D.A. Wooff
Statistical management of pay-per-click processes for search engines
Wooff, D.A.; Anderson, J.M.; Jamalzadeh, A.
Authors
J.M. Anderson
A. Jamalzadeh
Contributors
P. Aston
Editor
A. Mulholland
Editor
K. Tant
Editor
Abstract
Suppose you want to buy a dishwasher. What you might do is go to a search engine such as Google or Bing and type “dishwasher” in the search field. If you are using Google, what you may see are some sponsored links (adverts), as well as the results of natural search offered by Google’s search algorithm. The sponsored links appear because the keyword you typed is a keyword that a company has paid Google to display whenever someone searches for it. Broadly what happens is that if you then click on the advert, the sponsoring company will pay Google—or the search engine you used—a small amount. This is called Pay-Per-Click (PPC). We describe statistical models and methods which are used to automate and optimize daily PPC bid-price setting over portfolios which can contain hundreds of thousands of products and keywords, with the aim of maximizing the flow of customers and revenue to online retailers.
Citation
Wooff, D., Anderson, J., & Jamalzadeh, A. (2016). Statistical management of pay-per-click processes for search engines. In P. Aston, A. Mulholland, & K. Tant (Eds.), UK success stories in industrial mathematics (297-303). Springer Verlag. https://doi.org/10.1007/978-3-319-25454-8_38
Online Publication Date | Feb 5, 2016 |
---|---|
Publication Date | Feb 5, 2016 |
Deposit Date | Jun 8, 2015 |
Publisher | Springer Verlag |
Pages | 297-303 |
Book Title | UK success stories in industrial mathematics. |
ISBN | 9783319254524 |
DOI | https://doi.org/10.1007/978-3-319-25454-8_38 |
Public URL | https://durham-repository.worktribe.com/output/1670228 |
You might also like
Bayes Linear Statistics: Theory and Methods
(2007)
Book
Inferring marketing channel relevance in the customer journey to online purchase
(2013)
Preprint / Working Paper
Time-weighted attribution of revenue to multiple e-commerce marketing channels in the customer journey
(2013)
Preprint / Working Paper
Downloadable Citations
About Durham Research Online (DRO)
Administrator e-mail: dro.admin@durham.ac.uk
This application uses the following open-source libraries:
SheetJS Community Edition
Apache License Version 2.0 (http://www.apache.org/licenses/)
PDF.js
Apache License Version 2.0 (http://www.apache.org/licenses/)
Font Awesome
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2025
Advanced Search