With two million sellers, spanning 10 countries and serving nearly 2 billion customers, Amazon uses its advanced data-driving technology to provide personalized recommendations to users. There is no doubt that Amazon is a pioneer in mining big data to provide personalized services. It induces users to buy by providing a well-planned shopping experience.

Amazon's personalized recommendation algorithm includes many factors. Before recommending products to users, it analyzes, for example, purchase history, browsing history, friend influence, specific product trends, advertisements of popular products on social media, and products purchased by users with similar purchase history. In order to provide better services to users, Amazon has been constantly improving its recommendation algorithm.

Of course, personalized recommendations are not only for customers. Sellers in the e-commerce market can also receive reliable suggestions from Amazon, such as recommending new products that can be added to their inventory, recommending the best delivery mode for specific products, etc. On average, each seller on Amazon will receive more than 100 suggestions for their product catalog list.