Digital profiling on limited data: Application in display advertising
Abstract
A user’s digital profile is a summary of the consumer’s interests and preferences revealed through the consumer’s online activity. It is a fundamental component of numerous applications in digital marketing. McKinsey & Company regards online user profiling as a promising opportunity that companies should leverage to unlock the potential of Big Data. This paper discusses a modelling approach that uncovers individual user profiles from online surfing data and allows online businesses to make profile predictions when only limited information is available. The approach is easily parallelised and scales well for processing massive records of user online activity. The paper demonstrates the application of the authors’ approach to display advertising. Using economic simulation it shows the potential gains the approach may offer to a firm if used for targeting display ads at the individual level.
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Author's Biography
Michael Trusov is Associate Professor, Robert H. Smith School of Business, University of Maryland. A UCLA PhD graduate, his research focuses on digital marketing, text analysis, eye-tracking and data mining. He is a recipient of several prestigious awards including the William F. O’Dell award, the Paul E. Green award, the Donald R. Lehmann Award, the Society for Marketing Advances Emerging Scholar Award, the Emerald Management Reviews Citation of Excellence Award and the Marketing Science Institute’s Alden G. Clayton Award.
Liye Ma is Assistant Professor, Robert H. Smith School of Business, University of Maryland. His research focuses on the dynamic interactions of consumers and firms on internet, social media and mobile platforms. He develops quantitative models to analyse the drivers of consumer actions in the digital economy. His work has been published in such journals as Marketing Science, Journal of Marketing Research, Management Science, Information Systems Research and Marketing Letters. One of his papers was a finalist for the John D.C. Little Best Paper Award. Professor Ma obtained his PhD degree from the Tepper School of Business at the Carnegie Mellon University.
Citation
Trusov, Michael and Ma, Liye (2016, November 5). Digital profiling on limited data: Application in display advertising. In the Applied Marketing Analytics: The Peer-Reviewed Journal, Volume 2, Issue 4. https://doi.org/10.69554/RYEI4760.
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