Towards a pay-per-action model in sponsored search

Subscribe (Full Service)


	Search: The ACM Digital Library The Guide

	Feedback

Towards a pay-per-action model in sponsored search

Full text

Pdf (155 KB)

Source

ACM International Conference Proceeding Series; Vol. 258 archive
Proceedings of the ninth international conference on Electronic commerce table of contents

Minneapolis, MN, USA

SESSION: Session M4: sponsored search on the internet I table of contents

Pages: 87 - 88

Year of Publication: 2007

ISBN:978-1-59593-700-1

Authors

Mohammad Mahdian	Yahoo! Inc., Santa Clara, CA
Kerem Tomak	Yahoo! Inc., Santa Clara, CA

Sponsors

SIGART: ACM Special Interest Group on Artificial Intelligence
ACM: Association for Computing Machinery
SIGEcom: ACM Special Interest Group on Electronic Commerce

Publisher

ACM New York, NY, USA

Bibliometrics

Downloads (6 Weeks): 4, Downloads (12 Months): 60, Citation Count: 2

Additional Information:

abstract references cited by index terms collaborative colleagues

Tools and Actions:	Review this Article Save this Article to a Binder Display Formats: BibTeX EndNote ACM Ref

DOI Bookmark:	Use this link to bookmark this Article: http://doi.acm.org/10.1145/1282100.1282118 What is a DOI?

ABSTRACT

The online advertising industry is currently based on two dominant business models: the pay-per-impression model and the pay-per-click model. These pricing models aim to address two dimensions of an advertisers' objective function: brand awareness and sales generation. An alternative model, discussed but not widely used in the advertising industry, is pay-per-conversion, or more generally, pay-per-action. In this note, we discuss mechanisms for the pay-per-action model and various challenges involved in designing such mechanisms.

REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

	1	Forrester Research, US Online Marketing Forecast: 2005 to 2010, May 2, 2005.
	2	N. Immorlica, K. Jain, M. Mahdian, and K. Talwar, Click Fraud Resistant Methods for Learning Click-Through Rates, Workshop on Internet and Network Economics (WINE), Hong Kong, 2005.

CITED BY 2

	Vishal Midha, The Glitch in On-line Advertising: A Study of Click Fraud in Pay-Per-Click Advertising Programs, International Journal of Electronic Commerce, v.13 n.2, p.91-112, Number 2 / Winter 2008-9
	Vishal Midha, The Glitch in On-line Advertising: A Study of Click Fraud in Pay-Per-Click Advertising Programs, International Journal of Electronic Commerce, v.13 n.2, p.91-112, Number 2 / Winter 2008-9