Some customers may find it odd when a store knows a lot about them simply by the products they purchase. Amazon.com, Inc. (AMZN) is a leader in collecting, storing, processing, and analyzing personal information from you and every other customer as a means of determining how customers are spending their money. The company uses predictive analytics for targeted marketing to increase customer satisfaction and build company loyalty. How Amazon uses big data has helped the brand evolve into a giant among online retail stores. However, what the company knows about you may feel a bit like stalking.

Personalized Recommendation System

Amazon is a leader in using a comprehensive, collaborative filtering engine (CFE). It analyzes what items you purchased previously, what is in your online shopping cart or on your wish list, which products you reviewed and rated, and what items you search for most. This information is used to recommend additional products that other customers purchased when buying those same items.

For example, when you add a DVD to your online shopping cart, similar movies purchased by other customers are also recommended for you to purchase. In this way, Amazon's big data uses the power of suggestion to encourage you to buy on impulse as a means of further satisfying your shopping experience and spending more money. This method generates 35% of the company’s sales annually.

Book Recommendations from Kindle Highlighting

After acquiring Goodreads in 2013, Amazon integrated the social networking service of approximately 25 million users into some Kindle functions. As a result, Kindle readers can highlight words and notes and share them with others as a means of discussing the book. Amazon regularly reviews words highlighted in your Kindle to determine what you are interested in learning about. The company may then send you additional e-book recommendations.

One-Click Ordering

Because big data shows that you shop elsewhere unless your products are delivered quickly, Amazon created One-Click ordering. One-Click is a patented feature automatically enabled when you place your first order and enter a shipping address and payment method. When choosing One-Click ordering, you have 30 minutes in which you may change your mind about the purchase. After that, the product is automatically charged via your payment method and shipped to your address.

Anticipatory Shipping Model

Amazon’s patented anticipatory shipping model also uses big data for predicting the products you are likely to purchase, when you may buy them, and where you might need the products. The items are sent to a local distribution center or warehouse so they will be ready for shipping once you order them. Amazon uses predictive analytics to increase its product sales and profit margins while decreasing its delivery time and overall expenses.

Supply Chain Optimization

Because Amazon wants to fulfill your orders quickly, the company links with manufacturers and tracks their inventory. Amazon's big data systems choose the warehouse closest to the vendor and/or you, the customer, to reduce shipping costs by 10 to 40%. Additionally, graph theory helps decide the best delivery schedule, route, and product groupings to reduce shipping expenses further.

Price Optimization

Big data is also used for managing Amazon’s prices to attract more customers and increase profits by an average of 25% annually. Prices are set according to your activity on the website, competitors’ pricing, product availability, item preferences, order history, expected profit margin, and other factors. Product prices typically change every 10 minutes as big data is updated and analyzed. As a result, Amazon typically offers discounts on best-selling items and earns larger profits on less-popular items. For example, the cost of a novel on the New York Times Best Sellers list may be 25% less than the retail price, while a novel not on the list costs 10% more than the same book sold by a competitor.

Amazon Web Services

Through Amazon Web Services (AWS), Amazon’s cloud computing service introduced in 2006, companies can create scalable big data applications and secure them without using hardware or maintaining infrastructure. Big data applications like clickstream analytics, data warehousing, recommendation engines, fraud detection, event-driven ETL, and Internet-of-Things (IoT) processing are through cloud-based computing. Companies may benefit from Amazon Web Services by using them to analyze customer demographics, spending habits, and other pertinent information to more effectively cross-sell company products in ways similar to Amazon. In other words, these retailers can use Amazon to stalk you, as well.