Managing the quality of cost-per-click traffic
Abstract/Contents
- Abstract
- Traffic quality is critical to the security and viability of an online advertising network's business. As such, how might an advertising network detect and avoid paying for low-quality traffic? The online advertising market can be modeled as a large, multiplayer game with three classes of players: publishers, advertisers and advertising networks. We focus on cost-per-click (CPC) traffic, and identify two distinct-but-related aspects of click quality: validity and targetedness. Validity refers to whether a click-through is legitimate, whereas targetedness refers to the likelihood that valid clicks become conversions. We study three techniques that influence traffic quality on a network, namely filtering, predictive pricing and revenue sharing. We begin by asking whether it is in an advertising network's interest to filter (i.e., ensure traffic validity) in the first place. This question has been a topic of intense debate in the industry. Our analysis shows definitively that networks do, indeed, have a strong incentive to aggressively filter out invalid traffic. We then consider how a network might use predictive pricing and revenue sharing to attract targeted, high-conversion-rate traffic. We show that effective usage of predictive pricing can yield a competitive edge for a network, and that targetedness has a quantifiable impact on profits. Finally, we study how validity and targetedness can be managed together. What is the relation between filtering, predictive pricing and revenue sharing? We derive efficient, tractable algorithms for computing near-optimal traffic management policies, and also propose strategies to combat publisher click inflation. Perhaps the most important lessons learned from our work are that a) in the online advertising business, traffic quality has a direct impact on profits, and b) traffic quality is often more important than quantity.
Description
| Type of resource | text |
|---|---|
| Form | electronic; electronic resource; remote |
| Extent | 1 online resource. |
| Copyright date | 2011 |
| Publication date | 2010, c2011; 2010 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Associated with | Mungamuru, Lakshmi Nrisimha Bob |
|---|---|
| Associated with | Stanford University, Department of Electrical Engineering |
| Primary advisor | Garcia-Molina, Hector |
| Thesis advisor | Garcia-Molina, Hector |
| Thesis advisor | Saberi, Amin |
| Thesis advisor | Ullman, Jeffrey D, 1942- |
| Advisor | Saberi, Amin |
| Advisor | Ullman, Jeffrey D, 1942- |
Subjects
| Genre | Theses |
|---|
Bibliographic information
| Statement of responsibility | Bobji Mungamuru. |
|---|---|
| Note | Submitted to the Department of Electrical Engineering. |
| Thesis | Thesis (Ph.D.)--Stanford University, 2011. |
| Location | electronic resource |
Access conditions
- Copyright
- © 2011 by Lakshmi Nrisimha Bob Mungamuru
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
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