This item is a Paper in the Internet Monetization track.
- Yan, Jun - Microsoft Research Asia
- Liu, Ning - Microsoft Research Asia
- Wang, Gang - Microsoft Research Asia
- Zhang, Wen - University of Science & Technology
- Jiang, Yun - ShangHai Jiao Tong University
- Chen, Zheng - Microsoft Research Asia
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.
Export Record As...
- HTML Citation
- ASCII Citation
- Resource Map
- OpenURL ContextObject
- OpenURL ContextObject in Span
- EP3 XML
- Dublin Core
- Reference Manager
- Eprints Application Profile
- Simple Metadata