The Effects of Mobile Apps on Shopper Purchases and Product Returns

Do mobile apps influence shopper purchases and product returns? We model the effects of app adoption in the context of a large omnichannel retailer with 32 million shoppers. We leverage the launch of a mobile app by the retailer and use a difference-in-differences approach to identify and estimate the differences between app adopters and non-adopters in shopping outcomes, such as the incidence and monetary value of purchases and product returns. We find that app adopters buy 21% more often but spend 12% less per purchase occasion and return 73% more often than non-adopters in the month after adoption. Overall, app adoption results in a 24% increase in net monetary value of purchases. Our findings are robust to alternative explanations and measures. Furthermore, our analysis of the drivers of app use reveals that exposure to offers and rewards through the app plays a key role in driving shopping outcomes. Surprisingly, the number of unique app features accessed by the shopper has an inverted U-shaped relationship with shopping outcomes, suggesting managerial caution against “all-in-one” app designs.

[1]  Venkatesh Shankar,et al.  Mobile Shopper Marketing: Key Issues, Current Insights, and Future Research Avenues , 2016 .

[2]  Sam K. Hui,et al.  Mobile Promotions: A Framework and Research Priorities , 2016 .

[3]  Peter J. Danaher,et al.  Where, When, and how Long: Factors that Influence the Redemption of Mobile Phone Coupons , 2015 .

[4]  E. Malthouse,et al.  The Effects of Adopting and Using a Brand's Mobile Application on Customers’ Subsequent Purchase Behavior , 2015 .

[5]  L. Krishnamurthi,et al.  On the Go: How Mobile Shopping Affects Customer Purchase Behavior , 2015 .

[6]  Chris Forman,et al.  News Media Channels: Complements or Substitutes? Evidence from Mobile Phone Usage , 2013, ICIS.

[7]  Sam K. Hui,et al.  The Effect of In-Store Travel Distance on Unplanned Spending: Applications to Mobile Promotion Strategies , 2013 .

[8]  Eric T. Anderson,et al.  Wal-Mart's Impact on Supplier Profits , 2012 .

[9]  Jennifer A. Robinson,et al.  The Effectiveness of Branded Mobile Phone Apps , 2011 .

[10]  Michael Lewis,et al.  Stockouts in Online Retailing , 2011 .

[11]  Sridhar Balasubramanian,et al.  Mobile Marketing: A Synthesis and Prognosis , 2009 .

[12]  D. Rubin.  For objective causal inference, design trumps analysis , 2008, 0811.1640.

[13]  Florian von Wangenheim,et al.  Behavioral Consequences of Overbooking Service Capacity , 2007 .

[14]  Marco Caliendo,et al.  Some Practical Guidance for the Implementation of Propensity Score Matching , 2005, SSRN Electronic Journal.

[15]  Jeffrey M. Wooldridge,et al.  Solutions Manual and Supplementary Materials for Econometric Analysis of Cross Section and Panel Data , 2003 .

[16]  Shin-Yuan Hung,et al.  Critical factors of WAP services adoption: an empirical study , 2003, Electron. Commer. Res. Appl..

[17]  Scott A. Neslin,et al.  The Effect of Promotion on Consumption: Buying More and Consuming it Faster , 1998 .

[18]  R. Thaler.  Saving, Fungibility, and Mental Accounts , 1990 .

[19]  D. Rubin,et al.  The central role of the propensity score in observational studies for causal effects , 1983 .

[20]  Ruth N. Bolton,et al.  A Dynamic Model of the Duration of the Customer's Relationship with a Continuous Service Provider: The Role of Satisfaction , 1994 .

[21]  J. Heckman.  Sample selection bias as a specification error , 1979 .