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.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Summit.: Back to the future for performance marketing. White paper on predictive analytics (2015). http://www.summit.co.uk/predictive-analytics-for-performance-marketing/
Wooff, D.A., Anderson, J.M.: Time-weighted multi-touch attribution and channel relevance in the customer journey to online purchase. J. Stat. Theory Pract. 9(2), 227–249 (2015). doi:10.1080/15598608.2013.862753
Wooff, D.A., Jamalzadeh, A.: Robust and scale-free effect sizes for non-Normal two-sample comparisons, with applications in e-commerce. J. Appl. Stat. 40(11), 2495–2515 (2013)
Acknowledgments
Part of this research was funded by Knowledge Transfer Partnership KTP–7499, funded by Summit and by the UK Technology Strategy Board. We are grateful to Summit for providing data and to colleagues there for providing expertise.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer International Publishing Switzerland
About this chapter
Cite this chapter
Wooff, D.A., Anderson, J.M., Jamalzadeh, A. (2016). Statistical Management of Pay-Per-Click Processes for Search Engines. In: Aston, P., Mulholland, A., Tant, K. (eds) UK Success Stories in Industrial Mathematics. Springer, Cham. https://doi.org/10.1007/978-3-319-25454-8_38
Download citation
DOI: https://doi.org/10.1007/978-3-319-25454-8_38
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-25452-4
Online ISBN: 978-3-319-25454-8
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)