Review About Amazon And Its Market Position

Review about Amazon and its market position

Amazon is the market leader in cloud infrastructure and global electronic commerce. However, when they face such a wide range of options, customers can often feel overwhelmed. In fact, they become rich in data, with tons of options, but with little information, with little idea about what would be the best purchase decision for them.

To combat this, Amazon uses Big Data compiled from customers while sailing to build and adjust their recommendations engine. The more you know Amazon from you, the better you can predict what you want to buy. And, once the retailer knows what I could want, he can expedite the process of persuading him to buy it, for example, recommending several products instead of making him look for in the entire catalog. In addition to what a customer buys, Amazon observes the items consulted, the shipping address and if a customer leaves comments. Big Data has helped to boost Amazon at the top of electronic commerce. The company is linked to manufacturers and monitor its inventory to ensure that orders are fully fulfilled. By Big Data, it allows you to select the closest warehouse and considerably reduce shipping costs.

Amazon recommendation technology is based on collaborative filtering, which means that it decides what you think you want when creating an image of who you are and then offering products that people with similar profiles have bought.

Amazon collects data on each of its customers while using the site.

In addition to what you buy, the company monitors what you look at, your shipping address (Amazon can make a surprisingly good estimate of your income level depending on the place where you live) and if you leave reviews or comments.

The exponential propagation of the Coronavirus has caused an increase in the demand for food and home products delivered to homes through online channels.

Algorithms are the basis of artificial intelligence (AI). Automatic learning models trained in the behavior of normal people have detected that the ‘normal’ has changed and that some no longer work normally. The main products that were sold before the Pandemia on Amazon were housings for mobile phones, telephone loaders and lego. These were relegated from the lists of the best -selling products in a matter of days.

Automatic learning models are designed to respond to changes. But most are also fragile;They work badly when the input data differ too much from the data in which they were trained.

The problem lies the lack of data used to build algorithms, which means that they do not reflect the amplitude of our society and the unpredictable nature of events and human behavior.

The impact of pandemic has felt throughout, affecting mechanisms that in more normal times remain hidden. Now is the time to take stock of those recent systems and see how they could designed better. Not only should be trained on the ups and downs of recent years, but also on strange events such as the great depression of the 1930. "A pandemic like this is a perfect trigger to build better automatic learning models"