The User-journey in Online Search - An Empirical Study of the Generic-to-Branded Spillover Effect based on User-level Data

Florian Nottorf, Andreas Mastel, Burkhardt Funk

2012

Abstract

Traditional metrics in online advertising such as the click-through rate often take into account the users’ search activities separately and do not consider any interactions between them. In understanding online search behavior, this fact may favor a certain group of search type and, therefore, may mislead managers in allocating their financial spending efficiently. We analyzed a large query log for the occurrence of user-specific interaction patterns within and across three different industries (clothing, healthcare, hotel) and were able to show that users’ online search behavior is indeed a multi-stage process, whereas e.g. a product search for sneakers typically begins with general, often referred to as generic, keywords which becomes narrowed as it proceeds by including more specific, e.g. brand-related (“sneakers adidas”), keywords. Our method to analyze the development of users’ search process within query logs helps managers to identify the role of specific activities within a respective industry and to allocate their financial spending in paid search advertising accordingly.

References

  1. Abhishek, V., Hosanagar, K., and Fader, P. S. (2011). On aggregation bias in sponsored search data: Existence and implications.
  2. Agarwal, A., Hosanagar, K., and Smith, M. D. (2011). Location, location, location: An analysis of profitibality of position in online advertising markets. Journal of Marketing Research.
  3. Animesh, A., Viswanathan, S., and 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.
  4. Broder, A. (2002). A taxonomy of web search. SIGIR Forum, 36(2):3-10.
  5. Bucklin, R. E. and Sismeiro, C. (2009). Click here for internet insight: Advances in clickstream data analysis in marketing. Journal of Interactive Marketing, 23(1):35-48.
  6. Chan, T. Y., Xie, Y., and Wu, C. (2011). Measuring the lifetime value of customers acquired from google search advertising. Marketing Science.
  7. Ghose, A. and Yang, S. (2008). Comparing performance metrics in organic search with sponsored search advertising.
  8. Ghose, A. and Yang, S. (2009). An empirical analysis of search engine advertising: Sponsored search in electronic markets. Management Science, 55(10):1605- 1622.
  9. Ghose, A. and Yang, S. (2010). Modeling cross-category purchases in sponsored search advertising.
  10. Howard, J. A. and Sheth, J. N. (1968). A theory of buyer behavior. Rivista internazionale di scienze economiche e commerciali, 15(6):589-618.
  11. Interbrand & Business Week (2006). Interbrand's best global brands 2006.
  12. Janiszewski, C. (1998). The influence of display characteristics on visual exploratory search behavior. Journal of Consumer Research, 25(3):290-301.
  13. Jansen, B. J. and Mullen, T. (2008). Sponsored search: an overview of the concept, history, and technology. International Journal of Electronic Business, 6(2):114- 131.
  14. Jansen, B. J. and Spink, A. (2007). The effect on clickthrough of combining sponsored and non-sponsored search engine results in a single listing. Proc. 2007 Workshop on Sponsored Search Auctions, Banff, AB, Canada.
  15. Johnson, E. J., Moe, W. W., Fader, P. S., Bellman, S., and Lohse, G. L. (2004). On the depth and dynamics of online search behavior. Management Science, 50(3):299-308.
  16. Moe, W. W. (2003). Buying, searching, or browsing: Differentiating between online shoppers using in-store navigational clickstream. Journal of Consumer Psychology, 13(1-2):29-39.
  17. Narayana, C. L. and Markin, R. J. (1975). Consumer behavior and product performance: An alternative conceptualization. The Journal of Marketing, 39(4):1-6.
  18. Pass, G., Chowdhury, A., and Torgeson, C. (2006). A picture of search. In Proceedings of the 1st international conference on Scalable information systems, InfoScale 7806, New York, NY, USA. ACM.
  19. Rutz, O. J. and Bucklin, R. E. (2011). From generic to branded: A model of spillover in paid search advertising. Journal of Marketing Research, 48(1):87-102.
  20. Rutz, O. J., Trusov, M., and Bucklin, R. E. (2011). Modeling indirect effects of paid search advertising: Which keywords lead to more future visits? Marketing Science, 30:646-665.
  21. Search Engine Watch (2006). Delving deep inside the searcher's mind. http://searchenginewatch.com/3406911.
  22. Yang, S. and Ghose, A. (2010). Analyzing the relationship between organic and sponsored search advertising: Positive, negative, or zero interdependence? Marketing Science, 29(4):602-623.
Download


Paper Citation


in Harvard Style

Nottorf F., Mastel A. and Funk B. (2012). The User-journey in Online Search - An Empirical Study of the Generic-to-Branded Spillover Effect based on User-level Data . In Proceedings of the International Conference on Data Communication Networking, e-Business and Optical Communication Systems - Volume 1: ICE-B, (ICETE 2012) ISBN 978-989-8565-23-5, pages 145-154. DOI: 10.5220/0004052101450154


in Bibtex Style

@conference{ice-b12,
author={Florian Nottorf and Andreas Mastel and Burkhardt Funk},
title={The User-journey in Online Search - An Empirical Study of the Generic-to-Branded Spillover Effect based on User-level Data},
booktitle={Proceedings of the International Conference on Data Communication Networking, e-Business and Optical Communication Systems - Volume 1: ICE-B, (ICETE 2012)},
year={2012},
pages={145-154},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004052101450154},
isbn={978-989-8565-23-5},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Data Communication Networking, e-Business and Optical Communication Systems - Volume 1: ICE-B, (ICETE 2012)
TI - The User-journey in Online Search - An Empirical Study of the Generic-to-Branded Spillover Effect based on User-level Data
SN - 978-989-8565-23-5
AU - Nottorf F.
AU - Mastel A.
AU - Funk B.
PY - 2012
SP - 145
EP - 154
DO - 10.5220/0004052101450154