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  • September–October 2022
  • Article
  • Harvard Business Review

Should Your Company Sell on Amazon?: Reach Comes at a Price

By: Ayelet Israeli, Leonard A. Schlesinger, Matt Higgins and Sabir Semerkant
  • Format:Print
  • | Pages:9
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Abstract

Selling on Amazon allows brands to reach millions of consumers—but that exposure comes with costs. They include smaller margins, more competition, the risk of commoditization, and less knowledge about customers. In this article, the authors present a scorecard to help brands determine whether the benefits exceed those costs. Companies can evaluate themselves on such topics as ease of shipping their products, degree of customization needed, distribution issues, and counterfeiting concerns. Companies that choose to sell on the platform will need to make smart decisions about assortment offerings, page design, and fulfillment options so that they can take advantage of Amazon’s scale while protecting the long-term value of their brands.

Keywords

Retail; Retailing; Online Business; Ecommerce; E-commerce; E-Commerce Strategy; Omnichannel Retail; Omnichannel Retailing; Amazon; Amazon.com; Sales; Digital Marketing; Internet and the Web; Business Model; Retail Industry; Consumer Products Industry; Fashion Industry; Advertising Industry; Battery Industry; Apparel and Accessories Industry; Beauty and Cosmetics Industry; Distribution Industry; Electronics Industry; Food and Beverage Industry; United States

Citation

Israeli, Ayelet, Leonard A. Schlesinger, Matt Higgins, and Sabir Semerkant. "Should Your Company Sell on Amazon? Reach Comes at a Price." Harvard Business Review 100, no. 5 (September–October 2022): 38–46.
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About The Authors

Ayelet Israeli

Marketing
→More Publications

Leonard A. Schlesinger

General Management
→More Publications

More from the Authors

    • March 2025
    • Faculty Research

    Unintended Consequences of Algorithmic Personalization

    By: Ayelet Israeli and Eva Ascarza
    • 2025
    • Faculty Research

    Dynamic Personalization with Multiple Customer Signals: Multi-Response State Representation in Reinforcement Learning

    By: Liangzong Ma, Ta-Wei Huang, Eva Ascarza and Ayelet Israeli
    • October 2024 (Revised April 2025)
    • Faculty Research

    Nvidia

    By: Andy Wu and Matt Higgins
More from the Authors
  • Unintended Consequences of Algorithmic Personalization By: Ayelet Israeli and Eva Ascarza
  • Dynamic Personalization with Multiple Customer Signals: Multi-Response State Representation in Reinforcement Learning By: Liangzong Ma, Ta-Wei Huang, Eva Ascarza and Ayelet Israeli
  • Nvidia By: Andy Wu and Matt Higgins
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