Submit Your Requirement
Scroll down to discover

Amazon’s intelligent recommendation encourages impulse buys

August 10, 2018Category : Blog
Amazon’s intelligent recommendation encourages impulse buys

From selling books from a garage, under the initial name of Cadabra in 1994, to becoming a global internet giant, Amazon has come a long way. No wonder web scraping Amazon is becoming the goto practice for almost every eCommerce business today. With 1,000,000,000 gigabytes of data, amazon web crawler makes more sense than crawling any other eCommerce site.

While most businesses look to become profitable in the short run, Amazon claimed that it was not looking to turn profitable in its first five years! Then what turned Amazon into the giant it is today?

The thing is, Amazon started betting on data far earlier than its competitors did. That could have 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, 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

What started in 2003 as a system that would suggest 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 systems. It runs 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.

From making product recommendations based on purchase history, browsing, cart, to intelligently suggesting new products based on seasonal trends and customer behaviour, Amazon seems to have cracked it all. Web crawling is at the heart of this data. And how efficiently Amazon is using the extracted data, is making all the difference. 

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 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?”

Investments to Acquire New Features

1. Buying Goodreads in 2013, Amazon integrated the social networking service of approximately 25M 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. Amazon web crawlers could capture the near real-time data, fueling the recommendation engine with the latest information.

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 fulfilment centres. The items are then sent to a local distribution centre 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 25 percent annually. Price monitoring strategy was based on the activity of users on the website, prices of competitors, product availability, expected profit margin and other factors. Scraping competitor sites for product data and price comparison is an effective way to gather price information.

The Essential, Amazon Web Services

Although AWS was supposed to be an internal service offering, Amazon realised its potential early on. Companies dealing with massive amounts of data need a scalable infrastructure that they could set up fast, and for this, the cloud was the best place to store and compute data. 

There are many 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. The then issues forced the company to build its own internal systems that dealt with the mega growth it was experiencing. This laid the foundation for AWS aka Amazon Web Services.

AWS was initially started as an IAAS (Infrastructure as a Service), while the term was yet to get coined. It was supposed to be only used internally, for speedy infrastructure setup for projects. AWS was launched with little fanfare as a side business for Amazon.com. Today, it’s a highly successful company on its own and is riding a remarkable 10billion dollar valuation.

AWS has developed into the most successful cloud-infrastructure company on the planet, capturing more than 30percent 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

What is next on the cards for Amazon

In the past few years, Amazon has definitely moved away from a pure eCommerce player to a giant online behemoth that offers much more than just products. Its focus is moving rapidly to everything online from OTT platform to virtual grocery store, the leaps are giant and massive.  What has remained constant, though, is Amazon’s love for big data, and big data processing.  

Are you looking for an amazon web crawler or to scrape eCommerce data, you can consider web scraping service provider like PromptCloud

Web Scraping Service CTA

2 thoughts on “Amazon’s intelligent recommendation encourages impulse buys
  • Anees Shah

    Amazon uses big data to make decisions and understand its customers. What type of data Jeff Bezos’s company collects and how Amazon uses big data to boost its performance.

    If Data was a kingdom, Amazon would be its king.

    The company with a smile in its logo, that provides us with everything we desire, has already gotten a central position in our retail experience.

  • laiza

    Nice article o helpful.Thanks for sharing with us.

Leave a Reply

Your email address will not be published. Required fields are marked *

© Promptcloud 2009-2020 / All rights reserved.
To top