ML

Machine Learning (ML) refers to the development of algorithms that allow computers to analyze data, recognize patterns, and make decisions or predictions with minimal human intervention.

At Amazon, ML powers a wide range of functions across retail, logistics, and advertising, including:

• Product recommendations ("Customers also bought")
• Search result ranking and A9/A10 algorithms
• Dynamic pricing and forecasting
• Fraud detection and review filtering
• Alexa voice recognition
• Supply chain optimization
• Advertising bidding and targeting (e.g., DSP and Sponsored Ads)

ML models at Amazon are trained on massive datasets and improve over time through feedback loops and performance data.

Why ML matters to Amazon sellers and vendors:

• Understanding ML helps explain why products rank the way they do
• Influences advertising strategies, especially automated campaigns
• Impacts inventory planning via demand forecasting models
• Drives customer personalization that can boost sales

💡 Example: Amazon uses ML to predict which products a customer is likely to reorder - enabling “Buy it Again” suggestions and replenishment ads.

In short:
ML (Machine Learning) is the technology behind Amazon’s intelligent systems that continuously learn and optimize everything from search and pricing to logistics and ads - directly impacting seller success.