Executive Summary
The emergence of large recorded communication networks (telecom data, e-mail traffic data, social network data) has led to the development of methodologies that try to track customers' word-of-mouth communication to predict and influence their purchasing behaviors. Social Network Analysis (SNA) is a fast growing field within the market research industry and SNA software is becoming part of standard Customer Relationship Management (CRM) systems. A recent estimate from The Economist claims that total industry revenues total well over a billion dollars worldwide. Besides numerous startups, large IT firms (e.g. IBM) are also entering the industry.
The paper studies the growth of the membership base of a dominant national social network in Eastern Europe. Specifically, the authors examine how the structure of individuals' real-life friendship networks affect their own and their friends' likelihood of becoming a member. The data covers a particular time period, when membership could only be acquired if an already existing member invited the candidate. Furthermore, the service was not advertised; therefore, it is safe to assume that the membership base grew via word-of-mouth only. One of the key findings is that, besides network size (number of 'friends'), the interconnectedness of one's network is equally relevant to predict high adoption probability.
The authors also identify a variety of factors that predict the influential power of individuals. Besides traditional variables (e.g. demographics), local network characteristics are important in predicting influential power. Finally, the average influential power of an individual is lower as her total network grows although we also find that the total influential power of people with large networks is higher. These findings confirm that social network analysis is a promising tool for marketers to predict and influence consumer behavior. Furthermore, the results have practical implications for viral marketing in a context where, increasingly, a variety of technology platforms are considering to leverage their consumers' revealed connection patterns. In particular, the novel methodology used in the paper performs well in predicting the next set of adopters based on network data.
Biography
Zsolt Katona is Assistant Professor of Marketing at the Haas School of Business, UC Berkeley. He has a Ph.D. in Management from INSEAD. Previously he had earned a Ph.D. in Computer Science from Eotvos University, Budapest. His current research focuses on understanding the interaction between Web sites’ online advertising strategies. He also studies the role that link structure of social networks plays in word-of-mouth effects and community formation, publishing in Marketing Science and the Journal of Consumer Research. Previously, he had analyzed characteristics of different random networks and published his work in such journals as the Journal of Applied Probability, Statistics and Probability Letters and Random Structures and Algorithms.
Peter Pal Zubcsek is Assistant Professor of Marketing at University of Florida. He primarily studies the role of social network structure in consumer interactions. His work has applications in customer relationship management, new product diffusion and community sociology. Peter holds a Ph.D. in Management from INSEAD and a M.Sc. in Informatics from the Budapest University of Technology and Economics. His research experience prior to joining INSEAD includes projects done for Global Market Insite, Simon Fraser University and the Computer and Automation Institute of the Hungarian Academy of Sciences. Competing for Hungary, in 1998 Peter won a silver medal at the 39th International Mathematical Olympiad in Taipei, Taiwan R.O.C.
Miklos Sarvary is Professor of Marketing and at Dean of Executive Education at INSEAD. Before, he was a faculty member at the Harvard Business School and the Graduate School of Business at Stanford University. He has a Ph.D. in Management from INSEAD. His current research focuses on social networks and new media (metaverses) and how these technologies transform marketing. His recent papers study media competition, online advertising, the structure of the Internet and techniques related to 'community management'. Previously, he worked on information marketing, the worldwide pricing of cellular telephone services and the global diffusion of telecommunications products. His work has been published in Marketing Science, Journal of Marketing Research, Management Science, Quantitative Marketing and Economics, and International Journal of Research in Marketing, among others. He is Associate Editor of Marketing Science and Quantitative Marketing and Economics and member of the Editorial Boards of International Journal of Research in Marketing and the Journal of Interactive Marketing.
Journal of Marketing Research, Volume 48, Number 3, June 2011
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