Skip to main content
SpringerLink
Log in

The impact of ad positioning in search engine advertising: a multifaceted decision problem

  • Published:
Electronic Commerce Research Aims and scope Submit manuscript

Abstract

A general desire in search engine advertising is to rank at the topmost position for maximum attention. Based on a search engine advertising campaign, this study provides empirical evidence that this approach does not necessarily maximize sales. The analysis reveals relationships that result in a non-linear rank profitability. As a consequence, advertisers face the multifaceted decision problem of identifying the optimal rank for their search engine advertisements. The outcome of the advertising activity is determined by three dimensions: the number of prospects (quantity), their acquisition costs (price), and their quality, i.e. is the likelihood to result in sales revenue. The results also differ if evaluated on campaign or keyword level. Consequently, research and practice have to consider the effect of a non-monotone rank profitability in search engine advertising, which has been neglected in previous studies. Furthermore, the differences on campaign and keyword level affect the evaluation and corresponding decisions when managing search engine advertising.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

Notes

  1. Keyword performance refers to key performance indicators based on a keyword level. Examples are click-through rate, cost per click, conversion rate, and cost/return per conversion.

References

  1. Abou Nabout, N. (2015). A novel approach for bidding on keywords in newly set-up search advertising campaigns. European Journal of Marketing, 49(5/6), 668–691.

    Google Scholar 

  2. Abrams, Z., Ghosh, A., & Vee, E. (2007). Cost of conciseness in sponsored search auctions. In Third workshop on sponsored search auctions. International world wide web conference (WWW2007), Banff, Canada.

  3. Agarwal, A., Hosanagar, K., & Smith, M. D. (2011). Location, location, location: An analysis of profitability of position in online advertising markets. Journal of Marketing Research, 48(6), 1057–1073.

    Google Scholar 

  4. Agarwal, A., Hosanagar, K., & Smith, M. D. (2015). Do organic results help or hurt sponsored search performance? Information Systems Research, 26(4), 695–713.

    Google Scholar 

  5. Agarwal, A., & Mukhopadhyay, T. (2016). The impact of competing ads on click performance in sponsored search. Information Systems Research, 27(3), 538–557.

    Google Scholar 

  6. Amaldoss, W., Jerath, K., & Sayedi, A. (2016). Keyword management costs and “broad match” in sponsored search advertising. Marketing Science, 35(2), 259–274.

    Google Scholar 

  7. Animesh, A., Viswanathan, S., & Agarwal, R. (2011). Competing “creatively” in sponsored search markets: The effect of rank, differentiation strategy, and competition on performance. Information Systems Research, 22(1), 153–169.

    Google Scholar 

  8. Ayanso, A., & Karimi, A. (2015). The moderating effects of keyword competition on the determinants of ad position in sponsored search advertising. Decision Support Systems, 70(1), 42–59.

    Google Scholar 

  9. Balachander, S., Kannan, K., & Schwartz, D. G. (2009). A theoretical and empirical analysis of alternate auction policies for search advertisements. Review of Marketing Science, 7(1), 1–49.

    Google Scholar 

  10. Bremer, V., & Funk, B. (2017). Analysing clickstream data: Do paid and organic search affect each other? International Journal of Electronic Business, 13(2/3), 205–215.

    Google Scholar 

  11. Broder, A. (2002). A taxonomy of web search. ACM SIGIR Forum, 36(2), 3–10.

    Google Scholar 

  12. Chan, T. Y., & Park, Y.-H. (2015). Consumer search activities and the value of ad positions in sponsored search advertising. Marketing Science, 34(4), 606–623.

    Google Scholar 

  13. Chandrasekaran, D., Srinivasan, R., & Sihi, D. (2018). Effects of offline ad content on online brand search: Insights from super bowl advertising. Journal of the Academy of Marketing Science, 46(3), 403–430.

    Google Scholar 

  14. Chen, J., Feng, J., & Whinston, A. B. (2009). Keyword auctions, unit-price contracts, and the role of commitment. Production and Operations Management, 19(3), 305–321.

    Google Scholar 

  15. Chen, Y., Xue, G.-R., & Yu, Y. (2008). Advertising keyword suggestion based on concept hierarchy. In Proceedings of the international conference on web search and web data mining (pp. 251–260). Palo Alto, CA: ACM.

  16. Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale, NJ: Erlbaum.

    Google Scholar 

  17. Dou, W., Lim, K. H., Su, C., Zhou, N., & Cui, N. (2010). Brand positioning strategy using search engine marketing. MIS Quarterly, 34(2), 261–279.

    Google Scholar 

  18. Du, X., Su, M., Zhang, X., & Zheng, X. (2017). Bidding for multiple keywords in sponsored search advertising: Keyword categories and match types. Information Systems Research, 28(4), 711–722.

    Google Scholar 

  19. Edelman, B., Ostrovsky, M., & Schwarz, M. (2007). Internet advertising and the generalized second-price auction: Selling billions of dollars worth of keywords. The American Economic Review, 97(1), 242–259.

    Google Scholar 

  20. Even-Dar, E., Feldman, J., Muthukrishnan, S., & Mansour, Y. (2008). Position auctions with bidder-specific minimum prices. In Fourth workshop on ad auctions. Conference on electronic commerce (EC08), Chicago, Illinois, USA.

  21. Feng, J. (2008). Optimal mechanism for selling a set of commonly ranked objects. Marketing Science, 27(3), 501–512.

    Google Scholar 

  22. Feng, J., Bhargava, H. K., & Pennock, D. M. (2007). Implementing sponsored search in web search engines: Computational evaluation of alternative mechanisms. INFORMS Journal on Computing, 19(1), 137–148.

    Google Scholar 

  23. Ganchev, K., Kulesza, A., Tan, J., Gabbard, R., Liu, Q., & Kearns, M. (2007). Empirical price modeling for sponsored search. In Third workshop on sponsored search auctions, International world wide web conference (WWW2007), Banff, Canada.

  24. Ghose, A., & Yang, S. (2009). An empirical analysis of search engine advertising: Sponsored search in electronic markets. Management Science, 55(10), 1605–1622.

    Google Scholar 

  25. Glick, M., Richards, G., Sapozhnikov, M., & Seabright, P. (2014). How does ranking affect user choice in online search? Review of Industrial Organization, 45(2), 99–119.

    Google Scholar 

  26. Gomes, R., Immorlica, N., & Markakis, V. (2009). Externalities in keyword auctions: An empirical and theoretical assessment. In Fifth workshop on ad auctions. Conference on electronic commerce (EC09), Stanford, California, USA.

  27. Graepel, T., Candela, J. Q., Borchert, T., & Herbrich, R. (2010). Web-scale Bayesian click-through rate prediction for sponsored search advertising in Microsoft’s bing search engine. In Proceedings of the 27th international conference on international conference on machine learning, Haifa, Israel.

  28. Huang, H., & Kauffman, R. J. (2011). On the design of sponsored keyword advertising slot auctions: An analysis of a generalized second-price auction approach. Electronic Commerce Research and Applications, 10(2), 194–202.

    Google Scholar 

  29. IAB. (2018). IAB internet advertising revenue report—2017 full year results. https://www.iab.com/wp-content/uploads/2018/05/IAB-2017-Full-Year-Internet-Advertising-Revenue-Report.REV2_.pdf. Accessed June 20, 2018.

  30. Jansen, B. J., Booth, D. L., & Spink, A. (2008). Determining the informational, navigational, and transactional intent of Web queries. Information Processing and Management, 44(3), 1251–1266.

    Google Scholar 

  31. Jansen, B. J., Brown, A., & Resnick, M. (2007). Factors relating to the decision to click on a sponsored link. Decision Support Systems, 44(1), 46–59.

    Google Scholar 

  32. Jansen, B. J., & Clarke, T. B. (2017). Conversion potential: A metric for evaluating search engine advertising performance. Journal of Research in Interactive Marketing, 11(2), 142–159.

    Google Scholar 

  33. Jansen, B. J., Liu, Z., & Simon, Z. (2013). The effect of ad rank on the performance of keyword advertising campaigns. Journal of the American Society for Information Science and Technology, 64(10), 2115–2132.

    Google Scholar 

  34. Jansen, B. J., & Spink, A. (2006). How are we searching the World Wide Web? A comparison of nine search engine transaction logs. Information Processing and Management, 42(1), 248–263.

    Google Scholar 

  35. Jansen, B. J., Spink, A., Blakely, C., & Koshman, S. (2007). Defining a session on Web search engines. Journal of the American Society for Information Science and Technology, 58(6), 862–871.

    Google Scholar 

  36. Jerath, K., Ma, L., & Park, Y.-H. (2014). Consumer click behavior at a search engine: The role of keyword popularity. Journal of Marketing Research, 51(4), 480–486.

    Google Scholar 

  37. Jerath, K., Ma, L., Park, Y.-H., & Srinivasan, K. (2011). A “position paradox” in sponsored search auctions. Marketing Science, 30(4), 612–627.

    Google Scholar 

  38. Jeziorski, P., & Moorthy, S. (2018). Advertiser prominence effects in search advertising. Management Science, 64(3), 1365–1383.

    Google Scholar 

  39. Joachims, T., Granka, L., Pan, B., Hembrooke, H., Radlinski, F., & Gay, G. (2007). Evaluating the accuracy of implicit feedback from clicks and query reformulations in web search. ACM Transactions on Information Systems, 25(2), 7.

    Google Scholar 

  40. Johnson, E. J., Moe, W. W., Fader, P. S., Bellman, S., & Lohse, G. L. (2004). On the depth and dynamics of online search behavior. Management Science, 50(3), 299–308.

    Google Scholar 

  41. Joo, M., Wilbur, K. C., & Zhu, Y. (2016). Effects of TV advertising on keyword search. International Journal of Research in Marketing, 33(3), 508–523.

    Google Scholar 

  42. Kapoor, K. K., Dwivedi, Y. K., & Piercy, N. C. (2016). Pay-per-click advertising: A literature review. The Marketing Review, 16(2), 183–202.

    Google Scholar 

  43. Kempe, D., & Mahdian, M. A. (2008). Cascade model for externalities in sponsored search. In Fourth workshop on ad auctions. Conference on electronic commerce (EC08), Chicago, Illinois, USA.

  44. Kitts, B., & Leblanc, B. (2004). Optimal bidding on keyword auctions. Electronic Markets, 14(3), 186–201.

    Google Scholar 

  45. Klapdor, S., Anderl, E. M., von Wangenheim, F., & Schumann, J. H. (2014). Finding the right words: The influence of keyword characteristics on performance of paid search campaigns. Journal of Interactive Marketing, 28(4), 285–301.

    Google Scholar 

  46. Kshetri, N. (2010). The economics of click fraud. IEEE Security and Privacy, 8(3), 45–53.

    Google Scholar 

  47. Lahaie, S., & Pennock, D. M. (2007). Revenue analysis of a family of ranking rules for keyword auctions. In Proceedings of the 8th ACM conference on electronic commerce, San Diego, California, USA.

  48. Laurent, G., & Kapferer, J.-N. (1985). Measuring consumer involvement profiles. Journal of Marketing Research, 22(1), 41–53.

    Google Scholar 

  49. Liu, D., Chen, J., & Whinston, A. B. (2010). Ex ante information and the design of keyword auctions. Information Systems Research, 21(1), 133–153.

    Google Scholar 

  50. Lewandowski, D. (2006). Query types and search topics of German Web search engine users. Information Services & Use, 26(4), 261–269.

    Google Scholar 

  51. Lu, S., & Yang, S. (2017). Investigating the spillover effect of keyword market entry in sponsored search advertising. Marketing Science, 36(6), 976–998.

    Google Scholar 

  52. Michaelidou, N., & Dibb, S. (2008). Consumer involvement: A new perspective. Marketing Review, 8(1), 83–99.

    Google Scholar 

  53. Muehling, D. D., Laczniak, R. N., & Andrews, J. C. (1993). Defining, operationalizing, and using involvement in advertising research: A review. Journal of Current Issues & Research in Advertising, 15(1), 21–57.

    Google Scholar 

  54. Naldi, M., D’Acquisto, G., & Italiano, G. F. (2010). The value of location in keyword auctions. Electronic Commerce Research and Applications, 9(2), 160–170.

    Google Scholar 

  55. Nettleton, D., Calderón-Benavides, L., & Baeza-Yates, R. (2006). Analysis of web search engine query sessions. In Knowledge discovery on the web (WebKDD 2006), workshop on web mining and web usage analysis, held in conjunction with the 12th ACM SIGKDD international conference on knowledge discovery and data mining (KDD 2006), Philadelphia, Pennsylvania, USA.

  56. Olbrich, R., & Schultz, C. D. (2014). Multichannel advertising: Does print advertising affect search engine advertising? European Journal of Marketing, 48(9/10), 1731–1756.

    Google Scholar 

  57. Park, C. H., & Agarwal, M. K. (2018). The order effect of advertisers on consumer search behavior in sponsored search markets. Journal of Business Research, 84, 24–33.

    Google Scholar 

  58. Qiao, D., Zhang, J., Wei, Q., & Chen, G. (2017). Finding competitive keywords from query logs to enhance search engine advertising. Information & Management, 54(4), 531–543.

    Google Scholar 

  59. Regelson, M., & Fain, D. C. (2006). Predicting click-through rate using keyword clusters. In Second workshop on sponsored search auctions. ACM conference on electronic commerce (EC’06), Ann Arbor, Michigan, USA.

  60. Rose, D. E., & Levinson, D. (2004). Understanding user goals in web search. In Proceedings of the 13th international conference on World Wide Web (pp. 13–19). New York, NY: ACM.

  61. Rutz, O. J., Bucklin, R. E., & Sonnier, G. P. (2012). A latent instrumental variables approach to modeling keyword conversion in paid search advertising. Journal of Marketing Research, 49(3), 306–319.

    Google Scholar 

  62. Schultz, C. D. (2016). An overview of search engine advertising research. In I. Lee (Ed.), Encyclopedia of E-commerce development, implementation, and management (pp. 310–328). Hershey, PA: IGI Global.

    Google Scholar 

  63. Schultz, C. D. (2016). Do web site visitors vary in their search and surf behavior. In I. Lee (Ed.), Encyclopedia of E-commerce development, implementation, and management (pp. 1582–1592). Hershey, PA: IGI Global.

    Google Scholar 

  64. Schultz, C. D. (2013). Ranking for the top: A misconception of search engine advertisers. In J. Järveläinen, H. Li, A.-M. Tuikka, & T. Kuusela (Eds.), Co-created effective, agile, and trusted eServices (pp. 15–25). Berlin: Springer.

    Google Scholar 

  65. Selçuk, B., & Özlük, Ö. (2013). Optimal keyword bidding in search-based advertising with target exposure levels. European Journal of Operational Research, 226(1), 163–172.

    Google Scholar 

  66. Shannon, C. E. (1948). A mathematical theory of communication. Bell System Technical Journal, 27(4), 623–656.

    Google Scholar 

  67. Shannon, C. E., & Weaver, W. (1949). The mathematical theory of communication. Urbana, IL: The University of Illinois Press.

    Google Scholar 

  68. Skiera, B., & Abou Nabout, N. (2013). Practice prize paper—PROSAD: A bidding decision support system for profit optimizing search engine advertising. Marketing Science, 32(2), 213–220.

    Google Scholar 

  69. Varian, H. R. (2006). Position auctions. International Journal of Industrial Organization, 25(6), 1163–1178.

    Google Scholar 

  70. Wiesel, T., Pauwels, K., & Arts, J. (2011). Marketing’s profit impact: Quantifying online and off-line funnel progression. Marketing Science, 30(4), 604–611.

    Google Scholar 

  71. Wilbur, K. C., & Zhu, Y. (2009). Click fraud. Marketing Science, 28(2), 293–308.

    Google Scholar 

  72. Xu, L., Chen, J., & Whinston, A. (2011). Price competition and endogenous valuation in search advertising. Journal of Marketing Research, 48(3), 566–586.

    Google Scholar 

  73. Yang, S., & Ghose, A. (2010). Analyzing the relationship between organic and sponsored search advertising: Positive, negative, or zero interdependence? Marketing Science, 29(4), 585–601.

    Google Scholar 

  74. Yao, S., & Mela, C. F. A. (2011). Dynamic model of sponsored search advertising. Marketing Science, 30(3), 447–468.

    Google Scholar 

  75. Yoo, C. Y. (2014). Branding potentials of keyword search ads: The effects of ad rankings on brand recognition and evaluations. Journal of Advertising, 43(1), 85–99.

    Google Scholar 

  76. Zaichkowsky, J. L. (1985). Measuring the involvement construct. Journal of Consumer Research, 12(3), 341–352.

    Google Scholar 

Download references

Acknowledgements

The author would like to express his gratitude to the service company for providing the dataset and thanks participants at the 15th International Conference on Electronic Commerce [64] for discussions and comments on an earlier version. The author also thanks the anonymous reviewers for their valuable comments and suggestions.

Author information

Authors and Affiliations

  1. University of Hagen, Universitätsstraße 11, 58097, Hagen, Germany

    Carsten D. Schultz

Authors
  1. Carsten D. Schultz
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Carsten D. Schultz.

Ethics declarations

Conflict of interest

The author states that there is no conflict of interest.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Schultz, C.D. The impact of ad positioning in search engine advertising: a multifaceted decision problem. Electron Commer Res 20, 945–968 (2020). https://doi.org/10.1007/s10660-018-9313-z

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10660-018-9313-z

Keywords

Search

Navigation