Case Study: Amazon’s Recommendation Engine – The Personalization Powerhouse Driving 35% of Sales
Brief Summary In the late 1990s, Amazon.com transformed online shopping by introducing a personalized recommendation engine that suggests products based on each customer’s behavior. This “Customers who bought X also bought Y” approach revolutionized eCommerce, making it easier for users to discover products and for Amazon to increase sales. Over the years, Amazon’s AI-driven recommendations became increasingly sophisticated, contributing up to 35% of the company’s revenue. This case study examines how Amazon’s recommendation strategy evolved through innovation and trial-and-error, the public’s reaction including a notable controversy, and the lessons modern marketers can learn about personalization, data, and trust. Company Involved