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Case Study

Retail Rocket: Personalizing the online shopping experience

By Benoit F. Leleux and Marc Chauvet

16 pages

December 2020

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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

Keywords

Entrepreneurship, Operations, Marketing, Big Data, Artificial Intelligence, Value Pricing, Search Engine, Optimization, Online Business, Business to Business, Digital Marketing, Traffic

Settings

Eastern Europe, Russia
Retail Rocket, Information Technology, eCommerce, Information Technology
2012-2020

Type

Field Research

Available Languages

English

Related material

Teaching note, Video

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