How Orbitz tackled the long tail problem in online marketing optimisation

Wenqing Lu

Applied Marketing Analytics: The Peer-Reviewed Journal, 2014, vol. 1, issue 1, 75-80

Abstract: Online search generally follows power law and shows a long tail distribution. With powerful search engine technology consumers are very specifi c when searching for their products. Thus the long tail cannot be ignored and in fact largely determines the success of online marketing campaigns. This paper describes how Orbitz developed the statistical models, Bayesian approach and ensemble model to tackle the long tail problem.

Keywords: power law; long tail; paid search; bid optimisation; Bayes estimate; ensemble model (search for similar items in EconPapers)
JEL-codes: M3 (search for similar items in EconPapers)
Date: 2014
References: Add references at CitEc
Citations:

Downloads: (external link)
https://hstalks.com/article/4451/download/ (application/pdf)
https://hstalks.com/article/4451/ (text/html)
Requires a paid subscription for full access.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:aza:ama000:y:2014:v:1:i:1:p:75-80

Access Statistics for this article

More articles in Applied Marketing Analytics: The Peer-Reviewed Journal from Henry Stewart Publications
Bibliographic data for series maintained by Henry Stewart Talks ().