Expertise
- Digital Media
- Interpretable Machine Learning
Research Publications
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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 delivery on streaming media that balances the interest of the viewer (to increase content consumption) with that of the platform (to decrease ad avoidance). In another project, he identifies the elements (across text, audio and images) in YouTube influencer videos that explain a change in viewer engagement. His analytical framework avoids making a tradeoff between interpretability and predictive ability, and helps identify a subset of theory-based relationships.
Teaching
- Marketing Management
Programs Taught
- HBA
Education
- 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
Experience
- Marketing Strategy – ventureLAB and Capgemini, Canada
- Sales Strategy – PepsiCo, Canada
- Marketing Management – Bharat Petroleum Corporation Limited, India