Amazon and Big Data

How Amazon combines its customer-centric approach with data-driven decision making to create and capture value.

Introduction

Amazon manages a marketplace platform that leverages big data and a customer-centric focus to improve the customer experience and internal operations. In this way it creates and captures value in a virtuous cycle involving increasing customers and transactions in order to generate more data that feeds into further improvements and more customers.

 

Site Data and Customer Service

Amazon collects extensive information on how users interact with the various elements of the site – tracking their journey from discovering products at the start to the purchase of products and final delivery or return of a product. The entire process is captured by the site and Amazon heavily uses this data to run tests and refine the site for performance which benefits customers and sellers on the platform. For customers, Amazon actively modifies the site and underlying algorithms to surface the best and most relevant products and sellers. For sellers, the data and other metrics that Amazon provides them can help them manage their own operations while optimizing how they display information on the site or conduct advertising. Amazon captures value derived from this data by drawing more customers and sellers to the site and collecting a subscription fee through Prime (from customers) and a transaction percentage and advertising revenue (from sellers).

 

Customer Service, Alexa, and Echo

In addition to leveraging the data collected from functional interactions with the site and the sales process, Amazon also leverages the extensive amount of data generated by customer service interactions as well as through recordings from Alexa and Echo. These further touchpoints and collected data are used to further refine the site, algorithms, and overall sales process by creating platforms for users (both customers and sellers) to give direct feedback on pain points or other potential aspirational features they would like to see on the site or in the process. New features or other tests often come out of user requested features or through observations of pain points. Value here is driven back to users through changes to the site and process and is captured by Amazon by increased users and advertising. There have also been reports that Amazon may be opening some of this data up to outside developers who could generate applications that would further improve the functionality of the site and process.

 

Amazon Fresh and Whole Foods

Amazon Fresh is another example of Amazon moving into a large market and using its data-driven logistics expertise to create and capture value. Like the primary site, Amazon Fresh gathers, analyzes, and leverages a lot of data about how users buy groceries, with the goal of optimizing this process over time by increasing efficiencies and driving more users to the program. This value creation cycle allows them to improve the flow of the site and process as more users generate more data that can be further analyzed in order to improve the experience for the users and allow Amazon to capture more of the value by improving its internal operations. Whole Foods in the same way can be viewed as another play around data, and not just a shift into higher end brick and mortar retail. Focusing on the data, Whole Foods, which was founded in 1980, has a lot of data on how customers buy their groceries and how suppliers interact with the grocer as well. While this data is centered on actual physical interactions in a brick and mortar store, the analyses of the data can yield interesting observations and insights that could be fed into the Amazon Fresh operations.

 

Path to Current and Continued E-commerce Dominance

Amazon began this path by focusing all of its attention on how to provide the best customer experience it could. To achieve this, it leveraged extensive amounts of data that it was actively collecting to refine and automate many of the site’s functionality and back end processes. This obsessive focus on using data to drive decisions has been a common theme through many platforms that have rapidly grown and been successful. As the digital age continues on, increasing amounts of data are available to be captured and leveraged. A core element of capturing the value from this data is asking the right questions and testing the right hypotheses. Amazon achieves this by employing many data scientists and incorporating this data driven approach into many of their internal processes. Furthermore, their ability to rapidly run tests and evaluate the results is driven by the sheer volume of traffic and transactions on their sites. Amazon will continue to leverage this data-driven, customer-centric focus as it moves forward, constantly analyzing the data to improve current operations and also as a means of finding and exploring new markets as well.

 

Sources

https://sellercentral.amazon.com/gp/help/external/200421970?language=en-US&ref=mpbc_1161254_cont_200421970

https://www.forbes.com/sites/jonmarkman/2017/06/05/amazon-using-ai-big-data-to-accelerate-profits/#2f1743d76d55

https://www.forbes.com/sites/forbesleadershipforum/2017/09/06/how-amazon-will-use-analytics-to-shake-up-the-supermarket-industry/#553719565be9

https://www.wsj.com/articles/amazons-grocery-sales-gained-weight-after-it-devoured-whole-foods-1515934801

https://www.wired.com/story/amazon-echo-and-google-home-voice-data-delete/

http://nymag.com/selectall/2017/07/amazon-echos-alexa-will-possibly-share-more-data-with-devs.html

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