
Y1 - 2014/1/1
N2 - 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
AB - 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
KW - Business informatics
KW - Bayesian analysis of variance
KW - Bayesian statistics
KW - Multivariate testing
KW - Paid search advertising
KW - Search engine advertising
KW - Sponsored search
UR - http://www.scopus.com/inward/record.url?scp=84910030855&partnerID=8YFLogxK
UR - https://www.mendeley.com/catalogue/6f18ade7-4e78-39a5-b593-7a77d842881e/
U2 - 10.5220/0005048400550062
DO - 10.5220/0005048400550062
M3 - Published abstract in conference proceedings
SN - 9789897580437
T3 - ICE-B 2014 - Proceedings of the 11th International Conference on e-Business, Part of ICETE 2014 - 11th International Joint Conference on e-Business and Telecommunications
SP - 55
EP - 62
BT - ICE-B 2014 - Proceedings of the 11th International Conference on e-Business, Part of ICETE 2014 - 11th International Joint Conference on e-Business and Telecommunications
A2 - Holzinger, Andreas
A2 - van Sinderen, Marten
A2 - Dolog, Peter
A2 - Obaidat, Mohammad S.
PB - Science and Technology Publications, Lda (SciTePress)
T2 - 11th International Conference on e-Business - ICE-B 2014
Y2 - 28 August 2014 through 30 August 2014
ER -