Authors: Weiguo Liu, Shi Zhong, Mayank Chaudhary, Shyam Kapur
Addresses: Strategic Data Solutions, Yahoo! Inc., 701 First Ave., Sunnyvale, CA 94089, USA. ' Pricing Science Group, Zilliant Inc., 3815 S Capital of Texas Hwy Ste 300, Austin, TX 78704, USA. ' 130 Red Cedar Lane, Union City, CA 94587, USA. ' TipTop Technologies, Inc., 1030 Heatherstone Way, Sunnyvale, CA 94087, USA
Abstract: Like any marketing campaigns, online advertisement campaigns need to be monitored, analysed and optimised. The quantitative methods are more crucial to online campaigns because of their dynamic pricing and highly interactive nature. Not only can marketing effectiveness be measured almost instantly in terms of measures such as click through rate and/or the acquisition/conversion rate, but a rich set of user data can also be collected and used by learning algorithms. The huge sets of dynamic data raise many challenging problems. In order to run a successful campaign, any serious advertiser, publisher or ad exchange network need a system that combines forecasting, data mining and optimisation techniques. In this paper, we propose such a methodology for a systematic analysis of the relevant problems and describe techniques that work on real world data as satisfactory solutions.
Keywords: internet marketing; online advertising; display ads; banner ads; ad networks; user targeting; forecasting; data mining; optimisation; internet advertising; adverts.
International Journal of Services Operations and Informatics, 2009 Vol.4 No.1, pp.3 - 15
Available online: 01 Dec 2008 *Full-text access for editors Access for subscribers Purchase this article Comment on this article