Estimating Search with Learning

Networks, the Internet, and Cloud Computing, Internet and Search and Advertising

Article Snapshot

Author(s)

Sergei Koulayev

Source

NET Institute Working Paper #08-29, 2008

Summary

This paper analyzes the different types of searching consumers go through before buying a product.

Policy Relevance

With an adequate understanding of consumer search behavior, businesses can implement processes that will make them more profit and consumers will benefit by having processes tailored to their behavior, so they find the products they want with great efficiency.

Main Points

  • The analytical approach and modeling used in this paper builds on previous modeling and analysis in this area and improves it.
    • This paper uses extremely detailed data which enables an explanation on search patterns themselves, and within a model that explicitly accounts for specifics of the actual search environment.  Therefore the conclusions generated by this paper are more sound.  However, since the approach utilized by this paper is more data-intensive and costly, the scope of search behavior explained in more limited in scope.

 

  • This paper makes the first step in estimating structural models of search with learning, when detailed data on search histories is available.

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