Communications of the ACM
New metrics for new media: toward the development of Web measurement standards
World Wide Web Journal - Special issue on advancing HTML: style and substance
Data mining: practical machine learning tools and techniques with Java implementations
Data mining: practical machine learning tools and techniques with Java implementations
E-metrics: tomorrow's business metrics today (invited talk) (abstract only)
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining
Enabling scalable online personalization on the Web
Proceedings of the 2nd ACM conference on Electronic commerce
Personalization from incomplete data: what you don't know can hurt
Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining
Data Mining Your Website
Forecasting repeat sales at CDNOW: a case study
Interfaces - Special issue: marketing engineering
Using e-CRM for a unified view of the customer
Communications of the ACM - Digital rights management
On Active Learning for Data Acquisition
ICDM '02 Proceedings of the 2002 IEEE International Conference on Data Mining
An investigation of repeat visit behavior on the internet: models and applications
An investigation of repeat visit behavior on the internet: models and applications
On the Depth and Dynamics of Online Search Behavior
Management Science
Dynamic Conversion Behavior at E-Commerce Sites
Management Science
Modeling Browsing Behavior at Multiple Websites
Marketing Science
Accelerating customer relationships: using crm and relationship technologies™
Accelerating customer relationships: using crm and relationship technologies™
Discovering company revenue relations from news: A network approach
Decision Support Systems
Electronic Commerce Research and Applications
Web user behavioral profiling for user identification
Decision Support Systems
Accelerated Learning of User Profiles
Management Science
Editor's comments: perspectives on time
MIS Quarterly
Internet Technologies, ECRM Capabilities, and Performance Benefits for SMEs: An Exploratory Study
International Journal of Electronic Commerce
Can visible cues in search results indicate vendors' reliability?
Decision Support Systems
Predictive analytics in information systems research
MIS Quarterly
A prediction framework based on contextual data to support Mobile Personalized Marketing
Decision Support Systems
How do competitive environments moderate CRM value?
Decision Support Systems
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Due to the vast amount of user data tracked online, the use of data-based analytical methods is becoming increasingly common for e-businesses. Recently the term analytical eCRM has been used to refer to the use of such methods in the online world. A characteristic of most of the current approaches in eCRM is that they use data collected about users' activities at a single site only and, as we argue in this paper, this can present an incomplete picture of user activity. However, it is possible to obtain a complete picture of user activity from across-site data on users. Such data is expensive, but can be obtained by firms directly from their users or from market data vendors. A critical question is whether such data is worth obtaining, an issue that little prior research has addressed. In this paper, using a data mining approach, we present an empirical analysis of the modeling benefits that can be obtained by having complete information. Our results suggest that the magnitudes of gains that can be obtained from complete data range from a few percentage points to 50 percent, depending on the problem for which it is used and the performance metrics considered. Qualitatively we find that variables related to customer loyalty and browsing intensity are particularly important and these variables are difficult to derive from data collected at a single site. More importantly, we find that a firm has to collect a reasonably large amount of complete data before any benefits can be reaped and caution against acquiring too little data.