What Matters Most in Internet Retailing

Although online retailers theoretically have unlimited trading areas, they need to know where to look for customers.

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Online retailing is far and away the fastest growing retail sector in the United States, with overall growth of about 15% in the past year and with categories such as apparel and footwear up by more.1 Internet retailing currently represents approximately 8% of U.S. retail sales, and in many countries it’s an even larger percentage. Forrester Research expects that from 2010 to 2015 online retail sales in China will more than triple, to about $160 billion.

What’s driving the growth, and to what extent do the principles of success for online retail differ from those of traditional brick-and-mortar retail? Internet retailing expansion is being fed by two forces: (1) traditional retailers are getting their “Internet acts” together, and (2) “pure play” retailers are becoming increasingly innovative. Consumers are now at least willing to consider purchasing more categories of products online than before. Many are expanding from an early emphasis on items such as books and CDs (which can be specifically described online in terms such as title, number of pages and shipping time) to other types of merchandise such as fashion apparel and gourmet food (which are characterized by “nondigital” attributes such as the fit and feel).2

Traditional and Internet retailing differ in two critical ways. First, in theory at least, Internet retailers have “unlimited” trading areas.3 Second, and less obvious, while traditional retailers can identify and target customers with relative ease (most customers either work or live within a few miles of the store), Internet retailers without physical stores find this much more difficult to do. Many Internet retailers have trouble getting noticed and acquiring customers. Indeed, having an unlimited trading area can be a mixed blessing: There are no straightforward rules about where to look for customers. As a result, some Internet retailers are making small forays into traditional retailing, using strategies that include pop-up stores, kiosks and partnerships with well-known retailers.



1. U.S. Census Bureau, “Quarterly Retail E-Commerce Sales 2nd Quarter 2012,” news release, Aug. 16, 2012, and “Online Apparel Sales Forecast,” 2012, www.internetretailer.com

2. Digital attributes of products can be communicated over the Internet without any loss of information whatsoever; nondigital attributes cannot be perfectly communicated over the Internet — they need to be experienced by the customer directly. This distinction was perhaps first introduced to the marketing literature by R. Lal and M. Sarvary, “When and How Is the Internet Likely to Decrease Price Competition?” Marketing Science 18, no. 4 (1999): 485-503.

3. The seminal work of Charles Reilly in the 1930s and David Huff in the 1960s developed and introduced retail gravitation models and solidified the idea of a well-defined trading area for offline retail stores. The fixed trading areas described in those papers are in stark contrast to the expansive trading areas for Internet retailers. See D. Huff, “Defining and Estimating a Trading Area,” Journal of Marketing 28, no. 3 (1964): 34-38; and D. Bell and S. Song, “Neighborhood Effects and Trial on the Internet: Evidence from Online Grocery Retailing,” Quantitative Marketing and Economics 5, no. 4 (2007): 361-400.

4. See, for example, P. Farris, J. Olver and C. De Kluyver, “The Relationship Between Distribution and Market Share,” Marketing Science 8, no. 2 (1989): 107-128; and D. Bell, T-H. Ho and C. Tang, “Determining Where to Shop: Fixed and Variable Costs of Shopping,” Journal of Marketing Research 35, no. 3 (1998): 352-369.

5. See, for example, C. Forman, A. Ghose and A. Goldfarb, “Competition Between Local and Electronic Markets: How the Benefit of Buying Online Depends on Where You Live,” Management Science 55, no. 1 (2009): 47-57.

6. See, for example, E. Brynjolfsson, M. Smith and M. Rahman, “Battle of the Retail Channels: How Product Selection and Geography Drive Cross-Channel Competition,” Management Science 55, no. 11 (2009): 1755-1765.

7. In addition to showing that the Internet serves as a substitute for physical retail in locations where consumers have fewer or less-accessible offline options, Sinai and Waldfogel (2004) show that residents of large cities use the Internet to gather information about local products, services and events. T. Sinai and J. Waldfogel, “Geography and the Internet: Is the Internet a Substitute or Complement for Cities?” Journal of Urban Economics 56, no. 1 (2004): 1-24.

8. L. Burkitt, “China’s Web Gets the Luxury Look,” Dec. 2, 2010, http://cn.wsj.com.

9. A. Goolsbee, “In a World Without Borders: The Impact of Taxes on Internet Commerce,” Quarterly Journal of Economics 115, no. 2 (2000): 561-576.

10. E. Anderson, N. Fong, D. Simester and C. Tucker, “How Sales Taxes Affect Customer and Firm Behavior: The Role of Search on the Internet,” Journal of Marketing Research 47, no. 2 (2010): 229-239.

11. J. Choi, D. Bell and L. Lodish, “Traditional and IS-Enabled Customer Acquisition on the Internet,” Management Science 58, no. 4 (2012): 754-769.

12. See S. Bikhchandani, D. Hirshleifer and I. Welch, “Learning from the Behavior of Others: Conformity, Fads and Informational Cascades,” Journal of Economic Perspectives 12, no. 3 (1998): 151-170; and O. Oyen and M. De Fleur, “The Spatial Diffusion of an Airborne Leaflet Message,” American Journal of Sociology 59, no. 2 (1953): 144-149.

13. Bell and Song, “Neighborhood Effects.” See also Figure 1 on p. 66 of J. Choi, S. Hui and D. Bell, “Spatio-Temporal Analysis of Imitation Behavior Across New Buyers at an Online Grocery Retailer,” Journal of Marketing Research 47, no. 1 (2010): 65-79.

14. Internet retailers are increasingly trying to find ways to get their product directly in front of potential customers, either through pop-up stores or alliances. In 2012, Bonobos will open stores in Chicago, Palo Alto and Washington D.C., as well as two additional stores in New York; see A. Pasquarelli, “E-tailer Becomes Retailer,” June 3, 2012, www.crainsnewyork.com. For an overview of the April 2012 $16 million deal struck between Bonobos.com and Nordstrom, see E. Rusli, “Stores Go Online to Find a Perfect Fit,” April 11, 2012, http://dealbook.nytimes.com.

15. J. Lee and D. Bell, “Social Learning and Trial on the Internet,” unpublished ms, 2012.

16. R. Putnam, “Bowling Alone: The Collapse and Revival of American Community” (New York: Simon & Schuster, 2000).

17. C. Anderson, “The Long Tail: Why the Future of Business Is Selling More of Less” (New York: Hyperion, 2006).

18. Choi, Hui and Bell, “Spatio-Temporal Analysis.”

19. If you are one of only a few people in your local neighborhood who happens to want a particular product or service, then you will likely be a “preference minority,” and the local offline stores are unlikely to pay attention to your needs and deliver what you want. See J. Choi and D. Bell, “Preference Minorities and the Internet,” Journal of Marketing Research 48, no. 4 (2011): 670-682.

20. For details see Choi, Bell and Lodish, “Traditional and IS-Enabled Customer Acquisition.”

21. More formally, physical neighbors face very similar offline shopping costs (access to offline stores, shipping times from online stores, online sales tax rates, etc.). As a result, they share the same incentives for shopping online versus offline.

22. M. Kim, J. Choi and D. Bell, “Customer Migration, Online Shopping Behavior and Brand Preference,” unpublished ms, 2012.

23. B. Bronnenberg, J-P. Dube and M. Gentzkow, “The Evolution of Brand Preferences: Evidence from Consumer Migration,” American Economic Review, in press.


This work was supported by the National Research Foundation of Korea Grant, funded by the Korean government [NRF-2011-330-B00076]. The authors would like to thank Andy Dunn and Craig Elbert of Bonobos.com, Marc Lore and Scott Hilton of Diapers.com, Ari Sabah and Yoram Evan of Netgrocer.com and Neil Blumenthal and Dave Gilboa of WarbyParker.com for permission to conduct research using their data.

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Comments (2)
Hemant Warudkar
Perhaps my comments on this article are about two years late and may not get much notics but I find the findings in the article fascinating. I have found identical insights while working with a specialty retailer. Some of these insights have been very effectively used by the retailer to predict response rates of customers in zip codes with preference isolation.
Our predictive models incorporate most of the findings in the article in classifying customers by propensity to buy and estimation of the increase in amount bought by these customers. Thus we are able to predict with a high degree of accuracy the return on investment of a campaign well before execution of the campaign.

The current coursera.org class on introduction to marketing from the wharton school of business is a great place to get introduced to these same priciples.
Al Rose
Agree, online retailing is growing fast.  When addressing the leading question: How can companies increase their online sales?, it’s interesting that there’s no mention of the importance of online customer service in this article. With online research and comparison shopping now the norm for techno-savvy consumers, Internet retailers have a huge opportunity to proactively support their customers online.  The use of proactive chat (a proactive invitation to connect with an agent) can be an excellent way to help customers while they are actively looking.  Studies have shown that online chat increases sales. Having online customer service channels readily available with the click of a mouse can also reduce shopping cart abandonment. We have seen impressive sales increases from our own contact center clients as a result of proactive online customer support.
Al Rose, VP Retail & Internet Properties, TELUS International - @TELUSint