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Abstract Details
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Activity Number:
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41
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Type:
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Contributed
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Date/Time:
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Sunday, July 31, 2011 : 2:00 PM to 3:50 PM
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Sponsor:
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Section on Statistics and Marketing
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| Abstract - #303286 |
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Title:
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Modeling Click-Stream Data to Understand Users' Path to Conversion
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Author(s):
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Douglas Galagate*+ and Wolfgang Jank
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Companies:
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University of Maryland and University of Maryland
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Address:
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Department of Mathematics, College Park, MD, 20742-4015,
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Keywords:
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click-stream data ;
data mining ;
advertising ;
internet
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Abstract:
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Advertisers spend a lot of time and effort directing consumers' attention to their client's website, enticing them to purchase a product or a service. While most models attribute a consumer's conversion only to the last site they visited ("last click model"), it is generally accepted that all of the information in a consumer's search path (i.e. in the sequence of all websites visited) play some role in the ultimate purchase decision. In this project, we use data mining techniques to characterize and model a consumer's "path to conversion." That is, we characterize the network of websites and sequence of clicks in order to gauge the impact of different types of online content, its order and its relationship to one another on the probability of a consumer's conversion.
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