Information seeking in electronic environments
Information seeking in electronic environments
The anatomy of a large-scale hypertextual Web search engine
WWW7 Proceedings of the seventh international conference on World Wide Web 7
Stochastic modeling of usage patterns in a Web-based information system
Journal of the American Society for Information Science and Technology
An Efficient k-Means Clustering Algorithm: Analysis and Implementation
IEEE Transactions on Pattern Analysis and Machine Intelligence
ACM SIGIR Forum
Query type classification for web document retrieval
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
Understanding user goals in web search
Proceedings of the 13th international conference on World Wide Web
On the Depth and Dynamics of Online Search Behavior
Management Science
Automatic identification of user goals in Web search
WWW '05 Proceedings of the 14th international conference on World Wide Web
Detecting online commercial intention (OCI)
Proceedings of the 15th international conference on World Wide Web
A semantic approach to contextual advertising
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Determining the informational, navigational, and transactional intent of Web queries
Information Processing and Management: an International Journal
Modeling anchor text and classifying queries to enhance web document retrieval
Proceedings of the 17th international conference on World Wide Web
Context-aware query classification
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
Analysis of web search engine query session and clicked documents
WebKDD'06 Proceedings of the 8th Knowledge discovery on the web international conference on Advances in web mining and web usage analysis
Understanding User-Web Interactions via Web Analytics
Understanding User-Web Interactions via Web Analytics
The seventeen theoretical constructs of information searching and information retrieval
Journal of the American Society for Information Science and Technology
The intention behind web queries
SPIRE'06 Proceedings of the 13th international conference on String Processing and Information Retrieval
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Traffic from search engines is important for most online businesses, with the majority of visitors to many websites being referred by search engines. Therefore, an understanding of this search engine traffic is critical to the success of these websites. Understanding search engine traffic means understanding the underlying intent of the query terms and the corresponding user behaviors of searchers submitting keywords. In this research, using 712,643 query keywords from a popular Spanish music website relying on contextual advertising as its business model, we use a k-means clustering algorithm to categorize the referral keywords with similar characteristics of onsite customer behavior, including attributes such as clickthrough rate and revenue. We identified 6 clusters of consumer keywords. Clusters range from a large number of users who are low impact to a small number of high impact users. We demonstrate how online businesses can leverage this segmentation clustering approach to provide a more tailored consumer experience. Implications are that businesses can effectively segment customers to develop better business models to increase advertising conversion rates. © 2012 Wiley Periodicals, Inc.