According to Forbes, Amazon will become the next company in the world to join the very exclusive $2 trillion market cap club.
The company, which started as a digital marketplace for books, has become an internet empire that offers everything from online shopping to web services.
Most people, however, still know Amazon as the company that sells products online, which is understandable given its dominance in the online marketplace.
In recent years, the online giant has taken steps to further solidify its dominance across global online businesses. One of these steps has been the launch of its private label, AmazonBasics.
AmazonBasics has allowed the company to reach more consumers with its lineup of affordable everyday products including everything from dog poop bags to microwave ovens.
The private label has become so successful, in fact, that it is now the third most popular brand across Amazon’s entire online marketplace. According to a market survey, it offers over 1,500 different products in its catalogue; a marked improvement from its early days.
What’s more astonishing is that the range of products the brand sells does not normally fall under one brand due to their diversity. Amazon has found a way to do this while keeping prices low.
The rise of AmazonBasics, however, is not a coincidence. Nothing is a stroke of luck or coincidence in the business world.
One of the primary driving forces behind its success is data analytics, which has helped the brand become profitable and popular among online shoppers. In this post, we explore how this came to be.
One benefit of owning the largest online shopping platform in the world is the ability to collect vast quantities of data, which includes everything from prices, specifications, consumer behaviour to seller popularity and reviews.
The retailing giant uses data analytics to extract critical insights from this data, which is then used to make recommendations to shoppers and to rank products on the search results page.
Amazon also uses this data to power its in-house label. The data is processed through data analytics tools to gain insights into the popularity of products and consumer preferences. The company then uses these insights to make decisions about which products to supply as part of its private label.
Alkaline batteries, for example, are one of the most popular products on Amazon’s online platform. Naturally, they became one of the first products to be sold under the AmazonBasics brand.
Now, online shoppers buy AmazonBasics’ line of batteries more than any other brand. Even more established manufacturers like Duracell sell significantly fewer batteries.
Data analytics, however, is not only helping Amazon decide what to produce but also how much to produce, as the company has a measure of demand for each product across the year.
Using data analytics as a demand prediction tool, they meet this demand, which is generally high year-round, considering the popularity of these products.
Additionally, data analytics is helping Amazon find the best and most efficient producers of a given item to keep prices low and unbeatable.
Amazon’s private label has quickly become one of the most successful brands on its online shopping platform, the success of which can be attributed to data analytics.
Analytics is supporting the company’s decision-making on the type of products to produce, their quantity and price.
With analytics, there is little doubt that AmazonBasics will become its own financial force and a shining example of what you can achieve with the right data.