9.13 Search Engine
(Guan and Cutrell 2007) found the Google golden triangle where people pay attention the the top 3 organic results and spill over to the fourth one (paid).
(E. J. Johnson et al. 2004) On the Depth and Dynamics of Online Search Behavior
Examination of search behavior across competing e-commerce sites
Study based on panel data from over 10,000 households and 3 products (books, CDs, air travel)
On average, households visit 1.2 book sites, 1.3 CD sites, and 1.8 travel sites per active month
Characterization of search behavior in terms of depth, dynamics, and activity
Search modeled as a logarithmic process, with limited search across few sites
Model allows for time-varying dynamics, with only mild evidence of decreasing search over time in one product category
Results suggest more-active online shoppers tend to search across more sites, driving the dynamics of search.
(Kulkarni, Kannan, and Moe 2012) Using online search data to forecast new product sales
Data on consumer search terms provides valuable measures and indicators of consumer interest
Can be useful to managers in gauging product interest in a new product launch or consumption interest post-release
Model of pre-launch search activity developed and linked to early sales
Model applied to motion picture industry and found to provide significant forecasting power for release week sales
Advertising data included in model increases explanatory and forecasting power
Managerial insights offered on how search volume data and the model can be used for new product release planning.