Measuring The Effectiveness of Mobile Marketing: Evidence From Field Experiments



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 two studies that are designed to measure the effectiveness of mobile marketing promotions.  In the first large scale 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 the 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.