How Amazon Leveraged Big Data To Become The No. 1 In E-Commerce

Amazon needs no formal introduction to today’s consumers. But what many might not know is that this giant e-commerce platform didn’t achieve success by chance.
To stay upbeat among the competition and win over customers continuously, Amazon has been using Big Data to Rule E-Commerce, and that too for a long time. And that is not all, for, Amazon has been expanding its usage of Big Data to become what it is today.

How has Amazon leveraged the effectiveness of Big Data?

For today’s e-commerce organizations to thrive amidst the cut-throat competition, adopting Big Data Analytics, like Amazon, can be highly rewarding by helping them in the following ways.
• Stay competitive by implementing dynamic pricing
Earlier, no matter how many times a visitor frequented stores or websites to buy a product, prices usually remained the same at all times. But now prices are often seen to change frequently. Why, because companies now try to assess a customer’s willingness to buy a product using Big Data. This helps them stay afloat amidst competitors. Studies suggest that Amazon changes prices of products about 2.5 million times a day every day which basically means that the cost of a product changes every 10 minutes!
• Detect possibilities of fraudulence by screening purchases and return requests
Amazon collects about 2000 real-time and historical data-points on every order and then employs Machine Learning to identify transactions that have higher chances of becoming fraudulent. (Source) This has helped the company prevent losses worth millions of dollars. Amazon has also been tweaking algorithms to scrutinize return requests which they deem suspicious.
• Encouraging people to increase their order size
The most evident Big Data outcomes in recent days are Amazon’s product recommendations that display items to users that are relevant to the ones already placed in their carts. Another interesting thing is the ‘Amazon personalize’ feature, which enables developers to make use of the highly-scalable platform to send recommendations to users across all domains.
As Amazon is appealing to customers by showing them personalized products, they are ultimately making their customers spend more on their products.
• Influencing physical stores
After acquiring the Whole Foods Market, Amazon started using data to change the brand’s operations which also included lowering the prices of the popular items. Needless to say, this is still considered to be a substantially big effort in adopting Big Data Analytics in customer support and has got the potential to transform how supermarkets currently function.
Another example that can be cited in this regard is Amazon Go, the “cashier-less convenience store” of Amazon, which also relies on data for its everyday operations. Sensors work by detecting the items that customers select, and cameras ensure that customers don’t leave without paying. And in this process, the data that Amazon collects is used to improve the shopping experience by making it comfortable, convenient and exciting even without the human workforce.
So it goes without saying that the combination of Amazon and Big Data is indeed powerful and transformative.