IDEAS home Printed from https://ideas.repec.org/a/inm/ormksc/v30y2011i3p389-404.html
   My bibliography  Save this article

Online Display Advertising: Targeting and Obtrusiveness

Author

Listed:
  • Avi Goldfarb

    () (Rotman School of Management, University of Toronto, Toronto, Ontario M5S 3E6, Canada)

  • Catherine Tucker

    () (MIT Sloan School of Management, Cambridge, Massachusetts 02142)

Abstract

We use data from a large-scale field experiment to explore what influences the effectiveness of online advertising. We find that matching an ad to website content and increasing an ad's obtrusiveness independently increase purchase intent. However, in combination, these two strategies are ineffective. Ads that match both website content and are obtrusive do worse at increasing purchase intent than ads that do only one or the other. This failure appears to be related to privacy concerns: the negative effect of combining targeting with obtrusiveness is strongest for people who refuse to give their income and for categories where privacy matters most. Our results suggest a possible explanation for the growing bifurcation in Internet advertising between highly targeted plain text ads and more visually striking but less targeted ads.

Suggested Citation

  • Avi Goldfarb & Catherine Tucker, 2011. "Online Display Advertising: Targeting and Obtrusiveness," Marketing Science, INFORMS, vol. 30(3), pages 389-404, 05-06.
  • Handle: RePEc:inm:ormksc:v:30:y:2011:i:3:p:389-404
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/mksc.1100.0583
    Download Restriction: no

    References listed on IDEAS

    as
    1. Campbell, Margaret C & Kirmani, Amna, 2000. " Consumers' Use of Persuasion Knowledge: The Effects of Accessibility and Cognitive Capacity on Perceptions of an Influence Agent," Journal of Consumer Research, Oxford University Press, vol. 27(1), pages 69-83, June.
    2. David Godes & Dina Mayzlin, 2009. "Firm-Created Word-of-Mouth Communication: Evidence from a Field Test," Marketing Science, INFORMS, vol. 28(4), pages 721-739, 07-08.
    3. Friestad, Marian & Wright, Peter, 1994. " The Persuasion Knowledge Model: How People Cope with Persuasion Attempts," Journal of Consumer Research, Oxford University Press, vol. 21(1), pages 1-31, June.
    4. Alessandro Acquisti & Hal R. Varian, 2005. "Conditioning Prices on Purchase History," Marketing Science, INFORMS, vol. 24(3), pages 367-381, May.
    5. Horrace, William C. & Oaxaca, Ronald L., 2006. "Results on the bias and inconsistency of ordinary least squares for the linear probability model," Economics Letters, Elsevier, vol. 90(3), pages 321-327, March.
    6. Morwitz, Vicki G. & Steckel, Joel H. & Gupta, Alok, 2007. "When do purchase intentions predict sales?," International Journal of Forecasting, Elsevier, vol. 23(3), pages 347-364.
    7. Patrali Chatterjee & Donna L. Hoffman & Thomas P. Novak, 2003. "Modeling the Clickstream: Implications for Web-Based Advertising Efforts," Marketing Science, INFORMS, vol. 22(4), pages 520-541, May.
    8. Anindya Ghose & Sha Yang, 2007. "An Empirical Analysis of Search Engine Advertising: Sponsored Search and Cross-Selling in Electronic Markets," Working Papers 07-35, NET Institute, revised Sep 2007.
    9. Russell, Cristel Antonia, 2002. " Investigating the Effectiveness of Product Placements in Television Shows: The Role of Modality and Plot Connection Congruence on Brand Memory and Attitude," Journal of Consumer Research, Oxford University Press, vol. 29(3), pages 306-318, December.
    10. Ai, Chunrong & Norton, Edward C., 2003. "Interaction terms in logit and probit models," Economics Letters, Elsevier, vol. 80(1), pages 123-129, July.
    11. James Levinsohn & Amil Petrin, 2003. "Estimating Production Functions Using Inputs to Control for Unobservables," Review of Economic Studies, Oxford University Press, vol. 70(2), pages 317-341.
    12. Avi Goldfarb & Catherine Tucker, 2011. "Search Engine Advertising: Channel Substitution When Pricing Ads to Context," Management Science, INFORMS, vol. 57(3), pages 458-470, March.
    13. Yuxin Chen & Chakravarthi Narasimhan & Z. John Zhang, 2001. "Individual Marketing with Imperfect Targetability," Marketing Science, INFORMS, vol. 20(1), pages 23-41, November.
    14. P. M. Bentler & Chih-Ping Chou, 1987. "Practical Issues in Structural Modeling," Sociological Methods & Research, , vol. 16(1), pages 78-117, August.
    15. Anindya Ghose & Sha Yang, 2009. "An Empirical Analysis of Search Engine Advertising: Sponsored Search in Electronic Markets," Management Science, INFORMS, vol. 55(10), pages 1605-1622, October.
    16. C. Clark & Ulrich Doraszelski & Michaela Draganska, 2009. "The effect of advertising on brand awareness and perceived quality: An empirical investigation using panel data," Quantitative Marketing and Economics (QME), Springer, vol. 7(2), pages 207-236, June.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    e-commerce; privacy; advertising; targeting;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:inm:ormksc:v:30:y:2011:i:3:p:389-404. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Mirko Janc). General contact details of provider: http://edirc.repec.org/data/inforea.html .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.