A Study of First Click Behaviour and User Interaction on the Google SERP

Conference paper


Firms use Search Engine Marketing (SEM) to drive users to their Website. Some are prepared to pay for placement; others use Search Engine Optimization (SEO) hoping their result percolates up the organic SERP. Despite extensive SEM efforts, firms can only speculate over the first critical interaction between the first SERP and a user’s first click. This study sheds some light on users’ first click behaviour on Google and the early interaction thereafter. The research reveals that users evaluate the SERP from the top downwards, deciding instantly whether to click into each link, while first clicks are predominantly at the top of the SERP, especially towards organic links. For certain queries top sponsored links received almost as many clicks as organic links despite what users profess. Recommendations to firms include advice that strategies should be primarily SEO focused and that paid search campaigns should maintain a position in the top sponsored links section of the Google SERP.


Information Systems Website Design Search Engine Optimization Search Engine Marketing Link Assessment Strategy 


  1. Argyris C (1980) Inner contradictions of rigorous research. Academic Press, New YorkGoogle Scholar
  2. Bar-Ilan J (2007) Manipulating search engine algorithms: the case of Google. J Inf Commun Ethics Soc 5(2/3):155–166CrossRefGoogle Scholar
  3. Bar-Ilan J, Levene M, Mat-Hassan M (2006) Methods for evaluating dynamic changes in search engine rankings: a case study. J Doc 62(6):708–729CrossRefGoogle Scholar
  4. Barry C, Charleton D (2008) Researching search—a study into search engine marketing practices in Ireland. In: Proceedings of the international conference on e-business, Porto, Portugal. 26–29 July 2008 (CD-ROM)Google Scholar
  5. Browne GJ, Pitts MG, Wetherbe JC (2007) Cognitive stopping rules for terminating information search in online tasks. MIS Q 31(1):89–104CrossRefGoogle Scholar
  6. Cho J, Roy S (2004) Impact of search engines on page popularity. In: Proceedings of the 13th international world wide web conference, 17–20 May 2004. ACM Press, New York, pp 20–29Google Scholar
  7. Ciaramita M, Murdock V, Plachouras V (2008) Online learning from click data for sponsored search. In: Proceedings of world wide web conference, Beijing, China, 17–22 May 2008. ACM Press, New York, pp 227–236Google Scholar
  8. Crutcher R (1994) Telling what we know: the use of verbal report methodologies in psychological research. Psychol Sci 5(5):241–244CrossRefGoogle Scholar
  9. Hochstotter N, Lewandowski D (2009) What users see—structures in search engine results pages. Inf Sci 179(12):1796–1812CrossRefGoogle Scholar
  10. Hotchkiss G, Garrison M, Jensen S (2004) Search engine usage in North America. Accessed Dec 2008Google Scholar
  11. iProspect (2008) Search engine marketing research: iProspect blended search results study. Accessed June 2009Google Scholar
  12. Jansen BJ, Resnick M (2005) Examining searcher perceptions of and interactions with sponsored results. In: The workshop on sponsored search auctions at ACM conference on electronic commerce (EC’05), 5–8 June, Vancouver, BC, Canada, pp 1–8Google Scholar
  13. Jansen BJ, Molina PR (2006) The effectiveness of web search engines for retrieving relevant ecommerce links. Inf Process Manage 42:1075–1098CrossRefGoogle Scholar
  14. Jansen BJ, Brown A, Resnick M (2007) Factors relating to the decision to click-on a sponsored link. Decision Support Syst 44(1):46–59CrossRefGoogle Scholar
  15. Jansen BJ, Booth DL, Spink A (2008) Determining the informational, navigational, and transactional intent of web queries. Inf Process Manage 44:1251–1266CrossRefGoogle Scholar
  16. Joachims T, Granka L, Pan B, Hembrooke H, Gay G (2005) Accurately interpreting clickthrough data as implicit feedback. In: Proceedings of the 28th international conference on research and development in information retrieval, Salvador, Brazil, 15–19 August, SIGIR’05, ACM Press, New York, pp 154–161Google Scholar
  17. Jones R (2008) SEO site structure 101. Accessed 22 Dec 2008Google Scholar
  18. Keane MT, O’Brien M, Smyth B (2008) Are people biased in their use of search engines? 379 Commun ACM 51:49–52CrossRefGoogle Scholar
  19. Klöckner K, Wirschum N, Jameson A (2004) Depth and breadth-first processing of search results list. In: CHI’04 extended abstracts on human factors in computing systems, Vienna, Austria, 24–29 April. ACM Press, New York, pp 1539–1539Google Scholar
  20. Laffey D (2007) Paid search: the innovation that changed the web. Bus Horizons, 50:211–218CrossRefGoogle Scholar
  21. Lewandowski D (2008) The retrieval effectiveness of web search engines. Considering results descriptions. J Doc 64(6):915–937CrossRefGoogle Scholar
  22. Marable L (2003) False oracles: consumer reaction to learning the truth about how search engines work, results of an ethnographic study, Research Report. Consumer WebWatch, YonkersGoogle Scholar
  23. O’Brien M, Keane M (2006) Modelling result—list searching in the world wide web: the role of relevance topologies and trust bias. In proceedings of the 28th annual conference of the cognitive science society, Vancouver, Canada, 26–29 July, pp 1881–1886Google Scholar
  24. O’Brien M, Keane MT, Smyth B (2006) Predictive modelling of first-click behaviour in web-search. In: Proceedings of the 15th international conference on world wide web, Edinburgh, Scotland, 23–26 May, ACM Press, New York, pp 1031–1032Google Scholar
  25. Richardson M, Dominowska E, Ragno R (2007) Predicting clicks: estimating the click-through rate for new ads. In: Proceedings of the 16th international conference on world wide web, Banff, AB, Canada, 8–12 May, ACM Press, New York, pp 521–530Google Scholar
  26. Rose DE, Levinson D (2004) Understanding user goals in web search. In proceedings of the 13th international conference on the world wide web, New York, NY, USA, 17–20 May, ACM, pp 13–19Google Scholar
  27. Szetela D (2008) PPC landing pages: PPC visitors have ADD. Accessed 19 Dec 2008Google Scholar
  28. Todd M (2006) Getting high traffic from search engines is wasted on poor sites. New Media Age, Accessed 29 June 2008Google Scholar
  29. Van Waes L (1998) Evaluating on-line and off-line searching behavior using thinking-aloud protocols to detect navigation barriers. In: Proceedings of the 16th annual international conference on computer documentation, Quebec, September 1998, pp 180–183Google Scholar
  30. Zhang Y, Jansen BJ, Spink A (2009) Time series analysis of a web search engine transaction log. Inf Process Manage 45(2):230–245CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  1. 1.National University of IrelandGalwayIreland

Personalised recommendations