Today, Big Data is everywhere, but the key problem is – it is too big to tackle and, too complex to evaluate and draw insights from. Also, Big Data Analytics relatively being a state-of-the-art concept, there is a lack of copious knowledge and expertise in the field of Big Data, which is often leading most organizations to misuse their data.
The ideal way to discover how companies can use Big Data to the fullest is by keeping a close attention on those companies/businesses, which have already implemented such practices successfully. One such company that strikes instantly in our minds is ‘Amazon’.
In this article, we are going to figure out how Big Data Analytics has fueled Amazon to grow vigorously in the global e-commerce market.
The Recommender Systems
Undoubtedly, Amazon is one of the key visionaries in the realm of Big Data technology, which has conveyed several successful methods of collecting, analyzing, and implementing data analytical reports for generating business revenues. According to the Digital Stats Market report, Amazon has 300+ millions of users, with all their information it has profoundly developed a huge customer database. Since years, Amazon is using such data strategically to build effective recommender systems. It is the recommendations approach that paved a strong success track for Amazon across the globe in no time.
If you have an Amazon account, which you use on a regular basis, then you can observe that all the recommendations that are displayed on your homepage, such as offers, discounts, products are based on your previous purchasing activities and browsing history. Though today, most of the online retailers are offering recommendations to its customers, but it was Amazon, who has started the trend of ‘recommender systems’.