'Bricks and Clicks': The Impact of Product Returns on the Strategies of Multichannel Retailers

Elie  Ofek; Zsolt   Katona; Miklos  Sarvary

Article | Marketing Science | January – February 2011

'Bricks and Clicks': The Impact of Product Returns on the Strategies of Multichannel Retailers

by Elie Ofek, Zsolt Katona and Miklos Sarvary

Abstract

The Internet has increased the flexibility of retailers, allowing them to operate an online arm in addition to their physical stores. The online channel offers potential benefits in selling to customer segments that value the convenience of online shopping, but it also raises new challenges. These include the higher likelihood of costly product returns when customers' ability to "touch and feel" products is important in determining fit. We study competing retailers that can operate dual channels ("bricks and clicks") and examine how pricing strategies and physical store assistance levels change as a result of the additional Internet outlet. A central result we obtain is that when differentiation among competing retailers is not too high, having an online channel can actually increase investment in store assistance levels (e.g., greater shelf display, more-qualified sales staff, floor samples) and decrease profits. Consequently, when the decision to open an Internet channel is endogenized, there can exist an asymmetric equilibrium where only one retailer elects to operate an online arm but earns lower profits than its bricks-only rival. We also characterize equilibria where firms open an online channel, even though consumers only use it for research and learning purposes but buy in stores. A number of extensions are discussed, including retail settings where firms carry multiple product categories, shipping and handling costs, and the role of store assistance in impacting consumer perceived benefits.

Keywords: Price; Profit; Marketing Channels; Consumer Behavior; Online Technology; Retail Industry;

Format: Print

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Citation:

Ofek, Elie, Zsolt Katona, and Miklos Sarvary. "'Bricks and Clicks': The Impact of Product Returns on the Strategies of Multichannel Retailers." Marketing Science 30, no. 1 (January–February 2011).

Since its launch in 1998 as “the Amazon.com of DVDs,” Netflix had evolved from a DVD rental company to a video streaming platform and producer of original films and television shows. As the company matured, it regularly increased prices and adjusted its product offerings while continuing to add new subscribers. However, between late 2019 and mid-2020, competition within the streaming industry intensified with the launch of new entrants such as Disney+, Apple TV+, and HBO Max, jeopardizing Netflix’s position as the industry leader. In spite of the heightened competition in the streaming industry, some analysts and customer willingness-to-pay surveys suggested that Netflix had the opportunity to implement another rate hike in the near future. By May 2020, Netflix must decide whether to increase prices again, or whether it should consider a different pricing model altogether.

Case | HBS Case Collection | July 2020

Pattern Brands

Sunil Gupta, Elie Ofek and Julia Kelley

In March 2020, direct-to-consumer (DTC) company Pattern Brands needed to decide how to allocate resources across its different brands. Pattern Co-Founders Nick Ling and Emmett Shine hoped to avoid the pitfalls faced by some DTC companies—such as inability to scale and lack of competitive differentiation—by relying on their previous experience running a successful branding and marketing agency. Rather than focusing on a single brand, they conceived Pattern as a “DTC 2.0” model—a portfolio of 5 to 10 brands that shared a common theme of activities related to the home and a common mission of helping millennials enjoy daily life. Since its founding in August 2019, Pattern had launched cookware brand Equal Parts and home organization brand Open Spaces. Although Pattern’s team still believed strongly in the benefits of a multi-brand strategy, Open Spaces’ sales and unit economics had significantly outperformed Equal Parts’ to date. Pattern’s leadership wanted to build on Open Spaces’ early momentum with new product colors and product lines, but they debated whether to act on the results of a recent customer survey indicating a positive response to an Equal Parts product redesign. Ling and Shine now had several decisions to consider. How should they allocate resources between repositioning Equal Parts and continuing to grow Open Spaces? How and when should they continue building Pattern’s portfolio by developing a third brand? How much should they invest in marketing parent brand Pattern? More broadly, did Pattern’s model represent the future of DTC brands?

Keywords: Brands and Branding; Marketing Channels; Marketing Strategy; Product Marketing; Product Launch; Product Positioning; Business Model; Business Startups; Growth and Development Strategy; Demand and Consumers; Business Strategy; Diversification; Competitive Advantage; Consumer Products Industry; Retail Industry; North and Central America; United States; New York (city, NY); New York (state, US);

Citation:

Gupta, Sunil, Elie Ofek, and Julia Kelley. "Pattern Brands." Harvard Business School Case 521-009, July 2020. View Details

Cite View Details Educators

The digital revolution has allowed companies to amass considerable amounts of data on their customers. Using this information to generate actionable insights is fast becoming a critical skill that firms must master if they wish to effectively compete and win in today’s data-driven marketplace. This note explains the value of examining customer metrics, such as retention rate, revenues, and social influence (k-factor), on an ongoing basis by conducting a cohort analysis. Such an analysis segments customers using one or more criteria, and tracks the behavior and performance of each of these segments over time. Using several instructive examples, the presentation highlights the benefits of running a cohort analysis for deriving a deep understanding of customer trends. Moreover, the examples expose the pitfalls that arise from not accounting for segment characteristics (such as when a customer joined, from what media vehicle they were acquired, how heavily they use the product, etc.) and not paying attention to the evolution of customer metrics over time. The implications of conducting a cohort analysis for firm strategy and for determining customer lifetime value (CLV) are discussed.

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'Bricks and Clicks': The Impact of Product Returns on the Strategies of Multichannel Retailers

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