So you are thinking of buying a few productivity boosting products, so you open up your laptop or desktop and search for a journal, which fits your needs based. After browsing for quite a while, you get back to you daily chores. Do you notice similar utility products, popping up on every new tab that you open, including your social networking sites. This eventually does lead to you buying that particular product. This is know as target marketing but, it has a more complex concept backing it up. It is all brought together as a result of data science. The process that uses data science to bring about such great revenues for online marketplaces, is known as data analytics.
These few months saw a lot of companies advertising sales with massive discounts, with one of those online giants, Snapdeal’s Unbox Sale actually witnessing a nine-fold increase in sales volume, 80% of orders coming from its mobile platforms. This was the result of the data analytics strategy used for their sale on the 1st week of October. Amazon, which is literally the biggest e-commerce website worldwide, also hosted the largest number of servers to store the massive amounts of data that they generate daily.
Flipkart’s Big Billion Day 2016 is also following similar lines and is experiencing explosive revenues in return. Below are few key points on their sales:
- Around 100 mobile phones were bought per second within the first hour
- Around 50 million items were added by customers to their wishlists
- The total amount of TVs that were bought could cover 6,000 cricket pitches; cover to cover
- All packages weighed close to 15 million kilograms
- 30,000 executives fulfilled all the orders
- Garments and curtains measuring a total of 5.8 million metres were purchased during the sale
- Shoppers totally saved Rs. 150 crores via no-cost EMIs and exchange offers
Amazon during their Great Indian Sale said:
“Over 10,000 sellers saw their biggest sales ever in the Great Indian Festival and 100 new sellers entered the crorepati club during the event.”
With the world rapidly going digital, and the advent of data analytics and predictive analytic solutions, a lot of the e-commerce giants have heavily invested in logistics and gotten themselves efficient teams of Data scientists as well. The question arises here, as to how exactly was data analytics successful in helping out these companies. One of these mega-giants, Flipkart goes ahead and segregates its data into three categories.
- Customers: Here, a lot of research is done on the kind of products customers like, their preferences towards a certain kind of product, based on their location, the time of the year, the changes in their likes and dislikes on the basis of the quality, price, value, lifestyle and class quotient of the product.
- Product Behaviour: Data is extracted, mined and studied in order to research why a product has higher sales, as compared to others, what products are complimentary and which ones can be substituted on the basis of the customer response.
- Vendor side of the scales: The data collected from the hundreds and thousands of vendors out there and this data analytics is then assimilated, in the growth model of the companies.
A lot of these e-commerce companies entirely depend on their team of data scientists and various tools to achieve these staggering results. For instance, Snapdeal makes use of a multi-tier system, which they call the Hadoop-based farm. Hadoop is one such open sourced data analytics software, which enables companies like Snapdeal get to know what strategy works effectively. Machine learning and logistical research and increasingly becoming the go to solutions of many e-commerce companies in achieving their set goals. Giants like Amazon and Snapdeal with revenues that break the roof are examples of the same. The Great Indian Sale Of Amazon, which ran from 2nd to 6th of October was also the result of such cleverly executed data analytic strategies.
Imarticus Learning is a leading education institute, offering state-of-art, industry endorsed courses in data analytics software platforms like, Big Data Hadoop, SAS programming, R Programming and more.
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