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Amazon manages a marketplace platform that leverages big data and customer-centric approach to improve customer experience.
In this research study, the focus is to understand how “Amazon Go” uses the vast variety of data, derives useful information from the data and uses data-driven approach to enhance customer experience using predictive models to recommend products to customers. This study also aims to understand the importance of big data, how it helps in driving growth in business and improving business model from online portal to automated physical store (amazon go).
Seattle-based e-commerce giant Amazon, is leveraging big data on its 200 million customer accounts by hosting their 1,000,000,000 GB of data on more than 1,400,000 servers to increase sales through predictive analytics. Amazon’s concept of convenience store “Amazon Go” opened to public in January 2018. The store has an array of cameras which track purchases and automatically charge customer through a smartphone app.
The “Amazon Go” store is only 1,800 square feet. Amazon Go has prices printed on the shelf tags. The shopping experience is amazing, one can just browse around, place items into the bag and just walk out. But in reality, customer gets charged automatically from their Amazon account for what all they take out the door. The deep learning technology is able to recognize every item in the store without any special tags like RFID chips.
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