Marketing Papers
Document Type
Journal Article
Date of this Version
8-2002
Publication Source
Marketing Letters
Volume
13
Issue
3
Start Page
245
Last Page
258
DOI
10.1023/A:1020231107662
Abstract
The authors discuss research progress and future opportunities for modeling consumer choice on the Internet using clickstream data (the electronic records of Internet usage recorded by company web servers and syndicated data services). The authors compare the nature of Internet choice (as captured by clickstream data) with supermarket choice (as captured by UPC scanner panel data), highlighting the differences relevant to choice modelers. Though the application of choice models to clickstream data is relatively new, the authors review existing early work and provide a two-by-two categorization of the applications studied to date (delineating search versus purchase on the one hand and within-site versus across-site choices on the other). The paper offers directions for further research in these areas and discusses additional opportunities afforded by clickstream information, including personalization, data mining, automation, and customer valuation. Notwithstanding the numerous challenges associated with clickstream data research, the authors conclude that the detailed nature of the information tracked about Internet usage and e-commerce transactions presents an enormous opportunity for empirical modelers to enhance the understanding and prediction of choice behavior.
Copyright/Permission Statement
This is a pre-publication version. The final publication is available at Springer via http://dx.doi.org/10.1023/A:1020231107662
Keywords
Internet, choice models, clickstream data
Recommended Citation
Bucklin, R. E., Lattin, J. M., Ansari, A., Bell, D., Coupey, E., Little, J. D., Mela, C., Montgomery, A. L., & Steckel, J. (2002). Choice and the Internet: From Clickstream to Research Stream. Marketing Letters, 13 (3), 245-258. http://dx.doi.org/10.1023/A:1020231107662
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Behavioral Economics Commons, Business Administration, Management, and Operations Commons, Business Analytics Commons, Business Intelligence Commons, E-Commerce Commons, Marketing Commons, Technology and Innovation Commons
Date Posted: 15 June 2018
This document has been peer reviewed.