Amrita Dey
Each week, Daniels is featuring a researcher who conducts meaningful research that impacts their field and the wider community. Learn more about their work in Q&As with the Daniels Research team and email them to nominate yourself or a colleague for a future Q&A.
Amrita Dey is an assistant professor in the Department of Marketing. Her primary areas of research include crowdfunding, sustainability, donations and human-AI interactions. She uses computational methods involving deep learning to make sense of unstructured data in text and images, then employs econometric methods to quantify the effects and present the meaning through marketing theories to derive useful insights about businesses and consumers.
Her work has been featured in many prestigious conferences, such as the ISMS Marketing Science Conference, the Marketing Analytics Symposium-Sydney , and the Academy of Marketing Science Annual Conference, among others. She holds a PhD in marketing from the University of Utah. She also holds an MBA from Goa Institute of Management, India, and a bachelor’s in commerce from Narsee Monjee College of Commerce and Economics, Mumbai.
Before joining academia, she led marketing for both B2C and B2B brands within the Tata and Mahindra Group of companies in India. Her work won numerous prestigious awards for marketing and innovation, including the Wall Street Journal Asia Innovation Award. Amrita holds several patents and design registrations.
What do you research and how did you become interested in the topic?
Before embarking on my PhD journey, I led marketing departments in both B2B and B2C organizations. However, I constantly encountered a lack of transparency from marketing agencies regarding the specifics of digital marketing processes. My curiosity made me want to learn more, especially about how artificial intelligence (AI) could change marketing. Seeing AI’s growing role convinced me it was the way forward. So, I focused my studies on computational marketing, particularly on how images are used in marketing and communication. Research in psychology and neuroscience has demonstrated that humans process images and text through fundamentally distinct mechanisms. Visual content engages our attention more efficiently and is processed at a faster rate compared to textual information. Furthermore, organizations invest substantially more resources in the visual components of marketing compared to textual elements. Despite this, scholarly focus has historically been skewed toward text-based content. This imbalance primarily stems from the fact that the computational technologies necessary for in-depth image analysis have only become broadly accessible in recent years.
What are you working on currently?
Previous approaches to image analysis faced scalability challenges, primarily due to reliance on methods such as consumer surveys and eye-tracking studies. However, the advent of machine learning has revolutionized this domain. We can now employ feature extraction techniques—similar to the facial recognition technology used to unlock smartphones—and other advanced algorithms to interpret images with a level of depth and nuance akin to textual analysis.
I’m applying this technology across the areas of crowdfunding innovation and prosocial products, areas that I’m particularly passionate about. Startups and crowdfunding projects, in my view, represent the underdogs of the future. Take Kickstarter as an example: My research focuses on how entrepreneurs can boost their chances of securing funding by optimizing the combination of images and text in their presentations.
How would you like to see your work impact society?
With my roots in the practical side of the field, I’m committed to conducting research that offers tangible, impactful insights for the industry. For instance, I’m also looking into how AI affects consumer perceptions, exploring critical issues like fear, fairness, and the broader dynamics of human-AI interaction. This focus ensures my work not only advances academic understanding but also addresses real-world challenges and concerns within the interface of technology and consumer behavior.
How do you integrate your research into the classroom?
In my introductory marketing course, I aim to lay a solid foundation in marketing principles while integrating insights from my research into our discussions. For example, in the segment on ethics and bias, I highlight the importance of understanding AI’s implications and potential risks in contemporary marketing practices. My teaching philosophy goes beyond the confines of the textbook. I encourage active engagement with the latest business news to critically examine marketing strategies and controversies, including how companies face legal challenges over sustainability claims. The students know that they are in an era of constant change, and they are very remarkably skilled at navigating it.