Amazon is the world’s largest online shopping website that helps people to order things in one click. During the initial stage of its business, Amazon was a bookseller, then gradually they expanded their company by selling a wide variety of consumer goods, electronic devices like mobile phones, e-commerce, and logistics, and Kindle was a huge hit among the people.
Amazon has innovated and executed a model called 'everything under one roof' where people can shop for anything on their website with ease. Customers experience a wide variety of options, but they do not have a clear insight into what to buy and which product is the best from the customer's point of view. To overcome this problem and to help customers decide, Amazon started using big data to gather information from the customers who bought the product or who viewed the product, from which they created the recommendation engine. The more Amazon knows about you, the better it can predict what you want to buy. Once they have a clear picture of what they want to buy, the website comes up with similar recommendations instead of making the customer search through the whole catalog. Amazon gathers data from every single individual who uses its site. It keeps track of what you buy, and most importantly, it can even make a good guess on your monthly income based on your shipping address. This huge amount of data that is gathered from the customer is used to come up with a '360-degree view' of an individual customer. Amazon then finds other people who fit into the same category and makes recommendations based on what those other customers like.
These are the ways Amazon uses big data to stalk customers:
Personalized recommendation system. Amazon is one of the leading companies in using a comprehensive collaborative filtering engine (CFE). It keeps track of what you purchased last time when you visited the site, what is in your wish list or cart, and what items you have viewed the most. This information is used to recommend additional products that other customers purchased when buying those same items. For example, if you are looking for a swimming suit to buy, it will come up with similar products that other customers purchased like swimming goggles, shower caps, etc. By using this method, Amazon uses the power of suggestion to recommend you buy those products. This method generates the company’s sales annually by 15%.
E-book recommendations from Kindle. When Kindle was launched, it was a huge hit among people in various age groups, which had kids and adults, and there were approximately 25 million users. Kindle had a great feature where the reader can highlight important words and phrases and share them with other readers who are reading the same book. Amazon on a regular basis views what you have read, and it finds out what fascinates you the most based on this they send you recommendations on other e-books.
One-click ordering. By the use of big data, Amazon concluded that people order only from websites that are very quick in delivering their products to the customer. So, Amazon came up with an idea called 'one-click ordering'. When a customer places their first order along with their shipping address and payment details, the company gives you a grace time of thirty minutes in which you can decide whether you want the product or not. After the time limit, the payment will be made from the account, and the product will be delivered to the shipping address mentioned.
Anticipatory shipping model. Amazon’s anticipatory shipping model uses big data to predict what products you are likely to buy and which city you are from. Based on this prediction, they send the products to the nearest distribution center, and when you order the product, it is sent to the customer's place. Thus, Amazon uses predictive analysis from big data to increase the sales of the product while reducing the delivery time, which might attract customers.
Supply chain optimization. In order to reduce the shipping time, Amazon connects with the manufacturers, and by the use of big data, it finds out the closest warehouse between the manufacturer and the customer so that they can reduce the shipping cost by 10 to 40%. In addition, they use graph theory to help them to decide which is the best delivery schedule and which is the shortest route, which helps them to reduce the shipping cost.
Price optimization. Big data is also used for determining the price of the product, which attracts more customers by giving a lot of offers, which increases the profits rates by 25%. Prices are usually determined based on the requirement of the product among customers, product availability, competitors' prices, etc. The price of the product changes every ten minutes because the big is updated frequently.
Though there are many ways how big data can help Amazon grow in its business, using big data has one fundamental drawback. I feel that people have no privacy whatsoever about their personal information and everything that customers have access to, from what they view a product to what they buy and where they live, these things are routinely tracked in the name of big data.