Michelle Andrews

Mobile Targeting

Mobile technologies enable marketers to target consumers by time and location. This study builds on a large-scale randomized experiment of short message service SMS texts sent to 12,265 mobile users. We draw on contextual marketing theory to hypothesize how different combinations of mobile targeting determine consumer responses to mobile promotions. We identify that temporal targeting and geographical targeting individually increase sales purchases. Surprisingly, the sales effects of employing these two strategies simultaneously are not straightforward. When targeting proximal mobile users, our findings reveal a negative sales--lead time relationship; sending same-day mobile promotions yields an increase in the odds of consumer purchases compared with sending them two days prior to the promoted event. However, when targeting nonproximal mobile users, there is an inverted-U, curvilinear relationship. Sending one-day prior SMSs yields an increase in the odds of consumer purchases by 9.5 times compared with same-day SMSs and an increase in the odds of consumer purchases by 71% compared with two-day prior SMSs. These results are robust to unobserved heterogeneity, alternative estimation models, bootstrapped resamples, randomization checks, consumer mobile usage behavior, and segmentation of consumer scenarios. In addition, we conducted follow-up surveys to delve into the psychological mechanisms explaining the findings in our field experiment. In line with consumer construal arguments, consumers who received SMSs close far in time and location formed a more less concrete mental construal, which in turn, increased their involvement and purchase intent. These findings suggest that understanding the when, where, and how of mobile targeting strategies is crucial. Marketers can save money by carefully designing their mobile targeting campaigns. This paper was accepted by Sandra Slaughter, information systems.

Group-Buying Deal Popularity

Group-buying (GB) deals entail a two-phase decision process. First, consumers decide whether to buy a deal. Second, they decide when to redeem the deal, conditional on purchase. Guided by theories of social influence and observational learning, the authors develop a framework predicting that (1) deal popularity increases consumers’ purchase likelihood and decreases redemption time, conditional on purchase, and (2) the social influence–related factors of referral intensity and group consumption amplify these effects. The authors test this framework and support it using a unique data set of 30,272 customers of a GB website with several million data points. Substantially, these findings reveal a two-phase perspective of GB, longevity effects of deal popularity, and the amplifying role of customer referrals (influencing others) in the effects of deal popularity (others’ influence). In light of the criticism of GB industry practice, this study builds the case for GB websites and merchants to heed deal popularity information and the social influence–related contingencies.