Last Updated on by
From selling books from a garage, under the initial name of Cadabra in the year of 1994, to becoming an internet giant, Amazon has come a long way. While most businesses look to become profitable in the short run, Amazon, during its initial public offering on the fifteenth of May 1997, claimed that it was not looking to turn profitable in its first five years. This was indeed a headache for most stakeholders who wanted to make the most of their money. Its long-term plans are one of the reasons why Amazon did not get flushed away in the dot-com bubble, like many other companies. Amazon first made a profit, only in the year 2001. The thing is, Amazon started betting on data far earlier than its competitors did. And that is what has made all the difference.
Although Amazon has diversified its portfolio and is currently buying companies left and right, it has two major businesses- the online Marketplace of Amazon, and the cloud computing services called AWS (Amazon Web Services). We will be talking about the major developments and growth in both the sectors.
How Amazon developed as an e-commerce giant
While you can order an item on Amazon from almost anywhere in the world, as long as your country has some international courier services, Amazon runs thirteen country-specific websites as well. What started in 2003 as a system that would suggest you similar items based on an item to item comparison using collaborative filtering, has now grown into one of the world’s best and most data-driven recommendation system, that runs in real time and feeds on users’ activities and data, on the go. Amazon has a database of a hundred and fifty million customers. It is a leader in the collection, storage, processing and analysis of personal information of millions of customers, and it uses this data to determine how customers spend their money.
It analyzes items you purchased previously, items that are not bought by you yet but are added to your online shopping cart or on your wishlist, products that you have reviewed and rated, and your search history in the website search box. This information is used to recommend you items in the home screen or to recommend items when a customer adds some items to his cart and is trying to check out. For example, when you buy a mobile phone and add it to your cart, Amazon will recommend you to buy the mobile cover, screen protector, and earphones that other customers who buy the same mobile phone, prefer the most.
This is the way, Amazon uses intelligent suggestion algorithms to encourage customers to buy on impulse. This improves customer’s shopping experience, giving them a customized personal feel, and also makes them spend more money on the website. Sale of recommended items, or items sold in addition to the main item, results in a thirty percent increase in Amazon’s sale yearly. Predictive analytics in this way helps Amazon to indulge in target marketing that increases customer satisfaction and builds company loyalty. Big data has helped Amazon evolve into a goliath among online retail stores. Don’t you love it, when you enter your favorite coffee shop and the person at the counter just asks you… “Your regular sir?”
It also invested in some other features to boost sales
1. Buying Goodreads in the year of twenty-thirteen, Amazon integrated the social networking service of approximately twenty-five million users into its Kindle to provide some excellent features. Kindle users can now highlight words on their devices and create notes that they can share with others to discuss the book. Amazon’s recommendation engine reviews words highlighted in Kindle devices all over the world, so as to match you with books and accordingly send you e-book recommendations.
2. Amazon has patented its anticipatory shipping model that uses big data for predicting which items might get ordered at which point of time, near which of its fulfillment centers. The items are then sent to a local distribution center or warehouse so that when they are ordered, the users get same day or next day delivery which increases their trust in the brand.
3. Amazon makes sure that your orders are delivered quickly, and for this, the company goes to great lengths. It links with manufacturers and tracks their inventory. Amazon uses big data systems for choosing the warehouse that is at the most optimized distance between you and the vendor. This reduces shipping costs by ten to forty percent.
4. Big data is also used for managing and updating Amazon’s prices to attract more customers and increase profits by an average of twenty-five percent annually. Prices are changed based on the activity of users on the website, prices of competitors, product availability, expected profit margin and other factors. For example, the cost of a novel that in on the top spot in New York best seller list might be twenty-five percent less than the retail price, while a novel not on the list may cost ten percent more than the same book sold by a competitor. Thus Amazon even loses money on some top selling items but makes a profit as a whole through its competitive pricing mechanism.
The other major wing of Amazon, the Amazon Web Services:
Although AWS was supposed to be an internal service offering, Amazon had realised with time, that companies dealing with massive amounts of data will be needing scalable infrastructure that they could set up fast, and for this the cloud was the best place to store and compute data. There are lots of stories about the formation of Amazon Web Services, and although most reports say that it was started in 2006, the truth is that the roots for the idea of Amazon Web Services go back to the year 2000, when Amazon was a far different company than it is today- an e-commerce company struggling with scalability problems. Those issues forced the company to build its own internal systems that dealt with the mega growth it was experiencing. This is what laid the foundation for AWS.
Whenever Amazon was trying to start up a new service, Amazon’s excellent engineers and scientists were taking a lot of time to start their projects. This was because infrastructure and software setup itself took months to set up. Because of this AWS was started as an IAAS (Infrastructure as a Service), when the term was not yet coined. Ten years ago, Amazon Web Services, the cloud Infrastructure was a Service arm of Amazon.com and was supposed to be only used internally for speedy infrastructure setup for projects. It was launched with little fanfare as a side business for Amazon.com. Today, it’s a highly successful company and is riding a remarkable ten billion dollar valuation.
AWS has developed into the most successful cloud-infrastructure company on the planet, capturing more than thirty percent of the market. This is more than its three closest rivals, Microsoft, IBM, and Google combined. At Amazon Web Services, it also hosts public big data sets at no cost. All available big data sets can be used and seamlessly integrated into AWS cloud-based solutions. Everyone can now use this public data, such as the data from mapping the Human Genome Project. Through Amazon Web Services, companies can create scalable big data applications without worrying about infrastructure, maintenance, and scalability.
Thousands of big data applications and IOT based apps use the processing power of EC2 instances of AWS.
In the past few years, Amazon has definitely moved away from a pure e-commerce player to a giant online player who offers much more than just products. It focuses massively on big data, and big data processing and is changing from an online retailer into a big data company.