TY  - CONF
ID  - www200927
UR  - http://www2009.eprints.org/27/
A1  - Yan, Jun
A1  - Liu, Ning
A1  - Wang, Gang
A1  - Zhang, Wen
A1  - Jiang, Yun
A1  - Chen, Zheng
Y1  - 2009/04//
N2  - Behavioral Targeting (BT) is a technique used by online
advertisers to increase the effectiveness of their campaigns, and is
playing an increasingly important role in the online advertising
market. However, it is underexplored in academia how much BT
can truly help online advertising in search engines. In this paper
we provide an empirical study on the click-through log of
advertisements collected from a commercial search engine. From
the experiment results over a period of seven days, we draw three
important conclusions: (1) Users who clicked the same ad will
truly have similar behaviors on the Web; (2) Click-Through Rate
(CTR) of an ad can be averagely improved as high as 670% by
properly segmenting users for behavioral targeted advertising in a
sponsored search; (3) Using short term user behaviors to represent
users is more effective than using long term user behaviors for BT.
We conducted statistical t-test which verified that all conclusions
drawn in the paper are statistically significant. To the best of our
knowledge, this work is the first empirical study for BT on the
click-through log of real world ads.

TI  - How Much Can Behavioral Targeting Help Online Advertising?
SP  - 261
M2  - Madrid, Spain
AV  - public
EP  - 261
T2  - 18th International World Wide Web Conference
ER  -