How does Amazon use Machine Learning (ML)?

First published on March 8, 2022

Last updated at April 13, 2022

 

3 minute read

Mayank S.

Guest

TLDR

Amazon is one of the first companies to successfully use artificial intelligence (AI) on such a large scale. Intelligent and bold use of machine learning (ML) algorithms resulted in enormous success for the retail giant. Eventually increasing its sales by providing an exceptional customer experience.

Outline

  • Introduction

  • Product recommendation

  • Alexa-enabled voice shopping

  • Conclusion

Introduction

The online retail giant utilizes machine learning (ML) to attract, engage, and deliver the best shopping experience to its customers. Amazon uses ML algorithms to cater the personalized shopping experience to its customers and increase its average order value.

Amazon has designed its system so that every time a user comes to buy a product, the ML algorithms suggest products that match the buyer’s search pattern. These proficiently designed algorithms are one of the significant reasons that Amazon’s net sales revenue reached

$469.82 billion in 2021

and was listed as the world’s top marketplace.

Over 197 million

people visit Amazon.com to shop for their preferred products every month. If we take the count to all the domains, including Africa, America, Asia, Europe, and Oceania, the monthly visit count reached

5.2 billion in 2021

. Here are some of the most prominent implementations of ML that Amazon used to become one of the most successful online retailers.

Product recommendation

Amazon uses item-to-item collaborative filtering for product recommendations. The recommendation method uses ML algorithms to identify similar products based on other users’ likes and interactions. It is also known as IBCF (Item-based collaborative filtering).

Here’s an example to better understand. Suppose user A purchased products X, Y, and Z. User B purchased W, X, and Y. Amazon’s product recommendation system will recommend product W to user A and product Z to user B. To further complement the buying experience, Amazon has designed ML algorithms to suggest products purchased together. For example, if a user buys a smartphone, the algorithm will recommend related accessories to purchase as a combo.

Amazon also has a dedicated section titled ‘recommended for you’, in which users will find the best options based on their recent purchases or online search. Amazon has successfully increased its sales and delivered an exceptional customer experience by implementing this feature. Making them a market leader for online shopping.

Alexa-enabled voice shopping

Amazon’s ML efforts primarily revolve around improving the customer experience. Amazon allows its users to buy products using voice commands. Amazon’s AI assistant, Alexa, helps users do shopping by using Natural Language Processing (NLP) algorithms . It recognizes the command based on defined models and eventually processes the task through Amazon’s cloud.

Alexa helps users prepare a list of orders, place an order, make payment, track the shipment, and get notified. By doing this, Amazon has served its customers with the ease of shopping through voice commands and getting recommendations about new products and gift ideas. All the interactions are encrypted in transit to Amazon’s secure cloud to ensure the safety of customer privacy.

Alexa-enabled voice shopping gives Amazon a clear edge over its competitors across the globe. It trains itself with every interaction and eventually delivers a seamless customer experience. This eventually makes Alexa the most easy-to-use shopping medium for millions of Amazon users.

Conclusion

Amazon is one of the early adopters of cloud computing and AI. Its endeavors to build a competent and reliable marketplace using artificial intelligence have made it a pioneer in the segment. It started implementing AI algorithms in 1998. With perpetual growth, Amazon has today mastered the technology and has become a cloud solution provider through its subsidiary AWS (Amazon Web Services).

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