Consumer Search Behavior on the Mobile Internet: An Empirical Analysis
Stephan Daurer, Dominik Molitor, Martin Spann, and Puneet Manchanda, 2015, 15-111
The rapid diffusion of smartphones has facilitated access to the Internet anywhere and at any time. As a result, consumers are increasingly using the mobile Internet to search for product information to help them in their purchase decisions. A consumer can obtain this information by searching the mobile web, but the use of smartphone apps is becoming the default mechanism for such searches. These apps use a combination of barcode scanning and location-based services to provide relevant information, e.g., showing only stores near the consumer when she is carrying out a price comparison.
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How, where, and when consumers search on mobile
Surveys suggest that most consumers conduct product information search at or close to the point of purchase, both in space and time (TNS infratest 2013), and that this leads to significant changes in consumer behavior. For example, according to a recent study, 75% of all smartphone users cancelled a purchase in a store shortly before check-out in order to buy the product somewhere else (IntelliAd 2014).
While there is a lot of anecdotal and survey-based knowledge on product information search via mobile devices, there is very little documentation of how, where, and when consumers actually carry out search.
In this report, Stephan Daurer, Dominik Molitor, Martin Spann, and Puneet Manchanda use a very large and unique behavioral dataset from a leading provider of mobile product information applications to conduct an empirical analysis of consumer search behavior. Their dataset contains more than 80 million observations across more than 2.5 million individual consumers. In addition, the dataset provides granular detail on consumer location, which allows the authors to analyze location-based search behavior at an individual level.
Several novel findings emerge from their analysis. First, their results show that consumers search using different types of information. This information choice depends on various factors including context, product category, user experience, and availability of (other) information. An important result here is that access to more types of information, especially product-related information, reduces search on price information, suggesting that information content can lower price sensitivity.
Second, mobile search does not seem to be focused at the point of purchase. Specifically, the authors find that search volumes are not different between Sundays (when stores in the market of analysis are closed) and weekdays. This suggests that consumers also carry out mobile search in many situations other than shopping (e.g., while consuming the product).
Third, geographic travel (mobility), the availability of specific types of product information and contextual factors (e.g., economic surroundings, competition, and weather) influence search intensity.
Stephan Daurer is Professor of Business Information Systems at DHBW Ravensburg, Baden-Wuerttemberg Cooperative State University, Germany. Dominik Molitor is a Visiting Scholar at the Department of Information, Operations, and Management Sciences, Leonard N. Stern School of Business, New York University. Martin Spann is Professor of Electronic Commerce and Digital Markets at the Ludwig-Maximilians-University of Munich, Institute of Electronic Commerce and Digital Markets, Germany. Puneet Manchanda is the Isadore and Leon Winkelman Professor and Professor of Marketing at the Stephen M. Ross School of Business, University of Michigan.
The authors would like to thank an anonymous company for providing the data, participants of the 2014 INFORMS Marketing Science Conference at Goizueta Business School, Emory University and the participants of the Big Data Conference at LMU Munich for feedback, and the Marketing Science Institute for research funding and support. The usual disclaimer applies.
The Effects of Mobile Apps on Shopper Purchases and Product Returns
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