Cost-Per-Action 광고 방법을 이용한 Conversion Action Data 메커니즘의 평가

Evaluation of Conversion Action Data Mechanisms in Cost- Per-Action Advertising

  • 이첨 (경희대학교 경영대학 & 경영연구원) ;
  • 이경전 (경희대학교 경영대학)
  • Li, Tian (School of Business Adminstration and Management Research Institute, Kyung Hee University) ;
  • Lee, Kyoung-Jun (School of Business Adminstration and Management Research Institute, Kyung Hee University)
  • 발행 : 2008.08.31

초록

온라인 광고모델의 기본 모델은 CPM (cost-per-mille) 기반 모델에서 CPC (cost-per-click) 기반 모델로 변화해왔으며, CPA (cost-per-action) 모델이 온라인 광고산업의 새로운 대안 모델로 제시되고 있다. CPA 모델에서는 사용자가 어떤 광고를 클릭 했는지에 관한 정보를 퍼블리셔(Publisher)가 보유할 수 있어야 하며, 그래서, CPA 모델의 핵심은 Conversation Action Data를 확보하는 것이다. 이 논문에서는 이를 획득하는 두 가지 기존 메커니즘을 소개하고, 이들의 특징을 비교하고, 각 메커니즘의 한계를 분석한다. 그 다음에 두 가지 새로운 메커니즘을 설계하고, 작동 요건을 분석하고, 실용성을 평가한다. 마지막으로, 기존의 메커니즘들과 새로운 메커니즘들의 특징을 비교하고, 각 메커니즘의 비즈니스 가치와 유용성, 응용 범위를 분석한다. 이 논문에서 제안된 2가지의 새로운 메커니즘과 기존 메커니즘과 비교 분석을 통해 퍼블리셔에게 최적 CPA 메커니즘에 관한 판단정보를 제공할 수 있을 것으로 판단된다.

The online advertising industry's business model undertakes the change from CPM (cost-per-mille)-based to CPC(cost-per-click)-based. However, due to the problem of 'Click Fraud', CPA (cost-per-action) has been regarded as a new step. For CPA, publishers need to get information after a user clicks an advertisement. Therefore, in CPA, the key is to get Conversion Action Data (CAD). This paper introduces two existing mechanisms for getting CAD, compare their characteristics, and analyze their limitations. Then the two new mechanisms are introduced and their requirements and feasibility are analyzed. Lastly, we compare the existing two and the new two mechanisms, and point out each mechanism's business possibility, value and Application Area. This paper will help publishers choose the most appropriate mechanism on the basis of their situation.

키워드

참고문헌

  1. Crawford, K., "Fraud a Big Threat", CNN/Money, 2004/12/02 http://money.cnn.com/2004/12/02/technology/google_fraud/
  2. Penenberg, A., "Click fraud threatens web", Wired News, 2004/10/13
  3. Stone, B., "When mice attack: Internet scammers steal money with `click fraud'", Newsweek, 2005/1/24
  4. Tuzhilin, A., "The Lane's Gifts v. Google Report", http://googleblog.blogspot.com/pdf/Tuzhilin_Report. pdf, 2006, pp. 07-13
  5. Mahdian, M. and K. Tomak, "Pay-per-action model for online advertising", In Proceedings of the 1st international workshop on Data mining and audience intelligence for advertising Conference on Knowledge Discovery in Data (ADKDD 2007), 2007, pp. 04-07
  6. Immorlica, N., K. Jain, M. Mahdian, and Talwar, "Click Fraud Resistant Methods for Learning Click-Through Rates", Lecture Notes in Computer Science, Vol.3828, 2005. pp. 34-45
  7. Timmers, P., "Business Model for Electronic Markets", Electronic Markets, Vol.8, No.2, 1998. pp. 03-08
  8. Charlene L. and S. VanBoskirk. "US Online Marketing Forecast 2005 to 2010", Forrester Research, 2005/5/12
  9. Nazerzadeh, H., A. Saberi, and R. Vohra, "Dynamic Cost-Per-Action Mechanisms and Applications to Online Advertising", In Discussion Papers from Northwestern University, Center for Mathematical Studies in Economics and Management Science, No.1450, 2007, pp. 01-04
  10. Shin, B., "Research in IT Business Model Assessment: Current Status and Future Prospects in Assumption Analysis", 2006 Spring proceedings of the KMIS, 2006
  11. Dewar, J., "Assumption-based Planning, A Tool for Reducing Avoidable Surprises", Cambridge University Press, ISBN: 0521001269, 2002. pp. 64-87