guest article by Michelle Andrews, Finalist of the SERVSIG Best Dissertation Award 2016 (granted by Maastricht U)
Have you ever wondered why some people look at their phones in elevators? Since they can’t do much during the short elevator ride, perhaps their phones help them deal with proximity to others. If so, my colleagues and I mused, what about instances in which people are in close proximity to others for longer periods of time? Consider the case of public transit. Millions of people take it every day, in which they are surrounded by others, with not much to do. To see whether people’s response to mobile promotions differed by how crowded their commute was, we partnered with a wireless provider and conducted a study in the subway system of an Asian city.
One challenge we faced was randomization. Ideally, we would randomly assign commuters into more or less crowded trains. But, this would have been logistically difficult and would not have reflected a normal commute. To get around this, we used mobile technology to determine how crowded the trains were that commuters were riding in. This is because the subway was equipped with subway-specific cellular lines, which enables commuters to use their cell phones underground throughout their transit in the same manner they would be able to above ground. By instantly gauging the number of mobile phones that automatically connect to this subway line, in combination with our knowledge of the exact size of each subway car, we calculated crowdedness as the number of people per square meter.
We then sent a mobile promotion to a random sample of almost 15,000 commuters. The promotion was for a service that notified people of calls they missed, since phone plans in the city of our study were piecemeal, meaning that subscribers must buy services separately. Commuters in crowded trains, in turns out, were twice as likely to purchase the mobile promotion compared with commuters in non-crowded trains. In fact, when there were fewer than 2 passengers per square meter, purchase rates averaged 2.1%. But when crowdedness increased to 5 people per square meter, purchase rates jumped to 4.3% on average.
These results were robust to controlling for peak versus non-peak traffic hours, train direction, line and stop, weekdays versus weekends, mobile use behaviors, promoted product category, and sudden variations in crowdedness, as well as selection bias using propensity score matching. Moreover, the results of follow-up field surveys conducted through the wireless service provider’s call center support the notion that people may escape from the crowded space of their physical world by immersing themselves into the personal space of their digital world. This immersion into their cell phones, in turn, may increase their attention and positive response to mobile promotions.
It’s possible people’s response to mobile promotions will differ by the type of crowd they are in. At stadiums and restaurants, for example, people are often with others, and pay attention to what is going on around them (the game or the meal). In such cases, receiving mobile promotions may be perceived as more of an annoying intrusion than a welcoming distraction. Hopefully future research will reveal more contexts that influence the effectiveness of mobile promotions.
Assistant Professor of Marketing
Goizueta Business School
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