Producing reliable sales forecasts for new products is notoriously difficult. Traditional surveys have been popular for decades but they are relatively cumbersome and expensive to implement. Use of readily available data from social networks is becoming increasingly popular. Can the customer buzz measures obtained from social networks be a convenient and inexpensive substitute of traditional tools? Using movie industry as a backdrop, the authors compare forecasts derived from a large-scale purchase intention survey with those obtained via social networks. They find that while the survey approach is more reliable in predicting performance overall, customer buzz-based forecasts outperform surveys under conditions of high uncertainly, e.g., for niche and low-budget movies.
Texas A&M University-Commerce
Yuying Shi is an assistant professor in the Department of Marketing and Business Analytics at the Texas A & M university-commerce. She received both her Ph.D. in Marketing and Master of statistics from University of Florida. Her research area focuses on marketing...
Ekaterina (Kate) Karniouchina
Dr. Kate Karniouchina is the Dean of Lorry I. Lokey School of Business and Public Policy. Kate holds a PhD in Marketing, an MBA, and a BA degree in Finance from the University of Utah. Her work has been widely published in academic and industry journals including the...
Rutgers University, USA
Can Uslay (MBA and Ph.D., Georgia Institute of Technology) is Vice Dean for Innovation and Strategic Partnerships for Rutgers Business School at Newark and New Brunswick and oversees new, nascent, and international programs and their development; research, program-based...
by Francisco J. Quevedo, Kobi Lee
The Non-Profit Sector contributes almost $1 trillion to the US economy, representing 5.4% of GDP and generating over 12 million jobs. Nonprofits have become...
by Jonathan Zhang, Oliver R. Müller
Compared to many other industries, the luxury industry relies more heavily on strong brands to achieve long-term competitive advantage. Accordingly, this...