Contents lists available at ScienceDirect Journal of Retailing and Consumer Services journal homepage: www.elsevier.com/locate/jretconser Fundamental patterns of in-store shopper behavior Herb Sorensen a , Svetlana Bogomolova a , Katherine Anderson a , Giang Trinh a , Anne Sharp a , Rachel Kennedy a , Bill Page a, ⁎ , Malcolm Wright b a Ehrenberg-Bass Institute for Marketing Science, University of South Australia, GPO Box 2471, Adelaide 5001, Australia b College of Business, Massey University, Private Bag 11 222, Palmerston North 4442, New Zealand ARTICLE INFO Keywords: In-store research Shopper observational research Consumer behavior Empirical generalization ABSTRACT This research confirms empirical patterns about in-store behaviors based on a large number of shops and store visits, specifically 654,000 transactions in 40 supermarkets, hypermarkets, convenience and specialty stores in the USA, UK, China, and Australia. Integrating new data with past findings highlights that: (i) many shopping trips are short; (ii) shoppers typically only cover a small proportion of the store on any trip, and (iii) the heterogeneity of key behavioral measures (store coverage, number of items bought, and trip length) is generalizable across countries, most store formats, and store size. These patterns can help retailers and manufacturers benchmark and predict behavior and provide a base for further theoretical developments. 1. Introduction The in-store behavior of shoppers has been studied for more than 60 years (e.g. see Applebaum, 1951; Frisbie, 1980; Kollat and Willett, 1967; Stern, 1962). However, more systematic documentation of the underlying patterns of shopper behavior remains necessary. The retail sector has increased in complexity, where retailers now operate stores in multiple retail formats (i.e. supermarkets, supercenters, conveni- ence, online) across a range of countries. Similarly, manufacturers increasingly sell their products across a range of retail formats and countries (Deloitte, 2013). While models to describe consumers switching between retail outlets (Keng et al., 1998), regularity of shopping trips (Kim and Park, 1997), and shopper purchases (Kamakura, 2012) have been identified, models to describe shopper behavior inside retail outlets are scarce and largely based on laboratory rather than field experiments (Hui et al., 2009c). Prior research has established that consumers vary in their motivations for shopping (e.g. Tauber, 1972), shopping styles (e.g. Inman et al., 2009; Kollat and Willett, 1967), in-store behaviors (e.g. Kim and Park, 1997; MacKay, 1973) and frequency of shopping trips. However, a better understanding of the heterogeneity of shopper behavior inside retail outlets is needed and is possible. We focus on three related metrics relevant to the management and design of retail outlets and to the implementation and evaluation of shopper marketing programs: the proportion of the store visited on a shopping trip, the number of items purchased per shopping trip (basket size), and the amount of time spent in the store. The proportion of store area visited is particularly under-researched, despite its relevance to retailers, manufacturers, and researchers. We utilize data from 42 retail outlets to identify generalizable patterns of shopper behavior. Consistent with an empirical general- izations approach, the data was purposefully selected to provide both close replications (i.e. supermarkets in different US cities) and differ- entiated replications (a hypermarket in China, specialist wine stores in Australia) to test the generalizability of the findings (as recommended by Lindsay and Ehrenberg, 1993). 2. Key shopper metrics and current knowledge To build a comprehensive description of in-store behavior to advance the science of shopping (Underhill, 1999), a multi-measure approach providing insight into different aspects of in-store behavior is useful. For example, the proportion of a store covered may be determined by how much time the shopper has available to spend in the store or the items the shopper intends to purchase. Alternatively, the items needed may dictate how much of the store the shopper covers, which may, in turn, influence the time taken to complete a shopping trip. There will be variation across individuals and across shops. Regardless of the direction of these relationships, all measures— trip length, store coverage, and basket size—yield valuable insights into how shoppers behave. While clearly the measures are correlated and there is important work (e.g. in-store experiments) required to under- http://dx.doi.org/10.1016/j.jretconser.2017.02.003 Received 18 July 2016; Received in revised form 4 February 2017; Accepted 5 February 2017 ⁎ Corresponding author. E-mail addresses: Herb.Soreson@MarketingScience.info (H. Sorensen), Svetlana.Bogomolova@MarketingScience.info (S. Bogomolova), Katherine.Anderson@MarketingScience.info (K. Anderson), Giang.Trinh@MarketingScience.info (G. Trinh), Anne.Sharp@MarketingScience.info (A. Sharp), Rachel.Kennedy@MarketingScience.info (R. Kennedy), Bill.Page@MarketingScience.info (B. Page), Malcolm.Wright@Massey.ac.nz (M. Wright). Journal of Retailing and Consumer Services (xxxx) xxxx–xxxx 0969-6989/ © 2017 Elsevier Ltd. All rights reserved. Please cite this article as: Sorensen, H., Journal of Retailing and Consumer Services (2017), http://dx.doi.org/10.1016/j.jretconser.2017.02.003