Case Study

Retail Rocket: Personalizing the online shopping experience

16 pages
December 2020
Reference: IMD-7-2129

The case, based on extensive interviews with Retail Rocket’s co-founders (Nikolay Khlebinsky and Andrey Chizh), several employees and one of the start-up’s investors, documents the genesis and rapid growth of the company. Launched in 2012 in Moscow, Russia, Retail Rocket was a big data-based personalization platform for e-commerce and omnichannel retail identifying the needs of customers based on their online behavior and, thanks to artificial intelligence, offering personalized product recommendations through the website, e-mail and other marketing channels, increasing the conversion rate, average order value and retention rate of its clients. In effect, it makes available to small and mid-sized online firms the same website optimization functionalities associated with powerhouses such as Amazon or Yandex. Its value proposition included superior shopping-pattern prediction algorithms and value-based pricing using randomized A/B testing. What would it take to monetize and grow its exceptional IT competencies?

Learning Objective
  • Capitalizing on big data analytics, developing top-quality algorithms and artificial intelligence tools to generate insights from consumers’ online shopping patterns
  • Doing business in Russia and Eastern Europe
  • Developing a unique value proposition in a contested marketplace
  • Differentiating through the business model, in particular value-based pricing
Operations, Big Data, Artificial Intelligence, Value Pricing, Search Engine, Optimization, Online Business, Business to Business, Digital Marketing, Traffic
Eastern Europe, Russia
Retail Rocket, Information Technology, eCommerce, Information Technology
Field Research
© 2020
Available Languages
Related material
Teaching note, Video
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