Seminar by Prof. Anindya Ghose, New York University
Event details
| Date | 27.05.2016 |
| Hour | 12:00 › 13:30 |
| Speaker | Prof. Anindya Ghose, New York University |
| Location | |
| Category | Conferences - Seminars |
Measuring The Effectiveness of Mobile Marketing: Evidence From Field Experiments
Abstract:
The explosive growth of smartphones and location-based services (LBS) has contributed to the rise of mobile advertising. In this talk, we will present results from multiple studies that are designed to measure the effectiveness of mobile marketing promotions. In the first field study where we exploit a quasi-natural experiment we examine the role of contextual crowdedness on the redemption rates of mobile coupons. We find that people become increasingly engaged with their mobile devices as their context get more crowded, and in turn become more likely to respond to targeted mobile messages. These studies causally show that mobile advertisements based on real-time static geographical location and contextual information can significantly increase consumers’ likelihood of redeeming a geo-targeted mobile coupon. However, beyond the location and contextual information, the overall mobile trajectory of each individual consumer can provide even richer information about consumer preferences. In a second study, we propose a new mobile advertising strategy that leverages full information on consumers’ offline moving trajectories. To examine the effectiveness of this new mobile trajectory-based advertising strategy, we designed a large-scale randomized field experiment in one of the largest shopping malls in the world. Using machine learning techniques, we find that mobile trajectory-based advertising can lead to highest redemption probability, fastest redemption behavior, and highest satisfaction rate from customers at the focal advertising store. Our studies help firms better understand the question of which kinds of mobile advertising are most effective and how machine learning techniques can be combined with statistical models and field experiments to offer the right product to the right audience at the right time on the right channel.
Bio
Anindya Ghose (Ph.D., Carnegie Mellon) is a professor of IT and a professor of Marketing at NYU's Leonard N. Stern School of Business, and the Director of the Center for Business Analytics at Stern. He is a NEC Faculty Fellow. In 2014, he was selected by Poets & Quants as one of the “Top 40 Business School Professors Under 40 in the World” and by Analytics Week as one the "Top 200 Thought Leaders in Big Data and Business Analytics". He is also the youngest ever receipient of the INFORMS ISS Distinguished Fellow award. His work has been published in leading journals in Marketing, Economics, IS, and Computer Science. He has received 14 best paper awards. He is a Marketing Science Institute Young Scholar and a National Science Foundation CAREER award winner. He has published more than 80 papers in premier scientific journals and peer reviewed conferences, and has given more than 200 talks internationally. He is a frequent keynote speaker in executive gatherings and thought leading events globally. He has been awarded 14 grants from Google, Microsoft, Adobe and several other corporations. He teaches courses on digital marketing and business analytics at the undergraduate, MBA, EMBA, MSBA, and Executive Education level in various parts of the world including the US, India, China, Europe, and South Korea. He serves as a Senior Editor in ISR and an Associate Editor in Management Science. He has consulted in various capacities for Berkeley Corporation, CBS, Dataxu, Facebook, NBC Universal, OneVest, Samsung, Showtime, and 3TI World, and collaborated with Adobe, Alibaba, China Mobile, Google, IBM, Indiegogo, Microsoft, Recobell, Travelocity and many other leading Fortune 500 firms on realizing business value from IT investments, internet marketing, business analytics, mobile marketing, digital analytics, social media, and other areas. He serves as Chief Data Scientist of 3TI World, Scientific Advisor to OneVest and a Scientific Expert with Cornerstone Research on litigation consulting. His research has been profiled numerous times in the BBC, Bloomberg TV, CNBC, China Daily, The Economist, Financial Times, Fox News, Forbes, Knowledge@Wharton, Korean Broadcasting News Company, Los Angeles Times, Marketplace Radio, MSNBC, National Public Radio, NBC, Newsweek, New York Times, New York Daily, NHK Japan Broadcasting, Reuters, Time Magazine, Washington Post, and the Wall Street Journal. His biggest passion is high altitude mountaineering and in his spare time he climbs in the Andes, Himalayas, Alps, and other mountains across the world.
Abstract:
The explosive growth of smartphones and location-based services (LBS) has contributed to the rise of mobile advertising. In this talk, we will present results from multiple studies that are designed to measure the effectiveness of mobile marketing promotions. In the first field study where we exploit a quasi-natural experiment we examine the role of contextual crowdedness on the redemption rates of mobile coupons. We find that people become increasingly engaged with their mobile devices as their context get more crowded, and in turn become more likely to respond to targeted mobile messages. These studies causally show that mobile advertisements based on real-time static geographical location and contextual information can significantly increase consumers’ likelihood of redeeming a geo-targeted mobile coupon. However, beyond the location and contextual information, the overall mobile trajectory of each individual consumer can provide even richer information about consumer preferences. In a second study, we propose a new mobile advertising strategy that leverages full information on consumers’ offline moving trajectories. To examine the effectiveness of this new mobile trajectory-based advertising strategy, we designed a large-scale randomized field experiment in one of the largest shopping malls in the world. Using machine learning techniques, we find that mobile trajectory-based advertising can lead to highest redemption probability, fastest redemption behavior, and highest satisfaction rate from customers at the focal advertising store. Our studies help firms better understand the question of which kinds of mobile advertising are most effective and how machine learning techniques can be combined with statistical models and field experiments to offer the right product to the right audience at the right time on the right channel.
Bio
Anindya Ghose (Ph.D., Carnegie Mellon) is a professor of IT and a professor of Marketing at NYU's Leonard N. Stern School of Business, and the Director of the Center for Business Analytics at Stern. He is a NEC Faculty Fellow. In 2014, he was selected by Poets & Quants as one of the “Top 40 Business School Professors Under 40 in the World” and by Analytics Week as one the "Top 200 Thought Leaders in Big Data and Business Analytics". He is also the youngest ever receipient of the INFORMS ISS Distinguished Fellow award. His work has been published in leading journals in Marketing, Economics, IS, and Computer Science. He has received 14 best paper awards. He is a Marketing Science Institute Young Scholar and a National Science Foundation CAREER award winner. He has published more than 80 papers in premier scientific journals and peer reviewed conferences, and has given more than 200 talks internationally. He is a frequent keynote speaker in executive gatherings and thought leading events globally. He has been awarded 14 grants from Google, Microsoft, Adobe and several other corporations. He teaches courses on digital marketing and business analytics at the undergraduate, MBA, EMBA, MSBA, and Executive Education level in various parts of the world including the US, India, China, Europe, and South Korea. He serves as a Senior Editor in ISR and an Associate Editor in Management Science. He has consulted in various capacities for Berkeley Corporation, CBS, Dataxu, Facebook, NBC Universal, OneVest, Samsung, Showtime, and 3TI World, and collaborated with Adobe, Alibaba, China Mobile, Google, IBM, Indiegogo, Microsoft, Recobell, Travelocity and many other leading Fortune 500 firms on realizing business value from IT investments, internet marketing, business analytics, mobile marketing, digital analytics, social media, and other areas. He serves as Chief Data Scientist of 3TI World, Scientific Advisor to OneVest and a Scientific Expert with Cornerstone Research on litigation consulting. His research has been profiled numerous times in the BBC, Bloomberg TV, CNBC, China Daily, The Economist, Financial Times, Fox News, Forbes, Knowledge@Wharton, Korean Broadcasting News Company, Los Angeles Times, Marketplace Radio, MSNBC, National Public Radio, NBC, Newsweek, New York Times, New York Daily, NHK Japan Broadcasting, Reuters, Time Magazine, Washington Post, and the Wall Street Journal. His biggest passion is high altitude mountaineering and in his spare time he climbs in the Andes, Himalayas, Alps, and other mountains across the world.
Practical information
- General public
- Free