- Digital Media
- Interpretable Machine Learning
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Prashant Rajaram is an Assistant Professor of Marketing at the Ivey Business School. He earned his PhD from the Ross School of Business at the University of Michigan. His research interests lie in understanding and documenting the experiential consumption of digital products and media. He does this by implementing causal and/or interpretable machine learning methods on behavioral data. In one project, he studies the sweet spot of ad targeting on streaming media that balances the interest of the viewer (content consumption) with that of the platform (ad exposure). In another project, he identifies the elements (across text, audio and images) in influencer videos that are associated with an increase in viewer appeal using a novel interpretation strategy that eliminates spurious relationships. His approach not only predicts well out-of-sample but also allows for interpretation of the attention paid on video elements.
- Marketing Management
- PhD, Ross School of Business, University of Michigan
- MBA, Schulich School of Business, York University
- BEng, Faculty of Technology & Engineering, M.S. University of Baroda
Honours & Awards
- Finalist, ASA Statistics in Marketing Best Doctoral Dissertation Proposal Competition, 2021
- AMA-Sheth Foundation Doctoral Consortium Fellow, Indiana University, 2020
- Best Paper Award, 49th Annual Haring Symposium, Indiana University, 2019
- Most Likely Transformative Scientific Impact Award, 4th Annual Symposium Poster Competition, Michigan Institute for Data Science (MIDAS), University of Michigan, 2018
- Marketing Strategy – ventureLAB and Capgemini, Canada
- Sales Strategy – PepsiCo, Canada
- Marketing Management – Bharat Petroleum Corporation Limited, India