The effect of raising searching obstacles on online purchasing behavior: proof from field experiment

8. Conclusion

Online retail represents a rapidly growing proportion of all retail sales. However, margins in online retail can often be lower than in offline retail. One of the guesses behind this discrepancy is that online sellers are less able to discriminate by price than offline sellers. In this article, we explore how charging research costs to online buyers can improve gross margins by serving as a sorting mechanism among customers.

We find encouraging evidence that minor changes to the design of an online store (i.e. friction) can significantly improve its margins and profitability. By simply increasing search frictions - by removing selected links, reducing product sorting options, and limiting visual markers - online sellers can make more full-price sales to price-sensitive buyers who have higher search costs. Although significant enough to influence the purchasing behavior of price-insensitive buyers, these search frictions are minor enough for price-sensitive buyers to make the extra effort to locate discounted items. As a result, the average selling price increases as the number of items sold remains stable.

Our results have direct implications for online sellers. Without changing prices or the product mix, online sellers can improve their margins by making subtle changes to their website design. We note that this is essentially free manipulation with low data requirements, but which can lead to significant margin gains. Our point of view implies that by unduly favoring the ease of research and purchase, online sellers give up their gross margins by granting discounts to price-insensitive consumers.

Adding search frictions, we expected some decrease in conversion: by making high discounts more difficult to find, some price-sensitive consumers might choose not to spend more time and effort on the website and leave. We find it rather surprising that the conversion rates are not lower, and even higher in some of our processing conditions. This can be explained by branding effects: by hiding high discounts, new customers can perceive the seller as being of better quality, which increases the number of purchases. Another possible explanation can be explained by the overload of choice associated with very large assortments so that a more limited set of considerations can improve the expected utility (e.g., Iyengar and Lepper, 2000). For our research question, the point to remember is that any improvement in unit margins does not necessarily have to be at the expense of weaker conversions. This is a speculative statement

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and more research is needed in the online retail field to validate it and provide boundary conditions.

Our research also suggests that certain online browsing behaviors can be painful enough or take enough time for buyers to pay more. We consider it useful to conduct future research to determine the specific properties of online interaction that consumers find most demanding. This can provide useful advice for a wide range of applications, from online store design to digital advertising.

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References

Bakos, J.Yannis. 1997. Reducing buyer search costs: Implications for electronic marketplaces. Management Science, 43(12), pp.1676-1692.

Bankrate. 2016. Insurance `loyalty tax' in the crosshairs. By Jay MacDonald, published January 7, 2016. Accessed on January 7, 2016, at

http://www.bankrate.com/financing/insurance/loyalty-tax-in-thecrosshairs-for-2016.

Bell, David R., Teck-Hua Ho, and Christopher S. Tang. 1998. Determining where to shop: Fixed and variable costs of shopping. Journal of Marketing Research, pp.352-369.

Brynjolfsson, Erik, and Smith, Michael D. 2000. Frictionless commerce? A comparison of Internet and conventional retailers. Management Science, 46(4), pp.563-585.

Eisingerich, A.B. and Kretschmer, T., 2008. In e-commerce, more is more. Harvard Business Review, 86(3), pp.20-21.

Ellison, Glen, and Ellison, Sara F., 2005. Lessons about Markets from the Internet. Journal of Economic Perspectives, pp.139-158.

Ellison, Glen and Ellison, Sara F. 2009. Search, Obfuscation, and Price Elasticities on the Internet. Econometrica, 77(2), pp.427-452.

Ellison, Glenn and Wolitzky, Alexander. 2012. A search cost model of obfuscation. The RAND Journal of Economics, 43(3), pp.417-441.

Hannak, Aniko, Gary Soeller, David Lazer, Alan Mislove, and Christo Wilson. 2014. Measuring price discrimination and steering on e-commerce web sites. In Proceedings of the 2014 Conference on Internet Measurement Conference, ACM. pp. 305-318

Hughes, Ian. 2008. Customer loyalty in the UK general insurance market. Journal of Direct, Data and Digital Marketing Practice, 10(1), pp.29-42.

Internet Retailer. 2015. Top 500 Guide, 2015 Ed.

Iyengar Sheena S., Lepper Mark R. (2000), «When Choice Is Demotivating: Can One Desire Too Much of a Good Thing?» Journal of Personality and

Social Psychology, 79 (6), 995-1006.

Kim, Byung-Do, Srinivasan, Kannan and Wilcox, Ronald T. 1999. Identifying price-sensitive consumers: the relative merits of demographic vs. purchase pattern information. Journal of Retailing, 75(2), pp.173-193.

26

Kopalle, Praveen, Biswas, Dipayan, Chintagunta, Pradeep K., Fan, Jia, Pauwels, Koen, Ratchford, Brian T. and Sills, James A. 2009. Retailer pricing and competitive effects. Journal of Retailing, 85(1), pp.56-70.

Lal, Rajiv, and David E. Bell. 2003. The impact of frequent shopper programs in grocery retailing." Quantitative marketing and economics 1.2, pp.179-202.

Lynch Jr, John G., and Ariely, Dan. 2000. Wine online: Search costs affect competition on price, quality, and distribution. Marketing Science, 19(1), pp.83-103.

Monga, Ashwani, and Saini, Ritesh. 2009. The currency of search: How spending time on

search is not the same as spending money. Journal of Retailing, 85(3), pp.245-257. Ngwe, Donald. 2016.Why Outlet Stores Exist: Averting Cannibalization in Product Line

Extensions. Marketing Science, forthcoming.

Paquette, Danielle. 2015. Why you should always buy the men's version of almost anything. The Washington Post. Dec. 22, 2015. Accessed on January 7, 2016, at https://www.washingtonpost.com/news/wonk/wp/2015/12/22/women-really-do-pay-more-for-razorsand-almost-everything-else/.

Ratchford, Brian T. 2009. Online pricing: review and directions for research. Journal of Interactive Marketing, 23(1), pp.82-90.

Rigby, D., 2011. The future of shopping. Harvard Business Review, 89(12), pp.65-76.

Stahl, Dale O. 1996. Oligopolistic pricing with heterogeneous consumer search. International Journal of Industrial Organization, 14(2), pp.243-268.

Teixeira, Thales S., and Sunil Gupta. 2015. Can Retailers Win Back Shoppers Who Browse then Buy Online? Harvard Business Review 93(9).

Varian, Hal R. 1980. A model of sales. The American Economic Review, pp.651-659. Wilson, Chris M. 2010. Ordered search and equilibrium obfuscation. International Journal of Industrial Organization, 28(5), pp.496-506.

Zettelmeyer, Florian. 2000. Expanding to the Internet: Pricing and communications strategies when firms compete on multiple channels. Journal of Marketing Research,

37(3), pp.292-308.